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Extraordinary Popular Miscarriages of Science, Part 5 – Climate Science
Posted in History of Science on April 6, 2025
NASA reports that ninety-seven percent of climate scientists agree that human-caused climate change is happening.
As with earlier posts on popular miscarriages of science, I look at climate science through the lens of the 20th century historians of science and philosophers of science and conclude that climate science is epistemically thin.
To elaborate a bit, most sensible folk accept that climate science addresses a potentially critical concern and that it has many earnest and talented practitioners. Despite those practitioners, it can be critiqued as bad science. We can do that without delving into the levels or claims, disputations, and counterarguments on relationships between ice cores, CO₂ concentrations and temperature. We can instead use the perspectives of prominent historians and philosophers of science of the 20th century, including the Logical Positivists in general, positivist Carl Hempel in particular, Karl Popper, Thomas Kuhn, Imre Lakatos, and Paul Feyerabend. Each perspective offers a distinct philosophical lens that highlights shortcomings in climate science’s methodologies and practices. I’ll explain each of those perspectives, why I think they’re important, and I’ll explore the critiques they would likely advance. These critiques don’t invalidate climate science conceptually as a field of inquiry but they highlight serious logical and philosophical concerns about its methodologies, practices, and epistemic foundations.
The historians and philosophers invoked here were fundamentally concerned with the demarcation problem: how to differentiate good science, bad science, and pseudoscience using a methodological perspective. They didn’t necessarily agree with each other. In some cases, like Kuhn versus Popper, they outright despised each other. All were flawed, but they were giants who shone brightly and presented systematic visions of how science works and what good science is.
Carnap, Ayer and the Positivists: Verification
The early Logical Positivists, particularly Rudolf Carnap and A.J. Ayer, saw empirical verification as the cornerstone of scientific claims. To be meaningful, a claim must be testable through observation or experiment. Climate science, while rooted in empirical data, struggles with verifiability because of its focus on long-term, global phenomena. Predictions about future consequences like sea level change, crop yield, hurricane frequency, and average temperature are not easily verifiable within a human lifespan or with current empirical methods. That might merely suggest that climate science is hard, not that it is bad. But decades of past predictions and retrodictions have been notoriously poor. Consequently, theories have been continuously revised in light of failed predictions. The reliance on indirect evidence – proxy data and computer simulations – rather than controlled experiments (which would be impossible or unethical) would not satisfy the positivists’ demand for direct, observable confirmation. Climatologist Michael Mann (originator of the “hockey stick” graph) often refers to climate simulation results as data. It is not – not in any sense that a positivist would use the term data. Positivists would see these difficulties and predictive failures as falling short of their strict criteria for scientific legitimacy.
Carl Hempel: Absence of Appeal to Universal Laws
The philosophy of Carl Hempel centered on the deductive-nomological model (aka covering-law model), which holds that scientific explanations should be derived from universal, timeless laws of nature combined with deductive logic about specific sense observations (empirical data). For Hempel, explanation and prediction were two sides of the same coin. If you can’t predict, then you cannot explain. For Hempel to judge a scientific explanation valid, deductive logic applied to laws of nature must confer nomic expectability upon the phenomenon being explained.
Climate science rarely operates with the kinds of laws of nature Hempel considered suitably general, simple, and verifiable. Instead, it relies on statistical correlations and computer models such as linking CO₂ concentrations to temperature increases through statistical trends, rather than strict, law-like statements. These approaches contrast with Hempel’s ideal of deductive certifiability. Scientific explanations should, by Hempel’s lights, be structured as deductive arguments, where the truth of the premises (law of nature plus initial conditions plus empirical data) entails the truth of the phenomenon to be explained. Without universal laws to anchor its explanations, climate science would appear to Hempel to lack the logical rigor of good science. On Hempel’s view, climate science’s dependence on complex models having parameters that are constantly re-tuned further weakens its explanatory power.
Hempel’s deductive-nomological model was a solid effort at removing causality from scientific explanations, something the positivists, following David Hume, thought to be too metaphysical. The deductive-nomological model ultimately proved unable to bear the load Hempel wanted it to carry. Scientific explanation doesn’t work in certain cases without appeal to the notion of causality. That failure of Hempel’s model doesn’t weaken its criticism of climate science, or criticism of any other theory, however. It merely limits the deductive-nomological model’s ability to defend a theory by validating its explanations.
Karl Popper: Falsifiability
Karl Popper’s central criterion for demarcating good science from bad science and pseudoscience is falsifiability. A scientific theory, in his view, must make risky predictions that can be tested and potentially proven false. If a theory could not in principle be falsified, it does not belong to the realm of science.
The predictive models of climate science face severe challenges under this criterion. Climate models often project long-term trends, typically, global temperature increases over decades or centuries, which are probabilistic and difficult to test. Shorter-term, climate science has made abundant falsifiable predictions that were in fact falsified. Popper would initially see this as a mark of bad science, rather than pseudoscience.
But climate scientists have frequently adjusted their models or invoked external factors like previously unknown aerosol concentrations or volcanic eruptions to explain discrepancies. This would make climate science look, to Popper, too much like scientific Marxism and psychoanalysis, both of which he condemned for accommodating all possible outcomes to a prediction. When global temperatures temporarily stabilize or decrease, climate scientists often argue that natural variability is masking a long-term trend, rather than conceding a flaw in the theory. On this point, Popper would see climate science more akin to pseudoscience, since it lacks clear, testable predictions that could definitively refute its core claims.
For Popper, climate science must vigorously court skepticism and invite attempts at disputation and refutation, especially from dissenting insiders like Tol, Curry, and Michaels (more on below). Instead, climate science brands them as traitors.
Thomas Kuhn: Paradigm Rigidity
Thomas Kuhn agreed that Popper’s notion of falsifiability was how scientists think they behave, eager to subject their theories to disconfirmation. But scientific institutions don’t behave like that. Kuhn described science as progressing through paradigms, the frameworks, shared within a scientific community, that define normal scientific practice, periodically interrupted by revolutionary shifts, with a new theory displacing an older one.
A popular criticism of climate science is that science is not based on consensus. Kuhn would disagree, arguing that all scientific paradigms are fundamentally consensus-based.
“Normal science” for Kuhn was the state of things in a paradigm where most activity is aimed at defending the paradigm, thereby rationalizing the rejection of any evidence that disconfirms its theories. In this sense, everyday lab-coat scientists are some of the least scientific of professionals.
“Even in physics,” wrote Kuhn, “there is no standard higher than the assent of the relevant community.” So for Kuhn, evidence does not completely speak for itself, since assent about what evidence exists (Is that blip on the chart a Higgs boson or isn’t it?) must exist within the community for a theory to show consistency with observation. Climate science, more than any current paradigm except possibly string theory, has built high walls around its dominant theory.
That theory is the judgement, conclusion, or belief that human activity, particularly CO₂ emissions, has driven climate change for 150 years and will do so at an accelerated pace in the future. The paradigm virtually ensures that the vast majority of climate scientists agree with the theory because the theory is the heart of the paradigm, as Kuhn would see it. Within a paradigm, Kuhn accepts the role of consensus, but he wants outsiders to be able to overthrow the paradigm.
Given the relevant community’s insularity, Kuhn would see climate scientists’ claim that the anthropogenic warming theory is consistent with all their data as a case of anomalies being rationalized to preserve the paradigm. He would point to Michael Mann’s resistance to disclose his hockey stick data and simulation code as brutal shielding of the paradigm, regardless of Mann’s being found innocent of ethics violations.
Climate science’s tendency to dismiss solar influence and alternative hypotheses would likely be interpreted by Kuhn as the marginalization of dissent and paradigm rigidity. Kuhn might not see this rigidity as a sign of dishonesty or interest – as Paul Feyerabend (below) would – but would see the prevailing framework as stifling the revolutionary thinking he believed necessary for scientific advancement. From Kuhn’s perspective, climate science’s entrenched consensus could make it deeply flawed by prioritizing conformity too heavily over innovation.
Imre Lakatos: Climate as “Research Programme”
Lakatos developed his concept of “research programmes” to evaluate scientific progress. He blended ideas from Popper’s falsification and Kuhn’s paradigm shifts. Lakatos distinguished between progressive and degenerating research programs based on their ability to predict new facts and handle challenges effectively.
Lakatos viewed scientific progress as developing within research programs having two main components. The hard core, for Lakatos, was the set of central assumptions that define the program, which are not easily abandoned. The protective belt is a flexible layer of auxiliary hypotheses, methods, and data interpretations that can be adjusted to defend the hard core from anomalies. A research program is progressive if it predicts novel phenomena and those predictions are confirmed empirically. It is degenerating if its predictions fail and it relies on ad hoc modifications to explain away anomalies.
In climate science, the hard core would be that global climate is changing, that greenhouse gas emissions drive this change, and that climate models can reliably predict future trends. Its protective belt would be the evolving methods of collecting, revising, and interpreting weather data adjustments due to new evidence such as volcanic activity.
Lakatos would be more lenient than Popper about continual theory revision and model-tweaking on the grounds that a progressive research agenda’s revision of its protective belt is justified by the complexity of the topic. Signs of potential degeneration of the program would include the “pause” in warming from 1998–2012, explained ad hoc as natural variability, particularly since natural variability was invoked too early to know whether the pause would continue. I.e., it was called a pause with no knowledge of whether the pause would end.
I suspect Lakatos would be on the fence about climate science, seeing it as more progressive (in his terms, not political ones) than rival programs, but would be concerned about its level of dogmatism.
Paul Feyerabend: Tyranny of Methodological Monism
Kuhn, Lakatos, and Paul Feyerabend were close friends who, while drawing on each other’s work, differed greatly in viewpoint. Feyerabend advocated epistemological anarchism, defending his claim that no scientific advancement ever proceeds purely within what is taught as “the scientific method.” He argued that science should be open to diverse approaches and that imposing methodological rules suppresses necessary creativity and innovation. Feyerabend often cited Galileo’s methodology, which bears little in common with what is called the scientific method. He famously claimed that anything goes in science, emphasizing the importance of methodological pluralism.
From Feyerabend’s perspective, climate science excessively relies on a narrow set of methodologies, particularly computer modeling and statistical analysis. The field’s heavy dependence on these tools and its discounting of historical climatology is a form of methodological monism. Its emphasis on consensus, rigid practices, and public hostility to dissent (more on below) would be viewed as stifling the kind of creative, unorthodox thinking that Feyerabend believed essential for scientific breakthroughs. The pressure to conform coupled with the politicization of climate science has led to a homogenized field that lacks cognitive diversity.
Feyerabend distrusted the orthodoxy of the social practices in what Kuhn termed “normal science” – what scientific institutions do in their laboratories. Against Lakatos, Feyerabend distrusted any rule-based scientific method at all. Science in the mid 1900’s had fallen prey to the “tyranny of tightly knit, highly corroborated, and gracelessly presented theoretical systems.”
Viewing science as an institution, he said that science was a threat to democracy and that there must be “a separation of state and science just as there is a separation between state and religious institutions.” He called 20th century science “the most aggressive, and most dogmatic religious institution.” He wrote that institutional science resembled more the church of Galileo’s day than it resembled Galileo. I think he would say the same of climate science.
Feyerabend complained that university research requires “a willingness to subordinate one’s ideas to those of a team leader.” In the case of global warming, government and government-funded scientists are deciding not only what is important as a scientific program but what is important as energy policy and social agenda. Feyerabend would be utterly horrified.
Feyerabend’s biggest concern, I suspect, would be the frequent alignment of climate scientists with alternative energy initiatives. Climate scientists who advocate for solar, wind, and hydrogen step beyond their expertise in diagnosing climate change into prescribing solutions, a policy domain involving engineering and economics. Michael Mann still prioritizes “100% renewable energy,” despite all evidence of its engineering and economical infeasibility.
Further, advocacy for a specific solution over others (nuclear power is often still shunned) suggests a theoretical precommitment likely to introduce observational bias. Climate research grants from renewable energy advocates including NGOs the Department of Energy’s ARPA-E program create incentives for scientists to emphasize climate problems that those technologies could cure. Climate science has been a gravy train for bogus green tech, such as Solyndra and Abound Solar.
Why Not Naomi Oreskes?
All my science history gods are dead white men. Why not include a prominent living historian? Naomi Oreskes at Harvard is the obvious choice. We need not speculate about how she would view climate science. She has been happy to tell us. Her activism and writings suggest she functions more as an advocate for the climate political cause than a historian of science. Her role extends past documenting the past to shaping contemporary debate.
Oreskes testified before U.S. congressional committees (House Select Committee on the Climate Crisis, 2019, and the Senate Budget Committee, 2023), as a Democratic-invited witness. There she accused political figures of harassing scientists and pushed for action against fossil fuel companies. She aligns with progressive anti-nuclear leanings. An objective historian would limit herself to historical facts and the resulting predictions and explanations rather than advocating specific legislative actions. She embraces the term “climate activist,” arguing that citizen engagement is essential for democracy.
Oreskes’s scholarship, notably her 2004 “The Scientific Consensus on Climate Change” and her book Merchants of Doubt, employ the narrative of universal scientific agreement on anthropogenic climate change while portraying dissent solely as industry-driven disinformation. She wrote that 100% of 928 peer-reviewed papers supported the IPCC’s position on climate change. Conflicting peer-reviewed papers show Oreskes to have, at best, cherry-picked data to bolster a political point. Pursuing legal attacks on fossil fuel companies is activism, not analysis.
Acts of the “Relevant Community”
Countless scientists themselves engage in climate advocacy, even in the analysis of effectiveness of advocacy. Advocacy backed by science, and science applied to advocacy. A paradigmatic example – using Kuhn’s term literally – is Dr. James Lawrence Powell’s 2017 “The Consensus on Anthropogenic Global Warming Matters.” In it, Powell addresses a critic’s response to Powell’s earlier report on the degree of scientific consensus. Powell argues that 99.99% of scientists accept anthropogenic warming, rather than 97% as his critic claims. But the thrust of Powell’s paper is that the degree of consensus matters greatly, “because scholars have shown that the stronger the public believe the consensus to be, the more they support the action on global warming that human society so desperately needs.” Powell goes on for seven fine-print pages, citing Oreskes’ work, with charts and appendices on the degree of scientific consensus. He not only focuses on consensus, he seeks consensus about consensus.
Of particular interest to anyone with Kuhn’s perspective – let alone Feyerabend’s – is the way climate science treats its backsliders. Dissenters are damned from the start, but those who have left the institution (literally, in the case of The Intergovernmental Panel on Climate Change) are further vilified.
Dr. Richard Tol, lead author for the Fifth IPCC Assessment Report, later identified methodological flaws in IPCC work. Dr. Judith Curry, lead author for the Third Assessment Report, later became a prominent critic of the IPCC’s consensus-driven process. She criticized climate models and the IPCC’s dismissal of natural climate variability. She believes (in Kuhnian terms) that the IPCC’s theories are value-laden and that their observations are theory-laden, the theory being human causation. Scientific American, a once agenda-less publication, called Curry a “climate heretic.” Dr. Patrick Michaels, contributor to the Second Assessment Report later emerged as a vocal climate change skeptic, arguing that the IPCC ignores natural climate variability and uses a poor representation of climate dynamics.
These scientists represent a small minority of the relevant community. But that community has challenged the motives and credentials of Tol, Curry, and Michaels more than their science. Michael Mann accused Curry of undermining science with “confusionism and denialism” in a 2017 congressional testimony. Mann said that any past legitimate work by Curry was invalidated by her “boilerplate denial drivel.” Mann said her exit strengthened the field by removing a disruptive voice. Indeed.
Tampering with Evidence
Everything above deals with methodological and social issues in climate science. Kuhn, Feyerabend, and even the Strong Program sociologists of science, assumed that scientists were above fudging the data. Tony Heller, Harvard emeritus professor of Geophysics, has, for over a decade, assembled screenshots of NASA and NOAA temperature records that prove continual revision of historic data, making the past look colder and the present look hotter. Heller’s opponents relentlessly engage in ad hominem attacks and character-based dismissals, rather than focusing on the substance of his arguments. If I can pick substance from his opponents’ positions, it would be that Heller cherry-picks U.S.-only examples and dismisses global evidence and corroboration of climate theory by evidence beyond temperature data. Heller may be guilty of cherry-picking. I haven’t followed the debate closely for many years.
But in 2013, I wrote to Judith Curry on the topic, assuming she was close to the issue. I asked her what fraction of NASA’s adjustments were consistent with strengthening the argument for 20th-century global warming, i.e., what fraction was consistent with Heller’s argument. She said the vast majority of it was.
Curry acknowledged that adjustments like those for urban heat-island effects and differences in observation times are justified in principle, but she challenged their implementation. In a 2016 interview with The Spectator, she said, “The temperature record has been adjusted in ways that make the past look cooler and the present warmer – it’s not a conspiracy, but it’s not neutral either.” She ties the bias to institutional pressures like funding and peer expectations. Feyerabend would smirk and remark that a conspiracy is not needed when the paradigm is ideologically aligned from the start.
In a 2017 testimony before the U.S. House Committee on Science, Space, and Technology, Curry said, “Adjustments to historical temperature data have been substantial, and in many cases, these adjustments enhance the warming trend.” She cited this as evidence of bias, implying the process lacks transparency and independent validation.
Conclusion
From the historical and philosophical perspectives discussed above, climate science can be critiqued as bad science. For the Logical Positivists, its global, far-future claims are hard to verify directly, challenging their empirical basis. For Hempel, its reliance on models and statistical trends rather than universal laws undermines its deductive explanatory power. For Popper, its long-term predictions resist falsification, blurring the line between science and non-science. For Kuhn, its dominant paradigm suppresses alternative viewpoints, hindering progress. Lakatos would likely endorse its progressive program, but would challenge its dogmatism. Feyerabend would be disgusted by its narrow methodology and its institutional rigidness. He would call it a religion – a bad one. He would quip that 97% of climate scientists agree that they do not want to be defunded. Naomi Oreskes thinks climate science is vital. I think it’s crap.
Fuck Trump: The Road to Retarded Representation
Posted in History of Science on April 2, 2025
-Bill Storage, Apr 2, 2025
On February 11, 2025, the American Federation of Government Employees (AFGE) staged a “Rally to Save the Civil Service” at the U.S. Capitol. The event aimed to protest proposed budget cuts and personnel changes affecting federal agencies under the Trump administration. Notable attendees included Senators Brian Schatz (D-HI) and Chris Van Hollen (D-MD), and Representatives Donald Norcross (D-NJ) and Maxine Dexter (D-OR).
Dexter took the mic and said that “we have to fuck Trump.” Later Norcross led a “Fuck Trump” chant. The senators and representatives then joined a song with the refrain, “We want Trump in jail.” “Fuck Donald Trump and Elon Musk,” added Rep. Mark Pocan (D-WI).
This sort of locution might be seen as a paradigmatic example of free speech and authenticity in a moment of candid frustration, devised to align the representatives with a community that is highly critical of Trump. On this view, “Fuck Trump” should be understood within the context of political discourse and rhetorical appeal to a specific audience’s emotions and cultural values.
It might also be seen as a sad reflection of how low the Democratic Party has sunk and how low the intellectual bar has dropped to become a representative in the US congress.
I mostly write here about the history of science, more precisely, about History of Science, the academic field focused on the development of scientific knowledge and the ways that scientific ideas, theories, and discoveries have evolved over time. And how they shape and are shaped by cultural, social, political, and philosophical contexts. I held a Visiting Scholar appointment in the field at UC Berkeley for a few years.
The Department of the History of Science at UC Berkeley was created in 1960. There in 1961, Thomas Kuhn (1922 – 1996) completed the draft of The Structure of Scientific Revolutions, which very unexpectedly became the most cited academic book of the 20th century. I was fortunate to have second-hand access to Kuhn through an 18-year association with John Heilbron (1924 – 2023), who, outside of family, was by far the greatest influence on what I spend my time thinking about. John, Vice-Chancellor Emeritus of the UC System and senior research fellow at Oxford, was Kuhn’s grad student and researcher while Kuhn was writing Structure.
I want to discuss here the uncannily direct ties between Thomas Kuhn’s analysis of scientific revolutions and Rep. Norcross’s chanting “Fuck Trump,” along with two related aspects of the Kuhnian aftermath. The second is academic precedents that might be seen as giving justification to Norcross’s pronouncements. Third is the decline in academic standards over the time since Kuhn was first understood to be a validation of cultural relativism. To make this case, I need to explain why Thomas Kuhn became such a big deal, what relativism means in this context, and what Kuhn had to do with relativism.
To do that I need to use the term epistemology. I can’t do without it. Epistemology deals with questions that were more at home with the ancient Greeks than with modern folk. What counts as knowledge? How do we come to know things? What can be known for certain? What counts as evidence? What do we mean by probable? Where does knowledge come from, and what justifies it?
These questions are key to History of Science because science claims to have special epistemic status. Scientists and most historians of science, including Thomas Kuhn, believe that most science deserves that status.
Kernels of scientific thinking can be found in the ancient Greeks and Romans and sporadically through the Middle Ages. Examples include Adelard of Bath, Roger Bacon, John of Salisbury, and Averroes (Ibn Rushd). But prior to the Copernican Revolution (starting around 1550 and exploding under Galileo, Kepler, and Newton) most people were happy with the idea that knowledge was “received,” either through the ancients or from God and religious leaders, or from authority figures of high social status. A statement or belief was considered “probable”, not if it predicted a likely future outcome but if it could be supported by an authority figure or was justified by received knowledge.
Scientific thinking, roughly after Copernicus, introduced the radical notion that the universe could testify on its own behalf. That is, physical evidence and observations (empiricism) could justify a belief against all prior conflicting beliefs, regardless of what authority held them.
Science, unlike the words of God, theologians, and kings, does not deal in certainty, despite the number of times you have heard the phrase “scientifically proven fact.” There is no such thing. Proof is in the realm of math, not science. Laws of nature are generalizations about nature that we have good reason to act as if we know them to be universally and timelessly true. But they are always contingent. 2 + 2 is always 4, in the abstract mathematical sense. Two atoms plus two atoms sometimes makes three atoms. It’s called fission or transmutation. No observation can ever show 2 + 2 = 4 to be false. In contrast, an observation may someday show E = MC2 to be false.
Science was contagious. Empiricism laid the foundation of the Enlightenment by transforming the way people viewed the natural world. John Locke’s empirical philosophy greatly influenced the foundation of the United States. Empiricism contrasts with rationalism, the idea that knowledge can be gained by shear reasoning and through innate ideas. Plato was a rationalist. Aristotle thought Plato’s rationalism was nonsense. His writings show he valued empiricism, though was not a particularly good empiricist (“a dreadfully bad physical scientist,” wrote Kuhn). 2400 years ago, there was tension between rationalism and empiricism.
The ancients held related concerns about the contrast between absolutism and relativism. Absolutism posits that certain truths, moral principles, and standards are universally and timelessly valid, regardless of perspectives, cultures, or circumstances. Relativism, in contrast, holds that truth, morality, and knowledge are context-sensitive and are not universal or timeless.
In Plato’s dialogue, Theaetetus, Plato, examines epistemological relativism by challenging his adversary Protagoras, who asserts that truth and knowledge are not absolute. In Theaetetus Socrates, Plato’s mouthpiece, asks, “If someone says, ‘This is true for me, but that is true for you,’ then does it follow that truth is relative to the individual?”
Epistemological relativism holds that truth is relative to a community. It is closely tied to the anti-enlightenment romanticism that developed in the late 1700s. The romantics thought science was spoiling the mystery of nature. “Our meddling intellect mis-shapes the beauteous forms of things: We murder to dissect,” wrote Wordsworth.
Relativism of various sorts – epistemological, moral, even ontological (what kinds of things exist) – resurged in the mid 1900s in poststructuralism and postmodernism. I’ll return to postmodernism later.
The contingent nature of scientific beliefs (as opposed to the certitude of math), right from the start in the Copernican era, was not seen by scientists or philosophers as support for epistemological relativism. Scientists – good ones, anyway – hold it only probable, not certain, that all copper is conductive. This contingent state of scientific knowledge does not, however, mean that copper can be conductive for me but not for you. Whatever evidence might exist for the conductivity of copper, scientists believe, can speak for itself. If we disagreed about conductivity, we could pull out an Ohmmeter and that would settle the matter, according to scientists.
Science has always had its enemies, at times including clerics, romantics, Luddites, and environmentalists. Science, viewed as an institution, could be seen as the monster that spawned atomic weapons, environmental ruin, stem cell hubris, and inequality. But those are consequences of science, external to its fundamental method. They don’t challenge science’s special epistemic status, but epistemic relativists do.
Relativism about knowledge – epistemological relativism – gained steam in the 1800s. Martin Heidegger, Karl Marx (though not intentionally), and Sigmund Freud, among others, brought the idea into academic spheres. While moral relativism and ethical pluralism (likely influenced by Friedrich Nietzsche) had long been in popular culture, epistemological relativism was sealed in Humanities departments, apparently because the objectivity of science was unassailable.
Enter Thomas Kuhn, Physics PhD turned historian for philosophical reasons. His Structure was originally published as a humble monograph in International Encyclopedia of Unified Science, then as a book in 1962. One of Kuhn’s central positions was that evidence cannot really settle non-trivial scientific debates because all evidence relies on interpretation. One person may “see” oxygen in the jar while another “sees” de-phlogisticated air. (Phlogiston was part of a theory of combustion that was widely believed before Antoine Lavoisier “disproved” it along with “discovering” oxygen.) Therefore, there is always a social component to scientific knowledge.
Kuhn’s point, seemingly obvious and innocuous in retrospect, was really nothing new. Others, like Michael Polanyi, had published similar thoughts earlier. But for reasons we can only guess about in retrospect, Kuhn’s contention that scientific paradigms are influenced by social, historical, and subjective factors was just the ammo that epistemological relativism needed to escape the confines of Humanities departments. Kuhn’s impact probably stemmed from the political climate of the 1960s and the detailed way he illustrated examples of theory-laden observations in science. His claim that, “even in physics, there is no standard higher than the assent of the relevant community” was devoured by socialists and relativists alike – two classes with much overlap in academia at that time. That makes Kuhn a relativist of sorts, but he still thought science to be the best method of investigating the natural world.
Kuhn argued that scientific revolutions and paradigm shifts (a term coined by Kuhn) are fundamentally irrational. That is, during scientific revolutions, scientific communities depart from empirical reasoning. Adherents often defend their theories illogically, discounting disconfirming evidence without grounds. History supports Kuhn on this for some cases, like Copernicus vs. Ptolemy, Einstein vs. Newton, quantum mechanics vs. Einstein’s deterministic view of the subatomic, but not for others like plate tectonics and Watson and Crick’s discovery of the double-helix structure of DNA, where old paradigms were replaced by new ones with no revolution.
The Strong Programme, introduced by David Bloor, Barry Barnes, John Henry and the Edinburgh School as Sociology of Scientific Knowledge (SSK), drew heavily on Kuhn. It claimed to understand science only as a social process. Unlike Kuhn, it held that all knowledge, not just science, should be studied in terms of social factors without privileging science as a special or uniquely rational form of knowledge. That is, it denied that science had a special epistemic status and outright rejected the idea that science is inherently objective or rational. For the Strong Programme, science was “socially constructed.” The beliefs and practices of scientific communities are shaped solely by social forces and historical contexts. Bloor and crew developed their “symmetry principle,” which states that the same kinds of causes must be used to explain both true and false scientific beliefs.
The Strong Programme folk called themselves Kuhnians. What they got from Kuhn was that science should come down from its pedestal, since all knowledge, including science, is relative to a community. And each community can have its own truth. That is, the Strong Programmers were pure epistemological relativists. Kuhn repudiated epistemological relativism (“I am not a Kuhnian!”), and to his chagrin, was still lionized by the strong programmers. “What passes for scientific knowledge becomes, then, simply the belief of the winners. I am among those who have found the claims of the strong program absurd: an example of deconstruction gone mad.” (Deconstruction is an essential concept in postmodernism.)
“Truth, at least in the form of a law of noncontradiction, is absolutely essential,” said Kuhn in a 1990 interview. “You can’t have reasonable negotiation or discourse about what to say about a particular knowledge claim if you believe that it could be both true and false.”
No matter. The Strong Programme and other Kuhnians appropriated Kuhn and took it to the bank. And the university, especially the social sciences. Relativism had lurked in academia since the 1800s, but Kuhn’s scientific justification that science isn’t justified (in the eyes of the Kuhnians) brought it to the surface.
Herbert Marcuse, ” Father of the New Left,” also at Berkeley in the 1960s, does not appear to have had contact with Kuhn. But Marcuse, like the Strong Programme, argued that knowledge was socially constructed, a position that Kuhnians attributed to Kuhn. Marcuse was critical of the way that Enlightenment values and scientific rationality were used to legitimize oppressive structures of power in capitalist societies. He argued that science, in its role as part of the technological apparatus, served the interests of oppressors. Marcuse saw science as an instrument of domination rather than emancipation. The term “critical theory” originated in the Frankfurt School in the early 20th century, but Marcuse, once a main figure in Frankfurt’s Institute for Social Research, put Critical Theory on the map in America. Higher academics began its march against traditional knowledge, waving the banners of Marcusian cynicism and Kuhnian relativism.
Postmodernism means many things in different contexts. In 1960s academia, it referred to a reaction against modernism and Enlightenment thinking, particularly thought rooted in reason, progress, and universal truth. Many of the postmodernists saw in Kuhn a justification for certain forms of both epistemic and moral relativism. Prominent postmodernists included Jean-François Lyotard, Michel Foucault, Jean Baudrillard, Richard Rorty, and Jacques Derrida. None of them, to my knowledge, ever made a case for unqualified epistemological relativism. Their academic intellectual descendants often do.
20th century postmodernism had significant intellectual output, a point lost on critics like Gross and Levitt (Higher Superstition, 1994) and Dinesh De Souza. Derrida’s application of deconstruction of written text took hermeneutics to a new level and has proved immensely valuable to analysis of ancient texts, as has the reader-response criticism approach put forth by Louise Rosenblatt (who was not aligned with the radical skepticism typical of postmodernism) and Jacques Derrida, and embraced by Stanley Fish (more on whom below). All practicing scientists would benefit from Richard Rorty’s elaborations on the contingency of scientific knowledge, which are consistent with those held by Descartes, Locke, and Kuhn.
Michel Foucault attacked science directly, particularly psychology and, oddly, from where we stand today, sociology. He thought those sciences constructed a specific normative picture of what it means to be human, and that the farther a person was from the idealized clean-cut straight white western European male, the more aberrant those sciences judged the person to be. Males, on Foucault’s view, had repressed women for millennia to construct an ideal of masculinity that serves as the repository of political power. He was brutally anti-Enlightenment and was disgusted that “our discourse has privileged reason, science, and technology.” Modernity must be condemned constantly and ruthlessly. Foucault was gay, and for a time, he wanted sex to be the center of everything.
Foucault was once a communist. His influence on identity politics and woke ideology is obvious, but Foucault ultimately condemned communism and concluded that sexual identity was an absurd basis on which to form one’s personal identity.
Rosenblatt, Rorty, Derrida, and even at times Foucault, despite their radical positions, displayed significant intellectual rigor. This seems far less true of their intellectual offspring. Consider Sandra Harding, author of “The Gender Dimension of Science and Technology” and consultant to the U.N. Commission on Science and Technology for Development. Harding argues that the Enlightenment resulted in a gendered (male) conception of knowledge. She wrote in The Science Question in Feminism that it would be “illuminating and honest” to call Newton’s laws of motion “Newton’s rape manual.”
Cornel West, who has held fellowships at Harvard, Yale, Princeton, and Dartmouth, teaches that the Enlightenment concepts of reason and of individual rights, which were used since the Enlightenment were projected by the ruling classes of the West to guarantee their own liberty while repressing racial minorities. Critical Race Theory, the offspring of Marcuse’s Critical Theory, questions, as stated by Richard Delgado in Critical Race Theory, “the very foundations of the liberal order, including equality theory, legal reasoning, Enlightenment rationalism, and neutral principles of constitutional law.”
Allan Bloom, a career professor of Classics who translated Plato’s Republic in 1968, wrote in his 1987 The Closing of the American Mind on the decline of intellectual rigor in American universities. Bloom wrote that in the 1960s, “the culture leeches, professional and amateur, began their great spiritual bleeding” of academics and democratic life. Bloom thought that the pursuit of diversity and universities’ desire to increase the number of college graduates at any cost undermined the outcomes of education. He saw, in the 1960s, social and political goals taking priority over the intellectual and academic purposes of education, with the bulk of unfit students receiving degrees of dubious value in the Humanities, his own area of study.
At American universities, Marx, Marcuse, and Kuhn were invoked in the Humanities to paint the West, and especially the US, as cultures of greed and exploitation. Academia believed that Enlightenment epistemology and Enlightenment values had been stripped of their grandeur by sound scientific and philosophical reasoning (i.e. Kuhn). Bloom wrote that universities were offering students every concession other than education. “Openness used to be the virtue that permitted us to seek the good by using reason. It now means accepting everything and denying reason’s power,” wrote Bloom, adding that by 1980 the belief that truth is relative was essential to university life.
Anti-foundationalist Stanley Fish, Visiting Professor of Law at Yeshiva University, invoked Critical Theory in 1985 to argue that American judges should think of themselves as “supplementers” rather than “textualists.” As such, they “will thereby be marginally more free than they otherwise would be to infuse into constitutional law their current interpretations of our society’s values.” Fish openly rejects the idea of judicial neutrality because interpretation, whether in law or literature, is always contingent and socially constructed.
If Bloom’s argument is even partly valid, we now live in a second or third generation of the academic consequences of the combined decline of academic standards and the incorporation of moral, cultural, and epistemological relativism into college education. We have graduated PhDs in the Humanities, educated by the likes of Sandra Harding and Cornel West, who never should have been in college, and who learned nothing of substance there beyond relativism and a cynical disgust for reason. And those PhDs are now educators who have graduated more PhDs.
Peer reviewed journals are now being reviewed by peers who, by the standards of three generations earlier, might not be qualified to grade spelling tests. The academic products of this educational system are hired to staff government agencies, HR departments, and to teach school children Critical Race Theory, Queer Theory, and Intersectionality – which are given the epistemic eminence of General Relativity – and the turpitude of national pride and patriotism.
An example, with no offense intended to those who call themselves queer, would be to challenge the epistemic status of Queer Theory. Is it parsimonious? What is its research agenda? Does it withstand empirical scrutiny and generate consistent results? Do its theorists adequately account for disconfirming evidence? What bold hypothesis in Queer Theory makes a falsifiable prediction?
Herbert Marcuse’s intellectual descendants, educated under the standards detailed by Bloom, now comprise progressive factions within the Democratic Party, particularly those advocating socialism and Marxist-inspired policies. The rise of figures like Bernie Sanders, Alexandria Ocasio-Cortez, and others associated with the “Democratic Socialists of America” reflects a broader trend in American politics toward embracing a combination of Marcuse’s critique of capitalism, epistemic and moral relativism, and a hefty decline in academic standards.
One direct example is the notion that certain forms of speech including reactionary rhetoric should not be tolerated if they undermine social progress and equity. Allan Bloom again comes to mind: “The most successful tyranny is not the one that uses force to assure uniformity but the one that removes the awareness of other possibilities.”
Echoes of Marcuse, like others of the 1960s (Frantz Fanon, Stokely Carmichael, the Weather Underground) who endorsed rage and violence in anti-colonial struggles, are heard in modern academic outrage that is seen by its adherents as a necessary reaction against oppression. Judith Butler of UC Berkeley, who called the October 2023 Hamas attacks an “act of armed resistance,” once wrote that “understanding Hamas, Hezbollah as social movements that are progressive, that are on the left, that are part of a global left, is extremely important.” College students now learn that rage is an appropriate and legitimate response to systemic injustice, patriarchy, and oppression. Seing the US as a repressive society that fosters complacency toward the marginalization of under-represented groups while striving to impose heteronormativity and hegemonic power is, to academics like Butler, grounds for rage, if not for violent response.
Through their college educations and through ideas and rhetoric supported by “intellectual” movements bred in American universities, politicians, particularly those more aligned with relativism and Marcuse-styled cynicism, feel justified in using rhetorical tools born of relaxed academic standards and tangential admissions criteria.
In the relevant community, “Fuck Trump” is not an aberrant tantrum in an echo chamber but a justified expression of solidary-building and speaking truth to power. But I would argue, following Bloom, that it reveals political retardation originating in shallow academic domains following the deterioration of civic educational priorities.
Examples of such academic domains serving as obvious predecessors to present causes at the center of left politics include:
- 1965: Herbert Marcuse (UC Berkeley) in Repressive Tolerance argues for intolerance toward prevailing policies, stating that a “liberating tolerance” would consist of intolerance to right-wing movements and toleration of left-wing movements. Marcuse advanced Critical Theory and a form of Marxism modified by genders and races replacing laborers as the victims of capitalist oppression.
- 1971: Murray Bookchin’s (Alternative University, New York) Post-Scarcity Anarchism followed by The Ecology of Freedom (1982) introduce the eco-socialism that gives rise to the Green New Deal.
- 1980: Derrick Bell’s (New York University School of Law) “Brown v. Board of Education and the Interest-Convergence Dilemma” wrote that civil rights advance only when they align with the interests of white elites. Later, Bell, Kimberlé Crenshaw, and Richard Delgado (Seattle University) develop Critical Race Theory, claiming that “colorblindness” is a form of oppression.
- 1984: Michel Foucault’s (Collège de France) The Courage of Truth addresses how individuals and groups form identities in relation to truth and power. His work greatly informs Queer Theory, post-colonial ideology, and the concept of toxic masculinity.
- 1985: Stanley Fish (Yeshiva University) and Thomas Grey (Stanford Law School) reject judicial neutrality and call for American judges to infuse into constitutional law their current interpretations of our society’s values.
- 1989: Kimberlé Crenshaw of Columbia Law School introduced the concept of Intersectionality, claiming that traditional frameworks for understanding discrimination were inadequate because they overlooked the ways that multiple forms of oppression (e.g., race, gender, class) interacted.
- 1990: Judith Butler’s (UC Berkeley) Gender Trouble introduces the concept of gender performativity, arguing that gender is socially constructed through repeated actions and expressions. Butler argues that the emotional well-being of vulnerable individuals supersedes the right to free speech.
- 1991: Teresa de Lauretis of UC Santa Cruz: introduced the term “Queer Theory” to challenge traditional understandings of gender and sexuality, particularly in relation to identity, norms, and power structures.
Marcusian cynicism might have simply died an academic fantasy, as it seemed destined to do through the early 1980s, if not for its synergy with the cultural relativism that was bolstered by the universal and relentless misreading and appropriation of Thomas Kuhn that permeated academic thought in the 1960s through 1990s. “Fuck Trump” may have happened without Thomas Kuhn through a different thread of history, but the path outlined here is direct and well-travelled. I wonder what Kuhn would think.
Extraordinary Popular Miscarriages of Science, part 4 – Marxism
Posted in History of Science on February 24, 2024
Marxists are ignorant. In a very literal sense. They are capable of willfully ignoring the universe of evidence showing the fundamentals of Marxian thought to have been disproved before Marx’s ink dried. Maybe some of them are just childish or stupid. They can be excused. But most Marxists are intelligent adults who have made a bad faith decision to pretend that their theory is not disproved by every semiconductor in their cars and mobile phones, and every LED light bulb in existence. Every Marxist book denouncing private property is copyrighted. They want us to free ourselves of the restraints that made freedom possible.

Marx was a spoiled lout who never worked an honest day in his life, rarely repaid his unending loans, disparaged his creditors, blamed his infant son’s death on capitalism while he remained drunk and lived in squalor, abused his maid – whom he never paid a cent – and described Ferdinand Lassalle as “the Jewish Nigger Lassalle.” In his essay “On the Jewish Question,” Marx wrote that “The social emancipation of the Jew is the emancipation of society from Jewishness.” There’s lots more where those come from.
Marx wanted “… not to improve the existing society but to found a new one.” His writings for the Central Committee of the Communist League was devoured and put into practice by Lenin, resulting in genocide. His thought fueled totalitarian despots like Stalin, Mao, and Pol Pot, and the attempts to implement his poorly expressed ideas caused mass starvation, cultural stagnation, and tens of millions of deaths. Yet he probably has more influence on academic thought than Galileo, Newton, and Einstein. Pillars of the academic left are quick to point out that Marx would be horrified to find his words being used to defend the use of state power against individuals. Yet those words were quoted liberally by Lenin in defense of autocratic power and murder. Those self-important academic indoctrinators somehow imagine that there could be a different interpretation of Marx by the average power-hungry psychopath.
Marx was a miserable person, in every sense. His Doctrine of Misery is endlessly analyzed by intellectuals, though they cannot agree on what it is exactly. All boats simply cannot rise under Marxism. It’s a zero sum game. Where Marx occasionally leans toward admitting that all boats could in theory rise, his complaint reduces to envy. Better for all to starve than for some to have burgers while others eat fillet mignon.
“Thus although the enjoyments of the workers have risen, the social satisfaction that they give has fallen in comparison with the increased enjoyments of the capitalist, which are inaccessible to the worker.”
Marx’s poetry sheds light on his self-image. In one he penned, “with disdain I will throw my gauntlet full in the face of the world.” That poem goes on to add (translated):
Then will I wander god-like and victorious
through the ruins of the world.
and, giving my words an active force,
I will feel equal to the Creator.”
Marx was irresponsible, egotistical, and a thoroughly despicable human. But none of that makes Marx a bad scientist, or Marxism a bad science.
So let me start over.
Marx was not the first to embrace the Labor Theory of Value. David Ricardo and Adam Smith preceded him there. Marx was more certain than Smith that value was solely determined by the amount of manual labor it took to produce a thing plus the cost of the raw materials that went into it. Given his obscurant writing style, Marx was surprisingly clear in describing his own theory of value:
“The determination of price by the cost of production is equivalent to the determination of price by the labor time necessary for the manufacture of a commodity, for the cost of production consists of 1) raw materials and depreciation of instruments, that is, of industrial products the production of which has cost a certain amount of labor days and which, therefore, represent a certain amount of labor time, and 2) direct labor, the measure of which is, precisely, time.” – Wage Labor and Capital, 1847.
Marx undoubtedly had access to the first wave of the Austrian school of economics, but he ignored it rather than disputing it – rather like his present academic progenitors. Marx didn’t invite criticism or disputation and rarely responded to his critics. Instead he continued for decades to spew more from the same fountain, muddying the water to make it look deep. When Engels suggested to Marx that his theory of value might be misunderstood by those not accustomed to abstract thought, Marx replied, in his usual style rather than with the relative clarity of the above definition:
“. . . the conversion of surplus value into profit … presupposes a previous account of the process of circulation of capital, since the turnover of capital, etc., plays a part here. Hence this matter can be set forth only in the third book…. Here it will be shown whence the way of thinking of the philistine and the vulgar economist derives, namely, from the fact that only the immediate form in which relationships appear is always reflected in their brain, and not their inner connections. If the latter were the case, moreover, what would be the need for a science at all? If I were to silence all such objections in advance, I should ruin the whole dialectical method of development. On the contrary, this method has the advantage of continually setting traps for these fellows which provoke them to untimely demonstrations of their asininity.”
I enjoy the above quote, because in it he obfuscates his own defense of obfuscation. Some might be wondering what this idiot could really mean. The modern Marxist invariably responds that if you don’t agree with Marx, you’re not intelligent enough to understand him. Marx was no idiot. He was a skilled rhetorician who had terrible values and was profoundly dishonest. He wrote gibberish for the same reason that social scientists write it – to sound intelligent in the midst of others doing the same thing and to dupe impressionable youth. He wrote this intellectual twaddle on purpose.
Intellectuals, particularly academic ones, as Friedrich Hayek often noted, tend to overvalue intellectualism. But pseudo-intellectuals overvalue pseudo-intellectuals even more, and they have come to occupy of our academic institutions.
A favorite passage of mine comes from the Communist Manifesto, written by Marx and Engels in 1848:
“It has been objected that upon the abolition of private property, all work will cease, and universal laziness will overtake us. According to this, bourgeois society ought long ago to have gone to the dogs through sheer idleness; for those of its members who work, acquire nothing, and those who acquire anything do not work. The whole of this objection is but another expression of the tautology: that there can no longer be any wage-labor when there is no longer any capital.”
Charitably read, Marx means rich folk don’t know what work is. He seems to have no clue that some of the bourgeois’ wealth stems from putting capital at risk to predict future demand, which may involve some sort of work, sweat and misery. In fact, Marx does have such a clue, but he doesn’t want his reader to. Go back to writing poetry, you sot. It was bad, but at least it was honest.
Why should I bother analyzing Marxism as a science if no one today thinks Marxism to be a science? Ah, but they do. They just don’t write it down. It remains implicit.
Astrology and Creation Science do microscopically small harm compared to the science of Marxism. Academics routinely describe our era as “Late Capitalism,” seemingly a blind-faith acceptance of Marx’s assertion that capitalism would give rise to socialism and then communism. Thus late capitalism seems for them to be not merely an empirical fact but something axiomatic like a law of nature. Everything that comes out of university “theory” disciplines reeks of Marx’s obscurant form of expression.
Marxist-isms include modes of production, relations of production, wage-labor, social production, equivalent form, cultural hegemony, social consciousness, base and superstructure, discourse, commodity fetish, social division of labor, political economy, relative deprivation, and my favorite, theory and practice. That last phrase is so ubiquitous that, even in disciplines that feign being objective, it is shamelessly vomited out as if it would be vulgar to ask if any evidence validating said theory was ever collected prior to its being put into practice.
Nothing is really wrong with many of Marxism’s terms. Cultural hegemony can, if applied well, point to something observable in the real world. But academics across the social sciences, unfortunately often including economics, pack Marxian phraseology so tightly that not even vague meaning can be extracted.
If you’re not familiar with Marx, consider a few lines from the preface to A Contribution to the Critique of Political Economy before I move on to the havoc he has wreaked or wrought upon academia:
In the social production of their life, men enter into definite relations that are indispensable and independent of their will, relations of production which correspond to a definite stage of development of their material productive forces. The sum total of these relations of production constitutes the economic structure of society, the real foundation, on which rises a legal and political superstructure and to which correspond definite forms of social consciousness.
The mode of production of material life conditions the social, political and intellectual life process in general. It is not the consciousness of men that determines their being, but, on the contrary, their social being that determines their consciousness.
At a certain stage of their development, the material productive forces of society come in conflict with the existing relations of production, or — what is but a legal expression for the same thing — with the property relations within which they have been at work hitherto. From forms of development of the productive forces these relations turn into their fetters.
Obscurantism: muddying the water to make it look deep. He sneers at the reader, like his social-science descendants. The wording limits further inquiry to shield the writer from having the vacuousness of his content exposed. As Schopenhauer wrote of Hegel in On the Basis of Morality, “a colossal piece of mystification … by the most outrageous misuse of language, putting in its place the hollowest, most senseless, thoughtless, and, as is confirmed by its success, most stupefying verbiage” [emphasis added]. While Marx criticized Hegel’s philosophy, he loved his dialectical method and obscurant manner of expression. Such expression may work for abstract philosophical concepts but does not work in the realm of evidence, empiricism, theory selection, and theory confirmation.
Skip forward 150 years and consider the writings of modern academic Marxists, some who claim that title, others not. Judith Butler is the poster child for writing bullshit, but her stench is only slightly worse than most. Here’s her celebrated classic from the journal Diacritics in 1997:
The move from a structuralist account in which capital is understood to structure social relations in relatively homologous ways to a view of hegemony in which power relations are subject to repetition, convergence, and rearticulation brought the question of temporality into the thinking of structure, and marked a shift from a form of Althusserian theory that takes structural totalities as theoretical objects to one in which the insights into the contingent possibility of structure inaugurate a renewed conception of hegemony as bound up with the contingent sites and strategies of the rearticulation of power.
It’s not impossible to decipher this, but I think my above criticism stands. There is much less there than meets the eye. Butler replied to her critics that demands for intelligibility are aggressions intended to force her into conformity and that her shockingly radical thought simply cannot be contained by ordinary language. Mind you, Butler is not a Marxist. She just writes like one. The journal International Socialism draws a line: “Judith Butler is not a Marxist, but many of her concerns are ours too.” See also: Judith Butler’s Scientific Revolution: Foundations for a Transsexual Marxism.
Radical thought, Butler teaches, simply can’t be expressed clearly. So, when in the course of human events, it becomes necessary for one people to dissolve the political bands which have connected them with another, their only recourse shall be to rearticulate their ideological apparatus to reject structural totalities as theoretical objects with consequent commutation to those in which the insights into the contingent possibility of structure inaugurate a renewed conception of hegemony, not conceived in liberty, but bound up with the contingent strategies of the rearticulation of power.
Karl Marx, this bullshit is all on you. Your fault. I hope your hell is to listen to Judith Butler on endless replay. Better yet, Judith Butler doing an impersonation of Hegel. But then you’d probably like that. So instead, may you listen to Hemingway tape loops. Hemingway leaned Marxist. Yes. I know that. He didn’t write Marxist. He wrote well. It’s simple. Everyone knows it. I like Hemingway. The sun also rises. Isn’t it pretty to think so?
I’m going to need to start again…
Marxism: Claims to Scientific Status
Karl Marx was keenly interested in science. He claimed scientific objectivity for his theory. In Capital, for example, Marx compares himself to physicists and biologists, repeatedly characterizing his method as scientific in the same sense as those disciplines. Today’s Marxism also holds that it is a science. Marxists.org teaches that “Marxism is understood as scientific in the sense that it has understood correctly the laws of motion of a historical process taking place independently of men’s will.” It adds that all that is left for Marxists to do “is to fill in the details, to apply the scientific understanding of history.” Marxist.com (are they the for-profit alternative to Marxists.org?) teaches that “Marxism is distinguished by utilising all the developments of scientific method and historical analysis.”
My critique of modern Marxist science deals with Marxism, not Marx. Marxism relates to Marx in the way that Kuhnianism relates to Kunn: “I am not a Kuhnian,” Kuhn wrote.
“I am not a Marxist,” Marx wrote in an 1883 letter to the French Marxists, Paul Lafargue and Jules Guesde. Yet it seems impossible to leave Karl Marx out of discussion of the scientific status of Marxism or Marxian thought, because today’s Marxism still speaks in the language of Marx and Hegel. See above.
I won’t argue that Hegel has no value. But Hegel has no scientific value. Marx and Marxists put their science in the language of Hegel. See the problem?
“Reason… is Substance, as well as Infinite Power; its own Infinite Material underlying all the natural and spiritual life which it originates, as also the Infinite Form, – that which sets this Material in motion” – Hegel, Lectures on the Philosophy of World History.
Marx’s non-standard conception of evidence and scientific method is revealed in his writing:
“Scientific truth is always a paradox, if judged by everyday experience, which catches only the delusive appearance of things.” – Value, Price, and Profit, 1865
“All science would be superfluous, if the appearance, the form, and the nature of things were wholly identical.” – Capital, 1909
[Samuel Bailey] confuses the form of capital with capital itself – Capital, 1909
While Marx claimed to be following Darwin in his approach, quotes like the above make Marx seem to operate in the Platonic realm, not the scientific. Like Plato, Rousseau, and Descartes, Marx is entrenched in Theory, the sort of theory that no amount of evidence can refute, the world of Judith Butler.
Criteria of Scientificness
From the perspective of history and philosophy of science, in asking whether Marxism is good science, we need to look at its goals, claims, methods, research agenda, and explanatory ambitions. Marxism makes bold epistemic claims and gushes with explanatory aspirations. Its predictive success is an entirely different matter, and one that grabbed young Karl Popper’s attention.
Popper is the philosopher science, mentioned in the last few posts, most celebrated by modern scientists. He treated scientists as almost heroic. He thought that they court refutation by making falsifiable claims and predictions while continually putting their theories on trial. Lakatos and Popper used the term rational reconstruction to describe a hypothetical, abbreviated route between formulation of a theory and its justification. I.e., what matters to science is not the actual historical route with all the wrong turns and dead ends, but a route that could logically have been taken. As such, rational reconstruction lets us verify or vindicate theories after the fact.
Kuhn strongly disagreed with Popper that scientists put their theories on trial. Kuhn also saw it as a problem that science is taught as if the process of theory discovery and development was actually its rational reconstruction.
As a boy Popper had worked for the Communist Party and toyed with Marxism. Quickly disillusioned, he later compared the claims of Marx and Freud with those of Einstein. Popper concluded that Einstein made bold, falsifiable predictions while Marx and Freud made mostly vague predictions. Further, Einstein’s theories predicted things that defied common sense. The claims of Einstein’s theories, though unprovable for all cases, could be tested and found false in some cases, and therefore the theories could be disproven. If the rays from a distant star did not bend around the sun – a very nonintuitive effect – Einstein’s theory of gravity would be proven wrong. Was there an analog in the theories of Marx and Freud?
Marxism and Freudian psychology were held by the Vienna Circle, where Popper came of age, to be the scientific descendants of Darwinism. Popper thought Freud explained too many results – aggressive personality, shy personality, or comedian, for example – with the same cause, an abusive mother, for example. Popper thought that evidence that confirmed a theory was too easy to come by, but offered that “The criterion of the scientific status of a theory is its falsifiability” (Logic of Scientific Discovery, 1934).
He thought the Marxists made some falsifiable predictions, like that a revolution would occur in an industrialized country. But, Popper thought, those predictions were in fact falsified. Marxist predictions failed time after time. Thomas Sowell reports 40 failed predictions (yet see, e.g., “Capitalism is Unfolding Exactly as Karl Marx Predicted”). Revolutions occurred in peasant lands and not in industrial ones. Yet, in Popper’s view, on each such occasion, a post hoc revision was made by the Marxists to save their theory. The Marxists offered that if they had remembered to take into account the charisma of Lenin, then of course they would have predicted a revolution in Russia. Popper thought the Marxists continually modified their theories in the face of counterevidence, every time they were found to make wrong predictions. The result was that Marxist theories were also immune to possible falsification. For Popper, Marxism was pseudoscience.
Responses to Popper
Maurice Cornforth’s 1968 Reply to Dr. Karl Popper’s Refutations of Marxism consumes 381 pages and is similar to other Marxist responses. It contains the word evidence 14 times, theory 338 times, and revolution 170 times. In my view, a look at the points on which Conforth and Popper agree and disagree confirms Popper’s conclusions. In the passage below, Conforth agrees that science proceeds by making falsifiable theories but then adds that every scientific theory consists of more than that by resting on its fundamental theory and “is guided by it in its inquiries.”
The scrutiny of Marx’s fundamental ideas about society reveals, then, their scientific character. Dr. Popper’s failure to grasp this fact illustrates his failure, in his published work on scientific method, to grasp more than one single aspect of scientific procedures. He says that science proceeds by making “conjectures” which are “falsifiable”, and then devising all manner of ways of trying to falsify them. So far as it goes, that is true enough. But yet the body of scientific theory consists of more than just a collection of falsifiable conjectures which are variously revised or replaced by other conjectures as falsification actually overtakes them. Every well-developed science rests on its fundamental theory, and is guided by it in its inquiries. This is a feature of science which Dr. Popper never examines — possibly because he distrusts such expressions as “fundamental theory”, which he thinks redolent of pseudo-scientific metaphysics. (Cornforth, 1968)
On Conforth’s last point (resting on its fundamental theory and guided by it in its inquiries) I have two observations. First, a scientific theory does not rest on any particular fundamental theory. Newton’s theory of gravitation is a wrong but good scientific theory, by any standards. The fact that we can judge it wrong in light of the success of Einstein’s theory of gravitation, which is incompatible with Newton’s, does not lessen Newton’s status as a good theory. Its predictive success and explanatory power are incomparable. Newton’s theory of gravitation does not rest on its fundamental theory. It rests on generalizations inferred from evidence, i.e. laws of nature, but it is not self-justifying, which is the most charitable reading of “rest on its fundamental theory” that I can come up with.
Second, what might “guided by it [i.e., its fundamental theory] in its inquiries” mean in a scientific sense? I’m trying to interpret this charitably but am at a loss. It reads like what we see elsewhere in Marx’s and Marxian thought. Popper found “fundamental theory” to be pseudo-scientific metaphysics. Popper reached that conclusion because he couldn’t map those words onto any element or concept in his conception of scientific theories or in a theory of scientific explanations. I can’t, can you?
Private Language
Marxists’ only recourse to this challenge is one that we see often in Marxist responses to its critics: “you just don’t understand.” But it is the duty of Marxists to make sure they’re understood by those they wish to persuade or educate. Otherwise, their literature must be understood as dogma to be accepted by those who take the leap of faith – to believe a priori – and hope that some deeper understanding will follow. That makes Marxism a religion.
Even if such wording maps to specific concepts and the mapping is agreed upon by each Marxist, it exists as private language, and all of Wittgenstein’s concerns apply. Most centrally, if Marxism is in principle incapable of translation into ordinary language, then it can refer only to inner experiences shared by Marxists in isolation from non-Marxists. Again, this is the realm of religion, and Popper’s dogmatism critique still applies, by virtue of both belief system and language. I can find nothing that approaches a rational reconstruction of Marx’s theory or Marxist theory without the Hegelian windiness and circularity. Doctrinal disputes have always plagued Marxism, as reported even by Lenin and Stalin.
In response to Popper’s claim that Marxists continually invent supplemental hypotheses to modify their theory in light of failed predictions, Conforth, as does marxists.org, simply denies that Marxists do this: “the Marxist procedure has never been to invent supplementary hypotheses.”
Conforth admits outright that the theory is broad (vague) enough to accommodate a predicted revolution in England that never happened and an unpredicted in Russia that did happen. If Marxism’s “fundamental theory” is simply that all historical events are explained by class struggle, then the theory is purely explanatory and contains no predictive potential. And therefore, it is not scientific. Conforth argues for the predictive success of Marxism:
We simply examine what has actually happened, which has by no means exceeded the bounds of possibility allowed by the general theory of Marxism, and find that it has led to consequences predictable and accountable within the theory. And similarly with the Russian Revolution. (Cornforth, 1968)
Conforth, unsurprisingly, points out that all scientific theories undergo continual revision. Copernican heliocentrism bears little resemblance to Keplerian heliocentrism. Copernicus’s orbits were circular and still employed Ptolemaic epicycles. Indeed, but heliocentrism always made bold predictions, and when Einstein’s theory of gravitation disagreed with Newton’s revisions of Kepler and Copernicus, Newton’s theory was declared fundamentally wrong but still useful enough to predict the trajectories of spacecraft. Scientists who understand science do not say either that Newtonian mechanics is “true” or that Einstein’s theory is true. Contemporary Marxists may say the same of Marxism. It doesn’t claim truth but merely claims utility. More on Marxism’s utility below in Theory and Practice.
Granting that Marxist theory is not falsified by failed predictions requires us to accept that the theory is vague. Not only does it make vague predictions about revolutions, but sincere attempts at interpreting the theory draw different conclusions about where it sits on individual cases. If science, this seems like bad science. Imre Lakatos mostly argued against the scientificness of Marxism on the grounds of failed predictions. But from another perspective central to Lakatos, Marxism’s research agenda is paper thin. Like that of Creation Science, Marxist research, e.g. Marxist Institute for Research, does not involve increasingly specific subdomains but pedagogy and interpretation of current events (evidence) in light of Marxist theory.
Marxist Explanations
A Marxist might argue that predictive success is less important than explanatory power. Botany, some would say, is a legitimate science but makes relatively few predictions and its value is in its ability to explain the relationships between different species (forms, for the Marxists, kinds, for the Creation Scientists), along with their genetics, physiology and chemical processes. As an example, we might use botany to know what plants can live side by side and how to maximize their yield. Marxism might similarly claim to explain history and economics thereby telling us how to optimize manufacturing, distribution, and the economy in general. But that is not the focus of contemporary Marxism.
What does Marxism explain? Some would say it explains the impact of the ruling class on laborers or that all value derives from labor. But Marxism’s claims that the ruling class abuses workers and that labor is the sole source of value are not what scientists mean by explanations. They are Marxism’s claims of empirical evidence evidence itself – the things we would want a scientific explanation to explain.
There is a constant tension in scientific explanation to avoid going too deep into why questions. Doing so can quickly descend into metaphysics, as noted by the logical positivists and by Popper. But most historians and philosophers of science agree that why questions are still a primary goal of science and scientific explanations. A scientific explanation within Marxism might look at the decline of tire manufacturing in Akron in combination with the inflation-adjusted income of rubber company executives. On Marxists sites and in Marxist literature, studies of that sort are scarce in comparison to big-picture ideological writings denouncing capitalism and calling for a classless society.
Scientific explanations appeal to laws of nature. They historically have resorted to appeals to causation only after, in explaining a phenomenon, exhaustion of attempts to show that deductive logic applied to laws of nature necessitate – confer nomic expectability upon – the phenomenon being explained. In that sense explanation and prediction are mostly symmetrical. You can’t explain what you can’t predict. Alternate version: an economist is someone who can always explain why his last prediction was wrong.
Marx and Marxism use the term “laws of motion” in what seems to be an appeal to the status held by Newtonian mechanics. Kepler’s laws and Newton’s three laws are stated explicitly and concisely. Marx never tells us what his laws of motion are. Nor do more recent Marxists. In Late Capitalism, Ernest Mandel has a chapter titled “The Laws of Motion and the History of Capital.” In it he tells us that Marx “discovered” these laws and that they relate to one of the most complex problems of Marxist theory. Mandel is critical of Marx, and much of the chapter deals with the difference between Marx’s and Althusser’s understandings of markets. But Mandel never states or describes the laws and never bases an explanation of phenomena on the laws. He instead tells us that the dialectic method can explain decisive general connections between empirical material’s constituent abstract elements and Marx’s laws of motion. Here, in my third start on the topic of Marxism, I tried giving honest effort to doing right by Marxism. But this kind of writing calls up another of Schopenhauer’s comments on Hegel: “pseudo-philosophy paralyzing all mental powers, stifling all real thinking.”
Theory and Practice
The phrase Theory and Practice permeates Marxist writing. A charitable interpretation is something along the lines of: we don’t merely advocate this course of action, we put it into practice. But in what sense is that true. As Thomas Sowell points out, Marx’s contribution to economics can be readily summarized as zero: “Capital was a detour into a blind alley.” As for putting the Marxist utopia into practice, evidence suggests the practice doesn’t vindicate the theory. Marxists excel at comparing theoretical Marxism with as-deployed capitalism. Marxist theorists so undervalue evidence that they repeat a phrase attributed to Marx, “theory without practice is sterile,” as if it gives Marxism scientific status. Compare this to a phrase attributed to Immanuel Kant, “theory without evidence is mere intellectual play.” (The fact that both attributions may be spurious is irrelevant to the point.) Practice is not evidence, and, no, this is not merely a matter of translating German into English.
An example of Marx explicitly stating that theory can trump evidence is in an 1868 letter from Marx to Louis Kugelmann:
On the other hand, as you correctly assumed, the history of the theory certainly shows that the concept of the value relation has always been the same — more or less clear, hedged more or less with illusions or scientifically more or less definite. Since the thought process itself grows out of conditions, is itself a natural process, thinking that really comprehends must always be the same, and can vary only gradually, according to maturity of development, including the development of the organ by which the thinking is done. Everything else is drivel.
On Marx’s Labor Theory of Value, we now have the kind and volume of evidence about value that may not have been available to Karl Marx. We can grant Marx but not Marxists this concession. Today, integrated circuits clearly have value far above that of their raw materials and embodied labor. Integrated circuits, among countless other modern objects of consumption – software and data data, for example – are strong evidence that Carl Menger’s definition of value applies and that Karl Marx’s does not.
Value is nothing inherent in goods, no property of them, nor an independent thing existing by itself. It is a judgment economizing men make about the importance of goods at their disposal for the maintenance of their lives and well-being. Hence value does not exist outside the consciousness of men. (Menger, Principles of Economics, 1873)
Independent of accuracy or utility on Austrian economic theory, Menger’s claim that value is the quantitative relationship between requirements for a product and the availability of it is concise, and it is consistent with evidence from retail and wholesale markets. Evidence from modern life suggests that markets are far better at allocating people to production tasks than are individual persons in any role, corporate, governmental or otherwise. When asked what mechanism might in a communist (i.e. Marxist – by 1860 Marx used communism and socialism interchangeably) system to determine production requirements, Marx said “there would however be some sort of plan which would in some unspecified way determine what is really needed” [emphasis added].
History also seems to confirm Menger’s claim that Marx is wrong in believing that the spinning of yarn in a factory is the product of the labor of the operatives. Does Marx believe that systems of factory production are self-organizing?
Self-Organization in Markets
The concept of self-organization seems to me another primary defect of Marxian and Marxist belief. On this topic internal inconsistencies abound. Marx apparently believes that self-organization is possible in industry but impossible in markets. I.e., they deny that markets are emergent entities possessing knowledge about demand that no person holds individually. Likewise, today’s Marxists are perfectly comfortable with the concepts of self-organization, local reduction in entropy, and strong emergence – systems that possess emergent qualities not reduceable to the system’s constituents. Examples include belief in a naturally fined tuned universe, the natural formation of galaxies, and human evolution.
Yet today’s Marxists overwhelmingly reject that markets can know things that a specialist or bureaucrat cannot. Hayek expressed it well: “It is because every individual knows so little and because we rarely know which of us knows best that we trust the independent and competitive effort of many.” This, ironically, shows the capitalist to embrace a sort of collectivism that the modern Marxist, not Marx, rejects. Marxism applies the word collective to all sorts of things, but never to knowledge, perhaps because if they did they might be forced to allow that markets embody collective knowledge – a design without a designer, a design that extracts information from the world that no team of technocrats could acquire.
“Markets don’t solve everything” is a common retort (Robert Reich, 2, 3, 4, 5, 6). No one claims they do.
Conclusion
If Marxism is a science, either as Marx laid it out or as contemporary Marxists interpret it, it is a bad science. It either makes predictions that fail verification, and thus the theory is falsified, or it makes predictions so vague as to not be falsifiable. To the extent that it can be understood, it is internally inconsistent. A lack of precise language makes it difficult to understand, as is confirmed by historical factions and fragmentation of contemporary interpretations. Unlike Creation Science, Marxism generally lacks the trappings of science; it doesn’t publish scientific papers and its research agenda is thin. Its theory of value is inconsistent with pricing and price fluctuation of modern goods. Its arguments and explanations do not meet standard scientific criteria. For me, Marxism’s inconsistency on the tenability of self-organization and emergence shows a level of dogmatism sufficient to classify it as religion. An ugly religion at that. A radical aspect of the emergence after Galileo was the realization that while theories can be underdetermined by evidence, contrary evidence always trumps theory. Evidence is never disproved by theory. Modern Marxists fail to grasp this. Marxism does not merit the epistemic status that society affords to science but that academia grants to Marxism.
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The last capitalist we hang shall be the one who sold us the rope. – Karl Marx
The offspring of privilege have dominated the leadership of Marxist movements from the days of Marx and Engels through Lenin, Mao, Castro, Ho Chi Minh – Thomas Sowell
The Left should put a moratorium on theory. – Richard Rorty
Jordan Peterson’s thought is filled with pseudo-science, bad pop psychology, and deep irrationalism. In other words, he’s full of shit. – Jacobin.com
Prayer may not be very efficient when compared to celestial mechanics, but it surely holds its own vis-a-vis some parts of economics. – Paul Feyerabend
True tragedy occurs when the idea of justice leads to the destruction of higher values – Richard Rorty
The Communist Manifesto, written by two bright and articulate young men without responsibility even for their own livelihoods—much less for the social consequences of their vision—has had a special appeal for successive generations of the same kinds of people. – Thomas Sowell
When I was a child, I spoke as a child, I felt as a child, I thought as a child: now that I have become a man, I put away childish things. 1 Cor 13:11
We require that our theories harmonize in detail with the very wide range of phenomena they seek to explain. We insist that they provide us with useful guidance rather than with rationalizations. – John R. Piece, An Introduction to Information Theory
It may be said of Socialism, therefore, that its friends recommended it as increasing equality, while its foes resisted it as decreasing liberty….The compromise eventually made was one of the most interesting and even curious cases in history. It was decided to do everything that had ever been denounced in Socialism, and nothing that had ever been desired in it…we proceeded to prove that it was possible to sacrifice liberty without gaining equality….In short, people decided that it was impossible to achieve any of the good of Socialism, but they comforted themselves by achieving all the bad. – G.K. Chesterton
Value is nothing inherent in goods, no property of them, nor an independent thing existing by itself. It is a judgment economizing men make about the importance of goods at their disposal for the maintenance of their lives and well-being. Hence value does not exist outside the consciousness of men. – Carl Menger
Popular Miscarriages of Science, part 3 – The Great Lobotomy Rush
Posted in History of Science on January 25, 2024
On Dec. 16, 1960, Dr. Walter Freeman told his 12-year-old patient Howard Dully that he was going to run some tests. Freeman then delivered four electric shocks to Dully to put him out, writing in his surgery notes that three would have been sufficient. Then Freeman inserted a tool resembling an ice pick above Dully’s eye socket and drove it several inches into his brain. Dully’s mother had died five years earlier. His stepmother told Freeman, a psychiatrist, that Dully had attacked his brother, something the rest of Dully’s family later said never happened. It was enough for Freeman to diagnose Dully as schizophrenic and perform another of the thousands of lobotomies he did between 1936 and 1967.
“By some miracle it didn’t turn me into a zombie,” said Dully in 2005, after a two-year quest for the historical details of his lobotomy. His story got wide media coverage, including an NPR story called My Lobotomy’: Howard Dully’s Journey. Much of the media coverage of Dully and lobotomies focused on Walter Freeman, painting Freeman as a reckless and egotistical monster.
Weston State Hospital (Trans-Allegheny Lunatic Asylum), photo courtesy of Tim Kiser
In The Lobotomy Letters: The Making of American Psychosurgery, (2015) Mical Raz asks, “Why, during its heyday was there nearly no objection to lobotomy in the American medical community?” Raz doesn’t seem to have found a satisfactory answer.
(I’m including a lot of in-line references here, not to be academic, but because modern media coverage often disagrees with primary sources and scholarly papers on the dates, facts, and numbers of lobotomy. It appears that most popular media coverage seemed to use other current articles as their sources, rather than going to primary sources. As a trivial example, Freeman’s notes report that in Weston, WV, he did 225 lobotomies in 12 days. The number 228 is repeated in all the press on Howard Dully. This post is on the longer side, because the deeper I dug, the less satisfied I became that we have learned the right lesson from lobotomies.)
A gripping account of lobotomies appeared in Dr. Paul Offit’s (developer of the rotavirus vaccine) 2017 Pandora’s Lab. It tells of a reckless Freeman buoyed by unbridled media praise. Offit’s piece concludes with a warning about wanting quick fixes. If it seems too good to be true, it probably is.
In the 2005 book, The Lobotomist: A Maverick Medical Genius and his Tragic Quest to Rid the World of Mental Illness, Jack El-Hai gave a much more nuanced account, detailing many patients who thought their lobotomies hade greatly improved their lives. El-Hai’s Walter Freeman was on a compassionate crusade to help millions of asylum patients escape permanent incarceration in gloomy state mental institutions. El-Hai documents Freeman’s life-long postoperative commitment to his patients, crisscrossing America to visit the patients that he had crisscrossed America to operate on. Despite performing most of his surgery in state mental hospitals, Freeman always refused to operate on people in prison, against pressure from defense attorneys’ pleas to render convicts safe for release.
Contrasting El-Hai’s relatively kind assessment, the media coverage of Dully aligns well with Offit’s account in Pandora’s Lab. On researching lobotomies, opinions of the medical community, and media coverage, I found I disagreed with Offit’s characterization of the media coverage, more about which below. In all these books I saw signs that lobotomies are a perfect instance of bad science in the sense of what Thomas Kuhn and related thinkers would call bad science, so I want to dig into that here. I first need to expand on Kuhn, his predecessors, and his followers a bit.
Kuhn’s Precursors and the Kuhnian Groupies
Kuhn’s writing, particularly Structure of Scientific Revolutions, was unfortunately ambiguous. His friends, several of whom I was lucky enough to meet, and his responses to his critics tell us that he was no enemy of science. He thought science was epistemically special. But he thought science’s claims to objectivity couldn’t be justified. Science, in Kuhn’s view, was not simply logic applied to facts. In Structure, Kuhn wrote many things that had been said before, though by sources Kuhn wasn’t aware of.
Karl Marx believed that consciousness was determined by social factors and that thinking will always be ideological. Marx denied that what Francis Bacon (1561-1626) had advocated was possible. I.e., we can never intentionally free our minds of the idols of the mind, the prejudices resulting from social interactions and from our tribe. Kuhn partly agreed but thought that communities of scientists engaged in competitive peer review could still do good science.
Ludwik Fleck’s 1935 Genesis and Development of a Scientific Fact argued that science was a thought collective of a community whose members share values. In 1958, Norwood Hanson, in Patterns of Discovery, wrote that all observation is theory-laden. Hanson agreed with Marx that neutral observation cannot exist, so neither can objective knowledge. “Seeing is an experience. People see, not their eyes,” said Hanson.
Most like Kuhn was Michael Polanyi, a brilliant Polish polymath (chemist, historian, economist). In his 1946 Science, Faith and Society, Polanyi wrote that scientific knowledge was produced by individuals under the influence of the scientific collectives in which they operated. Polanyi long preceded Kuhn, who was unaware of Polanyi’s work, in most of Kuhn’s key concepts. Unfortunately, Polanyi’s work didn’t appear in English until after Kuhn was famous. An aspect of Polanyi’s program important to this look at lobotomies is his idea that competition in science works like competition in business. The “market” determines winners of competing theories based on the judgments of its informed participants. Something like a market process exists within the institutional structure of scientific research.
Kuhn’s Structure was perfectly timed to correspond to the hippie/protest era, which distrusted big pharma and the rest of science, and especially the cozy relationships between academia, government, and corporations – institutions of social and political power. Kuhn had no idea that he was writing what would become one of the most influential books of the century, and one that became the basis for radical anti-science perspectives. Some communities outright declared war on objectivity and rationality. Science was socially constructed, said these “Kuhnians.” Kuhn was appalled.
A Kuhnian Take on Lobotomies
Folk with STEM backgrounds might agree that politics and influence can affect which scientific studies get funded but would probably disagree with Marx, Fleck, and Hanson that interest, influence, and values permeate scientific observations (what evidence gets seen and how it is assimilated), the interpretation of measurements and data, what data gets dismissed as erroneous or suppressed, and finally the conclusions drawn from observations and data.
The concept of social construction is in my view mostly garbage. If everything is socially constructed, then it isn’t useful to say of any particular thing that it is socially constructed. But the Kuhnians, who, oddly, have now come to trust institutions like big pharma, government science, and Wikipedia, were right in principle that science is in some legitimate sense socially constructed, though they were perhaps wrong about the most egregious cases, then and now. The lobotomy boom seems a good fit for what the Kuhnians worried about.
If there is going to be a public and democratic body of scientific knowledge (science definition 2 above) based on scientific methods and testability (definition 1 above), some community of scientists has to agree on what has been tested and falsified for the body of knowledge to get codified and publicized. Fleck and Hanson’s positions apply here. To some degree, that forces definition 3 onto definitions 1 and 2. For science to advance mankind, the institution must be cognitively diverse, it must welcome debate and court refutation, and it must be transparent. The institutions surrounding lobotomies did none of these. Monstrous as Freeman may have been, he was not the main problem – at least not the main scientific problem – with lobotomies. This was bad institutional science, and to the extent that we have missed what was bad about it, it is ongoing bad science. There is much here to make your skin crawl that was missed by NPR, Offit’s Pandora’s Lab, and El-Hai’s The Lobotomist.
Background on Lobotomy
In 1935 António Egas Moniz (1874–1955) first used absolute alcohol to destroy the frontal lobes of a patient. The Nobel Committee called it one of the most important discoveries ever made in psychiatric medicine, and Moniz became a Nobel laureate in 1949. In two years Moniz oversaw about 40 lobotomies. He failed to report cases of vomiting, diarrhea, incontinence, hunger, kleptomania, disorientation, and confusion about time in postoperative patients who lacked these conditions before surgery. When the surgery didn’t help the schizophrenia or whatever condition it was done to cure, Moniz said the patients’ conditions had been too advanced before the surgery.
In 1936 neurologist Walter Freeman, having seen Moniz’s work, ordered the first American lobotomy. James Watts of George Washington University Hospital performed the surgery by drilling holes in the side of the skull and removing a bit of brain. Before surgery, Freeman lied to the patient, who was concerned that her head would be shaved, about the procedure. She didn’t consent, but her husband did. The operation was done anyway, and Freeman declared success. He was on the path to stardom.
The patient, Alice Hammatt, reported being happy as she recovered. A week after the operation, she developed trouble communicating, was disoriented, and experienced anxiety, the condition the lobotomy was intended to cure. Freeman presented the case at a medical association meeting, calling the patient cured. In that meeting, Freeman was surprised to find that he faced criticism. He contacted the local press and offered an exclusive interview. He believed that the press coverage would give him a better reception at his next professional lobotomy presentation.
By 1952, 18,000 lobotomies had been performed in the US, 3000 of which Freeman claimed to have done. He began doing them himself, despite having no training in surgery, after Watts cut ties because of Freeman’s lack of professionalism and sterilization. Technically, Freeman was allowed to perform the kind of lobotomies he had switched to, because it didn’t involve cutting. Freeman’s new technique involved using a tool resembling an ice pick. Most reports say it was a surgical orbitoclast, though Freeman’s son Frank reported in 2005 that his father’s tool came right out their kitchen cabinet. Freeman punched a hole through the eye sockets into the patient’s frontal lobes. He didn’t wear gloves or a mask. West Virginians received a disproportionate share of lobotomies. At the state hospital in Weston, Freeman reports 225 lobotomies in twelve days, averaging six minutes per procedure. In The Last Resort: Psychosurgery and the Limits of Medicine (1999), JD Pressman reports a 14% mortality rate in Freeman’s operations.
The Press at Fault?
The press is at the center of most modern coverage of lobotomies. In Pandora’s Lab, Offit, as in other recent coverage, implies that the press overwhelmingly praised the procedure from day one. Offit reports that a front page article in the June 7, 1937 New York Times “declared – ‘in what read like a patent medicine advertisement – that lobotomies could relieve ‘tension apprehension, anxiety, depression, insomnia, suicidal ideas, …’ and that the operation ‘transforms wild animals into gentle creatures in the course of a few hours.’”
I read the 1937 Times piece as far less supportive. In the above nested quote, The Times was really just reporting the claims of the lobotomists. The headline of the piece shows no such blind faith: “Surgery Used on the Soul-Sick; Relief of Obsessions Is Reported.” The article’s subhead reveals significant clinical criticism: “Surgery Used on the Soul-Sick Relief of Obsessions Is Reported; New Brain Technique Is Said to Have Aided 65% of the Mentally Ill Persons on Whom It Was Tried as Last Resort, but Some Leading Neurologists Are Highly Skeptical of It.”
The opening paragraph is equally restrained: “A new surgical technique, known as “psycho-surgery,” which, it is claimed, cuts away sick parts of the human personality, and transforms wild animals into gentle creatures in the course of a few hours, will be demonstrated here tomorrow at the Comprehensive Scientific Exhibit of the American Medical Association…“
Offit characterizes medical professionals as being generally against the practice and the press as being overwhelmingly in support, a portrayal echoed in NPR’s 2005 coverage. I don’t find this to be the case. By Freeman’s records, most of his lobotomies were performed in hospitals. Surely the administrators and staff of those hospitals were medical professionals, so they couldn’t all be against the procedure. In many cases, parents, husbands, and doctors ordered lobotomies without consent of the patient, in the case of institutionalized minors, sometimes without consent of the parents. The New England Journal of Medicine approved of lobotomy, but an editorial in the 1941 Journal of American Medical Association listed the concerns of five distinguished critics. As discussed below, two sub-communities of clinicians may have held opposing views, and the enthusiasm of the press has been overstated.
In a 2022 paper, Lessons to be learnt from the history of lobotomy, Oivind Torkildsen of the Department of Clinical Medicine at University of Bergen wrote that “the proliferation of the treatment largely appears to have been based on Freeman’s charisma and his ability to enthuse the public and the news media.” Given that lobotomies were mostly done in hospitals staffed by professionals ostensibly schooled in and practicing the methods of science, this seems a preposterous claim. Clinicians would not be swayed by tabloids.
A 1999 article by GJ Diefenbach in the Journal of the History of the Neurosciences, Portrayal of Lobotomy in the Popular Press: 1935-1960, found that the press initially used uncritical, sensational reporting styles, but became increasingly negative in later years. The article also notes that lobotomies faced considerable opposition in the medical community. It concluded that popular press may have been a factor influencing the quick and widespread adoption of lobotomy.
The article’s approach was to randomly distribute articles to two evaluators for quantitative review. The reviewers then rated the tone of the article on a five-point scale. I plotted its data, and a linear regression (yellow line below) indeed shows that the non-clinical press cooled on lobotomies from 1936 to 1958 (though, as is apparent from the broad data scatter, linear regression doesn’t tell the whole story). But the records, spotty as they are, of when the bulk of lobotomies were performed should also be considered. Of the 20,000 US lobotomies, 18,000 of them were done in the 5-year period from 1948 to 1952, the year that phenothiazines entered psychiatric clinical trials. A linear regression of the reviewers’ judgements over that period (green line) shows little change.
Applying the Methods of History and Philosophy of Science
One possibility for making sense of media coverage in the time, the occurrence of lobotomies, and the current perception of why lobotomies persisted despite opposition in the medical community is to distinguish between lobotomies done in state hospitals from those done in private hospitals or psychiatrists’ offices. The latter category dominated the press in the 1940s and modern media coverage. The tragic case of Rosemary Kennedy, whose lobotomy left her institutionalized and abandoned by her family and that of Howard Dully are far better known that the 18,000 lobotomies done in American asylums. Americans were not as in love with lobotomies as modern press reports. The latter category, private hospital lobotomies, while including some high-profile cases, was small compared to the former.
Between 1936 and 1947, only about 1000 lobotomies had been performed in the US, despite Howard Freeman’s charisma and self-promotion. We, along with Offit and NPR, are far too eager to assign blame to Howard Freeman the monster than to consider that the relevant medical communities and institutions may have been monstrous by failing to critically review their results during the lobotomy boom years.
This argument requires me to reconcile the opposition to lobotomies appearing in medical journals from 1936 on with the blame I’m assigning to that medical community. I’ll start by noting that while clinical papers on lobotomy were plentiful (about 2000 between 1936 and 1952), the number of such papers that addressed professional ethics or moral principles was shockingly small. Jan Frank, in Some Aspects of Lobotomy (Prefrontal Leucotomy) under Psychoanalytic Scrutiny (Psychiatry 13:1, 1950) reports a “conspicuous dearth of contributions to the theme.” Constance Holden, in Psychosurgery: Legitimate Therapy or Laundered Lobotomy? (Science, Mar. 16, 1973), concluded that by 1943, medical consensus was against lobotomy, and that is consistent with my reading of the evidence.
Enter Polanyi and the Kuhnians
In 2005, Dr. Elliot Valenstein (1923-2023), 1976 author of Great and Desperate Cures: The Rise and Decline of Psychosurgery, in commenting on the Dully story, stated flatly that “people didn’t write critical articles.” Referring back to Michael Polanyi’s thesis, the medical community failed itself and the world by doing bad science – in the sense that suppression of opposing voices, whether through fear of ostracization or from fear of retribution in the relevant press, destroyed the “market’s” ability to get to the truth.
By 1948, the popular lobotomy craze had waned, as is shown in Diefenbach’s data above, but the institutional lobotomy boom had just begun. It was tucked away in state mental hospitals, particularly in California, West Virginia, Virginia, Washington, Ohio, and New Jersey.
Jack Pressman, in Last resort: Psychosurgery and the Limits of Medicine (1998), seems to hit the nail on the head when he writes “the kinds of evaluations made as to whether psychosurgery worked would be very different in the institutional context than it was in the private practice context.”
Doctors in asylums and mental hospitals lived in a wholly different paradigm from those in for-profit medicine. Funding in asylums was based on patient count rather than medical outcome. Asylums were allowed to perform lobotomies without the consent of patients or their guardians, to whom they could refuse visitation rights.
While asylum administrators usually held medical or scientific degrees, their roles as administrators in poorly funded facilities altered their processing of the evidence on lobotomies. Asylum administrators had a stronger incentive than private practices to use lobotomies because their definitions of successful outcome were different. As Freeman wrote in a 1957 follow-up of 3000 patients, lobotomized patients “become docile and are easier to manage”. Success in the asylum was not a healthier patient, it was a less expensive patient. The promise of a patient’s being able to return to life outside the asylum was a great incentive for administrators on tight budgets. If those administrators thought lobotomy was ineffective, they would have had no reason to use it, regardless of their ethics. The clinical press had already judged it ineffective, but asylum administrators’ understanding of effectiveness was different from that of clinicians in private practice.
Pressman cites the calculus of Dr. Mesrop Tarumianz, administrator of Delaware State Hospital: “In our hospital, there are 1,250 cases and of these about 180 could be operated on for $250 per case. That will constitute a sum of $45,000 for 180 patients. Of these, we will consider that 10 percent, or 18, will die, and a minimum of 50 percent of the remaining, or 81 patients will become well enough to go home or be discharged. The remaining 81 will be much better and more easily cared for the in hospital… That will mean a savings $351,000 in a period of ten years.”
The point here is not that these administrators were monsters without compassion for their patients. The point is that significant available evidence existed to conclude that lobotomies were somewhere between bad and terrible for patients, and that this evidence was not processed by asylum administrators in the same way it was in private medical practice.
The lobotomy boom was enabled by sensationalized headlines in the popular press, tests run without control groups, ridiculously small initial sample sizes, vague and speculative language by Moniz and Freeman, cherry-picked – if not outright false – trial results, and complacence in peer review. Peer review is meaningless unless it contains some element of competition.
Some might call lobotomies a case of conflict of interest. To an extent that label fits, not so much in the sense that anyone derived much personal benefit in their official capacity, but in that the aims and interests of the involved parties – patients and clinicians – were horribly misaligned.
The roles of asylum administrators – recall that they were clinicians too – did not cause them to make bad decisions about ethics. Their roles caused and allowed them to make bad decisions about lobotomy effectiveness, which was an ethics violation because it was bad science. Different situations in different communities – private and state practices – led intelligent men, interpreting the same evidence, to reach vastly different conclusions about pounding holes in people’s faces.
It will come as no surprise to my friends that I will once again invoke Paul Feyerabend: if science is to be understood as an institution, there must be separation of science and state.
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Epilogical fallacies
A page on the official website the Nobel prize still defends the prize awarded to Moniz. It uncritically accepts Freeman’s statistical analysis of outcomes, e.g., 2% of patients became worse after the surgery.
…
Wikipedia reports that 60% of US lobotomy patients were women. Later in the same article it reports that 40% of US lobotomies were done on gay men. Thus, per Wikipedia, 100% of US male lobotomy patients were gay. Since 18,000 of the 20,000 lobotomies done in the US were in state mental institutions, we can conclude that mental institutions in 1949-1951 overwhelmingly housed gay men. Histories of mental institutions, even those most critical of the politics of deinstitutionalization, e.g. Deinstitutionalization: A Psychiatric Titanic, do not mention gay men.
…
Elliot Valenstein, cited above, wrote in a 1987 Orlando Sentinel editorial that all the major factors that shaped the lobotomy boom are still with us today: “desperate patients and their families still are willing to risk unproven therapies… Ambitious doctors can persuade some of the media to report untested cures with anecdotal ‘research’… it could happen again.” Now let’s ask ourselves, is anything equivalent going on today, any medical fad propelled by an uncritical media and single individual or small cadre of psychiatrists, anything that has been poorly researched and might lead to disastrous outcomes? Nah.
Extraordinary Miscarriages of Science, Part 2 – Creation Science
Posted in History of Science on January 21, 2024
By Bill Storage, Jan. 21, 2024
Creation Science can refer either to young-earth or old-earth creation theories. Young Earth Creationism (YEC) makes specific claims about the creation of the universe from nothing, the age of the earth as inferred from the Book of Genesis and about the creation of separate “kinds” of creatures. Wikipedia’s terse coverage, as with Lysenkoism, brands it a pseudoscience without explanation. But YEC makes bold, falsifiable claims about biology and genetics (not merely evolution), geology (plate tectonics or lack thereof), and, most significantly, Newtonian mechanics. While it posits unfalsifiable unobservables including a divinity that sculpts the universe in six days, much of its paradigm contrasts modern physics in testable ways. Creation Science is not a miscarriage of science in the sense of some of the others. I’m covering it here because it has many similarities to other bad sciences and is a great test of demarcation criteria. Creation Science does limited harm because it preaches to the choir. I doubt anyone ever joined a cult because they were persuaded that creationism is scientific.
Intelligent Design
Old-earth creationism, now known as Intelligent Design (ID) theory is much different. While ID could have confined itself to the realm of metaphysics and stayed out of our cross hairs, it did not. ID mostly confines itself to the realm of descriptions and explanations, but it explicitly claims to be a science. Again, Wikipedia brands ID as pseudoscience, and, again, this distinction seems shallow. I’m also concerned that the label is rooted in anti-Christian bias with reasons invented after the labelling as a rationalization. To be clear, I see nothing substantial in ID that is scientific, but its opponents’ arguments are often not much better than those of its proponents.
It might be true that a supreme being, benevolent or otherwise, guided the hand of cosmological and biological evolution. But simpler, adequate explanations of those processes exist outside of ID, and ID adds no explanatory power to the theories of cosmology and biology that are independent of it. This was not always the case. The US founding fathers, often labeled Christian by modern Christians, were not Christian at all. They were deists, mainly because they lacked a theoretical framework to explain the universe without a creator, who had little interest in earthly affairs. They accepted the medieval idea that complex organisms, like complex mechanisms, must have a designer. Emergent complexity wasn’t seen as an option. That they generally – notably excepting David Hume – failed to see the circularity of this “teleological argument” can likely be explained by Kuhn’s notion of the assent of the relevant community. Each of them bought it because they all bought it. It was the reigning paradigm.
While intelligent design could logically be understood to not require a Judeo-Christian god, ID seems to have emerged out of fundamentalist Christian objection to teaching evolution in public schools. Logically, “intelligent design” could equally apply to theories involving a superior but not supreme creator or inventor. Space aliens may have seeded the earth with amino acids – the Zoo Hypothesis. Complex organic molecules could have been sent to earth on a comet by highly advanced – and highly patient – aliens, something we might call directed panspermia. Or we could be living in a computer simulation of an alien school kid. Nevertheless, ID seems to be a Christian undertaking positing a Christian God.
Opponents are quick to point this out. ID is motivated by Christian sentiments and is closely aligned with Christian evangelism. Is this a fair criticism of ID as a science? I tend to think not. Newton was strongly motivated by Christian beliefs, though his religion, something like Arianism or Unitarianism, would certainly be rejected by modern Christians. Regardless, Newton’s religious motivation for his studies no more invalidates them than Linus Pauling’s (covered below) economic motivations invalidate his work. Motivations of practitioners, in my view, cannot be grounds for calling a field of inquiry pseudoscience or bad science. Some social scientists disagree.
Dominated by Negative Arguments
YEC and ID writings focus on arguing that much of modern science, particularly evolutionary biology, cannot be correct. For example, much of YEC’s efforts are directed at arguing that the earth cannot be 4.5 billion years old. Strictly speaking, this ( the theory that another theory is wrong) is a difficult theory to disprove. Most scientists tend to think that disproving a theory that itself aims to disprove geology is pointless. They hold that the confirming evidence for modern geologic theory is sufficient. Karl Popper, who held that absence of disconfirmation was the sole basis for judging a theory good, would seem to have a problem with this though. YEC also holds theories defending a single worldwide flood within the last 5,000 years. That seems reasonably falsifiable, if one accepts a large body of related science including several radioactive dating techniques, mechanics of solids, denudation rate calculations, and much more.
Further, it is flawed reasoning (“false choice”) to think that exposing a failure of classical geology is support for a specific competing theory.
YEC and, perhaps surprisingly, much of ID have assembled a body of negative arguments against Darwinism, geology, and other aspects of a naturalistic worldview. Arguing that fossil evidence is an insufficient basis for evolution and that natural processes cannot explain the complexity of the eyeball are characteristically negative arguments. This raises the question of whether a bunch of negative arguments can rightly be called a science. While Einstein started with the judgement that the wave theory of light could not be right (he got the idea from Maxwell), his program included developing a bold, testable, and falsifiable theory that posited that light was something that came in discreet packages, along with predictions about how it would behave in a variety of extreme circumstances. Einsteinian relativity gives us global positioning and useful tools in our cell phones. Creationism’s utility seems limited to philosophical realms. Is lack of practical utility or observable consequences a good basis for calling an endeavor unscientific? See String Theory, below.
Wikipedia (you might guess that I find Wikipedia great for learning the discography of Miley Cyrus but poor for serious inquiries), appealing to “consensus” and “the scientific community,” judges Creation Science to be pseudoscience because creationism invokes supernatural causes. In the same article, it decries the circular reasoning of ID’s argument from design (the teleological argument). But claiming that Creation Science invokes supernatural causes is equally circular unless we’re able to draw the natural/supernatural distinction independently from the science/pseudoscience distinction. Creationists hold that creation is natural; that’s their whole point.
Ignoring Disconfirming Evidence
YEC proponents seem to refuse to allow that any amount of radioactive dating evidence falsifies their theory. I’m tempted to say this alone makes YEC either a pseudoscience or just terrible science. But doing so would force me to accept the 2nd and 3rd definitions of science that I gave in the previous post. In other words, I don’t want to judge a scientific inquiry’s status (or even the status of a non-scientific one) on the basis of what its proponents (a community or institution) do at an arbitrary point in time. Let’s judge the theory, not its most vocal proponents. A large body of German physicists denied that Edington’s measurement confirmed Einstein’s prediction of bent light rays during an eclipse because they rejected Jewish physics. Their hardheadedness is no reason to call their preferred wave theory of light a bad theory. It was a good theory with bad adherents, a good theory for which we now have excellent reasons to judge wrong.
Some YEC proponents hold that, essentially, the fossil record is God’s little joke. Indeed it is possible that when God created the world in six days a few thousand years ago he laid down a lot of evidence to test our faith. The ancient Christian writer Tertullian argued that Satan traveled backward in time to plant evidence against Christian doctrine (more on him soon). It’s hard to disprove. The possibility of deceptive evidence is related to the worry expressed by Hume and countless science fiction writers that the universe, including fossils and your memories of today’s breakfast, could have been planted five minutes ago. Like the Phantom Time hypothesis, it cannot be disproved. Also, as with Phantom Time, we have immense evidence against it. And from a practical perspective, nothing in the future would change if it were true.
Lakatos Applied to Creation Science
Lakatos might give us the best basis for rejecting Creation Science as pseudoscience rather than as an extraordinarily bad science, if that distinction has any value, which it might in the case of deciding what can be taught in elementary school. (We have no laws against unsuccessful theories or poor science.) Lakatos was interested in how a theory makes use of laws of nature and what its research agenda looks like. Laws of nature are regularities observed in nature so widely that we assume them to be true, contingently, and ground predictions about nature on them. Creation Science usually has little interest in making testable predictions about nature or the universe on the basis of such laws. Dr. Duane Gish of the Institute for Creation Research (ICR) wrote in Evolution, The Fossils Say No that “God used processes which are not now operating anywhere in the natural universe.” This is a major point against Creation Science counting as science.
Creation Science’s lack of testable predictions might not even be a fair basis for judging a pursuit to be unscientific. Botany is far more explanatory than predictive, and few of us, including Wikipedia, are ready to expel botany from the science club.
Most significant for me, Lakatos casts doubt on Creation Science by the thinness of its research agenda. A look at the ICR’s site reveals a list of papers and seminars all by PhDs and MDs. They seem to fall in two categories: evolution is wrong (discussed above), and topics that are plausible but that don’t give support for creationism in any meaningful way. The ploy here is playing a game with the logic of confirmation.
By the Will of Elvis
Consider the following statement of hypothesis. Everything happens by the will of Elvis. Now this statement, if true, logically ensures that the following disjunctive statement is true: Either everything happens by the will of Elvis or all cats have hearts. Now let’s go out with a stethoscope and do some solid cat science to gather empirical evidential support for all cats having hearts. This evidence gives us reasonable confidence that the disjunctive statement is true. Since the original simple hypothesis logically implies the disjunction, evidence that cats have hearts gives support for the hypothesis that everything happens by the will of Elvis. This is a fun game (like Hempel’s crows) in the logic of confirmation, and those who have studied it will instantly see the ruse. But ICR has dedicated half its research agenda to it, apparently to deceive its adherents.
The creationist research agenda is mostly aimed at negating evolution and at large philosophical matters. Where it deals with small and specific scientific questions – analogous to cat hearts in the above example – the answers to those questions don’t in any honest sense provide evidentiary support for divine creation.
If anything fails the test of being valid science, Creation Science does. Yet popular arguments that attempt to logically dismiss it from the sciences seem prejudiced or ill motivated. As discussed in the last post, fair and honest demarcation is not so simple. This may be a case where we have to take the stance of Justice Potter Stewart, who, when judging whether Lady Chatterley’s Lover was pornography, said “I shall not today attempt further to define [it], but I know it when I see it, and this is not it.”
To be continued.
Extraordinary Popular Miscarriages of Science (part 1)
Posted in History of Science, Uncategorized on January 18, 2024
By Bill Storage, Jan. 18, 2024
I’ve been collecting examples of bad science. Many came from friends and scientists I’ve talked to. Bad science can cover several aspects of science depending on what one means by science. At least three very different things are called science now:
- An approach or set of rules and methods used to understand and predict nature
- A body of knowledge about nature and natural processes
- An institution, culture or community of people, including academic, government and corporate professionals, who are involved, or are said to be involved, in 1. or 2. above
Many of my examples of bad science fall under the 3rd category and involve, or are dominated by, the academicians, government offices, and corporations. Below are a few of my favorites from the past century or so. I think many people tend to think that bad science happened in medieval times and that the modern western world is immune to that sort of thing. On the contrary, bad science may be on the rise. For the record, I don’t judge a theory bad merely because it was shown to be wrong, even if spectacularly wrong. Geocentricity was a good theory. Phlogiston (17th century theoretical substance believed to escape from matter during combustion), caloric theory (18th century theory of a weightless fluid that flows from hot matter to cold), and the luminiferous ether (17-19th century postulated medium for the propagation of light waves) were all good theories, though we now have robust evidence against them. All had substantial predictive power. All posited unobservable entities to explain phenomena. But predictive success alone cannot justify belief in unobservable entities. Creation science and astrology were always bad science.
To clarify the distinction between bad science and wrong theories, consider Trofim Lysenko. He was nominally a scientist. Some of his theories appear to be right. He wore the uniform, held the office, and published sciencey papers. But he did not behave scientifically (consistent with definition 1 above) when he ignored the boundless evidence and prior art about heredity. Wikipedia dubs him a pseudoscientist, despite his having some successful theories and making testable hypotheses. Pseudoscience, says Wikipedia, makes unfalsifiable claims. Lysenko’s bold claims were falsifiable, and they were falsified. Wikipedia talks as if the demarcation problem – knowing science from pseudoscience – is a closed case. Nah. Rather than tackle that matter of metaphysics and philosophy, I’ll offer that Lysenkoism, like creation science, and astrology, are all sciences but they are bad science. While they all make some testable predictions, they also make a lot of vague ones, their interest in causation is puny, and their research agendas are scant.
Good science entails testable, falsifiable theories and bold predictions. Most philosophers of science, notably excluding Karl Popper, who thought that only withstanding falsification mattered, have held that making succinct, correct prediction makes a theory good, and that successful theories make for good science. Larry Laudan gave, in my view, a fine definition of a successful theory in his 1984 Philosophy of Science: A theory is successful provided it makes substantially more correct predictions, that it leads to efficacious interventions in the natural order, or that it passes a suitable battery of tests.
Concerns over positing unobservables opens a debate on the question of just how observable are electrons, quarks, and the Higgs Field. Not here though. I am more interested in bad science (in the larger senses of science) than I am with wrong theories. Badness often stems not from seeking to explain and predict nature and failing out of refusal to read the evidence fairly, but from cloaking a non-scientific agenda in the trappings of science. I’m interested in what Kuhn, Feyerabend, and Lakatos dealt with – the non-scientific interests of academicians, government offices, and corporations and their impact on what gets studied and how it gets studied, how confirming evidence is sought and processed, how disconfirming evidence is processed, avoided, or dismissed, and whether Popperian falsifiability was ever on the table.
Recap of Kuhn, Feyerabend, and Lakatos
Thomas Kuhn claimed that normal (day-to-day lab-coat) science consisted of showing how nature can be fit into the existing theory. That is, normal science is decidedly unscientific. It is bad science, aimed at protecting the reigning paradigm from disconfirming evidence. On Kuhn’s view, your scientific education teaches you how to see things as your field requires them to be seen. He noted that medieval and renaissance astronomers never saw the supernovae that were seen in China. Europeans “knew” that the heavens were unchanging. Kuhn used the terms dogma and indoctrination to piss off scientists of his day. He thought that during scientific crises (Newton vs. Einstein being the exemplar) scientists clutched at new theories, often irrationally, and then vicious competition ended when scientific methods determined the winner of a new paradigm. Kuhn was, unknown to most of his social-science groupies, a firm believer that the scientific enterprise ultimately worked. Kuhn says normal science is bad science. He thought this was okay because crisis science reverted to good science, and in crisis, the paradigm was overthrown when the scientists got interested in philosophy of science. When Kuhn was all the rage in the early 1960s, radical sociologists of science, all at the time very left leaning, had their doubts that science could stay good under the influence of government and business. Recall worries about the military industrial complex. They thought that interest, whether economic or political, could keep science bad. I think history has sided with those sociologists; though today’s professional sociologists, now overwhelmingly employed by the the US and state governments, are astonishingly silent on the matter. Granting, for sake of argument, that social science is science, its practitioners seem to be living proof that interest can dominate not only research agendas but what counts as evidence, along with the handling of evidence toward what becomes dogma in the paradigm.
Paul Feyerabend, though also no enemy of science, thought Kuhn stopped short of exposing the biggest problems with science. Feyerabend called science, referring to science as an institution, a threat to democracy. He called for “a separation of state and science just as there is a separation between state and religious institutions.” He thought that 1960s institutional science resembled more the church of Galileo’s day than it resembled Galileo. Feyerabend thought theories should be tested against each other, not merely against the world. He called institutional science a threat because it increasingly held complete control over what is deemed scientifically important for society. Historically, he observed, individuals, by voting with their attention and their dollars, have chosen what counts as being socially valuable. Feyerabend leaned rather far left. In my History of Science appointment at UC Berkeley I was often challenged for invoking him against bad-science environmentalism because Feyerabend wouldn’t have supported a right-winger. Such is the state of H of S at Berkeley, now subsumed by Science and Technology Studies, i.e., same social studies bullshit (it all ends in “Studies”), different pile. John Heilbronn rest in peace.
Imre Lakatos had been imprisoned by the Nazis for revisionism. Through that experience he saw Kuhn’s assent of the relevant community as a valid criterion for establishing a new post-crisis paradigm as not much of a virtue. It sounded a bit too much like Nazis and risked becoming “mob psychology.” If the relevant community has excessive organizational or political power, it can put overpowering demands on individual scientists and force them to subordinate their ideas to the community (see String Theory’s attack on Lee Smolin below). Lakatos saw the quality of a science’s research agenda as a strong indicator of quality. Thin research agendas, like those of astrology and creation science, revealed bad science.
Selected Bad Science
Race Science and Eugenics
Eugenics is an all time favorite, not just of mine. It is a poster child for evil-agenda science driven by a fascist. That seems enough knowledge of the matter for the average student of political science. But eugenics did not emerge from fascism and support for it was overwhelming in progressive circles, particularly in American universities and the liberal elite. Alfred Binet of IQ-test fame, H. G. Wells, Margaret Sanger, John Harvey Kellogg, George Bernard Shaw, Theodore Roosevelt, and apparently Oliver Wendell Holmes, based on his decision that compulsory sterilization was within a state’s rights, found eugenics attractive. Financial support for the eugenics movement included the Carnegie Foundation, Rockefeller Institute, and the State Department. Harvard endorsed it, as did Stanford’s first president, David S Jordan. Yale’s famed economist and social reformer Irving Fisher was a supporter. Most aspects of eugenics in the United States ended abruptly when we discovered that Hitler had embraced it and was using it to defend the extermination of Jews. Hitler borrowed from our 1933 Law for the Prevention of Hereditarily Defective Offspring drawn up by Harry Laughlin. Eugenics was a class case of advocates and activists, clueless of any sense of science, broadcasting that the science (the term “race science” exploded onto the scene as if if had always been a thing) had been settled. In an era where many Americans enjoy blaming the living – and some of the living enjoy accepting that blame – for the sins of our fathers, one wonders why these noble academic institutions have not come forth to offer recompense for their eugenics transgressions.
The War on Fat
In 1977 a Senate committee led by George McGovern published “Dietary Goals for the United States,” imploring us to eat less red meat, eggs, and dairy products. The U.S. Department of Agriculture (USDA) then issued its first dietary guidelines, which focused on cutting cholesterol and not only meat fat but fat from any source. The National Institutes of Health recommended that all Americans, including young kids, cut fat consumption. In 1980 the US government broadcast that eating less fat and cholesterol would reduce your risk of heart attack. Evidence then and ever since has not supported this edict. A low-fat diet was alleged to mitigate many metabolic risk factors and to be essential for achieving a healthy body weight. However, over the past 45 years, obesity in the US climbed dramatically while dietary fat levels fell. Europeans with higher fat diets, having the same genetic makeup, are far thinner. The science of low-fat diets and the tenets of related institutions like insurance, healthcare, and school lunches have seemed utterly immune to evidence. Word is finally trickling out. The NIH has not begged pardon.
The DDT Ban
Rachel Carson appeared before the Department of Commerce in 1963, asking for a “Pesticide Commission” to regulate the DDT. Ten years later, Carson’s “Pesticide Commission” became the Environmental Protection Agency, which banned DDT in the US. The rest of the world followed, including Africa, which was bullied by European environmentalists and aid agencies to do so.
By 1960, DDT use had eliminated malaria from eleven countries. Crop production, land values, and personal wealth rose. In eight years of DDT use, Nepal’s malaria rate dropped from over two million to 2,500. Life expectancy rose from 28 to 42 years.
Malaria reemerged when DDT was banned. Since the ban, tens of millions of people have died from malaria. Following Rachel Carson’s Silent Spring narrative, environmentalists claimed that, with DDT, cancer deaths would have negated the malaria survival rates. No evidence supported this. It was fiction invented by Carson. The only type of cancer that increased during DDT use in the US was lung cancer, which correlated cigarette use. But Carson instructed citizens and governments that DDT caused leukemia, liver disease, birth defects, premature births, and other chronic illnesses. If you “know” that DDT altered the structure of eggs, causing bird populations to dwindle, it is Carson’s doing.
Banning DDT didn’t save the birds, because DDT wasn’t the cause of US bird death as Carson reported. While bird populations had plunged prior to DDT’s first use, the bird death at the center of her impassioned plea never happened. We know this from bird count data and many subsequent studies. Carson, in her work at Fish and Wildlife Service and through her participation in Audubon bird counts, certainly knew that during US DDT use, the eagle population doubled, and robin, dove, and catbird counts increased by 500%. Carson lied like hell and we showered her with praise and money. Africans paid with their lives.
In 1969 the Environmental Defense Fund demanded a hearing on DDT. The 8-month investigation concluded DDT was not mutagenic or teratogenic. No cancer, no birth defects. In found no “deleterious effect on freshwater fish, estuarine organisms, wild birds or other wildlife.” Yet William Ruckleshaus, first director of the EPA, who never read the transcript, chose to ban DDT anyway. Joni Mitchell was thrilled. DDT was replaced by more harmful pesticides. NPR, the NY Times, and the Puget Sound Institute still report a “preponderance of evidence” of DDT’s dangers.
When challenged with the claim that DDT never killed kids, the Rachel Carson Landmark Alliance responded in 2017 that indeed it had. A two-year old drank and ounce of 5% DDT in a solution of kerosene and died. Now there’s scientific integrity.
Vilification of Cannabis
I got this one from my dentist; I had never considered it before. White-collar, or rather, work-from-home, California potheads think this problem has been overcome. Far from it. Cannabis use violates federal law. Republicans are too stupid to repeal it, and Democrats are too afraid of looking like hippies. According to Quest Diagnostics, in 2020, 4.4% of workers failed their employers’ drug tests. Blue-collar Americans, particularly those who might be a sub-sub-subcontractor on a government project, are subject to drug tests. Testing positive for weed can cost you your job. So instead of partying on pot, the shop floor consumes immense amounts of alcohol, increasing its risk of accidents at work and in the car, harming its health, and raising its risk of hard drug use. To the admittedly small sense in which the concept of a gateway drug is valid, marijuana is probably not one and alcohol almost certainly is. Racism, big pharma lobbyists, and social-control are typically blamed for keeping cannabis illegal. Governments may also have concluded that tolerating weed at the state level while maintaining federal prohibition is an optimal tax revenue strategy. Cannabis tolerance at state level appears to have reduced opioid use and opioid related ER admissions.
Stoners who scoff at anti-cannabis propaganda like Reefer Madness might be unaware that a strong correlation between psychosis and cannabis use has been known for decades. But inferring causation from that correlation was always either highly insincere (huh huh) or very bad science. Recent analysis of study participants’ genomes showed that those with the strongest genetic profile for schizophrenia were also more likely to use cannabis in large amounts. So unless you follow Lysenko, who thought acquired traits were passed to offspring, pot is unlikely to cause psychosis. When A and B correlate, either A causes B, B causes A, or C causes both, as appears to be the case with schizophrenic potheads.
To be continued.
Settled State Science
Posted in History of Science on August 15, 2022
Science is belief in the ignorance of experts, said Richard Feynman in 1969. Does that describe science today, or is science a state and/or academic institution that dispenses truth?
State science and science herded by well-funded and tenured academics has led to some mammoth missteps, muddles and misdeeds in the application of that science to policy.
It may be inaccurate to say, as Edwin Black did in War Against the Weak, that Hitlers racial hygienics ideology was imported directly and solely from American eugenics. But that Hitler’s race policy was heavily inspired by American eugenics is very well documented, as is the overwhelming support given eugenics by our reigning politicians and educators. For example, Hitler absolutely did borrow much of the 1933 Law for the Prevention of Hereditarily Defective Offspring from the draft sterilization law drawn up for US states by Harry Laughlin, then Superintendent of the Eugenics Record Office in affiliation with the American Association of the Advancement of Science (AAAS).
Academic progressives and the educated elite fawned over the brilliance of eugenics too. Race Science was deemed settled, and that science had to be embodied in policy to change the world for the better. John Maynard Keynes and Woodrow Wilson loved it. Harvard was all over it too. Stanford’s first president, David S Jordan and the Yale’s famed economist and social reformer Irving Fisher were leaders of the Eugenics movement. All the trappings of science were there; impressive titles like “Some Racial Peculiarities of the Negro Brain” (American Journal of Anatomy, 1906) appeared in sciencey journals. In fact, the prestigious journal Science, covered eugenics in it lead story of Oct. 7, 1921.
But 1906 was oh so very long ago. right? Was eugenics a one-off? The lobotomy/leucotomy craze of the 1950s saw similar endorsement from the political and academic elite. More recent, less grotesque, but equally bad and unjustified state science was the low-fat craze of the 1980s and the war on cholesterol.
Last month the California Assembly has passed AB 2098, designating “the dissemination or promotion of misinformation or disinformation related to the SARS-CoV-2 coronavirus, or COVID-19 as unprofessional conduct,” for which MDs could be subjected to loss of license. The bill defines misinformation as “false information that is contradicted by contemporary scientific consensus.”
The U.S. Department of Health & Human Services (HHS) now states, “If your child is 6 months or older, you can now help protect them from severe COVID illness by getting them a COVID vaccine.” That may be consensus alright. I cannot find one shred of evidence to support the claim. Can you?
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“The separation of state and church must be complemented by the separation of state and science, that most recent, most aggressive, and most dogmatic religious institution.” – Paul Feyerabend, Against Method, 1975
Fashionable Pessimism: Confidence Gap Revisited
Posted in Uncategorized on August 19, 2021
Most of us hold a level of confidence about our factual knowledge and predictions that doesn’t match our abilities. That’s what I learned, summarized in a recent post, from running a website called The Confidence Gap for a year.
When I published that post, someone linked to it from Hacker News, causing 9000 people to read the post, 3000 of which took the trivia quiz(es) and assigned confidence levels to their true/false responses. Presumably, many of those people learned from the post that the each group of ten questions in the survey had one question about the environment or social issues designed to show an extra level of domain-specific overconfidence. Presumably, those readers are highly educated. I would have thought this would have changed the gap between accuracy and confidence in those who used the site before and after that post. But the results from visits after the blog post and Hacker News coverage, even in those categories, were almost identical to those of the earlier group.
Hacker News users pointed out several questions where the the Confidence Gap answers were obviously wrong. Stop signs actually do have eight sides, for example. Readers also reported questions with typos that could have confused the respondents. For example “Feetwood Mac” did not perform “Black Magic Woman” prior to Santana, but Fleetwood Mac did. The site called the statement with “Feetwood” true; it was a typo, not a trick.
A Hacker News reader challenged me on the naïve averaging of confidence estimates, saying he assumed the whole paper was similarly riddled with math errors. The point is arguable, but not a math error. Philip Tetlock, Tony Cox, Gerd Gigerenzer, Sarah Lichtenstein, Baruch Fischhoff, Paul Slovic and other heavyweights of the field used the same approach I used. Thank your university system for teaching that interpretation of probability is a clear-cut matter of math as opposed to vexing issue in analytic philosophy (see The Trouble with Probability and The Trouble with Doomsday).
Those criticisms acknowledged, I deleted the response data from the questions where Hacker News reported errors and typos. This changed none of the results by more than a percentage point. And, as noted above, prior knowledge of “trick” questions had almost no effect on accuracy or overconfidence.
On the point about the media’s impact on people’s confidence about fact claims that involve environmental issues, consider data from the 2nd batch of responses (post blog post) to this question:
According to the United Nations the rate of world deforestation increased between 1995 and 2015
This statement about a claim made by the UN is false, and the UN provides a great deal of evidence on the topic. The average confidence level given by respondents was 71%. The fraction of people answering correctly was 29%. The average confidence value specified by those who answered incorrectly was 69%. Independent of different interpretations of probability and confidence, this seems a clear sign of overconfidence about deforestation facts.
Compare this to the responses given for the question of whether Oregon borders California. 88% of respondents answered correctly and their average confidence specified was 88%.
Another example:
According to OurWorldInData.org, the average number of years of schooling per resident was higher in S. Korea than in USA in 2010
The statement is false. Average confidence was 68%. Average correctness was 20%
For all environmental and media-heavy social questions answered by the 2nd group of respondents (who presumably had some clue that people tend to be overconfident about such issues) the average correctness was 46% and the average confidence was 67%. This is a startling result; the proverbial dart throwing chimps would score vastly higher on environmental issues (50% by chimps, 20% on the schooling question and 46% for all “trick” questions by humans) than American respondents who were specifically warned that environmental questions were designed to demonstrate that people think the world is more screwed up than it is. Is this a sign of deep pessimism about the environment and society?
For comparison, average correctness and confidence on all World War II questions were both 65%. For movies, 70% correct, 71% confidence. For science, 75% and 77%. Other categories were similar, with some showing a slightly higher overconfidence. Most notably, sports mean accuracy was 59% with mean confidence of 68%.
Richard Feynman famously said he preferred not knowing to holding as certain the answers that might be wrong (No Ordinary Genius). Freeman Dyson famously said, “it is better to be wrong than to be vague” (The Scientist As Rebel). For the hyper-educated class, spoon-fed with facts and too educated to grasp the obvious, it seems the preferred system might now be phrased “better wrong than optimistic.”
. . . _ _ _ . . .
The man who despairs when others hope is admired as a sage. – John Stuart Mill. Speech on Perfectibility, 1828
Optimism is cowardice. Otto Spengler, Man and Technics, 1931
The U.S. life expectancy will drop to 42 years by 1980 due to cancer epidemics. Paul Ehrlich. Ramparts, 1969
It is the long ascent of the past that gives the lie to our despair. HG Wells. The Discovery of the Future, 1902
Smart Folk Often Full of Crap, Study Finds
Posted in Uncategorized on April 22, 2021
For most of us, there is a large gap between what we know and what we think we know. We hold a level of confidence about our factual knowledge and predictions that doesn’t match our abilities. Since our personal decisions are really predictions about the future based on our available present knowledge, it makes sense to work toward adjusting our confidence to match our skill.
Last year I measured the knowledge-confidence gap of 3500 participants in a trivia game with a twist. For each True/False trivia question the respondents specified their level of confidence (between 50 and 100% inclusive) with each answer. The questions, presented in banks of 10, covered many topics and ranged from easy (American stop signs have 8 sides) to expert (Stockholm is further west than Vienna).
I ran this experiment on a website and mobile app using 1500 True/False questions, about half of which belonged to specific categories including music, art, current events, World War II, sports, movies and science. Visitors could choose between the category “Various” or from a specific category. I asked for personal information such as age, gender current profession, title, and education. About 20% of site visitors gave most of that information. 30% provided their professions.
Participants were told that the point of the game was not to get the questions right but to have an appropriate level of confidence. For example, if a your average confidence value is 75%, 75% of their your answers should be correct. If your confidence and accuracy match, you are said to be calibrated. Otherwise you are either overconfident or underconfident. Overconfidence – sometime extreme – is more common, though a small percentage are significantly underconfident.
Overconfidence in group decisions is particularly troubling. Groupthink – collective overconfidence and rationalized cohesiveness – is a well known example. A more common, more subtle, and often more dangerous case exists when social effects and the perceived superiority of judgment of a single overconfident participant can leads to unconscious suppression of valid input from a majority of team members. The latter, for example, explains the Challenger launch decision for more than classic groupthink does, though groupthink is often cited as the cause.
I designed the trivia quiz system so that each group of ten questions under the Various label included one that dealt with a subject about which people are particularly passionate – environmental or social justice issues. I got this idea from Hans Rosling’s book, Factfulness. As expected, respondents were both overwhelmingly wrong and acutely overconfident about facts tied to emotional issues, e.g., net change in Amazon rainforest area in last five years.
I encouraged people to use take a few passes through the Various category before moving on to the specialty categories. Assuming that the first specialty categories that respondents chose was their favorite, I found them to be generally more overconfident about topics they presumable knew best. For example, those that first selected Music and then Art showed both higher resolution (correctness) and higher overconfidence in Music than they did in Art.
Mean overconfidence for all first-chosen specialties was 12%. Mean overconfidence for second-chosen categories was 9%. One interpretation is that people are more overconfident about that which they know best. Respondents’ overconfidence decreased progressively as they answered more questions. In that sense the system served as confidence calibration training. Relative overconfidence in the first specialty category chosen was present even when the effect of improved calibration was screened off, however.
For the first 10 questions, mean overconfidence in the Various category was 16% (16% for males, 14% for females). Mean overconfidence for the nine question in each group excepting the “passion” question was 13%.
Overconfidence seemed to be constant across professions, but increased about 1.5% with each level of college education. PhDs are 4.2% more overconfident than high school grads. I’ll leave that to sociologists of education to interpret. A notable exception was a group of analysts from a research lab who were all within a point or two of perfect calibration even on their first 10 questions. Men were slightly more overconfident than women. Underconfidence (more than 5% underconfident) was absent in men and present in 6% of the small group identifying as women (98 total).
The nature of overconfidence is seen in the plot of resolution (response correctness) vs. confidence. Our confidence roughly matches our accuracy up to the point where confidence is moderately high, around 85%. After this, increased confidence occurs with no increase in accuracy. At at 100% confidence level, respondents were, on average, less correct than they were at 95% confidence. Much of that effect stemmed from the one “trick” question in each group of 10; people tend to be confident but wrong about hot topics with high media coverage.
The distribution of confidence values expressed by participants was nominally bimodal. People expressed very high or very low confidence about the accuracy of their answers. The slight bump in confidence at 75% is likely an artifact of the test methodology. The default value of the confidence slider (website user interface element) was 75%. On clicking the Submit button, users were warned if most of their responses specified the default value, but an acquiescence effect appears to have present anyway. In Superforecasters Philip Tetlock observed that many people seem to have a “three settings” (yes, no, maybe) mindset about matters of probability. That could also explain the slight peak at 75%.
I’ve been using a similar approach to confidence calibration in group decision settings for the past three decades. I learned it from a DoD publication by Sarah Lichtenstein and Baruch Fischhoff while working on the Midgetman Small Intercontinental Ballistic Missile program in the mid 1980s. Doug Hubbard teaches a similar approach in his book The Failure of Risk Management. In my experience with diverse groups contributing to risk analysis, where group decisions about likelihood of uncertain events are needed, an hour of training using similar tools yields impressive improvements in calibration as measured above.
Risk Neutrality and Corporate Risk Frameworks
Posted in Uncategorized on October 27, 2020
Wikipedia describes risk-neutrality in these terms: “A risk neutral party’s decisions are not affected by the degree of uncertainty in a set of outcomes, so a risk-neutral party is indifferent between choices with equal expected payoffs even if one choice is riskier”
While a useful definition, it doesn’t really help us get to the bottom of things since we don’t all remotely agree on what “riskier” means. Sometimes, by “risk,” we mean an unwanted event: “falling asleep at the wheel is one of the biggest risks of nighttime driving.” Sometimes we equate “risk” with the probability of the unwanted event: “the risk of losing in roulette is 35 out of 36. Sometimes we mean the statistical expectation. And so on.
When the term “risk” is used in technical discussions, most people understand it to involve some combination of the likelihood (probability) and cost (loss value) of an unwanted event.
We can compare both the likelihoods and the costs of different risks, but deciding which is “riskier” using a one-dimensional range (i.e., higher vs. lower) requires a scalar calculus of risk. If risk is a combination of probability and severity of an unwanted outcome, riskier might equate to a larger value of the arithmetic product of the relevant probability (a dimensionless number between zero and one) and severity, measured in dollars.
But defining risk as such a scalar (area under the curve, therefore one dimensional) value is a big step, one that most analyses of human behavior suggests is not an accurate representation of how we perceive risk. It implies risk-neutrality.
Most people agree, as Wikipedia states, that a risk-neutral party’s decisions are not affected by the degree of uncertainty in a set of outcomes. On that view, a risk-neutral party is indifferent between all choices having equal expected payoffs.
Under this definition, if risk-neutral, you would have no basis for preferring any of the following four choices over another:
1) a 50% chance of winning $100.00
2) An unconditional award of $50.
3) A 0.01% chance of winning $500,000.00
4) A 90% chance of winning $55.56.
If risk-averse, you’d prefer choices 2 or 4. If risk-seeking, you’d prefer 1 or 3.
Now let’s imagine, instead of potential winnings, an assortment of possible unwanted events, termed hazards in engineering, for which we know, or believe we know, the probability numbers. One example would be to simply turn the above gains into losses:
1) a 50% chance of losing $100.00
2) An unconditional payment of $50.
3) A 0.01% chance of losing $500,000.00
4) A 90% chance of losing $55.56.
In this example, there are four different hazards. Many argue that rational analysis of risk entails quantification of hazard severities, independent of whether their probabilities are quantified. Above we have four risks, all having the same $50 expected value (cost), labeled 1 through 4. Whether those four risks can be considered equal depends on whether you are risk-neutral.
If forced to accept one of the four risks, a risk-neutral person would be indifferent to the choice; a risk seeker might choose risk 3, etc. Banks are often found to be risk-averse. That is, they will pay more to prevent risk 3 than to prevent risk 4, even though they have the same expected value. Viewed differently, banks often pay much more to prevent one occurrence of hazard 3 (cost = $500,000) than to prevent 9000 occurrences of hazard 4 (cost = $500,000).
Businesses compare risks to decide whether to reduce their likelihood, to buy insurance, or to take other actions. They often use a heat-map approach (sometimes called risk registers) to visualize risks. Heat maps plot probability vs severity and view any particular risk’s riskiness as the area of the rectangle formed by the axes and the point on the map representing that risk. Lines of constant risk therefore look like y = 1 / x. To be precise, they take the form of y = a/x where a represents a constant number of dollars called the expected value (or mathematical expectation or first moment) depending on area of study.
By plotting the four probability-cost vector values (coordinates) of the above four risks, we see that they all fall on the same line of constant risk. A sample curve of this form, representing a line of constant risk appears below on the left.
In my example above, the four points (50% chance of losing $100, etc.) have a large range of probabilities. Plotting these actual values on a simple grid isn’t very informative because the data points are far from the part of the plotted curve where the bend is visible (plot below on the right).

Students of high-school algebra know the fix for the problem of graphing data of this sort (monomials) is to use log paper. By plotting equations of the form described above using logarithmic scales for both axes, we get a straight line, having data points that are visually compressed, thereby taming the large range of the data, as below.

The risk frameworks used in business take a different approach. Instead of plotting actual probability values and actual costs, they plot scores, say from one ten. Their reason for doing this is more likely to convert an opinion into a numerical value than to cluster data for easy visualization. Nevertheless, plotting scores – on linear, not logarithmic, scales – inadvertently clusters data, though the data might have lost something in the translation to scores in the range of 1 to 10. In heat maps, this compression of data has the undesirable psychological effect of implying much small ranges for the relevant probability values and costs of the risks under study.
A rich example of this effect is seen in the 2002 PmBok (Project Management Body of Knowledge) published by the Project Management Institute. It assigns a score (which it curiously calls a rank) of 10 for probability values in the range of 0.5, a score of 9 for p=0.3, and a score of 8 for p=0.15. It should be obvious to most having a background in quantified risk that differentiating failure probabilities of .5, .3, and .15 is pointless and indicative of bogus precision, whether the probability is drawn from observed frequencies or from subjectivist/Bayesian-belief methods.
The methodological problem described above exists in frameworks that are implicitly risk-neutral. The real problem with the implicit risk-neutrality of risk frameworks is that very few of us – individuals or corporations – are risk-neutral. And no framework is right to tell us that we should be. Saying that it is somehow rational to be risk-neutral pushes the definition of rationality too far.
As proud king of a small distant planet of 10 million souls, you face an approaching comet that, on impact, will kill one million (10%) in your otherwise peaceful world. Your scientists and engineers rush to build a comet-killer nuclear rocket. The untested device has a 90% chance of destroying the comet but a 10% chance of exploding on launch thereby killing everyone on your planet. Do you launch the comet-killer, knowing that a possible outcome is total extinction? Or do you sit by and watch one million die from a preventable disaster? Your risk managers see two choices of equal riskiness: 100% chance of losing one million and a 10% chance of losing 10 million. The expected value is one million lives in both cases. But in that 10% chance of losing 10 million, there is no second chance. It’s an existential risk.
If these two choices seem somehow different, you are not risk-neutral. If you’re tempted to leave problems like this in the capable hands of ethicists, good for you. But unaware boards of directors have left analogous dilemmas in the incapable hands of simplistic and simple-minded risk frameworks.
The risk-neutrality embedded in risk frameworks is a subtle and pernicious case of Hume’s Guillotine – an inference from “is” to “ought” concealed within a fact-heavy argument. No amount of data, whether measured frequencies or subjective probability estimates, whether historical expenses or projected costs, even if recorded as PmBok’s scores and ranks, can justify risk-neutrality to parties who are not risk-neutral. So why is it embed it in the frameworks our leading companies pay good money for?




