Guest essay by John Ridgway
It was late evening, April 19, 1995, that the crestfallen figure of McArthur Wheeler could be found slumped over a Pittsburgh Police Department’s interrogation room table. Forlorn and understandably distressed by his predicament, he could be heard muttering dumbfounded astonishment at his arrest. “I don’t understand it,” he would repeat, “I wore the juice, I wore the juice!”
Wheeler’s bewilderment was indeed understandable, since he had followed his expert accomplice’s advice to the letter. Fellow felon, Clifton Earl Johnson, was well acquainted with the use of lemon juice as an invisible ink. Surely, reasoned Clifton, by smearing such ‘ink’ on the face, one’s identity would be hidden from the plethora of CCTV cameras judiciously positioned to cause maximum embarrassment to any would-be bank robber. Sadly, even after appearing to have confirmed the theory by taking a polaroid selfie, Mr Wheeler’s attempts at putting theory into practice had proven a massive disappointment. Contrary to expectation, CCTV coverage of his grinning overconfidence was quickly broadcast on the local news and he was identified, found and arrested before the day was out.
Professor David Dunning of Cornell University will tell you that this sad tale of self-delusion inspired him to further investigate a cognitive bias known as Illusory Superiority, that is to say, the predisposition in us all to think we are above average.1 After collaboration with Justin Kruger of New York University’s Stern School of Business, Professor Dunning was then in a position to declare his own superiority by announcing to the world the Dunning-Kruger effect.2 The effect can be pithily summarised by saying that sometimes people are so stupid that they do not know they are stupid – a point that was considered so obvious by some pundits that it led to the good professor being awarded the 2000 Ig Nobel Prize for pointless research in psychology.3
The idea behind the Dunning-Kruger effect is that those who lack understanding will also usually lack the metacognitive skills required to detect their ignorance. Experts, on the other hand, may have gaps in their knowledge but their expertise provides them with the ability to discern that such gaps exist. Indeed, according to Professor Dunning’s research, experts are prone to underestimate the difficulties they have overcome and so underappreciate their skills. Modesty, it seems, is the hallmark of expertise.
And yet, the current perception of experts is that they persistently make atrocious predictions, endlessly change their advice, and say whatever their paymasters require. This paints a picture of experts whose superiority may be as delusory as that demonstrated by bank robbers gadding about with lemon juice smeared on their faces. If so, they may be fooling no-one but themselves. However, the real problem with experts is that, no matter what one might think of them, we can’t do without them. We would dearly wish to base all our decisions upon solid evidence but this is often unachievable. And where there are gaps in the data, there will always be the need for experts to stick their fat, little expert fingers into the dyke of certitude, lest we be overwhelmed by doubt. Nowhere is this service more important than in the assessment of risk and uncertainty, and nowhere is the assessment of risk and uncertainty more important than in climatology, particularly in view of the concerns for Catastrophic Anthropogenic Global Warming (CAGW). For that reason, I was more than curious as to what the experts of the Intergovernmental Panel on Climate Change (IPCC) had to say in their Fifth Assessment Report (AR5), Chapter 2, “Integrated Risk and Uncertainty Assessment of Climate Change Response Policies”. Does AR5 (2) reassure the reader that the IPCC’s position on climate change is supported by a suitably expert evaluation of risk and uncertainty? Does it even reassure the reader that the IPCC knows what risk and uncertainty are, and knows how to go about quantifying them? Well, let us see what my admittedly jaundiced assessment made of it.
But First, Let Us State the Obvious
I should point out that the credentials carried by the authors of AR5 (2) look very impressive. They are most definitely what you might call, ‘experts’. If it were down to merely examining CVs, I might be tempted to fall to my knees chanting, “I am not worthy”. In fact, not to do so would incur the ‘warmist’ wrath: Who am I to criticise the findings of the world’s finest experts?4 Nevertheless, if one ignores the inevitable damnation one receives whenever deigning to challenge IPCC output, there are plenty of conclusions to be drawn from reading AR5 (2). The first is that the expert authors involved, despite their impressive qualifications, are not averse to indulging in statements of the crushingly obvious. Take, for example:
“There is a growing recognition that today’s policy choices are highly sensitive to uncertainties and risk associated with the climate system and the actions of other decision makers.”
One wonders why such recognition had to grow. Then there is:
“Krosnick et al. (2006) found that perceptions of the seriousness of global warming as a national issue in the United States depended on the degree of certainty of respondents as to whether global warming is occurring and will have negative consequences coupled with their belief that humans are causing the problem and have the ability to solve it.”
Is there no end to the IPCC’s perspicacity?
Now, I appreciate that my sarcasm is unappealing, but this sort of padding and waffle would sit far more comfortably in an undergraduate’s essay than it does a document of supposedly world-changing importance. It’s not a fatal defect but there is quite a lot of it and it adds little value to the document. Fortunately, however, there is plenty within AR5 (2) that is of more substance.
The IPCC Discovers Psychology
To be honest, what I was really looking for in a document that includes in its title the phrase, ‘Integrated Risk and Uncertainty Assessment’ was a thorough account of the concepts of risk and uncertainty and a reassurance that the IPCC is employing best practice for their assessment. What I found was a great deal on the psychology of decision-making (based largely upon the research of Kahneman and Tversky) highlighting the distinction to be made between intuitive and deliberative thinking. In particular, much is made of the importance of loss aversion and ambiguity aversion in influencing organisations and individuals who are contemplating whether or not to take action on climate change. In the process, some pretty flaky theories (in my opinion) are expounded, such as the following assertion regarding intuitive thinking in general:
“. . .for low-probability, high-consequence events. . .intuitive processes for making decisions will most likely lead to maintaining the status quo and focusing on the recent past.”
And specifically on the subject of loss aversion:
“Yet, other contexts fail to elicit loss aversion, as evidenced by the failure of much of the global general public to be alarmed by the prospect of climate change (Weber, 2006). In this and other contexts, loss aversion does not arise because decision makers are not emotionally involved (Loewenstein et al., 2001).”
Well, that doesn’t accord with my understanding of loss aversion, but I don’t want to get drawn into a debate regarding the psychology of decision-making. It’s a fascinating subject but the IPCC’s interest in it seems to be purely motivated by the desire to psychoanalyse their detractors and to take advantage of people’s attitudes to risk and uncertainty in order to manipulate them into supporting green policy. For example, whilst they maintain that:
“Accurately communicating the degree of uncertainty in both climate risks and policy responses is therefore a critically important challenge for climate scientists and policymakers.”
they go on to say:
“. . .campaigns looking to increase the number of citizens contacting elected officials to advocate climate policy action should focus on increasing the belief that global warming is real, human-caused, a serious risk, and solvable.”
This leaves me wondering if they want to increase understanding or are really just looking to increase belief. I suspect that AR5’s concentration on the psychology of risk perception reveals that the IPCC’s primary interest is in the latter. The IPCC seems too interested in exploitation rather than education. For example, the authors explain how framing decisions so as to make the green choice the default option takes advantage of a presupposed psychological predilection for the status quo. This may be so, but this is a sales and marketing ploy; it has nothing to do with ‘accurately communicating the degree of uncertainty’.
Given the IPCC’s agenda, such emphasis is understandable, but once one has removed the waffle and the psychology lecture from AR5 (2), what is left? Remember, I’m still looking for a good account on the concepts of risk and uncertainty and how they should be quantified. Such an account would provide a good indication that the IPCC is consulting the right experts.
Another Expert, Another Definition
Let us look at the document’s definitions for risk and uncertainty:
“‘Risk’ refers to the potential for adverse effects on lives, livelihoods, health status, economic, social and cultural assets, services (including environmental), and infrastructure due to uncertain states of the world.”
Nothing too controversial here, although I would prefer to see a definition that emphasises that risk is a function of likelihood and impact and may be assessed as such.
For ‘uncertainty’, we are offered the following definition:
“‘Uncertainty’ denotes a cognitive state of incomplete knowledge that results from a lack of information and / or from disagreement about what is known or even knowable. It has many sources ranging from quantifiable errors in the data to ambiguously defined concepts or terminology to uncertain projections of human behaviour.”
I find this definition more problematic, since it only addresses epistemic uncertainty (a ‘cognitive state of incomplete knowledge’). The document therefore fails to explain how the propagation of uncertainty may take into account an incomplete knowledge of a system (the epistemic uncertainty) combined with its inherent variability (aleatoric uncertainty). The respective roles of epistemic and aleatoric uncertainties is a central and fundamental theme of uncertainty analysis that appears to be completely absent from AR5 (2).5
Later within the document one finds that:
“These uncertainties include absence of prior agreement on framing of problems and ways to scientifically investigate them (paradigmatic uncertainty), lack of information or knowledge for characterizing phenomena (epistemic uncertainty), and incomplete or conflicting scientific findings (translational uncertainty).”
Not only does this differ from the previously provided definition for uncertainty (a classic example of the ‘ambiguously defined concepts and terminology’ that the authors had been so keen to warn against), it also introduces terms that will be unfamiliar to all but those who have trawled the bowels of the sociology of science. What I would much rather have seen was a definition that one could use to measure uncertainty, for example:
“For a given probability distribution, the uncertainty H = – Σ(pi ln(pi)), where pi is the probability of outcome (i).”
Despite promising to explain how uncertainty may be quantified, there is nothing in AR5 (2) that comes close to doing so. Fifty-six pages of expert wisdom are provided with not a single formula in sight. I suspect that I am not as impressed as the authors expected me to be.
Finally, I see nothing in the document that comes near to covering ontological uncertainty, i.e. the concept of the unknown unknown. This is very telling since it is ontological uncertainty that lies at the heart of the Dunning-Kruger effect. Could it be that the good folk of the IPCC are unconcerned by the possibility that their analytical techniques lack metacognitive skill?
However, if the definitions offered for risk and uncertainty left me uneasy, this is nothing compared to the disquiet I experienced when reading what the authors had to say about uncertainty aversion:
“People overweight outcomes they consider certain, relative to outcomes that are merely probable — a phenomenon labelled the certainty effect.”
Embarrassingly enough, this is actually the definition for risk aversion, not uncertainty aversion!6
All of this creates very serious doubts regarding the expertise of the authors of AR5 (2). I’m not accusing them of being charlatans – far from it. But being an expert on risk and uncertainty can mean many things, and those who are experts often specialise in a way that gives them a narrow focus on the subject. This appears to be particularly evident when one looks at what the AR5 (2) authors have to say regarding the tools available to assess risk and uncertainty.
Probability, the Only Game in Town?
A major theme of AR5 (2) is the distinction that exists between deliberative thinking and intuitive thinking. The document (incorrectly, in my opinion) equates this with the distinction to be made between normative decision theory (how people should make their decisions) and descriptive decision theory (how people actually make their decisions). According to AR5 (2):
“Laypersons’ perceptions of climate change risks and uncertainties are often influenced by past experience, as well as by emotional processes that characterize intuitive thinking. This may lead them to overestimate or underestimate the risk. Experts engage in more deliberative thinking than laypersons by utilizing scientific data to estimate the likelihood and consequences of climate change.”
So what is this deliberative thinking that only experts seem to be able to employ when deciding climate change policy? According to AR5 (2), it entails decision analysis founded upon expected utility theory, combined with cost-benefits analysis and cost-effects analysis. All of these are probabilistic techniques. Unsurprisingly, therefore, when it comes to quantifying uncertainty, AR5 informs that:
“Probability density functions and parameter intervals are among the most common tools for characterizing uncertainty.”
This is actually true, but it doesn’t mean it is acceptable. Anyone who is familiar with the work of IPCC Lead Author, Roger Cooke, will understand the prominence given in AR5 (2) to the application of Structured Expert Judgement methods. These depend upon the solicitation of subjective probabilities and the propagation of uncertainty through the construction of probability distributions. In defence of the probabilistic representation of uncertainty, Cooke has written:7
“Opponents of uncertainty quantification for climate change claim that this uncertainty is ‘deep’ or ‘wicked’ or ‘Knightian’ or just plain unknowable. We don’t know which distribution, we don’t know which model, and we don’t know what we don’t know. Yet, science based uncertainty quantification has always involved experts’ degree of belief, quantified as subjective probabilities. There is nothing to not know.”
I agree that there is no such thing as an unknown probability; probability simply comes in varying degrees of subjectivity. However, it is factually incorrect to state that ‘science based’ uncertainty quantification has always involved degrees of belief quantified as subjective probabilities, and it is a gross misrepresentation to assert that opponents of their use are automatically opposed to uncertainty quantification. Even within climatology one can find scientists using non-probabilistic techniques to quantify climate model uncertainty. For example, modellers applying possibility theory to determine the mapping of parameter uncertainty on output uncertainty have found there to be a 5-fold increase in the ratio as compared to an analysis that used standard probability theory (Held H., von Deimling T.S., 2006).8 This is not a surprising result. Possibility theory was developed specifically for situations of incomplete and/or conflicting data, and the mathematics behind it is designed to ensure that the uncertainty, thereby entailed, is fully accounted for. Other non-probabilistic techniques that have found application in climate change research include Dempster-Shafer Theory, Info-gap analysis and fuzzy logic, none of which get a mention in AR5 (2).9
In summary, I find that AR5 (2) places undue confidence in probabilistic techniques and fails woefully in its attempt to survey the quantitative tools available for the assessment of climate uncertainty. At times, it just looks like a group of people who are pushing their pet ideas.
Beware the Confident Expert
The Dunning-Kruger effect warns that there comes a point when stupidity runs blind. Fortunately, however, we will always have our experts, and they are presupposed to be immune to the Dunning-Kruger effect because their background and learning provides them with the metacognitive apparatus to acknowledge and respect their own limitations. As far as Dunning and Kruger are concerned, experts are even better than they think they are. But even if I accepted this (and I don’t) it doesn’t mean that they are as good as they need to be.
AR5 (2) appears to place great store by the experts, especially when their opinions are harnessed by Structured Expert Judgement. However, insofar as experts continue to engage in purely probabilistic assessment of uncertainty, they are at risk of making un-evidenced but critical assumptions regarding probability distributions; assumptions that the non-probabilistic methods avoid. As a result, experts are likely to underestimate the level of uncertainty that is framing their predictions. Even worse, AR5 (2) pays no regard to ontological uncertainty, which is a problem, because ontological uncertainty calls into question the credence placed in expert confidence. All of this could mean that the potential for climate disaster is actually greater than currently assumed. Conversely, the risk may be far less than currently thought. The authors of AR5 (2) wrote at some length about the difference between risk and the perception of risk, and yet they failed to recognise the most pernicious of uncertainties in that respect – ontological uncertainty. In fact, when I hear an IPCC expert say, “There is nothing to not know”, I smell the unmistakable odour of lemon juice.
John Ridgway is a physics graduate who, until recently, worked in the UK as a software quality assurance manager and transport systems analyst. He is not a climate scientist or a member of the IPCC but feels he represents the many educated and rational onlookers who believe that the hysterical denouncement of lay scepticism is both unwarranted and counter-productive.
Notes:
1 This cognitive bias goes by many names, illusory superiority being the worst of them. The bias refers to a delusion rather than an illusion and so the correct term ought to be delusory superiority. However, the term illusory superiority was first used by the researchers Van Yperen and Buunk in 1991, and to this day, none of the experts within the field has seen fit to correct the obvious gaffe. So much for expertise.
2 Kruger J; Dunning D (1999). “Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments”. Journal of Personality and Social Psychology, vol. 77 no. 6, pp: 1121–1134.
3 See http://www.improbable.com/ig/winners.
4 As it happens, I am someone who made a living by (amongst other things) constructing safety cases for safety-critical computer systems. This requires a firm understanding of the concepts of risk and uncertainty and how to form an evidence-based argument for the acceptability of a system, prior to it being commissioned into service. In short, I was a professional forecaster who relied on statistics, facts and logic to make a case. As such, I might even allow you to call me an expert. So, whilst I fully respect the authors of AR5, Chapter 2, I do believe that I am sufficiently qualified to comment on their proclamations on risk and uncertainty.
5 See, for example, “Kiureghian A. (2007), Aleatory or epistemic? Does it matter?, Special Workshop on Risk Acceptance and Risk Communication, March 26-27 2007, Stanford University”. If nothing else, please read its conclusions.
6 In expected utility theory, if the value at which a person or organisation would be prepared to sell-out, rather than take a risk, (i.e. the ‘Certain Equivalent’) is less than the sum of the probability weighted outcomes (i.e. the ‘Expected Value’) then that person or organisation is, by definition, risk averse.
7 Cooke R. M. (2012), Uncertainty analysis comes to integrated assessment models for climate change…and conversely. Climatic Change, DOI 10.1007/s10584-012-0634-y.
8 Held H., von Deimling T.S. (2006), Transformation of possibility functions in a climate model of intermediate complexity. In: Lawry J. et al. (eds), Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg.
9 It is not surprising that fuzzy logic is overlooked, since its purpose is to address the uncertainties resulting from vagueness (i.e. uncertainties relating to set membership), and this source of uncertainty seems to have completely escaped the authors of AR5 (2); unless, of course, they are confusing vagueness with ambiguity, which wouldn’t surprise me to be honest.
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I remember this guy being held up to ridicule in the British press for this statement, but it always made perfect sense to me, and it’s basically what this piece is saying. It applies to individuals and society equally. “There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know”. Donald Rumsfeld.
What is missing is that the size of the unknown unknowns is infinite. All the others. What you know. What you know you don’t know. These are all finite.
Where the experts go wrong is to assume the unknown unknowns are finite. Which causes them to over estimate how much they actually know.
I clipped that quote from the newspaper when I first read it. I thought it was a brilliant summary, not just for military intelligence, but for every field of endeavor.
“Experts” do not necessarily know more about any subject than non-experts. They are just better at defending their positions on those subjects. They have a larger arsenal of tools and arguments, are better at expressing themselves, and can almost always point to a phalanx of other “experts” who agree with them. Knowedgeable non-experts can be very good at knocking down expert opinion, if they ask the right questions. It is all about understanding the vulnerabilities of the expert opinion, and pointing out the failures of their arguments. And there are ALWAYS vulnerabilities in their arguments.
This makes the job of the decisionmakers really hard, because it is rare for the decisionmaker to have a comparable “expert” at his/her side, to tell him/her that the experts are full of $hIt. And it is usually best to have two or your own experts for advice, because if you only have one, he/she will be swamped by the outside “experts”.
Been there, seen that, in government.
rxc: “Experts” do not necessarily know more about any subject than non-experts. They are just better at … expressing themselves”
Indeed, those with linguistic prowess, that think in language, have the advantage of presenting their arguments in language. Those that do not think in language are burdened with expressing their thoughts and knowledge with language. Understandably, language is how we communicate our thoughts, but this leads to linguistic prowess dominating any debate. Even when those with linguistic prowess cannot recognize their own limitations of thought without language.
I have often said that the primary difference between a Mensan and the average person is that the Mensan is able to better articulate their rationalizations for their irrational behavior.
The one [well one of them…] idea that sticks with me is just how LITTLE we know just a few hundreds years after the renaissance. We know almost NOTHING yet. And the science is settled?? I tell my children I am jealous about what they will know that I will never know.
For a better understanding of how “uncertain” the IPCC experts really are, look at the technical summary chapter 6 pages 114-115 (TS.6 Key Uncertainties). This is IMO the most damning two pages in the entire IPCC material. There is almost no area of climate study without high levels of uncertainty, low levels of confidence or stated challenges to their level of understanding.
http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_TS_FINAL.pdf
Can any of the IPCC supporters, GISS supporters or any other alarmists reconcile this with the perception of certainty which the Summary for Policymakers exudes?
I have read these pages before. Amazing how many “Supporters” of AGW there are that have not read these pages. The statements in that section remind me of the “contract” given to the poor guy that buys a car at one of those “Buy-here-Pay-here” dealerships.
Michael S,
The Technical Summary is indeed a very damning document! It should be ‘required reading’ for all with an interest in the topic, but especially for those who frequent this blog who are advocates of the extreme danger to humanity, based on model predictions. Should the Red/Blue Team exercise come to pass, all participants should be provided with a copy of the Technical Summary.
Michael S:
This is my favorite version of your similar observation:
“In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles. The generation of such model ensembles will require the dedication of greatly increased computer resources and the application of new methods of model diagnosis. Addressing adequately the statistical nature of climate is computationally intensive, but such statistical information is essential.”
http://ipcc.ch/ipccreports/tar/wg1/505.htm
Hello Michael S,
Following your suggestion I have reviewed those key pages and summarised them as follows. As you can see there are no claims of “high confidence”, although there is one claim of “likely”. In addition, there are a couple of mentions of either “little consensus” or “no consensus”.
< Total of 2.
Low confidence: 1b, 1c. 2a. 3a. 4a. 5a. => Total of 6.
Robust conclusions not possible/poorly characterised/sampling too sparse/time series too short/not yet adequately or comprehensively assessed/record remains poor: 6a. 7a. 8a. 10b. 12a, 12b. => Total of 6.
Coverage limited/limits the quantification/number is limited: 9a, 9c. 10a. => Total of 3.
Hampers more robust estimates/data inadequate: 9b. 11a => Total of 2.
Section TS.6.2 – Drivers of Climate Change. [3 bullet points (numbered from 13 to 15)]
Low confidence: 15a. => Total of 1.
Uncertainties large/uncertainties dominant: 13a, 13b. => Total of 2.
Quantification difficult: 14a. => Total of 1.
Likely: 14a => Total of 1.
Section TS.6.3 – Climate System & Its Recent Changes. [6 bullet points (numbered from 16 to 21)]
Remains challenging/challenges persist: 16a. 19b. => Total of 2.
(Modelling) Uncertainties or limits in understanding hamper attribution: 17a, 17b, 17c. 19a. 21b. => Total of 5.
Low agreement/Confidence remains low/Ability to simulate is limited/Modelling uncertainties/Less reliably modelled/limiting confidence/observational uncertainties/precludes more confident assessment: 18a, 18b, 18c, 18d. 20a. 21a, 21c. => Total of 7.
Section TS.6.4 – Projections of Global and Regional Climate Change. [9 bullet points (numbered 22 to 30)]
Medium confidence: 23a, 28a => Total of 2.
Low confidence: 24a. 26a. 27a, 27b. 28b. 29a. 30a => Total of 7.
Limited confidence/low predictability/uncertainty in projections: 22a, 22b, 22c. => Total of 3.
Not robust: 25a => Total of 1.
Little or no consensus: 26b, 29b => Total of 2.
End of file.>>
I plan to expand the review in the near future by comparing and contrasting the above confidence statements with those in the Review for Policy Makers – that comparison will, I anticipate, make interesting reading.
Regards,
Idiot_Wind.
Erratum: the analysis should started like this:-
< Total of 2.>>
Sorry for the cut-&-paste error.
Regards,
Idiot_Wind.
The text looks correct on my screen but when I post it the initial words are missing; is because I have used <> quotes?
Anyway the analysis should start like this:-
“Section TS.6.1 – Observation of Changes in the Climate System. [12 bullet points (here numbered from 1 to 12 with subordinate ordering indicated by a, b, c, …)]
Medium confidence: 1a. 2b. => Total of 2. …..”
I hope it works this time!
Idiot_Wind.
Yestirday I coodnt even spel expirt now I are one.
President Reagan summed this up quite well, “Well, the trouble with our liberal friends is not that they are ignorant, but that they know so much that isn’t so.”
The misuse of paid experts in courtrooms is also bad, such as when a generalist “expert” like a physician is set against a true subject expert in a case.
Or could it be they suffer from the old adage I heard repeated so many times about very senior PhD’s while going to college “He has specialized his expertise to point that he now knows everything there is about nothing at all.”
Reminds me of the old joke:
What is the difference between a Professor of Economics and a Professor of Finance?
A Professor of Economics knows nothing about everything.
A Professor of Finance knows everything about nothing.
Today’s word
ultracrepidarian
The IPCC’s mission was/is to provide cover to force spending, on green scams that do not work, at a time when there are ridiculous, unsustainable, high levels of government overspending, not to solve scientific problems.
The Age of CAGW will be an interesting science/sociological study, post mortem when the key observations that affect people’s gut feelings, concerning AGW, changes – planet significantly cools and CO2 levels fall.
A hot air balloonist was blown off course and lands in a field, and he yells over to a man: “Where am I?” and the man replies, “You’ve landed in a large field.”
The balloonist then tells the man that he must be an accountant (or an economist, or a mathematician, et al.) because the answer was completely accurate and utterly useless.
Not sure who came up with it (Taleb>), but I believe its called IYI: intelligent, yet idiot.
Its my job to gather and crunch numbers, for bosses who are the real “experts”. I have some math, so I can tell pretty much that x is > y, but its their jobs to fully understand What This Means, a job I gratefully allow them to consider as much more important than mine. That way, when the answer is supposed to be x < y, I'll still have a job, but at least one of them will be fired. Or, as in Seinfeld, moved upstairs where their genius can shine much further afield.
Oh, and our new Executive Director is a PhD, who came from academe to tell us how much wrong we've had it for a few decades. Yes, we'd never think of checking all the easy stuff first. And man does he loves him some InfoGraphics…
I'll basically be employed for life.
‘The balloonist then tells the man that he must be an accountant (or an economist, or a mathematician, et al.) because the answer was completely accurate and utterly useless. ‘
Reminds me of the Heisenberg joke: Cop stops Heisenberg for speeding. He approaches the car, and asks the question: COP: Do you know how fast you were going? Heisenberg: No, but I know exactly where I am,
“intelligent, yet idiot.”
—————————–
“Intellectual yet idot”, according to Taleb. Intellectuals are indeed mostly idiots. They have no real productive job, so never learn from challenge and failure to have a chance to become intelligent.
The most damning quote from the ‘Integrated Risk and Uncertainty Assessment’ chapter must be, “. . .campaigns looking to increase the number of citizens contacting elected officials to advocate climate policy action should focus on increasing the belief that global warming is real, human-caused, a serious risk, and solvable.” That sounds like something out of a Madison Avenue marketing campaign planning meeting. And it followed a paragraph in which they wrote: ” found that perceptions of the seriousness of global warming as a national issue in the United States depended on the degree of certainty of respondents as to whether global warming is occurring and will have negative consequences coupled with their belief that humans are causing the problem and have the ability to solve it. ” It is amazing that such statements are included in a chapter ostensibly about the uncertainties of the science. There seems instead nothing but certainty on display.
“Belief” is a religious term, not a scientific one. Need we say more?
Say an expert knows 10 times as much as a layman. Let x represent what the layman knows and 10x what the expert knows.
However the problem is never what you know. It is what you don’t know. The layman doesn’t know infinity – x. The expert doesn’t know infinity – 10x. Both of those two values are identical. They equal infinity.
No matter how much you know, what you don’t know is still the same size as anyone else.
The set of Real numbers has more values than the set of integers, yet each set is infinite.
Cantor’s theorem ranks infinities by ‘size’. Real number infinity > integer infinity. Original proof in set theory used the diagonal matching argument
Infinity = infinity + 1
Therefore 0 = 1
“However the problem is never what you know. It is what you don’t know.”
Scott Adams had a thread based on that insight. A warmist expert may know a lot and present it convincingly, but he isn’t telling you what he doesn’t know—he may not realize it himself.
http://blog.dilbert.com/post/165227772726/when-to-trust-the-experts-climate-and-otherwise
In performance, we can have true experts. These are people who show significantly above average skill at a given task. In theoretical subjects, the word ‘expert’ has an entirely different meaning. It is simply a person who can tell a large and/or influential group of people just what they want to hear.
IPCC ‘experts’ have no record of successful performance, consequently, they fall in the latter category.
A “climate science” expert is one who can impart a minimum amount of information using a maximum amount of words. This fools lots of people, which is the intended effect.
I call it “coach talk”, because professional sports coaches have raised talking lots and saying little to a near art form.
I am an ‘expert’ on a particular subject of some interest to the public, but a more authoritative looking chap dealing with environmental matters in a ‘modern’ way was viewed as the expert on a variety of subjects. He called me when stumped. The press considered him the expert. Our American founders knew about this tendency towards ‘worship of authority.’ This now deceased chap was a non-radical good guy, an expert in a physical science, but became famous for his feeling and mostly reasonable endeavors for the environment.
It is easy to see how radical types need their ‘15 minutes of fame’ at various levels over and over and over again. Some never obtain it and some misuse it over and over and over again.
I am about pushing on the boundary of the things I know I do not know..
In my experience on this planet I have found that any individual’s intelligence is generally inversely related to their degree of certainty that they are a genius.
I read somewhere that doctors are statistically among the worst investors, because they are convinced that their demonstrated skill relative to medicine translates to skill in other fields, and therefore won’t listen to advice. I’ve also heard this applied to being a private pilot – the smarter they think they are, the less likely to use the checklist, and therefore the more dangerous it is to fly with them.
Not surprising to see this effect in climate science, as incestuous and self-congratulating a group as was ever constituted.
Stock brokers love doctors and lawyers.
Statistically, the most successful hedge funds are those that acknowledge that they do not know, and instead merely follow the trend. Michael Covel’s book, Trend Following, can be bought here:
https://www.amazon.com/dp/B001UID8LY/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1
As my older brother, a trim carpenter, once told me, it’s not the beginning woodworkers who lose fingers. It’s the experienced ones who get caught up in routine and stop paying attention.
new definition of EXPERT . an ex is a has been and a spert is a drip under pressure.!!!!!!
“Experts engage in more deliberative thinking”
Politicians engage in both intuitive and deliberative thinking, or in other words, thinking driven by emotional arguments. Science requires objective thinking driven by logical arguments and the veracity of the scientific method, the most important attribute being the concept of falsification.
I love the question, “is it [climate change] solvable?”
Of course, that’s not the real question they’re asking at all. What they’re really asking is, can we get the general population to be as worried about climate change as we are? NO. Because the population of IPCC supported “scientists” is agenda driven, politically motivated, generally supportive of leftist causes, and so more than willing to deny people freedom and liberty, all of which causes their risk assessments to be so much BS, completely devoid of a rational cost / benefit assessment of what they’re asking.
The question “is worry about climate change solvable” is an easily answered ‘yes.’ Just stop worrying. Stop propagandizing and brainwashing our children. Educate the young and old, and leftists, on actual science, as replication, explaining about natural climate variability over the long haul. Insist that science is not about politics and eco-lunacy driven “green” agendas, but patiently waiting for ambiguity to erode in the face of solid, proven evidence.
I love a little more CO2 in the air. It will be a boon to the ecosystems they’re claiming to protect. They can learn to love it, too.
I have found that most actual “experts” tend to underrate their own expertise or the sureness of the “knowledge” while others tend to greatly overrate their own expertise or knowledge. Much like when I was 18 years old, I knew I knew just about everything there was to know about almost everything! Now I know much more than I knew then and know I don’t know but a tiny fraction of the stuff I probably should know.
Cheers!
Joe
“Accurately communicating the degree of uncertainty in both climate risks and policy responses is therefore a critically important challenge for climate scientists and policymakers.”
On its face, this is an unambiguous statement that communicating uncertainty is exceedingly difficult for climate scientists to do! I’m sure this uncharacteristic candor wasn’t intended. What the statement is trying to wrangle with is a way to conceal the magnitude of uncertainty because this makes the public not take the urgency serious. Hence the detour into egg head psychology. He wants to conceal also that he is going to lie about it (95% confidence!)
The worst revelation, though, is that the author doesn’t appreciate what the idea of uncertainty and gaps in knowledge and even unknowables or unknown unknowns are and what these do to your thesis! These are not just different colors. These are a picture of how far the journey to objective knowledge in climate science really is. The gobbledegookery is derived from the terrible legacy left by the late disasterhood peddlar Dr Stephen Schneider who advised fellow climate scientists that they had to decide how much their conscience could withstand in departing from the truth to make their case for CAGW. This is classic neo-left ends-justify-the-(always dubious) means behavior.
Yes the bulk of the American public react very rationally to the duct tape and bailing wire science of global warming.
My grandfather wasn’t “educated” but he was intelligent and wise. I will always remember what he said to me after I had won the gold medal for the highest marks in my graduating class (about 50 years ago): “The more you know, the more you know you don’t know.”