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Leaders and Managers in Startups
Posted in Innovation management on April 10, 2016
The distinction between leaders and managers has been worn to the bone in popular press, though with little agreement on what leadership is and whether leaders can be managers or vice versa. Further, a cult of leadership seems to exalt the most sadistic behaviors of charismatic leaders with no attention on key characteristics ascribed to leaders in most leader-manager dichotomies. Despite imprecision and ambiguity, a coarse distinction between leadership and management sheds powerful light on the needs of startups, as well as giving some advice and cautions about the composition of founder teams in startups.
Common distinctions between managers and leaders include a mix of behaviors and traits, e.g.:
Managers
- Process and execution-oriented
- Risk averse
- Allocates resources
- Bottom-line focus
- Command and control
- Schedule-driven
Leaders
- Risk tolerant
- Innovative
- Visionary
- Thinks long-term
- Charismatic
- Intuitive
The cult of leadership often also paints some leaders as dictatorial, authoritative and inflexible, seeing these characteristics as an acceptable price for innovative vision. Likewise, the startup culture often views management as being wholly irrelevant to startups. Warren Bennis, in Learning to Lead, gives neither concept priority, but holds that they are profoundly different. For Bennis, managers do things right and leaders do the right thing. Peter Drucker, from 1946 on, saw leadership mostly as another attribute of good management but acknowledged a difference. He characterized good managers as leaders and bad managers as functionaries. Drucker saw a common problem in large corporations; they’re over-managed and under-led. He defined leader simply as someone with followers. He thought trust was the only means by which people chose to follow a leader.
Accepting that the above distinctions are useful for discussion, it’s arguable that in early-stage startups leadership would trump management, simply because at that stage startups require innovation and risk tolerance to get off the ground. Any schedules or bottom-line considerations in the early days of a startup rely only on rough approximations. That said, for startups targeting more serious industry sectors – financial and healthcare, for example – the domain knowledge and organizational maturity of experienced managers could be paramount.
Over the past 15 years I’ve watched a handful of startups face the challenges and benefits of functional, experience, and cognitive diversity. Some of this was firsthand – once as a board director, once on an advisory board, and twice as an owner. I also have close friends with direct experience in founding teams composed partly of tech innovators and partly of early-retired managers from large firms. My thoughts below flow from observing these startups.
Failure is an option. Perfect is a verb.
Silicon Valley’s “fail early, fail often” mantra is misunderstood and misused. For some it is an excuse for recklessness with investors’ money. Others chant the mantra with bad counter-inductive logic; i.e., believing that exhausting all routes to failure will necessarily result in success. Despite the hype, the fail-early perspective has value that experienced managers often miss. A look at the experience profile of corporate managers shows why.
Managers are used to having things go according to plan. That doesn’t happen in startups. Managers in startups are vulnerable to committing to an initial plan. The leader/manager distinction has some power here. You cannot manage an army into battle; you can only lead one. Yes, startups are in battle.
For a manager, planning, scheduling, estimating and budgeting traditionally involve a great deal of historical data with low variability. This is more true in the design/manufacture world than for managers who oversee product development (see Donald Reinertsen’s works for more on this distinction). But startups are much more like product development or R&D than they are like manufacturing. In manufacturing, spreadsheets and projections tend to be mostly right. In startups they are today’s best guess, which must be continually revised. Discovery-driven planning, as promoted by MacMillan and McGrath, might be a good starting point. If “fail early” rubs you the wrong way, understand it to mean disproving erroneous assumptions early, before you cast them in stone, only to have the market point them out to you.
Managers, having joined a startup, may tend to treat wild guesses, once entered into a spreadsheet, as facts, or may be overly confident in predictions derived from them. This is particularly critical for startups with complex enterprise products – just the kind of startup where corporate experience is most likely to be attractive. Such startups are prone to high costs and long development cycles. The financing Valley of Death claims many victims who budget against an optimistic release schedule and revenue forecast. It’s a reckless move with few possible escape routes, often resulting in desperate attempts to create a veneer of success on which to base another seed round.
In startups, planning must be more about prioritizing than about scheduling. Startups must treat development plans as a hypotheses to be continually refined. As various generals have said, essential as battle plans are, none has ever survived contact with the enemy. The Lean Startup’s build-measure-learn concept – which is just an abbreviated statement of the hypothetico-deductive interpretation of scientific method – is a good guide; but one that may require a mindset shift for most managers.
Zero defects
For Philip Crosby, Zero Defects was not a motivational program. It was to be taken literally. It meant everyone should do things right the first time. That mindset, better embodied in William Deming’s statistical process control methodology, is great for manufacturing, as is obvious from results of his work with Japanese industries in the 1950s. Whether that mindset was useful to white collar workers in America, in the form of the Deming System and later Six Sigma, (e.g., Motorola, GE, and Ford) is hotly debated. Qualpro, which authored a competing quality program, reported a while back that 91% of large firms with Six Sigma programs have trailed the S&P 500 after implementing them. Some say the program was effective for its initial purpose, but doesn’t scale to today’s needs.
Whatever its efficacy, most experienced managers have been schooled in Zero Defects or something similar. Its focus on process excellence emphasizing precision, consistency, and detailed analysis seems at odds with the innovation, adaptability, and accommodation of failure we see in successful startups.
Focus on doing it right the first time in a startup will lead to excessively detailed plans containing unreliable estimates and a tendency toward unwarranted confidence in those estimates.
Motivation and hierarchy
Corporate managers are used to having clearly defined goals and plenty of resources. Startups have neither. This impacts team dynamics.
Successful startup members, biographers tell us, are self-motivated. They share a vision and are closely aligned; their personal goals match the startup’s goals. In most corporations, managers control, direct, and supervise employees whose interests are not closely aligned with those of the corporation. Corporate motivational tools, applied to startups, reek of insincerity and demotivate teams. Uncritical enthusiasm is dangerous in a startup, especially for the enthusiasts. It can blind crusaders to fatal flaws in a product, business model, marketing plan or strategy. Aspirational faith is essential, but hope is not a strategy.
An ex-manager in a CEO leadership role might also unduly don the cloak of management by viewing a small startup team of investing founders as employees. It leads to factions, resentment, and distraction from the shared objective.
Startup teamwork requires clear communications and transparency. Clinkle’s Lucas Duplan notwithstanding, I think former corporate managers are far more likely to try to filter and control communications in a startup than those without that experience. Managing communications and information flow maintains order in a corporation; it creates distrust in a startup. Leading requires followers who trust you, says Drucker.
High degrees of autonomy and responsibility in startups invariably lead to disagreements. Some organizational psychologists say conflict is a tool. While that may be pushing it, most would agree that conflict is an indication of an opportunity to work swiftly toward a more common understanding of problem definition and solutions. In the traditional manager/leader distinction, leaders put conflict front and center, seeing it as a valuable indicator of an unmet organizational need. Managers, using a corporate approach, may try to take care of things behind the scene or one-on-one, thereby preventing loss of productivity in those least engaged in the conflict. Neutralizing dissenting voices in the name of alignment likely suppresses exactly the conversation that needs to occur. Make conflict constructive rather than suppressing it.
Strategy
I’m wary of ascribing wisdom to hoodie-wearing Ferrari drivers, nevertheless I’ve cringed to see mature businessmen make strategic blunders that no hipster CEO would make. This says nothing about intellect or maturity, but much about experience and skills acquired through immersion in startupland. I’ll give a few examples.
Believing that seed funding increases your chance of an A round: Most young leaders of startups know that while the amount of seed funding has steadily and dramatically in recent years, the number of A rounds has not. By some measures it has decreased.
Accepting VC money in a seed round: This is a risky move with almost no upside. It broadcasts a message of lukewarm interest by a high-profile investor. When it’s time for an A round, every other potential investor will be asking why the VC who gave you seed money has not invested further. Even if the VC who supplied seed funding entertains an A round, this will likely result in a lower valuation than would result from a competitive process.
Looking like a manager, not a leader: Especially when seeking funding, touting your Six Sigma or process improvement training, a focus on organizational design, or your supervisory skills will raise a big red flag.
Overspending too early: Managers are used to having resources. They often spend too early and give away too much equity for minor early contributions.
Lack of focus/no target customer: Thinking you can be all things to all customers in all markets if you just add more features and relationships is a mistake few hackers would make. Again, former executives are used to having resources and living in a world where cost overruns aren’t fatal.
“Selling” to investors: VCs are highly skilled at detecting hype. Good ones bet more on the jockey than the horse. You want them as a partner, not a customer; so don’t treat them like one.
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Stop Orbit Change Denial Now
Posted in History of Science on March 31, 2016
April 1, 2016.
Just like you, I grew up knowing that, unless we destroy it, the earth would be around for another five billion years. At least I thought I knew we had a comfortable window to find a new home. That’s what the astronomical establishment led us to believe. Well it’s not true. There is a very real possibility that long before the sun goes red giant on us, instability of the multi-body gravitational dynamics at work in the solar system will wreak havoc. Some computer models show such deadly dynamism in as short as a few hundred millions years.
One outcome is that Jupiter will pull Mercury off course so that it will cross Venus’s orbit and collide with the earth. “To call this catastrophic is a gross understatement,” says Berkeley astronomer Ken Croswell. Gravitational instability might also hurl Mars from the solar system, thereby warping Earth’s orbit so badly that our planet will be ripped to shreds. If you can imagine nothing worse, hang on to your helmet. In another model, the earth itself is heaved out of orbit and we’re on a cosmic one-way journey into the blackness of interstellar space for eternity. Hasta la vista, baby.
Knowledge of the risk of orbit change isn’t new; awareness is another story. The knowledge goes right back to Isaac Newton. In 1687 Newton concluded that in a two-body system, each body attracts the other with a force (which we do not understand, but call gravity) that is proportional to the product of their masses and inversely proportional to the square of the distance between them. That is, he gave a mathematical justification for what Keppler had merely inferred from observing the movement of planets. Newton then proposed that every body in the universe attracts every other body according to the same rule. He called it the universal law of gravitation. Newton’s law predicted how bodies would behave if only gravitational forces acted upon them. This cannot be tested in the real world, as there are no such bodies. Bodies in the universe are also affected by electromagnetism and the nuclear forces. Thus no one can test Newton’s theory precisely.
Ignoring the other forces of nature, Newton’s law plus simple math allows us to predict the future position of a two-body system given their properties at a specific time. Newton also noted, in Book 3 of his Principia, that predicting the future of a three body system was an entirely different problem. Many set out solve the so-called three-body (or generalized n-body) problem. Finally, over two hundred years later, Henri Poincaré, after first wrongly believing he had worked it out – and forfeiting the prize offered by King Oscar of Sweden for a solution – gave mathematical evidence that there can be no analytical solution to the n-body problem. The problem is in the realm of what today is called chaos theory. Even with powerful computers, rounding errors in the numbers used to calculate future paths of planets prevent conclusive results. The butterfly effect takes hold. In a computer planetary model, changing the mass of Mercury by a billionth of a percent might mean the difference between it ultimately being pulled into the sun and it’s colliding with Venus.
Too many mainstream astronomers are utterly silent on the issue of potential earth orbit change. Given that the issue of instability has been known since Poincaré, why is academia silent on the matter. Even Carl Sagan, whom I trusted in my youth, seems party to the conspiracy. In Episode 9 of Cosmos, he told us:
“Some 5 billion years from now, there will be a last perfect day on Earth. Then the sun will slowly change and the earth will die. There is only so much hydrogen fuel in the sun, and when it’s almost all converted to helium the solar interior will continue its original collapse… life will be extinguished, the oceans will evaporate and boil, and gush away to space. The sun will become a bloated red giant star filling the sky, enveloping and devouring the planets Mercury and Venus, and probably the earth as well. The inner planets will be inside the sun. But perhaps by then our descendants will have ventured somewhere else.”
He goes on to explain that we are built of star stuff, dodging the whole matter of orbital instability. But there is simply no mechanistic predictability in the solar system to ensure the earth will still be orbiting when the sun goes red-giant. As astronomer Caleb Scharf says, “the notion of the clockwork nature of the heavens now counts as one of the greatest illusions of science.” Scharf is one of the bold scientists who’s broken with the military-industrial-astronomical complex to spread the truth about earth orbit change.
But for most astronomers, there is a clear denial of the potential of earth orbit change and the resulting doomsday; and this has to stop. Let’s stand with science. It’s time to expose orbit change deniers. Add your name to the list, and join the team to call them out, one by one.
Can Science Survive?
Posted in History of Science, Philosophy of Science on February 16, 2016
In my last post I ended with the question of whether science in the pure sense can withstand science in the corporate, institutional, and academic senses. Here’s a bit more on the matter.
Ronald Reagan, pandering to a church group in Dallas, famously said about evolution, “Well, it is a theory. It is a scientific theory only.” (George Bush, often “quoted” as saying this, did not.) Reagan was likely ignorant of the distinction between two uses of the word, theory. On the street, “theory” means an unsettled conjecture. In science a theory – gravitation for example – is a body of ideas that explains observations and makes predictions. Reagan’s statement fueled years of appeals to teach creationism in public schools, using titles like creation science and intelligent design. While the push for creation science is usually pinned on southern evangelicals, it was UC Berkeley law professor Phillip E Johnson who brought us intelligent design.
Arkansas was a forerunner in mandating equal time for creation science. But its Act 590 of 1981 (Balanced Treatment for Creation-Science and Evolution-Science Act) was shut down a year later by McLean v. Arkansas Board of Education. Judge William Overton made philosophy of science proud with his set of demarcation criteria. Science, said Overton:
- is guided by natural law
- is explanatory by reference to natural law
- is testable against the empirical world
- holds tentative conclusions
- is falsifiable
For earlier thoughts on each of Overton’s five points, see, respectively, Isaac Newton, Adelard of Bath, Francis Bacon, Thomas Huxley, and Karl Popper.
In the late 20th century, religious fundamentalists were just one facet of hostility toward science. Science was also under attack on the political and social fronts, as well an intellectual or epistemic front.
President Eisenhower, on leaving office in 1960, gave his famous “military industrial complex” speech warning of the “danger that public policy could itself become the captive of a scientific technological elite.” At about the same time the growing anti-establishment movements – perhaps centered around Vietnam war protests – vilified science for selling out to corrupt politicians, military leaders and corporations. The ethics of science and scientists were under attack.
Also at the same time, independently, an intellectual critique of science emerged claiming that scientific knowledge necessarily contained hidden values and judgments not based in either objective observation (see Francis Bacon) or logical deduction (See Rene Descartes). French philosophers and literary critics Michel Foucault and Jacques Derrida argued – nontrivially in my view – that objectivity and value-neutrality simply cannot exist; all knowledge has embedded ideology and cultural bias. Sociologists of science ( the “strong program”) were quick to agree.
This intellectual opposition to the methodological validity of science, spurred by the political hostility to the content of science, ultimately erupted as the science wars of the 1990s. To many observers, two battles yielded a decisive victory for science against its critics. The first was publication of Higher Superstition by Gross and Levitt in 1994. The second was a hoax in which Alan Sokal submitted a paper claiming that quantum gravity was a social construct along with other postmodern nonsense to a journal of cultural studies. After it was accepted and published, Sokal revealed the hoax and wrote a book denouncing sociology of science and postmodernism.
Sadly, Sokal’s book, while full of entertaining examples of the worst of postmodern critique of science, really defeats only the most feeble of science’s enemies, revealing a poor grasp of some of the subtler and more valid criticism of science. For example, the postmodernists’ point that experimentation is not exactly the same thing as observation has real consequences, something that many earlier scientists themselves – like Robert Boyle and John Herschel – had wrestled with. Likewise, Higher Superstition, in my view, falls far below what we expect from Gross and Levitt. They deal Bruno Latour a well-deserved thrashing for claiming that science is a completely irrational process, and for the metaphysical conceit of holding that his own ideas on scientific behavior are fact while scientists’ claims about nature are not. But beyond that, Gross and Levitt reveal surprisingly poor knowledge of history and philosophy of science. They think Feyerabend is anti-science, they grossly misread Rorty, and waste time on a lot of strawmen.
Following closely on the postmodern critique of science were the sociologists pursuing the social science of science. Their findings: it is not objectivity or method that delivers the outcome of science. In fact it is the interests of all scientists except social scientists that govern the output of scientific inquiry. This branch of Science and Technology Studies (STS), led by David Bloor at Edinburgh in the late 70s, overplayed both the underdetermination of theory by evidence and the concept of value-laden theories. These scientists also failed to see the irony of claiming a privileged position on the untenability of privileged positions in science. I.e., it is an absolute truth that there are no absolute truths.
While postmodern critique of science and facile politics in STC studies seem to be having a minor revival, the threats to real science from sociology, literary criticism and anthropology (I don’t mean that all sociology and anthropology are non-scientific) are small. But more subtle and possibly more ruinous threats to science may exist; and they come partly from within.
Modern threats to science seem more related to Eisenhower’s concerns than to the postmodernists. While Ike worried about the influence the US military had over corporations and universities (see the highly nuanced history of James Conant, Harvard President and chair of the National Defense Research Committee), Eisenhower’s concern dealt not with the validity of scientific knowledge but with the influence of values and biases on both the subjects of research and on the conclusions reached therein. Science, when biased enough, becomes bad science, even when scientists don’t fudge the data.
Pharmaceutical research is the present poster child of biased science. Accusations take the form of claims that GlaxoSmithKline knew that Helicobacter pylori caused ulcers – not stress and spicy food – but concealed that knowledge to preserve sales of the blockbuster drugs, Zantac and Tagamet. Analysis of those claims over the past twenty years shows them to be largely unsupported. But it seems naïve to deny that years of pharmaceutical companies’ mailings may have contributed to the premature dismissal by MDs and researchers of the possibility that bacteria could in fact thrive in the stomach’s acid environment. But while Big Pharma may have some tidying up to do, its opponents need to learn what a virus is and how vaccines work.
Pharmaceutical firms generally admit that bias, unconscious and of the selection and confirmation sort – motivated reasoning – is a problem. Amgen scientists recently tried to reproduce results considered landmarks in basic cancer research to study why clinical trials in oncology have such high failure rate. They reported in Nature that they were able to reproduce the original results in only six of 53 studies. A similar team at Bayer reported that only about 25% of published preclinical studies could be reproduced. That the big players publish analyses of bias in their own field suggests that the concept of self-correction in science is at least somewhat valid, even in cut-throat corporate science.
Some see another source of bad pharmaceutical science as the almost religious adherence to the 5% (+- 1.96 sigma) definition of statistical significance, probably traceable to RA Fisher’s 1926 The Arrangement of Field Experiments. The 5% false-positive probability criterion is arbitrary, but is institutionalized. It can be seen as a classic case of subjectivity being perceived as objectivity because of arbitrary precision. Repeat any experiment long enough and you’ll get statistically significant results within that experiment. Pharma firms now aim to prevent such bias by participating in a registration process that requires researchers to publish findings, good, bad or inconclusive.
Academic research should take note. As is often reported, the dependence of publishing on tenure and academic prestige has taken a toll (“publish or perish”). Publishers like dramatic and conclusive findings, so there’s a strong incentive to publish impressive results – too strong. Competitive pressure on 2nd tier publishers leads to their publishing poor or even fraudulent study results. Those publishers select lax reviewers, incapable of or unwilling to dispute authors. Karl Popper’s falsification model of scientific behavior, in this scenario, is a poor match for actual behavior in science. The situation has led to hoaxes like Sokal’s, but within – rather than across – disciplines. Publication of the nonsensical “Fuzzy”, Homogeneous Configurations by Marge Simpson and Edna Krabappel (cartoon character names) by the Journal of Computational Intelligence and Electronic Systems in 2014 is a popular example. Following Alan Sokal’s line of argument, should we declare the discipline of computational intelligence to be pseudoscience on this evidence?
Note that here we’re really using Bruno Latour’s definition of science – what scientists and related parties do with a body of knowledge in a network, rather than simply the body of knowledge. Should scientists be held responsible for what corporations and politicians do with their knowledge? It’s complicated. When does flawed science become bad science. It’s hard to draw the line; but does that mean no line needs to be drawn?
Environmental science, I would argue, is some of the worst science passing for genuine these days. Most of it exists to fill political and ideological roles. The Bush administration pressured scientists to suppress communications on climate change and to remove the terms “global warming” and “climate change” from publications. In 2005 Rick Piltz resigned from the U.S. Climate Change Science Program claiming that Bush appointee Philip Cooney had personally altered US climate change documents to lessen the strength of their conclusions. In a later congressional hearing, Cooney confirmed having done this. Was this bad science, or just bad politics? Was it bad science for those whose conclusions had been altered not to blow the whistle?
The science of climate advocacy looks equally bad. Lack of scientific rigor in the IPCC is appalling – for reasons far deeper than the hockey stick debate. Given that the IPCC started with the assertion that climate change is anthropogenic and then sought confirming evidence, it is not surprising that the evidence it has accumulated supports the assertion. Compelling climate models, like that of Rick Muller at UC Berkeley, have since given strong support for anthropogenic warming. That gives great support for the anthropogenic warming hypothesis; but gives no support for the IPCC’s scientific practices. Unjustified belief, true or false, is not science.
Climate change advocates, many of whom are credentialed scientists, are particularly prone to a mixing bad science with bad philosophy, as when evidence for anthropogenic warming is presented as confirming the hypothesis that wind and solar power will reverse global warming. Stanford’s Mark Jacobson, a pernicious proponent of such activism, does immeasurable damage to his own stated cause with his descent into the renewables fantasy.
Finally, both major climate factions stoop to tying their entire positions to the proposition that climate change has been measured (or not). That is, both sides are in implicit agreement that if no climate change has occurred, then the whole matter of anthropogenic climate-change risk can be put to bed. As a risk man observing the risk vector’s probability/severity axes – and as someone who buys fire insurance though he has a brick house – I think our science dollars might be better spent on mitigation efforts that stand a chance of being effective rather than on 1) winning a debate about temperature change in recent years, or 2) appeasing romantic ideologues with “alternative” energy schemes.
Science survived Abe Lincoln (rain follows the plow), Ronald Reagan (evolution just a theory) and George Bush (coercion of scientists). It will survive Barack Obama (persecution of deniers) and Jerry Brown and Al Gore (science vs. pronouncements). It will survive big pharma, cold fusion, superluminal neutrinos, Mark Jacobson, Brian Greene, and the Stanford propaganda machine. Science will survive bad science because bad science is part of science, and always has been. As Paul Feyerabend noted, Galileo routinely used propaganda, unfair rhetoric, and arguments he knew were invalid to advance his worldview.
Theory on which no evidence can bear is religion. Theory that is indifferent to evidence is often politics. Granting Bloor, for sake of argument, that all theory is value-laden, and granting Kuhn, for sake of argument, that all observation is theory-laden, science still seems to have an uncanny knack for getting the world right. Planes fly, quantum tunneling makes DVD players work, and vaccines prevent polio. The self-corrective nature of science appears to withstand cranks, frauds, presidents, CEOs, generals and professors. As Carl Sagan Often said, science should withstand vigorous skepticism. Further, science requires skepticism and should welcome it, both from within and from irksome sociologists.
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XKCD cartoon courtesy of xkcd.com
My Trouble with Bayes
Posted in Philosophy of Science, Probability and Risk, Uncategorized on January 21, 2016
In past consulting work I’ve wrestled with subjective probability values derived from expert opinion. Subjective probability is an interpretation of probability based on a degree of belief (i.e., hypothetical willingness to bet on a position) as opposed a value derived from measured frequencies of occurrences (related posts: Belief in Probability, More Philosophy for Engineers). Subjective probability is of interest when failure data is sparse or nonexistent, as was the data on catastrophic loss of a space shuttle due to seal failure. Bayesianism is one form of inductive logic aimed at refining subjective beliefs based on Bayes Theorem and the idea of rational coherence of beliefs. A NASA handbook explains Bayesian inference as the process of obtaining a conclusion based on evidence, “Information about a hypothesis beyond the observable empirical data about that hypothesis is included in the inference.” Easier said than done, for reasons listed below.
Bayes Theorem itself is uncontroversial. It is a mathematical expression relating the probability of A given that B is true to the probability of B given that A is true and the individual probabilities of A and B:
P(A|B) = P(B|A) x P(A) / P(B)
If we’re trying to confirm a hypothesis (H) based on evidence (E), we can substitute H and E for A and B:
P(H|E) = P(E|H) x P(H) / P(E)
To be rationally coherent, you’re not allowed to believe the probability of heads to be .6 while believing the probability of tails to be .5; the sum of chances of all possible outcomes must sum to exactly one. Further, for Bayesians, the logical coherence just mentioned (i.e., avoidance of Dutch book arguments) must hold across time (synchronic coherence) such that once new evidence E on a hypothesis H is found, your believed probability for H given E should equal your prior conditional probability for H given E.
Plenty of good sources explain Bayesian epistemology and practice far better than I could do here. Bayesianism is controversial in science and engineering circles, for some good reasons. Bayesianism’s critics refer to it as a religion. This is unfair. Bayesianism is, however, like most religions, a belief system. My concern for this post is the problems with Bayesianism that I personally encounter in risk analyses. Adherents might rightly claim that problems I encounter with Bayes stem from poor implementation rather than from flaws in the underlying program. Good horse, bad jockey? Perhaps.
Problem 1. Subjectively objective
Bayesianism is an interesting mix of subjectivity and objectivity. It imposes no constraints on the subject of belief and very few constraints on the prior probability values. Hypothesis confirmation, for a Bayesian, is inherently quantitative, but initial hypotheses probabilities and the evaluation of evidence is purely subjective. For Bayesians, evidence E confirms or disconfirms hypothesis H only after we establish how probable H was in the first place. That is, we start with a prior probability for H. After the evidence, confirmation has occurred if the probability of H given E is higher than the prior probability of H, i.e., P(H|E) > P(H). Conversely, E disconfirms H when P(H|E) < P(H). These equations and their math leave business executives impressed with the rigor of objective calculation while directing their attention away from the subjectivity of both the hypothesis and its initial prior.
2. Rational formulation of the prior
Problem 2 follows from the above. Paranoid, crackpot hypotheses can still maintain perfect probabilistic coherence. Excluding crackpots, rational thinkers – more accurately, those with whom we agree – still may have an extremely difficult time distilling their beliefs, observations and observed facts of the world into a prior.
3. Conditionalization and old evidence
This is on everyone’s short list of problems with Bayes. In the simplest interpretation of Bayes, old evidence has zero confirming power. If evidence E was on the books long ago and it suddenly comes to light that H entails E, no change in the value of H follows. This seems odd – to most outsiders anyway. This problem gives rise to the game where we are expected to pretend we never knew about E and then judge how surprising (confirming) E would have been to H had we not know about it. As with the general matter of maintaining logical coherence required for the Bayesian program, it is extremely difficult to detach your knowledge of E from the rest of your knowing about the world. In engineering problem solving, discovering that H implies E is very common.
4. Equating increased probability with hypothesis confirmation.
My having once met Hillary Clinton arguably increases the probability that I may someday be her running mate; but few would agree that it is confirming evidence that I will do so. See Hempel’s raven paradox.
5. Stubborn stains in the priors
Bayesians, often citing success in the business of establishing and adjusting insurance premiums, report that the initial subjectivity (discussed in 1, above) fades away as evidence accumulates. They call this washing-out of priors. The frequentist might respond that with sufficient evidence your belief becomes irrelevant. With historical data (i.e., abundant evidence) they can calculate P of an unwanted event in a frequentist way: P = 1-e to the power -RT, roughly, P=RT for small products of exposure time T and failure rate R (exponential distribution). When our ability to find new evidence is limited, i.e., for modeling unprecedented failures, the prior does not get washed out.
6. The catch-all hypothesis
The denominator of Bayes Theorem, P(E), in practice, must be calculated as the sum of the probability of the evidence given the hypothesis plus the probability of the evidence given not the hypothesis:
P(E) = [P(E|H) x p(H)] + [P(E|~H) x P(~H)]
But ~H (“not H”) is not itself a valid hypothesis. It is a family of hypotheses likely containing what Donald Rumsfeld famously called unknown unknowns. Thus calculating the denominator P(E) forces you to pretend you’ve considered all contributors to ~H. So Bayesians can be lured into a state of false choice. The famous example of such a false choice in the history of science is Newton’s particle theory of light vs. Huygens’ wave theory of light. Hint: they are both wrong.
7. Deference to the loudmouth
This problem is related to no. 1 above, but has a much more corporate, organizational component. It can’t be blamed on Bayesianism but nevertheless plagues Bayesian implementations within teams. In the group formulation of any subjective probability, normal corporate dynamics govern the outcome. The most senior or deepest-voiced actor in the room drives all assignments of subjective probability. Social influence rules and the wisdom of the crowd succumbs to a consensus building exercise, precisely where consensus is unwanted. Seidenfeld, Kadane and Schervish begin “On the Shared Preferences of Two Bayesian Decision Makers” with the scholarly observation that an outstanding challenge for Bayesian decision theory is to extend its norms of rationality from individuals to groups. Their paper might have been illustrated with the famous photo of the exploding Challenger space shuttle. Bayesianism’s tolerance of subjective probabilities combined with organizational dynamics and the shyness of engineers can be a recipe for disaster of the Challenger sort.
All opinions welcome.
Science, God, and the White House
Posted in Philosophy of Science on January 9, 2016
Back in the 80s I stumbled upon the book, Scientific Proof of the Existence of God Will Soon Be Announced by the White House!, by Franklin Jones, aka Frederick Jenkins, later Da Free John, later Adi Da Samraj. I bought it on the spot. Likely a typical 70s mystic charlatan, Jones nonetheless saw clearly our poor grasp of tools for seeking truth and saw how deep and misguided is our deference to authority. At least that’s how I took it.
Who’d expect a hippie mystic to be a keen philosopher of science. The book’s title, connecting science, church and state, shrewdly wraps four challenging ideas:
- That there can be such a thing as scientific proof of anything
- That there could be new findings about the existence of God
- That evidence for God could be in the realm of science
- That government should or could accredit a scientific theory
On the first point, few but the uneducated, TIME magazine, and the FDA think that proof is in the domain of science. Proof is deductive. It belongs to math, logic and analytic philosophy. Science uses evidence and induction to make inferences to the best explanation.
Accepting that strong evidence would suffice as proof, point number 2 is a bit trickier. Evidence of God’s existence can’t be ruled out a priori. God could be observable or detectable; we might see him or his consequences. An almighty god could easily have chosen to regularly show himself or to present unambiguous evidence. But Yahweh, at least in modern times, doesn’t play like that (A wicked and adulterous generation demands a sign but none will be given – Matthew 16:4). While believers often say no evidence would satisfy the atheist, I think a focused team could come up with rules for a demonstration that at least some nonbelievers would accept as sufficient evidence.
Barring any new observations that would constitute evidence, point number 3 is tough to tackle without wading deep into philosophy of science. To see why, consider the theory that God exists. Is it even a candidate for a scientific theory, as one WSJ writer thinks (Science Increasingly Makes the Case for God)? I.e., is it the content of a theory or the way it is handled by its advocates that makes the theory scientific? If the latter, it can be surprisingly hard to draw the line between scientific investigations and philosophical ones. Few scientists admit this line is so blurred, but how do string theorists, who make no confirmable or falsifiable predictions, defend that they are scientists? Their fondness for non-empirical theory confirmation puts them squarely in the ranks of the enlightenment empiricist, Bishop Berkeley of Cloyne (namesake of our fair university) who maintained that matter does not exist. Further, do social scientists make falsifiable predictions, or do they just continually adjust their theory to accommodate disconfirming evidence?
That aside, those who work in the God-theory space somehow just don’t seem to qualify as scientific – even the young-earth creationists trained in biology and geology. Their primary theory doesn’t seem to generate research and secondary theories to confirm or falsify. Their papers are aimed at the public, not peers – and mainly aim at disproving evolution. Can a scientific theory be primarily negative? Could plate-tectonics-is-wrong count as a proper scientific endeavor?
Gould held that God was simply outside the realm of science. But if we accept that the existence of God could be a valid topic of science, is it a good theory? Following Karl Popper, a scientific theory can withstand only a few false predictions. On that view the repeated failures of end-of-days predictions by Harold Camping and Herbert Armstrong might be sufficient to kill the theory of God’s existence. Or does their predictive failures simply exclude them from the community of competent practitioners?
Would NASA engineer, Edgar Whisenant be more credible at making predictions based on the theory of God’s existence? All his predictions of rapture also failed. He was accepted by the relevant community (“…in paradigm choice there is no standard higher than the assent of the relevant community” – Thomas Kuhn) since the Trinity Broadcast Network interrupted its normal programming to help watchers prepare. If a NASA engineer has insufficient scientific clout, how about our first scientist? Isaac Newton predicted, in Observations upon the Prophecies of Daniel and the Apocalypse of St. John, that the end would come in 2000 CE. Maybe Newton’s calculator had the millennium bug.
If we can’t reject the theory for any number of wrong predictions, might there be another basis for rejecting it? Some say absence of a clear mechanism is a good reason to reject theories. In the God theory, no one seems to have proposed a mechanism by which such a God could have arisen. Aquinas’s tortured teleology and Anselm’s ontological arguments still fail on this count. But it seems unfair to dismiss the theory of God’s existence on grounds of no clear mechanism, because we have long tolerated other theories deemed scientific with the same weakness. Gravity, for example.
Does assent of the relevant community grant scientific status to a theory, as Kuhn would have it? If so, who decides which community is the right one? Theologians spend far more time on Armageddon than do biologists and astrophysicists – and theologians are credentialed by their institutions. So why should Hawking and Dawkins get much air time on the matter? Once we’ve identified a relevant community, who gets to participate in its consensus?
This draws in point number 4, above. Should government or the White House have any more claim to a scientific pronouncement than the Council of Bishops? If not, what are we to think of the pronouncements by Al Gore and Jerry Brown that the science of climate is settled? Should they have more clout on the matter than Pope Francis (who, interestingly, has now made similar pronouncements)?
If God is outside the realm of science, should science be outside the jurisdiction of government? What do we make of President Obama’s endorsement of “calling out climate change deniers, one by one”? You don’t have to be Franklin Jones or Da Free John to see signs here of government using the tools of religion (persecution, systematic effort to censure and alienate dissenters) in the name of science. Is it a stretch to see a connection to Jean Bodin, late 16th century French jurist, who argued that only witches deny the existence of witches?
Can you make a meaningful distinction between our government’s pronouncements on the truth or settledness of the climate theory (as opposed to government’s role in addressing it) and the Kremlin’s 1948 pronouncement that only Lamarckian inheritance would be taught, and their call for all geneticists to denounce Mendelian inheritance? Is it scientific behavior for a majority in a relevant community to coerce dissenters?
In trying to draw a distinction between UN and US coercion on climate science and Lysenkoism, some might offer that we (we moderns or we Americans) are somehow different – that only under regimes like Lenin’s and Hitler’s does science get so distorted. In thinking this, it’s probably good to remember that Hitler’s eugenics was born right here, and flourished in the 20th century. It had nearly full academic support in America, including Stanford and Harvard. That is, to use Al Gore’s words, the science was settled. California, always a trendsetter, by the early 1920s, claimed 80% of America’s forced sterilizations. Charles Goethe, founder of Sacramento State University, after visiting Hitler’s Germany in 1934 bragged to a fellow California eugenicist about their program’s influence on Hitler.
If the era of eugenics seems too distant to be relevant to the issue of climate science/politics, consider that living Stanford scientist, Paul Ehrlich, who endorsed compulsory abortion in the 70s, has had a foot in both camps.
As crackpots go, Da Free John was rather harmless.
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“Indeed, it has been concluded that compulsory population-control laws, even including laws requiring compulsory abortion, could be sustained under the existing Constitution if the population crisis became sufficiently severe to endanger the society.” – Ehrlich, Holdren and Ehrlich, EcoScience, 3rd edn, 1977, p. 837
“You will be interested to know that your work has played a powerful part in shaping the opinions of the group of intellectuals who are behind Hitler in this epoch-making program.” – Charles Goethe, letter to Edwin Black, 1934
Fine Tuned Fibs for the Cause
Posted in Philosophy of Science on January 7, 2016
In my last post I compared our self-policing of facts that might chip away at our beliefs about environmental religion to lying for God in medieval and ancient times – something the writer of the epistles seems to boast of doing. Lying for God, on matters of science, may still be with us today.
William Lane Craig argues, in a line of thinking he calls reasonable faith (see his video), that the apparent fine tuning of the universe allowing life in it to exist can only be explained as the work a designer. For Craig that designer happens to be the God of evangelical Protestantism.
Fine tuning has two different but related meanings in physics. The first deals mainly with theory, the second mainly with observation – something for Descartes, and something for Bacon.
In theory selection, fine tuning refers to how the details of a theory might need to be tweaked to make them fit observations. For example, in Ptolemaic astronomy, as used prior to Copernicus, the model only matched measurements if the planets’ epicycles stayed put in comparison to the straight line connecting the earth and sun and if the periods of the epicycles were exactly one year. Given those restrictions, the Ptolemaic model made good predictions. But why would those particular quantities have such relations? No reason could be found other than that they needed to be that way for the model to work. In Ptolemy’s defense, he did not believe the model represented reality; it merely gave right predictions. But the church believed it; and they forbade the teaching of the Copernican model. Copernicus’s model gave no better predictions; and it didn’t explain the lack of parallax in star positions or why a rotating earth didn’t suffer from great winds. But, Copernicus didn’t rely on fine tuning of his theory. What criterion is most important in theory selection – absence of fine tuning, predictive success, or explanatory power? That’s a topic for another time I guess. Read Paul Feyerabend on the matter if it grabs you.
In modern physics, fine tuning more commonly refers to our observation that many of the measured values that are, to our knowledge, constant across the universe have values that, were they even slightly different, would prevent life from being possible anywhere. Martin Rees, perhaps the first scientist to delve deep into the matter, identified six dimensionless constants (ratios of things we measure in physics, basically) on which life as we know it depends. These include the ratio of electromagnetic strength to the strength of gravity, the ratio of the mass density of the universe to the density required to halt expansion, and the so-called cosmological constant, the ratio of dark energy density in the universe to the density that would be needed to halt its expansion.
Popular examples of such fine tuning include the claim that if the electromagnetism/gravity ratio differed by an almost infinitesimal amount – say 1 part in 10 to the 40th power (1E-40) – things would be very quiet indeed. With a bit more gravity, stars would be too small and would burn out far too fast. Tweaking the other constants makes things even worse. Adjusting the cosmological constant to a few parts in ten to the 120 in either direction would make the universe either expand too fast for galaxies and stars to form or to collapse upon itself just after the big bang. These are unimaginably large/small numbers. A few scientists argue that our thinking is wrong here – again a topic for later. If interested, see Why the Universe Is Not Designed for Us by Victor J. Stenger.
William Lane Craig accepts that fine tuning exists, giving three possible explanations: physical necessity, chance, or design. Craig rules out necessity because a life-prohibiting universe is easily imaginable. He notes that the probabilities for these incredibly fine-tuned values to occur by chance is ridiculously remote, thus leaving design as the only alternative.
Now I can’t know Craig’s motives or his state of mind, but his argument here is consistent with someone who knows more than he’s telling. That is, Craig is clearly highly intelligent; he has command of analytic philosophy, mathematics and at least a decent knowledge of physics. Yet he starts his fine tuning evangel with an egregious example of privileged hypothesis on top of false choice – just to start. Is he sure the given alternatives are the only live options? And can chance be ruled out in a multiverse model? I.e., in a model with 10 to the 500 instances of what we call our universe, you’re pretty much bound to get a few that look like ours with randomized values for the physical constants.
But we need not start with an exotic option. Did Craig rule out combinations of necessity and chance? Did he challenge the problem statement from the beginning? Many other have – questioning the notion that these measure values aren’t environmental constants at all; perhaps we’ve misconceived an underlying relationship that ties the values together in the same way pi is tied to 3.141592. Part of Stenger’s work is along these lines.
Having given his rationale for preferring the designer hypothesis to an artificially restricted set of alternatives, Craig then takes the leap from designer to the God of evangelical Christianity. That is, Krishna, Zeus, Ahura Mazda and the spaghetti monster are off the table. Craig holds that a being with unlimited cosmic power – who could construct any universe of his choosing – used his infinite powers to fine tune that universe to the precise values of constants that would allow that universe to support galaxies, stars and life. It’s hard for me to believe Craig doesn’t see the contradiction in an argument involving a God of ultimate power being bound by laws of physics. That is, Craig’s God is praiseworthy for essentially outwitting – by a tiny margin – physical laws that are nearly out of his control. This seems a better argument for the religion of the Assyrians than for evangelical Christianity; it recalls Marduk’s narrow defeat over Tiamat.
In Reasonable Faith, Craig deals often with the concept of insincere arguments. Do his religious convictions cause him to be blind to elementary fallacies and contradictions in his own doctrine? Or is he simply lying for the cause?
“…unbelief is at root a spiritual, not an intellectual, problem.” – William Lane Craig, Reasonable Faith: Christian Truth and Apologetics, 3rd edn., p.59
But You Need the Data
Posted in Multidisciplinarians on January 4, 2016
In my last post, But We Need the Rain, I suggested that environmentalist animism in San Francisco may fill the role once filled by religious belief, and may suffuse daily life as Christian belief did in medieval Europe. As the phrase “God be with ye” once reminded countrymen of correct thinking, so too might acknowledgment that we need the rain.
Medieval institutions – social and governmental – exerted constant pressure steering people away from wrong thinking; and the church dissuaded its flock from asking the wrong questions. Telling a lie to save a soul was OK; deceiving heathens into Christianity was just fine. I wonder if a weaker form of this sentiment remains in my fair city – in the form of failing to mention relevant facts about an issue and through the use of deceptive and selective truths. As theologian Thomas Burnet put it in the early 18th century, too much light is hurtful to weak eyes.
The San Francisco Chronicle, according to Google data, has published over 50 articles in the last two years mentioning the Shasta and Oroville reservoirs in connection with California’s four-year-old drought. Many of these pieces call attention to low levels of these reservoirs, e.g., Shasta was at 53% of normal level in January 2014.
None mention that Shasta and Oroville were, despite the drought, at 108% and 101% of normal level in April 2013, two years into the drought. Climate is mentioned in nearly all sfgate.com articles on the drought, but mismanagement of water resources by governments is mentioned in only one. Digging a bit deeper – with other sources – you’ll find bitter disputes between farmers saying water is wasted on environmental restoration and environmentalists asking why desert farmers want to grow thirsty crops like rice and cotton. I’d think Northern California citizens, asked by the governor to bathe less, might be interested in why so much of the Shasta and Oroville water left the reservoirs – whether they want to blame Sacramento, farmers, or environmentalists – and in the details of the dispute.
Is the Chronicle part of a conspiracy to get liberals in power by linking the water shortage to climate change rather than poor governance? I doubt it. There are no conservatives to displace. More likely, it seems to me, the Chronicle simply mirrors the values and beliefs held by its readers, an unusually monolithic community with a strong uniformity of views. The sense of identification with a community here somewhat resembles that of a religious group, where there’s a tendency for beliefs to be held as true by individuals because they are widely believed by the group – and to select or reject evidence based on whether it supports a preexisting belief.
“Being crafty, I caught you with guile.” – 2 Corinthians, 12:16
But We Need the Rain
Posted in Multidisciplinarians on January 1, 2016
Chance outdoor meetings on recent damp days in San Francisco tend to start or finish (or both) with the statement, “but we need the rain.” No information is conveyed by these words. Their recipient already knows we need the rain. And the speaker knows the recipient knows it. Perhaps it is said aloud to be sure the nature gods hear it and continue to pour forth the blessings. Perhaps it reveals competitive piety – a race to first claim awareness of our climate-change sins. Or maybe it has just become a pleasant closing of a street encounter along the lines of “good bye.”
Of course, we don’t need the rain. San Francisco’s water supply falls 200 miles east of here and is collected in Hetch Hetchy Reservoir, eternally under attack from activists who insist their motive is environmental restoration, not anti-capitalism. We don’t pump water that falls at sea level up into our reservoirs, nor do we collect water that falls on the coast. A coastal system that dumps rain in San Francisco does not mean it’s raining in the Sierras.
So California’s High Sierras need the rain, not us. But saying “but we need the rain” does little harm. Saying it lets the gods know we are grateful; and saying it reminds each other to be thankful.
“We need the rain” may have more in common with “good bye” than is apparent to most. Etymologists tell us that “God be with ye” became “God b’wy” by the mid-1600s, and a few decades later was “good b’wy,” well on its way to our “good bye,” which retains the ending “ye” as a reminder of its genesis
In the homogenous cultures of pre-enlightenment Europe, God was a fact of the world, not a belief of religion. “God be with ye” wasn’t seen as a religious sentiment. It was an expression of hopefulness about a universe that was powered by God almighty, the first cause and prime mover, who might just be a providential God hearing our pleas that He be with ye. Am I overly cynical in seeing a connection?
Rain be with ye.
Marcus Vitruvius’s Science
Posted in Engineering & Applied Physics, Philosophy of Science on June 26, 2015
Science, as an enterprise that acquires knowledge and justified beliefs in the form of testable predictions by systematic iterations of observation and math-based theory, started around the 17th century, somewhere between Copernicus and Newton. That, we learned in school, was the beginning of the scientific revolution. Historians of science tend to regard this great revolution as the one that never happened. That is, as Floris Cohen puts it, the scientific revolution, once an innovative and inspiring concept, has since turned into a straight-jacket. Picking this revolution’s starting point, identifying any cause for it, and deciding what concepts and technological innovations belong to it are problematic.
That said, several writers have made good cases for why the pace of evolution – if not revolution – of modern science accelerated dramatically in Europe, only when it did, why it has continuously gained steam rather than petering out, its primary driving force, and the associated transformations in our view of how nature works. Some thought the protestant ethic and capitalism set the stage for science. Others thought science couldn’t emerge until the alliance between Christianity and Aristotelianism was dissolved. Moveable type and mass production of books can certainly claim a role, but was it really a prerequisite? Some think a critical mass of ancient Greek writings had to have been transferred to western Europe by the Muslims. The humanist literary critics that enabled repair and reconstruction of ancient texts mangled in translation from Greek to Syriac to Persian to Latin and botched by illiterate medieval scribes certainly played a part. If this sounds like a stretch, note that those critics seem to mark the first occurrence of a collective effort by a group spread across a large geographic space using shared standards to reach a peer-reviewed consensus – a process sharing much with modern science.
But those reasons given for the scientific revolution all have the feel of post hoc theorizing. Might intellectuals of the day, observing these events, have concluded that a resultant scientific revolution was on the horizon? Francis Bacon comes closest to fitting this bill, but his predictions gave little sense that he was envisioning anything like what really happened.
I’ve wondered why the burst of progress in science – as differentiated from plain know-how, nature-knowledge, art, craft, technique, or engineering knowledge – didn’t happen earlier. Why not just after the period of innovation in from about 1100 to 1300 CE in Europe. In this period Jean Buridan invented calculators and almost got the concept of inertia right. Robert Grosseteste hinted at the experiment-theory model of science. Nicole Oresme debunked astrology and gave arguments for a moving earth. But he was the end of this line. After this brief awakening, which also included the invention of banking and the university, progress came to a screeching halt. Some blame the plague, but that can’t be the culprit. Literature of the time barley mentions the plague. Despite the death toll, politics and war went on as usual; but interest in resurrecting ancient Greek knowledge of all sorts tanked.
Why not in the Islamic world in the time of Ali al-Qushji and al-Birjandi? Certainly the mental capacity was there. A layman would have a hard time distinguishing al-Birjandi’s arguments and thought experiments for the earth’s rotation from those of Galileo. But Islamic civilization at the time had plenty of scholars but no institutions for making practical use of such knowledge and its society would not have tolerated displacement of received wisdom by man-made knowledge.
The most compelling case for civilization having been on the brink of science at an earlier time seems to be the late republic or early imperial Rome. This may seem a stretch, since Rome is much more known for brute force than for finesse, despite their flying buttresses, cranes, fire engines, central heating and indoor plumbing.
Consider the writings of one Vitruvius, likely Marcus Vitruvius Pollio, in the early reign of Augustus. Vitruvius wrote De Architectura, a ten volume guide to Roman engineering knowledge. Architecture, in Latin, translates accurately into what we call engineering. Rediscovered and widely published during the European renaissance as a standard text for engineers, Vitruvius’s work contains text that seems to contradict what we were all taught about the emergence of the – or a – scientific method.
Vitruvius is full of surprises. He acknowledges that he is not a scientist (an anachronistic but fitting term) but a collator of Greek learning from several preceding centuries. He describes vanishing point perspective: “…the method of sketching a front with the sides withdrawing into the background, the lines all meeting in the center of a circle.” (See photo below of a fresco in the Oecus at Villa Poppea, Oplontis showing construction lines for vanishing point perspective.) He covers acoustic considerations for theater design, explains central heating technology, and the Archimedian water screw used to drain mines. He mentions a steam engine, likely that later described by Hero of Alexandria (aeolipile drawing at right), which turns heat into rotational energy. He describes a heliocentric model passed down from ancient Greeks. To be sure, there is also much that Vitruvius gets wrong about physics. But so does Galileo.
Most of De Architectura is not really science; it could more accurately be called know-how, technology, or engineering knowledge. Yet it’s close. Vitruvius explains the difference between mere machines, which let men do work, and engines, which derive from ingenuity and allow storing energy.
What convinces me most that Vitruvius – and he surely could not have been alone – truly had the concept of modern scientific method within his grasp is his understanding that a combination of mathematical proof (“demonstration” in his terms) plus theory, plus hands-on practice are needed for real engineering knowledge. Thus he says that what we call science – theory plus math (demonstration) plus observation (practice) – is essential to good engineering.
The engineer should be equipped with knowledge of many branches of study and varied kinds of learning, for it is by his judgement that all work done by the other arts is put to test. This knowledge is the child of practice and theory. Practice is the continuous and regular exercise of employment where manual work is done with any necessary material according to the design of a drawing. Theory, on the other hand, is the ability to demonstrate and explain the productions of dexterity on the principles of proportion.
It follows, therefore, that engineers who have aimed at acquiring manual skill without scholarship have never been able to reach a position of authority to correspond to their pains, while those who relied only upon theories and scholarship were obviously hunting the shadow, not the substance. But those who have a thorough knowledge of both, like men armed at all points, have the sooner attained their object and carried authority with them.
It appears, then, that one who professes himself an engineer should be well versed in both directions. He ought, therefore, to be both naturally gifted and amenable to instruction. Neither natural ability without instruction nor instruction without natural ability can make the perfect artist. Let him be educated, skillful with the pencil, instructed in geometry, know much history, have followed the philosophers with attention, understand music, have some knowledge of medicine, know the opinions of the jurists, and be acquainted with astronomy and the theory of the heavens. – Vitruvius – De Architectura, Book 1
Historians, please correct me if you know otherwise, but I don’t think there’s anything else remotely like this on record before Isaac Newton – anything in writing that comes this close to an understanding of modern scientific method.
So what went wrong in Rome? Many blame Christianity for the demise of knowledge in Rome, but that is not the case here. We can’t know for sure, but the later failure of science in the Islamic world seems to provide a clue. Society simply wasn’t ready. Vitruvius and his ilk may have been ready for science, but after nearly a century of civil war (starting with the Italian social wars), Augustus, the senate, and likely the plebes, had seen too much social innovation that all went bad. The vision of science, so evident during the European Enlightenment, as the primary driver of social change, may have been apparent to influential Romans as well, at a time when social change had lost its luster. As seen in writings of Cicero and the correspondence between Pliny and Trajan, Rome now regarded social innovation with suspicion if not contempt. Roman society, at least its government and aristocracy, simply couldn’t risk the main byproduct of science – progress.
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History is not merely what happened: it is what happened in the context of what might have happened. – Hugh Trevor-Roper – Oxford Valedictorian Address, 1998
The affairs of the Empire of letters are in a situation in which they never were and never will be again; we are passing now from an old world into the new world, and we are working seriously on the first foundation of the sciences. – Robert Desgabets, Oeuvres complètes de Malebranche, 1676
Newton interjected historical remarks which were neither accurate nor fair. These historical lapses are a reminder that history requires every bit as much attention to detail as does science – and the history of science perhaps twice as much. – Carl Benjamin Boyer, The Rainbow: From Myth to Mathematics, 1957
Text and photos © 2015 William Storage
Mark Jacobson’s Science
Posted in Sustainable Energy on June 22, 2015
The writings of Stanford’s Mark Jacobson effortlessly blends science and ideology along a continuum to envision an all-renewable energy future for America. His success in doing this marks a sad state of affairs between science, culture and politics.
Jacobson’s popularity began with his 2009 Scientific American piece, A Plan to Power 100 Percent of the Planet with Renewables. The piece and his recent works argue both a means by which we could transition to renewable-only power and that an all-renewable energy mix is the means by which we should pursue greenhouse gas reduction. They seem to answer several questions, though the questions aren’t stated explicitly:
Is it possible to power 100% of the planet with renewables?
Is it feasible to power 100% of the planet with renewables?
Is it desirable to power 100% of the planet with renewables?
Is a renewable-only portfolio the best means of stopping the increase in atmospheric CO2?
The first question is an engineering problem. The 2nd is an engineering and economic question. The 3rd is economic, social, and political. The 4th is my restating of the 3rd to emphasize an a-priori exclusion of non-renewables from the goal of stopping the increase in atmospheric CO2. That objective, implied in the Sci Am article’s title, is explicitly stated in the piece’s opening paragraph:
“In December leaders from around the world will meet in Copenhagen to try to agree on cutting back greenhouse gas emissions for decades to come. The most effective step to implement that goal would be a massive shift away from fossil fuels to clean, renewable energy sources.”
It should be clear to readers that the possibility or technical feasibility of a global 100%-renewable energy portfolio in no way defends the assertion that it the most effective way to implement that goal is such a portfolio. Assuming that the most desirable way to cut greenhouse gas emissions is by using a 100% renewable portfolio, the feasibility of such a portfolio becomes an engineering, economic, and social challenge; but that is not the gist of Jacobson’s works, where the premise and conclusion are intertwined. Questions 1 and 2 would obviously be great topics for a paper, as would questions 3 and 4. Addressing all of them together is a laudable goal – and one that requires clear thinking about evidence and justification. On that requirement, A Plan to Power 100 Percent of the Planet with Renewables fails outright in my view, as do his recent writings.
Major deficiencies in Jacobson’s engineering and economic analyses have been discussed at length, most notably by Brian Wang, William Hannahan, Ted Trainer, Edward Dodge, Nate Gilbraith, Charles Barton, Gene Preston, and Barry W. Brook. The deficiencies they address include wrong facts, adverse selection, and vague language, e.g.:
“In another study, when 19 geographically disperse wind sites in the Midwest, over a region 850 km 850 km, were hypothetically interconnected, about 33% of yearly averaged wind power was calculated to be usable at the same reliability as a coal-fired power plant.”
Engineers will note that “usable at the same reliability” simply cannot be parsed into an intelligible claim; and if the intent was to say that that these sites had the same capacity factor as a coal-powered plant, the statement is obviously false.
Jacobson’s proposal for New York includes clearing 340 square miles of land to generate 39,000 MW with concentrated solar power facilities. CSP requires flat, sunny, unburdened land, kept free or rain and snow without addressing the possibility, let alone feasibility, of doing this. His NY plan calls for building 140 sq mi of photovoltaic farms, with similar requirements for land quality. He overstates capacity factor of both wind and photovoltaics in NY, as elsewhere. He calls for 12,500 5MW offshore wind turbines with no discussion of feasibility in light of bathymetry, shipping and commercial water route use. Further, his offshore wind turbine plan ignores efficiency reductions due to wind shadowing that would exist in his proposed turbine density. The economic impact, social acceptability, and environmental impact of clearing hundreds of square miles of mostly-wooded land and grading it level (NY is hilly), of erecting another 4000 onshore turbines, and of 12,500 offshore turbines is a very real – but unaddressed by Jacobson – factor in determining the true feasibility of the proposed solution.
The above writers cover many concerns about Jacobson’s work along these lines. Their criticism is aimed at the feasibility of Jacobson’s implementation plan. In my engineering judgment these complaints have considerable merit. But that is not where I want to go here. Instead, I’m intensely concerned about two related issues:
1) the lack of knowledge on the street that Jacobson has credible opponents that dispute his major claims
2) absence of criticism of Jacobson for doing bad science – not bad because of wrong details but bad because of poor method and bad values.
By values, I don’t mean ethics, beliefs or preferences. Jacobson and I share social values (cut CO2 emissions) but not scientific values. By scientific values I mean things like accuracy, precision, clarity (e.g., “useable at the same reliability”), testability, and justification – epistemic values focused on reliable knowledge. To clarify, I’m not so naïve as to think scientists and engineers shouldn’t have biases and personal beliefs, that they shouldn’t act on hunches, or that theory and observation are not intertwined. But misrepresenting normative statements as descriptive ones is a kind of bad science against which Bacon and Descartes would have railed; and that is what Jacobson has done. He answered one question (what we should do to level CO2 emissions) while pretending to answer a different one (are renewables sufficient to replace fossil fuels). This should not pass as science.
Jacobson’s writings are highly quantitative where they oppose fission, and grossly qualitative where they dodge the deficiencies in renewables. This holds particularly true on the matters of variability of renewables (e.g., large regions of Europe are often simultaneously without wind and sun), difficulties and inefficiencies of distribution, and the feasibility of energy storage and its inevitable inefficiencies (I mean laws-of-nature inefficiencies, not inefficiencies that can be cured with technology). He states the fission is not carbon-free because fossil fuels are used in its construction and maintenance, while failing to mention that the concrete and other CO2-emitters used in building and maintaining solar and wind power dwarf those of fission.
At times Jacobson’s claims might be called crypto-normative. For example, he says that “Nuclear power results in up to 25 times more carbon emissions than wind energy, when reactor construction and uranium refining and transport are considered.” As stated, the claim is absurd. Applying the principle of charity in argument, I dug down to see what he might have meant to say. Beneath it, he is actually including the CO2 footprint of his estimation of the impact of inevitable nuclear war. So, yes, with a big enough nuclear war included (not uranium refining and transport), the CO2 emissions of nuclear power plus nuclear war could result in up to 25 times more CO2 than wind. But why stop there? We could conceive of nuclear war (or non-nuclear was for that matter) that emitted thousands of time more CO2 than wind power. Speculation about nuclear war risks is a worthwhile topic, but not when buried in the calculation of CO2 footprints. And it has no place in calculating the most effective means to cut greenhouse gas.
How can Jacobson have so many mistakes in his details (all of which favor an all-renewables plan) and engage in such bad science while so few seem to notice? I’m not sure, but I fear that much of science has become the handmaid of politics and naïve ideological activism. I cannot know Jacobson’s motives, but I am certain of the incentives. Opposition to renewables is framed as opposing the need to cut CO2 and worse – like being in the pocket of evil corporations. I experience this personally, when I attend clean-tech events and when I use this example Philosophy of Science talks. As a career and popularity move, it’s hard to go wrong by jumping on the renewables-only bandwagon.
At a recent Silicon Valley clean-tech event, I challenged three different attendees on claims they made about renewables. Two of these were related to capacity factors given for solar power on the east coast and one dealt with the imminence (or lack thereof) of utility-scale energy storage technology. All three attendees, independently, in their responses cited Mark Jacobson’s work as justification for their claims. My attempts at reality checks on capacity factors using real-world values in calculations didn’t seem to faze them. Arguments hardly affect the faithful, noted Paul Feyerabend; their beliefs have an entirely different foundation.
Science was once accused of being the handmaid of religion. Under President Eisenhower, academic science was accused of being a pawn of the military industrial complex and then took big steps to avoid being one. The money flow is now different, but the incentives for institutional science – where it comes anywhere near policy matters – to conform to fickle societal expectations present a huge obstacle to the honest pursuit of a real CO2 solution.
I’m not sure how to fix the problem demonstrated by the unquestioning acceptance of Jacobson’s work as scientific knowledge. Improvements in STEM education will certainly help. But I doubt that spreading science and engineering education across a broader segment of society will be sufficient. It seems to me we’d benefit more from having engineers and policy makers develop a broader interpretation of the word science – one that includes epistemology and theory of justification. I’ve opined in the past that teaching philosophy of science to engineers would make them much better at engineering. It would also result in better policy makers in a world where technology has become integral to everything. Independent of whether a statement is true or false, every educated person should be able to differentiate a scientific statement from a non-scientific one, should know what constitutes confirming and disconfirming evidence, and should cry foul when a normative claim pretends to be descriptive.
“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.
“I tried hard to balance the needs of the science and the IPCC, which were not always the same.” – Keith Briffa – IPCC email correspondence, 2007.
“A philosopher who has been long attached to a favorite hypothesis, and especially if he have distinguished himself by his ingenuity in discovering or pursuing it, will not, sometimes, be convinced of its falsity by the plainest evidence of fact. Thus both himself, and his followers, are put upon false pursuits, and seem determined to warp the whole course of nature, to suit their manner of conceiving of its operations.” – Joseph Priestley – The History and Present State of Electricity, 1775
The Multidisciplinarian 
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