Chapter Review: Complex Adaptive Systems, Chaos and Prediction

Chaos

Reductionism: According to the Internet Encyclopedia of Philosophy, “reductionists are those who take one theory or phenomenon to be reducible to some other theory or phenomenon. For example, a reductionist regarding mathematics might take any given mathematical theory to be reducible to logic or set theory. Or, a reductionist about biological entities like cells [or a human brain] might take such entities to be reducible to collections of physico-chemical entities like atoms and molecules. The type of reductionism that is currently of most interest in metaphysics and philosophy of mind involves the claim that all sciences are reducible to physics. This is usually taken to entail that all phenomena (including mental phenomena like consciousness) are identical to physical phenomena.”

This is a review of chapters 1 (What is Complexity?) and 2 (Dynamics, Chaos, and Prediction) of Melanie Mitchell's 2009 book, Complexity: A guided Tour. The book is easy to read and is written for a general audience. It limits discussion of mathematics to what is necessary to understand general concepts. The complex, difficult to define concepts that Mitchell discusses in chapters 1 and 2 are critical to understanding the implications of complexity research for proper understanding of humans as individuals and as they operate in societies. One implication is that knowledge from complexity science apparently contradicts some aspects of a very common and persistent belief, reductionism, about how the world works.

Complex adaptive systems -- complex collective behavior:In chapter 1, Mitchell describes complex systems. Complex systems ranging from the behavior of army ants, a person's immune system or a human brain to a whole society, economies and the internet all constitute complex adaptive systems (CAS). Although there is not yet a single definition of complexity or CAS, they share traits that help describe them. A key trait is that all CAS exhibit complex collective behavior where each individual component follows simple rules of behavior with no central leader or controlling source. The individual components include nerve cells in a brain, individuals using the the internet and how people behave in economies.

Another common trait of CAS is their capacity to process signals and information that arise from both internal and external sources. Behavior is thus influenced arising from both internal and external environments. Another CAS trait is complex behaviors that adapt to changing real world conditions in unpredictable ways despite a lack of central system control. Based on those three common traits, Mitchell proposes two definitions for a CAS:

1. A system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaption via learning or evolution.

2. A system that exhibits nontrivial emergent and self-organizing behaviors.

In this definition, emergence refers to the idea that although the rules that guide behaviors are simple, that generates complex behaviors in unpredictable ways. In this sense, observable behavior is emergent from the CAS as a whole.

Dynamic systems and chaotic (non-linear) systems: Systems such as the solar system, a beating heart, a human or animal brain, the stock market and global climate are dynamic systems because they change over time. The study of dynamic systems led to the finding of chaotic systems, which are systems where a even a miniscule uncertainty about a full understanding of a system in its initial state can lead to massive errors in predictions about behaviors or subsequent states of the system. The upshot is that any small error about a chaotic system’s initial state will lead over time to huge errors in predictions of future states and behaviors. In essence, prediction becomes impossible over time.

An aspect of chaotic systems is that the whole is different from the sum of their parts and inputs are not proportional to outputs. That is called being non-linear. One linear system, or nearly linear, is a cup of sugar mixed with a cup of flour. The two components are unchanged and thus linear. A cup of baking soda and a cup of vinegar is non-linear because the components change and give off carbon dioxide fizz. Most systems in nature are non-linear. Mathematician Stanislaw Ulam put it like this: “Using a term like nonlinear science is like referring to the bulk of zoology as the study of non-elephant animals.” Apparently not much in nature is linear.

This aspect of chaos is what contradicts reductionism, which holds that future behaviors and states of various systems can be predicted if enough can be known about a system in advance. That is simply not true. That can never happen due to unavoidable, inherent uncertainty in trying to fully understand any chaotic system at any point in time. Tiny initial errors will lead to massive errors over time. The figure below shows how a tiny difference in an initial parameter, x0 = 0.2 vs x0 = 0.2000000001 eventually leads to different outcomes that are unpredictable.

The political upshot: Politics is a chaotic or non-linear system in any given country. Predictions about what will happen and how policies will play out over time cannot be predicted very far in advance. Existing evidence is that the best humans can predict events up to about 5 years in advance. After that, predictions fade into the chaos of random events and become mere blind guesses. Ideologues who assert their ideology is best for the long run cannot know that to be true. That kind of belief is faith, not a matter of truth.

B&B orig: 2/27/19

China: A Deep Surveillance State

Deep state: “In the United States, the term ‘deep state’ describes a form of cabal that coordinates efforts by government employees and others to influence state policy without regard for democratically elected leadership. . . . . Deep state was defined in 2014 by Mike Lofgren, a former Republican U.S. congressional aide, as ‘a hybrid association of elements of government and parts of top-level finance and industry that is effectively able to govern the United States without reference to the consent of the governed as expressed through the formal political process.’ It has become a key concept of the ‘alt right’ movement as expressed by Steve Bannon and Sean Hannity.”

Surveillance deep state: In China, a system to assign social standing and to regulate or control citizen behavior and ultimately belief, characterized by (i) constant monitoring of citizen movement, and financial, social and other personal and interpersonal activity, and (ii) controlling behavior using a ‘social credit system’ that (a) rewards personal, social, financial and other behaviors the government wants to encourage, and (b) punishes behaviors the government wants to discourage. Depending on their score, in essence, their social standing, citizens with high social credit scores earn varying degrees of access to good schools and universities, public transportation, financial services, travel visas, high paying jobs (or any job), the internet and any other good or service the government chooses to include in the social credit system. Computers running algorithms analyze citizen behavior as it flows in, e.g., from surveillance cameras, GPS movement tracking of cell phones, internet social interactions, or from cell phone purchases, and the system then rewards or punishes by adjusting credit scores. Control of beliefs flow naturally from public acquiescence to the social credit system, e.g., as unconsciously rationalized by the human mind in the face of no other choice. In theory, this form of behavior and belief control can apply to dictatorships, democracies and any other form of government that can or is forced to accommodate a similar social credit system. -- Germaine

Chinese policewoman using facial-recognition sunglasses linked to artificial intelligence data analysis algorithms while patrolling a train station in Zhengzhou, the capital of central China's Henan province

An article in the current issue of The Week magazine discusses China's social credit system, Chinese government progress in getting the system up and running and how it works. The Week writes: “China's 1.4 billion people are getting ‘social credit’ scores that rate their trustworthiness — and determine their place in society. . . . . All that data is fed into a computer algorithm that calculates a citizen's trust score. Take care of your parents, pay your bills on time, and give to charity and you'll be rewarded with a high rating, which can get you access to visas to travel abroad and good schools for your children. Run a red light, criticize the government on social media, or sell tainted food to consumers and you could lose access to bank loans, government jobs, and the ability to rent a car. Beijing aims to have the program running by 2020; pilot versions are underway in some 30 cities.”

The system is being put in place “partly, it's because China wants to better control its freewheeling and poorly regulated economy, now the world's second largest. A social credit system will let the government easily punish business people who sell toxic baby formula or rotten meat, as well as bureaucrats who take bribes.”

The system works in part “by monitoring the wealth of data generated by citizens’ smartphones. Many Chinese have given up on cash and almost exclusively use their phones to pay for goods and services — $5.5 trillion in mobile payments are made in China every year, compared with about $112 billion in the U.S.”

Data analysis works like this: “An algorithm assigns users a score between 350 and 950. The higher the number, the more perks you get. Low scorers have to pay larger deposits to do things like reserve hotel rooms, and they can be shut out of first-class seats on trains and planes. . . . . Personal factors weigh heavily — the degrees you hold, how much time you spend playing video games, and even the scores of your friends. So if your rating drops, your friends have an incentive to shun you, lest their scores dip too.”

The technology exists, but needs to be integrated into the system. “Some apartments already use facial recognition to unlock doors, and a growing number of restaurants let customers ‘smile to pay’. As more apps roll out, they will feed their data into a new government surveillance program called Sharp Eyes, a reference to the Mao Zedong–era system of neighbors informing on one another. Security cameras, ubiquitous in stores and on street corners, will be integrated into that surveillance platform, and artificial intelligence will analyze the mountain of video data.”

If the algorithm makes a mistake, “the consequences will be dire.” For example, when one person “entered an incorrect account number when paying a fine, the result was a blanket ban from all travel except the worst seats on the slowest trains.”

Chinese people cooling off at the beach - assuming they have the credit score to get there and to be there

The Wall Street Journal comments in an article today: “As hundreds of millions of Chinese begin traveling for the Lunar New Year holiday, police are showing off a new addition to their crowd-surveillance toolbox: mobile facial-recognition units mounted on eyeglasses. China is already a global leader in deploying cutting-edge surveillance technologies based on artificial intelligence. The mobile devices could expand the reach of that surveillance, allowing authorities to peer into places that fixed cameras aren’t scanning, and to respond more quickly.”

Examples of criminals the police have spotted using the AI-linked facial recognition glasses exist. “While the technology is probably useful in catching criminals, it could also make it easier for authorities to track political dissidents and profile ethnic minorities . . . . By making wearable glasses, with AI [artificial intelligence] on the front end, you get instant and accurate feedback,” Mr. Wu said. “You can decide right away what the next interaction is going to be.”

Given the collectivist culture of the Chinese people, most people accept the credit system and believe it is mostly good for their society and country. With that mindset, it is hard to see how a system like this can ever be dislodged.

Could this be the basis of a thousand year civilization? Is this the inevitable fate of societies and the human species, collectivist or individualist?

B&B orig: 2/7/18

A New World Order is Being Born

Chinese policewoman using facial-recognition sunglasses linked to artificial intelligence data analysis algorithms while patrolling a train station in Zhengzhou, the capital of central China's Henan province; China is instituting a nation-wide deep surveillance state to control both citizen thought and behavior

Writing a analysis piece for Bloomberg Businessweek (April 2, 2018 issue, pages 17-18), Michael Schuman argues that America's trade war with China could be and should be the beginning of a new world order. Schulman's brilliant analysis reflects an unparallelled grasp of reality in this observer's experience.

Schulman writes:
“Let's not sugar coat it any more. The US and China are in a trade war. . . . . The Chinese embassy in Washington, in a formal statement, pledged the country would ‘fight to the end’.

Perhaps this trade war will be resolved through negotiations . . . . The crisis might dissipate into a big nothing, with Xi tossing a few concessionary crumbs at an impatient and inconsistent Trump, who may prefer quick, tweetable wins to the hard work of changing Chinese trade practices that really threaten US businesses.

But a darker possibility cannot be ruled out: This trade war by be a critical turning point in history, the moment when irreconcilable ideological and economic differences between the world’s two most important countries burst into the open. In that case, the world my never be the same.

Some experts argue that such a conflict was inevitable . . . . as has happened [in similar circumstances] throughout history. . . . . Trump and Xi have both staked their political futures on making their nations ‘great again’, resulting a clash of nationalisms with potentially dire consequences for everybody. However the current trade spat works itself out, its fundamental causes aren't going away.

Trump is breaking with decades of US foreign policy designed to avoid just such a conflict. . . . . The whole idea was to cooperate with Beijing’s quest for economic development, to transform it from potential adversary to ally, and possibly, from dictatorship to democracy.

To Trump, that strategy was a historic mistake that allowed the country to grow wealthy and powerful at the expense of the Western world.

. . . . For much of the past 40 years, the country seemed to be moving in the ‘right’ direction. -- toward a more market-oriented economy and a more open society.

That case has become harder to make. Part of the reason is purely political. Many politicians in the US are fixating more on the perceived downside of China’s rise . . . . . and less on the benefits of lower prices to consumers and expanding business opportunities to US corporations.

A much bigger factor is Xi. Newspaper headlines may blame Trump for setting off the current trade war. But that’s not entirely fair. Xi is just as culpable, perhaps even more so. . . . . . China was never really following the path the West anticipated. It borrowed the tools and trappings of capitalism while dispensing with liberal political, economic and social principles that have traditionally accompanied it.

Certainly, Xi asserts the usual promises to continue ‘opening up’ and to champion globalization. But in real life, he’s dropped even the pretense that China is heading in the ‘right’ direction. His regime is regressing into a one-man dictatorship. . . . . He’s creating rival institutions to those of the West . . . . While blathering on about pro-market reform, Beijing is intensifying Communist Party influence over business and heavily subsidizing many high-tech companies to give them an advantage over Western competitors.

. . . . No longer content to join the US-led economic order, China is striving to change it to suit its own interests. All Trump is doing is calling out what’s become obvious: China is not a partner, but a competitor, and has to finally be treated as such.

. . . . [China’s] leaders that the country’s economic future depends on their ability to upgrade its industries and foster technological innovation, and they’re unlikely to significantly alter their industrial program under any circumstances. Trump may be able to pry open a market here or remove a regulatory hurdle there. . . . . But he’s not likely to persuade Xi to give up on his Chinese Dream.

Nor will his successors. Trump will eventually leave the White House . . . . . But the fundamental challenge from China isn’t likely to vanish. The danger that the world could again degenerate into competing blocks -- one democratic and free market and the other authoritarian and statist -- will remain a terrifying prospect. Washington invited China into its new world order. Now China could destroy it.”

Commentary: As unpleasant as that vision seems, it strikes this observer as completely accurate. It fully accords with what this observer experienced in person with how China does business with Western companies. In doing business with the West, China’s focus was unfailingly focused on:
(i) sucking up all the technology possible, even if the Chinese experts who received it were incapable of understanding what they received,
(ii) not allowing one Yuan more out of the Country than was absolutely necessary, and
(iii) adopting a patient, ultra-long term view, decades or centuries if needed, to build global technological and economic advantage.

China’s relentless focus and endless patience cannot be overstated.

Schulman’s analysis, including his warnings about Trump’s serious personal weaknesses, and America’s unstable form of government, ought to be required reading.

B&B orig: 4/6/18

China’s Deep Surveillance State is Awakening

Chinese policewoman using facial-recognition sunglasses linked to artificial intelligence data analysis algorithms while patrolling a train station in Zhengzhou, the capital of central China's Henan province

The Independent reports that China’s national public surveillance system is starting to bear fruit in its quest for law and social order: “Chinese police have used facial recognition technology to locate and arrest a man who was among a crowd of 60,000 concert goers.” The man was accused of ‘economic crimes’. Facial recognition cameras were set up at the entrances to the concert.

This isn't the first time China’s surveillance system has been able to find people sought by Chinese authorities. For example, 25 suspects using facial recognition were arrested at a beer festival last August.

China openly describes itself as a world leader in facial recognition technology. Chinese citizens are regularly reminded that the growing surveillance system makes it nearly impossible to evade authorities. Presently, China’s system employs 170 million CCTV cameras with another 400 million to be installed in the next three years.

It is easy to see that thins kind of technology would be appealing to tyrannies the world over. It may even be of more than passing interest to more than just tyrannies. The question is whether this kind of technology, coupled with other surveillance methods such as tracking of cell phone purchases, cell phone conversations, and cell phone locations, can form the basis to build a Thousand Year Reich that really could last 1,000 years or more. As it stands now, the Chinese people are rapidly and willingly abandoning cash for buying and using electronic purchases via cell phones and online instead.

It is hard to see how a person could remain out of sight in a country with about 470 million cameras constantly monitoring everything in the camera’s range of vision. This kind of a deep surveillance state really is starting to look like a new normal for at least the roughly 1.4 billion Chinese citizens.

B&B orig: 4/23/18

Book Review: The Myth of the Rational Voter

“I am suspicious of all the things that the average citizen believes.” -- H. L. Mencken

In The Myth of the Rational Voter: Why Democracies Choose Bad Policies (Princeton University Press, 2007), author Bryan Caplan looks at evidence of voter rationality from an economist’s point of view. What Caplan finds in the data is a consistent difference of opinion between professional economists (econs) and non-economists (non-econs). Caplan starts with survey data related to opinions about factors that affect the economy. Econs and non-econs rarely agree. Caplan asks why there’s such a consistent difference and what effect that can have for democracy.

Chapter one opens with Caplan’s observation that “What voters don’t know would fill a university library.” After that, things get interesting. Caplan raises the defense of voter ignorance called “rational ignorance.” Econs like the idea of rational ignorance because econs want to believe (are biased to believe) that people think and act rationally. That idea posits that it is rational for voters to be ignorant because their vote has no impact on election outcomes. After all, major elections are never decided by a single vote.

The logic behind that false vision of reality holds that “democracy can function well under almost any magnitude of voter ignorance.” The flaw in that logic assumes that voters don’t make systematic errors. The econ’s bias was that random errors are random and therefore mistakes in voting cancel each other out.

Systematic errors abound: It turns out that voters’ errors are far from random. Voter errors are usually systematic, not random. The argument that ignorance is rational turns out to be irrational. Voter errors may not affect a voter personally or in a way that they can directly see or feel. Nonetheless, voter misunderstandings do have demonstrable adverse impacts on societies. Regarding bad policy choices that voters can generate, Caplan puts it like this: “When a voter has mistaken beliefs about government policy, the whole population picks up the tab.”

Voters perceive realities through a lens of pervasive reality-distorting biases that underlies much of the difference of opinion between econs and non-econs. They include one or more of four major biases that tend to affect public opinion on most economic issues. The four biases are:
(1) an anti-market bias that causes people to underestimate market forces’ capacity to harmonize private greed with the public interest,
(2) an anti-foreign bias that causes underestimation of the benefits of foreign trade and immigration,
(3) a make-work bias that overestimates the adverse impacts of labor-saving technology and automation, and
(4) a pessimistic bias that leads to underestimation of current economic conditions, often expressed as a nostalgia for earlier times with conditions not as good as people usually imagine they were.

Economists have not been completely ignorant of systematic public biases about economic issues. The pre-industrial revolution economist and philosopher, Adam Smith, observed that “science is the great antidote to the poison of enthusiasm and superstition.” These biases are old and they run deep and across cultures.

Caplan acknowledges a problem. There is deep public resistance to disquieting knowledge, e.g., the destructive existence and power of the four biases. That kind of knowledge undermines personal beliefs and most people flatly reject it or rationalize it into insignificance. Regarding the make-work bias against automation, Caplan observes: “These arguments [in favor of automation] sound harsh. That is part of the reason they are so unpopular; people would rather feel compassionately than think logically.”

CRITICISM 1: Caplan is aware of and addresses common criticisms of economists and their opinions. He acknowledges that expert econs can be biased and can be wrong when the non-econ public is right. He also observes that both can be wrong, but that both can’t be right. Caplan points to public resistance to what social science is telling the public about human cognition and he fully expects the same flames of public rejection to scorch econs and their opinions.

CRITICISM 2: Two common beliefs about econ bias holds that econs express a self-serving bias because they are (1) privileged, well-off academics with protected jobs, and/or (2) ideologically biased in favor of businesses and wealthy people. Caplan goes through the data and finds that the econ bias can account for at most 20% of the difference of opinion between econs and non-econs. If there is systematic bias among econs, it isn’t the major source of opinion differences. The data argues that, if anything, econs are less far right in their political ideology than non-econs. And, the data shows that non-econs with increasing information or knowledge express usually opinions closer to econ opinion. Knowledge, or lack thereof, explains more of the econ vs. non-econ opinion split than systematic econ bias.

Caplan includes an appeal for economists to drop their indefensible lingering disbelief in irrationality and get on with accepting and dealing with the reality that the concept of the rational voter is a myth.

B&B orig: 9/26/16

Book Review: The Undoing Project

Author Michael Lewis' book The Undoing Project: A Friendship That Changed Our Minds (W.W. Norton & Co., 2017) describes the collaboration between Israeli psychologists Daniel Khaneman and Amos Tversky. In 2002, Khaneman won a Nobel prize in economics for his contribution to decision theory. To a large extent, their work transformed the professionalism of psychology and forced it's influence to the center of economics.

Given the generality of their work on human cognition, thinking and decision-making, it is reasonable to expect that their work will heavily influence research in many other areas of human activity over time. Whether the new knowledge will translate to American society and its thinking and behavior appears to be very unlikely for the foreseeable future.

Daniel Khaneman

For anyone interested in politics, the question of how the field of psychology went from mostly nonsense to relevant, serious science that could no longer be ignored by the 1980s makes this book well worth the money and time. The book is written for a general audience and is an easy read. It is light on technical details but nonetheless clearly conveys the state of psychology and cognitive biology and how that moved from the end of the dark ages in the 1900s to core modern relevance.

The book's central theme revolves around the intense academic relationship between two basically incompatible geniuses. Tversky was an organized but arrogant, optimistic and self-confident master of mathematical psychology. By contrast, Khaneman was disorganized, pessimistic and riddled with self-doubt, but he did have an amazing capacity to see core problems in psychology (quirks of human thinking and behavior) that the rest of the field simply could not see. Khaneman's creative insights, and his ability to articulate and experimentally get at the root of a problem were, and probably still are, astounding. Tversky's capacities were similar.

Eventually their academic relationship came to a prolonged, unpleasant end. Tversky died in 1996 of cancer, some years thereafter. Khaneman is professor emeritus at Princeton.

The book's title, The Undoing Project, refers to the effort of the two scientists to"undo", among other things,
(i) the then-dominant 'utility theory' of decision making that dominated and underpinned economic theory and belief; and
(ii) the human mind's intense desire to, and ease of, erasing (undoing) "what was surprising or unexpected."

The rational man: One area their research profoundly affected was economics and its 1700s-vintage utility theory. The theory was based on the assumption that people were usually rational in the economic decisions they made. Khaneman-Tversky research found that wasn't true.[0] One source of systematic error was a human cognitive trait of a common 'belief in small numbers'. They found that people, including professional statisticians and experimental psychologists who should know better, often drew conclusions from amounts of evidence that are too small to draw any conclusions from. The data was clear that "people mistook even a very small part of a thing for the whole." The normal human belief is that ANY sample of a large population was more representative of the population than it really was. Humans simply did not evolve to think in terms of statistics.

Heuristics: Tversky and Khaneman's research identified four basic rules (heuristics) the human mind uses to help make decisions, even when there is uncertainty of an unknowable degree. In essence, the human mind is a pleasure machine.[1] People's biological desire to avoid a loss is greater than their desire to secure a similar gain. From an evolutionary point of view, that makes sense. During evolution, people who underestimate risk tended to get eliminated from the gene pool.

Amos Tversky

The blow back: Khaneman and Tversky lost faith in decision analysis in the context of wars that Israel fought. Khaneman expressed the problem in public talks he called "Cognitive Limitations and Public Decision Making." Affecting decision making was their attempt to inject the implications of their research into high-stakes, real world decision making and government. They tried to do that by forcing experts on decision making to assign odds of events of all possible outcomes, e.g., war, peace, border skirmishes or attacks by less than all adversaries all at once.

In practice, the exercise failed. Despite their successful efforts to get Israeli intelligence agencies and politicians to understand scenarios in terms of probabilities, the data and analysis fell on deaf ears. Specifically, Israeli intelligence estimates gave a 10% increased of risk of another war if Henry Kissinger's peace efforts with Syria failed. Despite the warning, Israeli foreign minister Yigal Allon wasn't impressed and didn't work to bolster Kissinger's peace efforts. Khaneman said "That was the moment I gave up on decision analysis. No one ever made a decision because of a number. They need a story. . . . the understanding of numbers is so weak that they don't communicate anything. Everyone feels that those probabilities are not real -- that they are just something on somebody's mind."

Lewis puts it like this: "He [Allon] preferred his own internal probability calculator: his gut."

One bright spot - the young: Both Tversky and Khaneman had taught the biology of judgment to elementary or high school students and the two wrote in an unpublished manuscript that "we found these experiences highly encouraging." Lewis writes: "Adult minds were too self-deceptive. Children's minds were a different matter."

Khaneman wrote: "We have attempted to teach people at various levels in government, army, etc. but achieved only limited success."

Under the current retrograde political conditions, the public schools option seems to be the ONLY path to possibly injecting this new knowledge into mainstream American politics and society.

The lost cause: Post truth politics: Unfortunately, the impact of the new knowledge of human cognition and social behavior on politics is weak. It's not non-existent, but current political conditions strongly disfavor rationality. There's a faint pulse, at least for now, but it will be easy to kill.[2]

For decision making based on modern cognitive and social biology, the obvious and probably only path to possibly reach that lofty goal is to require at least one semester, probably two, of instruction in human cognitive and social biology for all public schools. Absent that, it's highly likely (>95% chance ?) that politics will remain as irrational and fantasy-based as it is now and as it will be in at least the upcoming 4 or 8 years.

Lewis' book has lots of other gems in it, for example, describing the impact of emotional states such as potential hope or regret on perceived experiences or reality. The human mind has many ways of distorting both reality and reason. This book makes that crystal clear using both real life anecdotes and descriptions of research by Khameman, Tversky and others. Given the role of human emotions, reality (including fact) is mostly personal and subjective, not mostly objective.

And, there's this nugget: "To Danny the whole idea of proving that people weren't rational felt a bit like proving that people didn't have fur. Obviously people were not rational, in any meaningful sense of that term."[3]

Questions: Is it true or at least plausible that children can be taught to self-question but adults cannot? If so, is there any point to even discussing this kind of science in the context of politics because adults are a lost cause?

Footnotes:
0. A personal guess as to why psychology had to stay dark ages until about the mid 1900's (1960s and later): (a) more wealth allowed more decisions that weren't just survival based (data shows that the more survival-critical a decision is, the more rational it usually is and poverty or near survival living focuses the mind on what's needed to survive), and (b) the rise of machines that could analyze much more data than people with just fingers and toes, an abacus or a slide rule.

1. The mind also is an impressive false reality-creating machine. In the context of driving a car: "The brain is limited. There are gaps in our attention. The mind contrives to make those gaps invisible to us. We think we know things we don't. . . . . It's that they [people] don't appreciate the extent to which they are fallible."

2. Given his rhetoric and animosity for (i) all that went before and (ii) truth, it seems more likely than not that Donald Trump will act to kill Obama's 2015 Behavioral Science Insights Policy Directive, which was based on work by Khaneman and Tversky as adopted for politics by Richard Thaler, a behavioral scientist and economist.

3. And this bizarre attack from an academic critic in the 1979 who felt that Khaneman and Tversky were being too pessimistic about human cognitive limitations. Lewis wrote: "The masses are not equipped to grasp Amos and Danny's message. The subtleties were beyond them. People needed to be protected from misleading themselves into thinking that their minds were less trustworthy than they actually were. 'I do not know whether you realize just how far that message has spread, or how devastating its effects have been'. . . . Even sophisticated doctors were getting from Danny and Amos only the crude, simplified message that their minds could never be trusted.** What would become of medicine? Of intellectual authority? Of experts?" Critics' fear was obvious and palpable. In the current political climate, the knowledge that Khaneman and Tversky generated will probably fall on deaf ears, or maybe even be subject to vicious post truth political attacks.

** That attack was typical - critics often exaggerated what Khaneman and Tversky kept saying explicitly in their publications, i.e., the mind isn't always wrong, but it is subject to errors and they are often systematic (not random), predictable and uncomfortably frequent.

B&B orig: 1/16/17