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Jul

2011

On Experts and Global Warming - NYTimes.com

Experts have always posed a problem for democracies. Plato scorned democracy, rating it the worst form of government short of tyranny, largely because it gave power to the ignorant many rather than to knowledgeable experts (philosophers, as he saw it). But, if, as we insist, the people must ultimately decide, the question remains: How can we, non-experts, take account of expert opinion when it is relevant to decisions about public policy?

opinionator.blogs.nytimes.com/...on-experts-and-global-warming

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Expertise Knowledge Democracy Decision Sense

we need to reflect on the logic of appeals to the authority of experts. First of all, such appeals require a decision about who the experts on a given topic are. Until there is agreement about this, expert opinion can have no persuasive role in our discussions.
Another requirement is that there be a consensus among the experts about points relevant to our discussion. Precisely because we are not experts, we are in no position to adjudicate disputes among those who are.
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- Finally, given a consensus on a claim among recognized experts, we non-experts have no basis for rejecting the truth of the claim.
- Consider, for example, current discussions about climate change, specifically about whether there is long-term global warming caused primarily by human activities (anthropogenic global warming or A.G.W.). All creditable parties to this debate recognize a group of experts designated as “climate scientists,” whom they cite in either support or opposition to their claims about global warming.
- The only questions are about the conclusions this project supports about global warming.
- There is, moreover, no denying that there is a strong consensus among climate scientists on the existence of A.G.W. — in their view, human activities are warming the planet. There are climate scientists who doubt or deny this claim, but even they show a clear sense of opposing a view that is dominant in their discipline.
- Non-expert opponents of A.G.W. usually base their case on various criticisms that a small minority of climate scientists have raised against the consensus view. But non-experts are in no position to argue against the consensus of expert opinion. As long as they accept the expert authority of the discipline of climate science, they have no basis for supporting the minority position.
- It follows that a non-expert who wants to reject A.G.W. can do so only by arguing that climate science lacks the scientific status needed be taken seriously in our debates about public policy. There may well be areas of inquiry (e.g., various sub-disciplines of the social sciences) open to this sort of critique. But there does not seem to be a promising case against the scientific authority of climate science. As noted, opponents of the consensus on global warming themselves argue from results of the discipline, and there is no reason to think that they would have had any problem accepting a consensus of climate scientists against global warming, had this emerged.
- Some non-expert opponents of global warming have made much of a number of e-mails written and circulated among a handful of climate scientists that they see as evidence of bias toward global warming. But unless this group is willing to argue from this small (and questionable) sample to the general unreliability of climate science as a discipline, they have no alternative but to accept the consensus view of climate scientists that these e-mails do not undermine the core result of global warming.
- I am not arguing the absolute authority of scientific conclusions in democratic debates. It is not a matter of replacing Plato’s philosopher-kings with scientist-kings in our polis. We the people still need to decide (perhaps through our elected representatives) which groups we accept as having cognitive authority in our policy deliberations. Nor am I denying that there may be a logical gap between established scientific results and specific policy decisions. The fact that there is significant global warming due to human activity does not of itself imply any particular response to this fact.
- once we have accepted the authority of a particular scientific discipline, we cannot consistently reject its conclusions. To adapt Schopenhauer’s famous remark about causality, science is not a taxi-cab that we can get in and out of whenever we like. Once we board the train of climate science, there is no alternative to taking it wherever it may go.
- The general argument of this article is flawed for the following reason; even when there is a body of recognized experts, the consensus opinion of those experts can be wrong. In the 1940's and 1950's the consensus of medical experts was that lobotomies were a valuable medical procedure (so much so that a Nobel in medicine was awarded for the discovery of therapeutic uses of lobotomy in 1949).
  
  It is not that there were no medical experts in the 1940's and 1950's; but rather that the consensus of the experts was wrong. It is never the case in ANY scientific discipline that the consensus opinion of the experts will be correct 100% of the time. Sometimes the consensus opinion will be deeply flawed, and the consensus will be forced to change over time.

Jun

2011

Common Sense: A Manifesto « Cognition « Critical Thinking « Skeptic North

[Common sense] is also somewhat curious, for a couple of reasons. First, while everyone thinks they have it, not everyone agrees with one another — a fact which causes shockingly little cognitive dissonance. And second, though this is certainly a quibble: we know for a fact that sense — meaning the ability to consistently reason soundly — is not at all common. It’s an unnatural skill for humans, and as a species we’ve only even been trying to do it for a few thousand years, with many of the most significant advances coming in the last few hundred. Indeed, to use “sense” as we know it today requires deliberate training of a sort that is most uncommon.

www.skepticnorth.com/...common-sense-a-manifesto

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Common Sense Sense Data Anecdote

. In the beginning, as any first year philosophy student can tell you, there were logic and rhetoric. Rhetoric dates back to the beginnings of written history (~3000 BCE), and is already recognized as a mixed blessing in Plato’s time, because it can manipulate as well as it can elucidate. (The Sophists do the former, Socrates the latter.) Logic, first codified by Aristotle, was the purer tool of thought — or at least one branch of it was. Deductive reasoning, the process of carefully determining new knowledge from a set of known premises, became the underpinning of human thought for the next 2000 years.
Aristotle identified a second branch of logic called inductive reasoning, which goes in the opposite direction, forming a general conclusion based on the observation of specific instances, and he recognized it as useful in science. But he didn’t do much more than that, and while it was taken up periodically over the ensuing millennia, including by such heavyweights as the Persian philosopher Avicenna, there were no real advances in that field until around the 17th century
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- much of the time it was brought up was to argue whether it should truly be part of logic at all. After all, the conclusions of induction could be false even when the premises were true and no logical flaw existed, so how could one derive reliable knowledge from such a process?
- there was no way of knowing just how closely a sample matched the population — at least until the development of statistics, which itself had to wait for the development of probability.
- And probability really only started to be codified with Fermat and Pascal in the mid-17th century, with antecedents no more than a century older than that. Statistics and probability gave induction its own language, and with Bacon and others also giving induction a second look as the Age of Reason began, the scientific method was born.
- Instead of all knowledge being a product or recombination of what we already know, we now had a mechanism to learn genuinely knew things in a new way — by direct measurement and a determination of the precise likelihood that our measurements were reflective of the natural world.
- numeracy is a big hurdle for any mode of thought aspiring to common use.
- So nearly 400 years after the Age of Reason began, humans still can’t speak the language of science, at least without significant training. And that training requirement has only grown in the ensuing centuries, for two reasons. First, science itself has continued to become more complex (and thus rarefied) as the field of statistics has developed over the last century or so. Today, hardly a study is conducted without the aid of a computer stats package. And second, a “third wave” of human thought has since begun.
- By the late 19th century, Charles Sanders Peirce — one of the main codifiers of the scientific method and an early statistics pioneer — was already calling attention to the impact of biases in scientific analysis, and recommending randomization and control as important tools in their elimination. Peirce was concerned mostly with statistical biases (e.g. sampling bias), but a century later we’d be starting to realize that the biases that formed the biggest obstacles to science were not mathematical, but cognitive
- What I’ll call the third wave of human thought — after deduction and induction — is the understanding of human cognitive processes pioneered in the 1970′s and codified by Kahneman, Tversky and Slovic (1982) in Judgment under uncertainty: heuristics and biases.
- it categorically refutes the notion, upon which the entire prior history of human thought is based, that the bulk of human thought is rational. Surely earlier thinkers recognized that humans were subject to irrational thought, even deliberate manipulation — witness Socrates against the Sophists — but until the recent advances in cognitive psychology, there was a belief that rational thought (particularly deductive reasoning) was our native mode. We now know this to be patently untrue.
- humans have two cognitive processes — one rational and one heuristic-based — that essentially debate decisions before a final judgment is made. The problem is, the rational part takes a lot of coffee breaks, and lets the heuristic part run unchecked unless the decision is deemed particularly important and time allows for careful analysis. Even then, heuristic judgments are viewed as important inputs to the rational process, meaning that not only are most of our day to day decisions intuitive, but even the rational ones are subject to influence by the heuristic process as well.
- it allows us to speed up our decision making process dramatically by substituting easier questions for harder ones. Take the availability heuristic I’ve mentioned before. If I want to know whether the water in a well is safe to drink, I’ll try to recall instances where people drank from it and got sick. I’m answering a different question, but it’s a reasonable way to get to quick, approximate answer if I’m thirsty.
- it’s subject to systematic biases which can make us consistently wrong in certain circumstances. Even when the rational brain does step in, these biases can be very hard to overcome. Some of the early research on conjunction fallacies and the representativeness heuristic was done with social science graduate students — and even stats and psych professors — who still made elementary errors because of the pull of the heuristic. That particular heuristic has also been associated with the base rate fallacy, regression fallacy, and gambler’s fallacy.
- If we’re honestly assessing what’s most common in human thought, it’s not using our sense at all.
- So for those of us aspiring to think and reason soundly, what’s really required? Here’s my list:
  
  The strength of will not to be mentally lazy — to overcome our default heuristic-based thought process and use our rational processes more of the time.
  Enough of a grounding in deductive reasoning to engender careful thought and the avoidance of logical fallacies.
  Solid numeracy skills, with a focus on probability and statistics.
  An understanding of the scientific method — the way in which knowledge is proposed, tested and affirmed — and its limitations.
  An awareness of the myriad common cognitive biases identified in the research, the ability to spot them in one’s own thinking, and practice debiasing.