Chapter review: Judgments and Models

Context

The 2021 book, Noise: A Flaw in Human Judgment, deals with the normal human illusion that the world is a usually causally understandable and predictable place. The book was written by Nobel laureate Daniel Kahneman and two other authors. The main point of the book is to argue that noise in the real world is an undeniable and important but shockingly ignored factor in human judgment error. Judgment errors have two components, bias and noise. In the context of this book, noise is observed and measured as an innate human tendency to make errors that are not due to a known bias. With bias, one can generally predict the kinds of error people will tend to make. This is aspect of the human condition is very well-known and and generally well accepted. A few people with the moral courage to face it, even try to account for their personal biases to qualitatively and/or quantitatively reduce their errors.

On the other hand, noise in human judgment does not lead to predictable errors. That is not so well known and hard for many people to accept. It manifests as random scatter in erroneous judgments with no apparent reason other than the uniqueness of the person making the mistakes.

Even various experts in social science, medicine and commerce, who all should know better, simply blow this aspect of reality off because it is psychologically uncomfortable and/or threatening. Human egos tend to be fragile and reflexively self-defensive in the face of threat. That helps mask unpredictability and sources of causation in real life. There is an awful lot of overconfidence going on among an awful lot of people, but it may be inevitable. Most humans just don’t easily learn and practice things outside the comfort zones of their cognitive capacity or their ego.

Most of us believe most events that have happened were causally understandable, predictable and easily explained. That is sometimes true in the physical sciences, but it usually isn’t true in the social sciences and human life generally, including politics. The reasons for overconfidence to the point of illusion are now reasonably understood. They are grounded in (i) how the human mind evolved to deal with reality with as little effort as possible, and (ii) an innate human inability to see and think about the people and the world according too sets of rules, even very simple rules, that significantly (but modestly) reduce human error. 

Based on the human error rates and the reasons therefore discussed in Parts III, Noise in Predictive Judgments, and V, Improving Judgments, it seems reasonable to believe (my estimate) that if that content was mandatory subject matter in public schools and in post high school education, society maybe could avoid about 10-15% of the error and waste inherent in how we do things. In a $20 trillion/year economy, that might translate to ~$2 trillion less economic and human waste per year, maybe more. 

Chapter 9, like most of the rest of the book, relies heavily on statistics and basic statistical concepts. Because statistics is not how the human mind usually thinks, this review downplays statistical concepts and jargon as much as possible without rendering it incoherent or incorrect. 

Chapter 9: Judgments and Models

Chapter 9 focuses on why even models of reality that are so simple as to seem ridiculous are almost always better than most experts and non-experts in making real world predictive judgments. That means judgments about all kinds of things, from medical diagnoses and corporate hiring decisions to predictions of war and decisions whether to grant bail before trial to someone in jail. 

What models of reality do is take noise out of human judgments. That’s all they do. It is the only thing they do. Simple models can be flawed, but even then, they usually beat most everyone most of the time. Few people can beat models, even simple flawed ones. Why is this the case?

It is the case because humans usually apply a form of thinking that Kahneman calls “clinical judgment” to real world problems and decisions. Clinical judgment has noise in it because it is unique to the person applying it. Models do not have this variability. Applying the rules of a model to solving a problem or making a decision uniformly applies various rules relevant to the problem or decision. Kahneman calls that kind of a process “mechanical judgment.” It lacks noise because the rules are applied uniformly.

And that is where the difficulty in seeing and accepting the power of mechanical judgment compared to clinical judgment hits a brick wall. Imagine a successful, experienced doctor, or a researcher with a PhD and many peer-reviewed publications, or a high level business executive with years of training and experience being told their judgment is not as good as a simple model based on just two or three rules. It does not matter how solid the evidence is that the model is better most of the time. The model threatens ego and professional esteem.[1] Most people making judgments and predictions suffer from the illusion of validity, which is a false belief that their judgment is significantly better than it really is. One problem is that the future is usually quite uncertain and people just do not accept that reality. People believe they have the information they need to make the right judgment, but fail to understand how likely their decision is to be undone by fate. Another is that the mind tends to morph bad decisions into good ones over time by memory distorting processes. Kahneman summed it up like this:

“If you are as confident in your predictions as you are in your evaluation of cases, however, you are a victim of the illusion of validity. .... The reaction is easy to understand: Mheel’s[1] pattern contradicts the subjective experience of judgment, and most of us will trust our [often illusory] experience over a scholar’s claim.”

And, it gets even weirder. Researchers found that when they build a model of individual professionals, the model beats the professional most of the time. In other words, the model of you beats you. Models of judges beat judges, and that was based on 50 years worth of data. Kahneman comments:

“The model-of-the-judge studies reinforce Meehl's conclusion that the subtlety is largely wasted. Complexity and richness do not generally lead to more accurate predictions. .... In short, replacing you with a model of you does two things: it eliminates your subtlety and it eliminates your pattern (personal) noise.”

And, it gets even weirder than that. When random models of individuals were built and tested, not the best simple models, the random ones generally did better than the experts:

“Their striking finding was that any linear model, when applied consistently to all cases, was likely to outdo human judges predicting an outcome from the same information. .... Or, to put it bluntly, it proved almost impossible in that study to generate a simple model that did worse than the experts did.”

Poor humans. What a hot mess. Professionals tend to dislike this line of research. No one likes their judgments being called noisy. Egos get banged up and shorts are in a twist. There is much consternation, huffing, puffing and criticisms of the research. So far, all the criticisms (over 20 by now) have been fully rebutted. The research and data are sound.

Footnote: 

1. In 1954 psychology professor Paul Meehl published a book that reviewed twenty studies where there was clinical judgment and then mechanical judgment predicting how the clinical judgments turned out.  His analysis clearly indicated that mechanical beat clinical, but professionals really did not like that outcome. “Meehl discovered that clinicians and other professionals are distressingly weak in what they often see as their unique strength: the ability to integrate information.” Turns out that their perceived unique strength was their actual unique weakness.

A different kind of Cancel Culture

 So, now Joe Biden wants to do outreach to isolated communities to inform them about Covid vaccines and the Right are going apoplectic?

On top of all that, there are multiple sites on the internet telling us ways we can reach those who don't want to take the vaccine:

https://www.thedrum.com/news/2021/03/01/how-do-you-convince-anti-vaxxers-get-vaccinated-covid-comms-around-the-world

Then there is this:

Almost All U.S. COVID-19 Deaths Now in the Unvaccinated

https://www.webmd.com/vaccines/covid-19-vaccine/news/20210629/almost-all-us-covid-19-deaths-now-in-the-unvaccinated

Here is what I think:

There are two groups, those in minority communities that distrust the government and the medical profession.

Then there are those who are just OBSTINANT, who refuse for religious reasons, conspiracy reasons, or just plain "I don't wanna" reasons.

We should ALL do all we can to do outreach to those who are fearful of vaccines and provide them with information and support, not ridicule them.

As for the second group, as nasty as it is for me to think this, maybe they just need to die out since they are going to be the ones dying. I would avoid them like the plague, make them unwelcome, and would go one step further, anyone who ends up spreading the virus because they went out publicly unmasked and unvaccinated should be charged. That last one likely won't happen, but wish it would.

Lastly, I would do NO outreach to that second group, NONE - ZIP, they won't change their minds anyways - so why waste an ounce of breath on them?

Time to Cancel Culture that group!

Predicting economic collapse: 1972 predictions revisited

Wheeee!!! I bought a brand new Black Smoker!

Loud, proud, does not care about the environment

and wants everyone to know how he feels

In 1972, a MIT study generated some scenarios indicating that slowed economic growth would lead to significant societal collapse or reversals in the 21st century. Collapse meant that economic growth would slow, stop and maybe even reverse. That would be accompanied by a decreasing standard of living for most people. Presumably rich folks would be, as usual, just fine, happy and rolling in dough. 

A recent reanalysis by a risk assessment wonk at KPMG (Gaya Herrington) of that original study based on current data indicates that according to two modeled scenarios, the human race is on track to basically follow the 1972 predictions. The updated study is published in the Journal of Industrial Ecology. One was the ‘BAU2’ or the business-as-usual scenario and the other was the ‘CT’ or comprehensive technology scenario. Both predicted a collapse would start sometime in the next decade or two in accord with the new analysis.

Gathering for a Black Smoker party!!

Vice writes:

The study represents the first time a top analyst working within a mainstream global corporate entity has taken the ‘limits to growth’ [LtG] model seriously. Its author, Gaya Herrington, is Sustainability and Dynamic System Analysis Lead at KPMG in the United States. However, she decided to undertake the research as a personal project to understand how well the MIT model stood the test of time.

Titled ‘Update to limits to growth: Comparing the World3 model with empirical data’, the study attempts to assess how MIT’s ‘World3’ model stacks up against new empirical data. Previous studies that attempted to do this found that the model’s worst-case scenarios accurately reflected real-world developments. However, the last study of this nature was completed in 2014.

Herrington’s new analysis examines data across 10 key variables, namely population, fertility rates, mortality rates, industrial output, food production, services, non-renewable resources, persistent pollution, human welfare, and ecological footprint. She found that the latest data most closely aligns with two particular scenarios, ‘BAU2’ (business-as-usual) and ‘CT’ (comprehensive technology).

“BAU2 and CT scenarios show a halt in growth within a decade or so from now,” the study concludes. “Both scenarios thus indicate that continuing business as usual, that is, pursuing continuous growth, is not possible. Even when paired with unprecedented technological development and adoption, business as usual as modelled by LtG would inevitably lead to declines in industrial capital, agricultural output, and welfare levels within this century.”

Study author Gaya Herrington told Motherboard that in the MIT World3 models, collapse “does not mean that humanity will cease to exist,” but rather that “economic and industrial growth will stop, and then decline, which will hurt food production and standards of living… In terms of timing, the BAU2 scenario shows a steep decline to set in around 2040.”

Unfortunately, the scenario which was the least closest fit to the latest empirical data happens to be the most optimistic pathway known as ‘SW’ (stabilized world), in which civilization follows a sustainable path and experiences the smallest declines in economic growth—based on a combination of technological innovation and widespread investment in public health and education.

While focusing on the pursuit of continued economic growth for its own sake will be futile, the study finds that technological progress and increased investments in public services could not just avoid the risk of collapse, but lead to a new stable and prosperous civilization operating safely within planetary boundaries. But we really have only the next decade to change course.  

“The necessary changes will not be easy and pose transition challenges but a sustainable and inclusive future is still possible,” said Herrington.

The 1972 scenarios predicting bad outcomes tend to be better matches with reality in 2021, than the scenarios predicting better outcomes. Maybe this gives us a reasonable indication of what is to come if rich and powerful people, special interests and rigid ideologues keep opposing regulations to protect the environment and masses of people, just like they have been for decades.

No doubt, climate science deniers, government-hating political and Christian ideologues, crackpot conspiracy theorists and the carbon energy and chemicals sectors, e.g., Exxon-Mobile, Dow Chemical, Koch Industries, some or most transportation companies, etc., will reject any analysis like this as flawed or whatever they deem is needed to argue this into oblivion and keep profits flowing and/or the cognitive dissonance at bay from reality-based ideological disturbances. We wouldn’t want to upset anyone’s serene Feng Shui, would we?

Hm. Yup, at least some of us would love to see some upset Feng Shui among the elites, rabid ideologues and crackpots.

Anyway, the seeds of human self-destruction and long-term misery are hard wired into our mostly irrational brains by evolution. Too bad we cannot learn from science or history. So let's just blindly blunder ahead into the hardship and misery that awaits us bottom ~99%. The misery fun and games maybe starts beginning about 20 years or thereabouts from now.

Real black smokers

Update: Brain-machine interface technology

Brain-machine interface (BMI) technology is an area of long-term personal interest. BMI tech links brains with machines. That is usually done by implanting electrodes into brains and then linking electrical brain signals to computers that analyze the signals and translate them into coherent speech or mind-controlled machine movement. In essence, the technology fuses aspects of consciousness or mind with machines. The point is to allow people who cannot speak or move to do so through machines. Progress in this area is slow and incremental.

Part of the interest in BMI tech is looking for hints about the nature and biological basis of consciousness and possible insights into the centuries old mind-body problem. Depending on the expert one listens to, the mind-body problem is either one of the hardest, most complex problems that humans have ever attempted to solve, or it is just a matter of figuring out how to read electrical signals in the brain. Incremental advances in BMI tech strike me as generally in the figuring out how to read signals category, but maybe we still don’t fully understand the problem. Despite several decades of research in this area, BMI tech is still in its infancy. There could still be major surprises along the way.

A recent article in the New England Journal of Medicine describes another incremental advance. In a person with anarthria (the loss of the ability to articulate speech), scientists implanted an electrode array into the sensorimotor cortex of his brain. The scientists used the electrode array to record 22 hours of the patient’s brain activity while he attempted to say individual words from a set of 50 words. Deep-learning algorithms created computational models for detecting and classifying words from electrical patterns in the recorded cortical activity. These computational models and a natural-language computer model were used to generate probabilities of a next word based on the preceding words in a sequence. That was used to decode full sentences as the patient tried to say them. The electrodes transmitted brain signals to a computer that analyzed them and displayed the intended words on a computer screen.

The researchers reported their results as follows: 

We decoded sentences from the participant’s cortical activity in real time at a median rate of 15.2 words per minute, with a median word error rate of 25.6%. In post hoc analyses, we detected 98% of the attempts by the participant to produce individual words, and we classified words with 47.1% accuracy using cortical signals that were stable throughout the 81-week study period.

 

The patient chatting through his BMI set-up

A New York Times article elaborates on what is going on here.

In nearly half of the 9,000 times Pancho [the patient] tried to say single words, the algorithm got it right. When he tried saying sentences written on the screen, it did even better.

By funneling algorithm results through a kind of autocorrect language-prediction system, the computer correctly recognized individual words in the sentences nearly three-quarters of the time and perfectly decoded entire sentences more than half the time.

“To prove that you can decipher speech from the electrical signals in the speech motor area of your brain is groundbreaking,” said Dr. Fried-Oken, whose own research involves trying to detect signals using electrodes in a cap placed on the head, not implanted.

After a recent session, observed by The New York Times, Pancho, wearing a black fedora over a white knit hat to cover the [electrode] port, smiled and tilted his head slightly with the limited movement he has. In bursts of gravelly sound, he demonstrated a sentence composed of words in the study: “No, I am not thirsty.”

In interviews over several weeks for this article, he communicated through email exchanges using a head-controlled mouse to painstakingly type key-by-key, the method he usually relies on.

The brain implant’s recognition of his spoken words is “a life-changing experience,” he said.

“I just want to, I don’t know, get something good, because I always was told by doctors that I had 0 chance to get better,” Pancho typed during a video chat from the Northern California nursing home where he lives.

Later, he emailed: “Not to be able to communicate with anyone, to have a normal conversation and express yourself in any way, it’s devastating, very hard to live with.”

Context

This is another example of machines being able to read and translate brain signals into some form of coherence that other minds can receive and understand. Past BMI tech accomplishments include mouse to mouse communication over the internet about how to navigate a maze to get to food. In that study one mouse was in Brazil and the other in the US. Their brains were linked by signals transmitted from one brain to the internet then from the internet to the other brain. 

Another BMI increment was getting a fully paralyzed person to successfully fly a modern jet fighter simulator (an F-35, I think) through BMI tech. A US military program attempted to use commands from a human brain to a rat brain with some success. It was an attempt to weaponize the rodents for use in armed conflicts. In another research project, limited human to human brain (mind?) communication was accomplished using recorded and decoded magnetic pulses that were converted to electrical signals and decoded by computers.

Clearly, this technology is still both complex and primitive. The computer algorithms have to be able to teach themselves how to read brain signals. That accomplishment appears to be beyond the ability of the human mind alone, maybe because the signal to noise ratio is too low for humans alone to work with. Progress just inches forward. 

Despite that, there are no limits on how far BMI tech can go that I am aware of. Decoding brain signals takes a lot of computer power and sophisticated programming, but there seems to be enough of that so far. Until some kind of a technological brick wall is hit, continued slow progress can be expected for the foreseeable future.

The fascinating question still remains unanswered. Is the brain the same thing as the mind (or consciousness, intelligence or sentience), or is there something more to it? So far, all the BMI data seems to be compatible with brain = mind, or maybe brain + CNS + PNS = mind.[1] Either one would be a possible solution to the old mind-body problem. As data slowly accumulates, it seems that room for something other than body being needed for mind gets smaller and smaller. Room for a God of the gaps seems to be decreasing as knowledge increases.

Footnote: 

1. CNS = central nervous system; PNS = peripheral nervous system

It is possible that brain + CNS + PNS + all or nearly all other cells and tissues = mind, maybe even brain + CNS + PNS + all or nearly all other cells and tissues + other people and the environment = mind.

For example, sometimes an amputee feels pain from a limb that has been amputated. The brain is heavily and intimately connected to almost the entire body and it can ‘remember’ something that just isn’t there. And, humans are inherently social creatures. Social structures or institutions can and do shape or control how we perceive and think about reality. What are the physical-biological-social limits of the mind, e.g., just the brain, or something(s) more than just that? Is the question even answerable?

And, also note that the brain isn’t just neurons. There are other cells there that can and do modulate neuron activity, and presumably that affects (is part of?) the mind too. 

The CNS is in yellow, the PNS is in blue 

humans are complicated little machines

In case of emergency, break glass… (or not)

It is no secret that we, here on DisPol, are not all that fond of the rank and file Republicans.  “We see” mentally “dead people” out there, raising political hell, and we are concerned.  We feel totally justified in our concern and can present case after case of what we (and the media) see as the systematic crumbling of American democracy.  Like the religious eat, drink and sleep their religions, we here do the same with our politics.  Let’s face it, we’re just as fanatical.  We’re here virtually every day, investigating and showcasing what we see as political trouble/shenanigans.  BUT…

Out there in the real world, I have to wonder if the rest of the people (you know, “the real people” as Jack Nicholson called them in Cuckoo’s Nest) are all that taken in by what we here see as the blatant and nefarious shenanigans of the Republican Party.  Are we really in as dire shape, politically, as we think we are?

Questions: What do you think?  Do we overreact around here?  Or, is democracy indeed on the verge of falling and Everyman’s hair should be on fire?  Make your for/against case.

Thanks for posting and recommending.

Is reality politically biased?

A quick reflex answer to the question is no, reality is not politically biased. It just is what it is without regard for human concerns or biases. But is that a complete or even correct answer right now in the context of American politics and human biology and behavior? It's arguably not. In politics, humans often perceive their realities according to the dictates of various factors such as personal identity, tribe loyalty, personal biases, self-interests, life experiences, cognitive ability, education, etc.

In that context, there is a significant difference between the perceived realities of the modern FRP (fascist Republican Party and its supporters) and non-FRP people and groups who are not so radical. Clearly, most of the FRP and the most of the rest of Americans see and believe in quite different realities. Which perceived reality is closer to real reality? Based on my politics and perception of reality, the FRP vision is significantly more distorted than most of the non-FRP perceptions. But is that true or just biased and/or flawed reasoning?

A few years ago, the question came up at Quora and some interesting thoughts were posted there:

There are basically two schools of Conservative thought throughout history. There are the Traditionalists, who work to preserve the status quo, preserving the ways of life, the social institutions of the day, and the stability and continuity that brings to a culture and a civilization. And then there are the Reactionaries, who actively fight against not only change but fight against the basic premises of the present day, and seek to return to some previous "golden age".

So immediately, we have a problem with Reactionaries: they are most often trying to return to a fictionalized, cleaned up version of that past era they view today as a golden age. That's one break with reality already.

Liberalism tends to value liberty and equality, so it was very much at odds with the status quo, when it came into its own as a movement in the 1700's Age of Reason. Liberals were people who opposed Monarchy and Oligarchy, who opposed state religion, etc. This philosophy and eventually politics was embraced by philosophers, such as John Locke, and generated all sorts of frightening new ideas that challenged the status quo: natural rights of mankind, a government based on a social contract with its people, the rule of law applies to leaders and citizens alike, a demand for representative democracy, tolerance of others and other ideas, etc. So basically Liberalism on its modern creation was set as a force to oppose the status quo of the day. In it's day, the American Revolution and the Constitution were radically liberal things ... godless representative democracy, rule by the consent of the people, not the divine right of kings, that was crazy stuff.

Following the traditions of Conservatism and Liberalism in the USA, it's been the Conservatives all along opposing change. In the slavery debate, the conservatives of the day (the Democrats) supported slavery, the way things were already. The Liberals (the Republicans) felt that slavery was wrong (1865) and that slaves should have the rights of citizens to vote (1870). Sure, it wasn't until 1920 that women won the same right... again, in it's day, a very liberal cause. Liberalism was a big reason for the USA's ascendancy in the world. When the US began, founded on some of the most liberal thinking to come out of the Age of Reason, we were established here without king, without aristocracy, and of course, without a status quo.  

If you follow American politics, you have absolutely heard that many, perhaps most, conservative leaders are not just conservatives, they're reactionaries. Sure, they're in opposition to social change ... I mean, look at the right wing hissy fit that erupted over the ACA (aka, Obamacare), the idea that healthcare should be affordably available to all US citizens (not claiming it's a perfect law, it's not, but it has pushed us just a little more in the direction of Locke's Egalitarianism). Look at the claim that LGBT folks should have the same rights to marry or adopt as anyone else. That's plain old conservatism.  

But you've heard all the "want my country back", "return to a Constitutional rule of Law", etc. That's all magical reactionary thinking, and it's rampant in today's Republican Party. They want to move us back to a 1955 that never happened -- of course, ignoring the 94% top tax bracket and the misogyny that allowed every wife to remain barefoot, pregnant, and chained to the stove. In order to actually believe these philosophies, you have ignore the realities of history.

That is one argument in favor of the FRP being reactionary and less tethered to reality. And, if one believes the kinds of things I have posted here about Christian nationalism (CN) (book review, chapter 6 review, chapter 7 review, etc.) and its agenda and influence on the FRP, it seems reasonable to categorize the FRP as "reactionary." The central lie that CN fights hard to establish as a fake reality is that the US was established as a Christian nation. That is historically false, but the lie is central to reactionary CN ideology and tribalism or social cohesion. And, as one expert on the CN political movement (Katherine Stewart) put it, to get people to believe a big lie, there needs to be lots of little lies to go along with the big lie narrative.

Arguably, the same thing is happening right now regarding the ex-president's and FRP's big lie about a stolen 2020 election. A hell of a lot of little lies litter the FRP political landscape in support of the overall whopper. The fascist media put great emphasis on spreading and reinforcing the stolen election lie.[1]

So, the question remains, is there in modern American politics a liberal bias in facts, true truths and sound reasoning, or is that just another illusion emanating from a self-deluded person?

Footnote: 

1. New York Times columnist Paul Krugman wrote this opinion in December of 2017:

There are two central facts about 21st-century U.S. politics. First, we suffer from asymmetric polarization: the Republican Party has become an extremist institution with little respect for traditional norms of any kind. Second, mainstream media – still the source of most political information for the great majority of Americans – haven’t been able to come to grips with this reality. Even in the age of Trump, they try desperately to be “balanced”, which in practice means bending over backwards to say undeserved nice things about Republicans and take undeserved swipes at Democrats.

This dynamic played a crucial role in last year’s election; it’s one of the reasons major news organizations devoted more time to Hillary Clinton’s emails than to all policy issues combined. But it has been going on for years. It’s the whole story of Paul Ryan’s career: journalists trying to be centrists desperately wanted to show their neutrality by praising a Serious, Honest, Conservative, and promoted Ryan into that role even though it was obvious from the beginning that he was a con man.

And it’s still playing out, as we can see from what looks like a looming debacle in Facebook’s efforts to institute fact-checking.

Facebook wanted responsible fact-checking organizations to partner with, and several such organizations exist. But all of these organizations are constantly attacked by the right as having a left-wing bias – so it added The Weekly Standard, even though it clearly failed to meet internationally accepted standards for that role.  

So what’s the basis for claims that, say, PolitiFact is biased? Hey, The Weekly Standard itself has explained the criteria:

Surveys done by the University of Minnesota and George Mason University have shown that the supposedly impartial “fact checking” news organization rates Republican claims as false three times as often as Democratic claims and twice as much, respectively.

Notice the implicit assumption here – namely, that impartial fact-checking would find an equal number of false claims from each party. But what if – bear with me a minute – Republicans actually make more false claims than Democrats? (emphasis added)  

Take a not at all arbitrary example: tax policy. The GOP is deeply committed to the proposition that tax cuts pay for themselves, a view that has no support whatsoever from professional economists. Can you find any comparable insistence on a view experts consider false on the Democratic side?

Similarly, the GOP is deeply committed to climate change denial, despite the overwhelming consensus of scientists that anthropogenic climate change is real and dangerous. Again, where’s the Democratic counterpart?

 

But the facade is so familiar and comfortable . . . .