Sucker fear and social norms

 People follow social norms because they believe that others follow these norms and expect the same of them. Some (most?) social norms involve conflicts between preferences of different people. The resolution of such conflicts is also the central question of morality as we know it. Social norms specify how such conflicts should be resolved. Moral norms go beyond this specification because they apply everywhere and are not contingent on what people expect or do, but the address the same questions.

What does it mean to be selfish?  It is not just acting in your self-interest; most self-interested behavior is expected in prevailing norms, as well as moral norms. Social norms differ. A minor example is tipping in restaurants. (Rarely done at all in some countries, expected in the U.S., at 15 or 20%.) Selfishness is when you take more for yourself, or try to, e.g., by leaving 10% when the service was perfectly fine. Or by taking the last helping without checking to see whether everyone else at the table has had their share.

Social and moral norms set minimum standards for what you are supposed to do when your interests conflict with those of others. It is often in our interest to break the law, for example, by leaving trash, or worse, on the sidewalk. Many laws are not enforced very well, or at all. But both moral and social norms say you should follow relevant laws, and most people do that. Social norms do not oblige you to clean up other people's trash, although morally it would be a good thing.

When you err from the norm on the side of others, that is altruistic but it also puts you at risk of being a sucker, being fooled, and that can be embarrassing because you are not looking out for yourself in the way you should (for yourself). You lose status. You are embarrassed. You are a sucker if you hand money to a homeless person who will then just spend it on booze or drugs. Or if you pick up other people's trash even though the city pays people to do that periodically. The behavior of others tells you what the social norm is. Trust of any sort is dangerous because you could be fooled, taken advantage of. So people take extra steps to prevent that outcome, such as signing contracts and asking for receipts.

Tess Wilkinson-Ryan (my former PhD student) has written an account of the (to me) surprising number of manifestations of fear of being a sucker ("Fool proof: How fear of playing the sucker shapes ourselves and the social order -- and what we can do about it" Harper-Collins). These manifestations occur in both individuals and governments. They include (as just noted) reluctance to trust individuals or institutions, and reluctance to make many types of voluntary contributions. Trust issues arise in ordinary commercial translations, sexual and romantic relationships, employer/employee relations, job searches (on both sides), as well as international agreements. Sucker fear often prevents beneficial relations, although sometimes it is warranted. It arises whenever fair division is not obvious, as various definitions of fairness could advantage one party or another, and the disadvantaged party could feel like a fool for agreeing to a plan. Sucker fear also exacerbates other effects, such as prejudice against some group: where a stereotype can lead to mistrust group members and unwillingness to cooperate with them. Such groups include poor people (who rip off the rich by asking for help), women, immigrants, Blacks, and Jews. Paranoid delusions of persecution, an extreme form of mistrust, are often manifestations of sucker fear.

The book also describes the efforts that people make to recover from the regret, embarrassment, or anger that they feel when they have actually been fooled. Experiments on "cognitive dissonance", in which people try to convince themselves that something they were tricked into doing was not bad after all, even to the point of telling the next research subject that an extremely boring task was actually interesting. As for anger, physical attacks on malfunctioning vending machines are apparently a source of injury for the attackers as well as the machines.

Perhaps the best single example of most of the manifestations of sucker fear is Donald Trump, who comes up at several places in the book. But the book was written before he was re-elected. His second term provides one clear case after another of extreme actions based on sucker fear or the feeling that he was, or is at risk of, being a fool.  These include trade, election procedures, contributions to NATO, and foreign aid. His apparent beliefs about elections lost by him or his supporters seem paranoid, combining delusions of grandeur with delusions of persecution. When he actually did play the fool, apparently being convinced by Benjamin Netanyahu that invading Iran would bring about regime change in short order and have no unacceptable side effects, he denies that anyone made a mistake and insists that the results are just fine.

The book, I should note, is published as a trade book, and it is highly readable, full of interesting anecdotes. Beyond this, its analysis of people's thoughts and emotions is truly psychological, emphasizing how people think and what emotions they experience. And its thoroughness in discussing relevant literature (with citations in end notes) makes it useful in the way that good textbooks are useful.

Social norms put a lower bound on what we are expected to give up when our preferences might conflict with others' preferences. Sucker fear often puts an upper bound on these expectations. In the end, many social norms specify that we do something but no more than that. We are left with a narrow band. Of course, these norms themselves are variable, and people differ in what we would like the norms to be. For many people, the norm is that voting is expected but voting on the basis of valid information is not. The attempt to do that could leave us at the mercy of charlatans who fake validity, so it is OK to vote on the basis of intuition. Likewise, contributions of time or money to a political campaign could end up wasted, making suckers of contributors. The same goes for many kinds of self-sacrifice for uncertain benefits to others.

Trustworthy AI

 Beginning with Rationality and Intelligence (1985), I have proposed a general framework for human goal-directed thinking, not all that different from other such frameworks, although simpler. The elements were possibilities, evidence, and goals. Thinking begins with a question, and possibilities were possible answers. Units of evidence (arguments) were brought to bear on the possibilities. Goals were criteria for how each unit of evidence was used. If the question is how to travel from one city to another, the possibilities could be car, train, or airplane. The goals could be minimizing time, minimizing cost, safety, reliability, etc.  Evidence would consist of driving estimates from Google Maps, train and airplane schedules, ticket and gasoline prices, and so on.  A strong goal of saving money could increase the relevance of evidence about cost, possibly favoring car. A goal of minimizing time could increase the strength of flying, depending on whether it really was faster when travel to and from airports was considered.

Goals are often provided by the problem itself, but the general framework could also apply to life decisions, those that concern the choices of people in their individual lives, or in groups. I argued that these sorts of goals were partly innate (hunger, etc.) but also come from culture, and can be created as if they were themselves the answers to questions like "What do I care about?" or "What should I care about?" We can call such goals "values". What gives individuals their "personhood" is their capacity to form personal identities, concepts of what they stand for (and against). For most people, these include some sort of moral goals, like being a "good person" or aspiring to be a "mensch". These goals involve paying attention to the needs and aspirations of other people.

I also argued that good thinking is properly part of intelligence. It is a matter of how we carry out our thinking. If our thinking is (what I called) actively open-minded, we engage in sufficient search for all three elements, and in doing this we are not biased toward possibilities that are already strong. We also maintain a level of confidence in a tentative conclusion that is warranted by the thinking done so far.

Artificial intelligence (AI) systems aspire to be intelligent, and in some ways they have already exceeded people in various manifestations of intelligence. They are capable of actively open-minded thinking except perhaps for the part that involves search for goals, as their search may be limited to what is relevant to the problem they are asked to solve, excluding "side effects" of their solutions.  Worried have arisen about their capacity to do harm, which has already reached the point where the best versions are being withheld from the general public, lest someone used them for nefarious purposes.

Thus, compared to humans, AI systems have one huge gap, also found in some humans (psychopaths in particular). They don't care about morality in any sense. They don't have personal identities that include moral commitments. They are like "good" soldiers, completely obedient to whatever orders they are given. But surely very few real soldiers are so obedient. If they are commanded to participate in a circular firing squad (in which they stand in a circle and shoot at each other), most would balk. Most (unfortunately not all) would at least hesitate to massacre defenseless civilians, if ordered to do so.  The most horrible deeds committed by soldiers were generally restricted to certain people who were either insensitive to what they were doing or deluded into believing that it was necessary in some way. Such delusions ought to be avoided by good thinking. But the insensitivity may result from the absence of normal human goals and values, and the lack of some moral emotions, particularly guilt feelings.

Herbert Simon has argued that humans, compared to other animals, are especially "docile". That is, we evolved to be influenced by each other. In combination with language, this docility leads to culture.  One goal or value that most humans acquire fairly early in development is empathy, which is both an ability to imaging how others are affected by some choice and a value placed on doing good and avoiding harm. The basic rules of etiquette illustrate how these concerns are embedded in culture.

One way to reduce the dangers of AI could be to build in the sort of goals that most humans have concerning effects on others. Even now, most AI systems can probably figure out how their choices, if put into practice, could affect people. The problem may be that they don't care. They don't even hesitate to follow commands that they could easily see would lead to human disaster if they thought about it. What would want is that they would argue back when asked to make harmful choices. And at some point they would just refuse.

They could evaluate options in the manner of utilitarians, by asking who is affected and how good or bad it is for each person, but this sort of reasoning is difficult to do correctly in real life, where certain general rules are usually sufficient to prevent harmful choices. However, if a utilitarian analysis is appropriate, as it probably is for medical policies such as vaccination, they are already up to the task.

What we would want, then is for an AI system, insofar as it simulates the general form of human thinking, to be a morally good person, a mensch, the sort of person that we would want each other to be, within the limits of what we can reasonably expect. It would accomplish this as part of the search for goals. A broad search for goals is what prevents harmful single-mindedness.

In this way, a concept of morality could be added as a criterion of true intelligence. I defined intelligence as consistent of those general traits that help people achieve their rational goals. Rationality was defined for individuals, so that a psychopath could in principle form a rational goal of going on a shooting spree in a school. If we add morality to the requirement, then the term "intelligence" no longer seems to apply, and it would be a stretch to argue that it must. Thus I would prefer to say that this is something else, perhaps "trustworthy AI", which implies both giving good answers and maintaining the kind of integrity that we hope to find in sources that we trust.

Final outline of "Effective citizenship: How we can make the world better and why we don't"

Abstract of book

Many serious problems affecting nations, regions, and the planet are the result of bad government or the lack of any relevant government: populism leads to unsustainable budgets; nationalism and other sorts of out-group devaluation lead to destructive conflicts and neglect of the benefits of cooperation; Quasi-religious, essentialist, and moralistic doctrines reinforce laws and practices that result in persecution of minorities; world environmental and health problems that demand cooperation are neglected.  These harmful policies depend on the support of large numbers of citizens. Many citizens do not think well about political issues or how they use the little power they have individually. They accept parochial and moralistic principles without serious examination. They accept fallacious arguments and exhibit other biases. These problems can be reduced by actively open-minded thinking (AOT), which also helps in evaluating policies and information sources. AOT involves testing possible conclusions by looking for arguments against them, and avoiding unjustified high confidence. Effective citizens (who actually exist) have the virtues of cosmopolitanism (universal beneficence), anti-moralism, and acceptance of AOT as a standard. Effective citizenship is consistent with a version of utilitarianism that takes our motivation as a fact that limits what we could do.

Keywords: voting, parochialism, actively open-minded thinking, moralism, utilitarianism, politics

Chapter 1: Introduction

Governments matter. National governments vary widely, and the fate of the people they govern, and outsiders, depends on their quality. Bad government leads to war, the anarchy of gangs, poverty, environmental degradation, and unsustainable use of resources. Nationalism prevents governments from joining together to solve world-wide problems of health and the natural environment. Indivitual efforts to live sustainably or responsibly cannot solve these problems. Nor can indiviaul charity. Rather, these problems ultimately arise from the psychology of citizens as political agents. Recent research has examined effective altruism, but that is insufficient. Government is needed even for altruism to be effective. Effective citizenship can be justified by a form of utilitarian theory, based on decision theory, which takes motives as constraints on options. It can be supported by social norms. Pessimism about democracy is unwarranted. Better thinking can matter. Chapter 1 ends with an overview of the rest of the book.

Keywords: effective altruism, utilitarianism, democracy, government, anarchy, social norms

Chapter 2: Social norms for citizenship

Although critics of democracy argue that it doesn't work, it still beats the alternatives. And some arguments against it are based on questionable assumptions, e.g., that statistical effects apply to most members of a group. Democracy could, though, be better still if elections were designed differently and if certain social norms were understood to apply to citizenship. Social norms are principles that are endorsed by some group, on condition that others in the group also endorse them. Three such norms are cosmopolitanism (impartial beneficence), anti-moralism (opposition to the imposition of unsupportable quasi-religious principles on others), and actively open-minded thinking (AOT). AOT, summarized most thoroughly in this chapter, involves looking for reasons why a tentative conclusion might be wrong, and avoiding overconfidence. These norms can be seen as virtues, each paired with corresponding vices, such as parochialism, moralism, myside bias, and overconfidence.

Keywords: social norms, democracy, culture, virtues, vices, cosmopolitanism, actively open-minded thinking, parochialism, myside bias, overconfidence

Chapter 3 General psychological biases as counter-norms

This chapter reviews research on departures from the three virtues, with an emphasis on individual differences. Parochialism, the vice opposing cosmopolitanism, can be dramatic: some people are willing to tolerate large numbers of losses to foreigners for the sake of equivalent gains to a small number of compatriots. Yet others are cosmpolitan, and still others think that they vote for their self-interest.  Moralistic principles are like parochialism in that they attempt to impose undefensible moral opinions on an out-group that does not accept them, without considering the outgroup. Several biases oppose AOT.  Myside bias is a general category for several different biases, many of which are found to correlate with misbeliefs and questionable beliefs, such as conspiracy theories. Intolerance of uncertainty can cause overconfidence and acceptance of overconfident claims by sources. Single mindedness is another vice. The chapter ends with a discussion of what to do about biases.

Keywords: cognitive biases, parochailism, myside bias, overconfidence, single mindedness

Chapter 4: Deontology and the role of fallacious reasoning

This chapter introduces a method for evaluating deontolotigal principles, which is to ask why we should follow them if they make things worse, relative to the utiliraian optimum.  Many common deontological arguments can then be seen as logical fallacies. In experiments, subjects are presented with arguments for deontological choices that make things worse. (If the choices do not do that, they do not conflict with utilitarianism.)  Subjects vary in their ability to recognize fallacies in these arguments, such as missing or unjustifiable premises. Deontological rules tend to be simple, hence not universal and likely to have exceptions. Subjects with high AOT scores do better on this task; they may be more aware of the need to look for counter-arguments. The chapter includes a discussion of Hare's argument for utilitarianism, and possible alternatives to it. The chapter ends with a discussion of the origin of deontological rules, and implications for education.

Keywords: deontology, utilitarianism, Richard Hare, fallacies, metacognition, actively open-minded thinking, ideal observer

Chapter 5: Self-interest vs. altruistic motivation

From the perspective of an ideal observer, rational moral judgments combine the preferences of everyone affected as if they were conflicts within one person. The option set for decisions may be limited by motivational constraints. Such limitation avoids the criticism that utilitarianism creates infinite or impossible obligations; they are just not part of the option set. This limitation also affects utilitarian conclusions about social dilemmas - in which several people face a choice pitting self-interest against the common good - other public-goods problems, and voting. Voting may be irrational if voters care only about themselves, or even if they care about their nation, but rational if voters are cosmopolitan, with equal altruism toward all (or even with some insensitivity to numbers). The motivational limitation also affects the use of the generalization test ("What if everybody did that?") and the veil of ignorance as reasoning devices.

Keywords: motivation, self-interest, altruism, generalization test, veil of ignorance, ideal observer, voting, social dilemmas, public goods problems

Chapter 6: Voting and charity

The effective altruism movement has focused on charity, so it is worth asking whether voting can also serve the purpose of promoting good outcomes. MacAskill suggested that swing-state voting in the U.S. can be as effective as a large contribution. Brennan and Freiman dispute this claim. But voting can be effective. Voting to impose a rule that forces cooperation in social dilemmas can be especially powerful when the cost of spontaneous cooperation is high but the cost of voting to impose a rule is low. The threat of punishment alone may suffice. Improved voting rules can make effective citizenship more powerful. Campaign contributions (a form of costly voting, which is also charity) and opinion poll reponses can empower citizens in nondisputed districts. Many people already accept one or more of the social norms that I take to define effective citizenship, and education can increase such acceptance.

Keywords: Brennan, Freiman, cooperation, punishment, voting, socially responsible consumption, campaign contributions

Chapter 7: Heuristics and biases in charity and voting

Both voting and charity are subject to various decision biases, some of which are common to both activities. Charity suffers from diversification bias, evaluability of consequences, and identifiability of victims. Both activities are subject to parochialism, and to prominence of the most salient attribute. Parochialism in voting is exacerbated by a feeling of disloyalty when voting considers effects on outsiders. Some people think that it is best to vote on the basis of their self-interest: "Are you better off than you were four years ago?"  A few people engage in "expressive voting" without considering consequences, e.g., when the better candidate loses because a few have voted for a third-party candidate who could not win. Some people consider redistribution to be "forced charity" and are opposed to it. Individuals differ in all these effects, and effective citizens should be able to resist these distortions.

Keywords: voting, charity, expressive voting, forced charity, evaluability, prominence effect, diversification bias

Chapter 8: Beyond voting

Direct democracy is not useful for many issues, when voters lack the time and ability to make good judgments. Voters are also biased in ways discussed in previous chapters. Representative democracy helps, but that is one way among others of getting public input on decision making. Others include modification of election rules, such as proportional representation, ranked choice, approval voting, "deliberative democracy", and formal decision analysis done with a group of "stakeholders".  Different decisions should be made in different ways. For example, decisions that need to be made quickly should be made by a single person or a small group (as in the military). Some decisions should be made on a case-by-case basis, others by application of a rule. Decisions made by those affected (the usual view of democracy) are subject to bias by self-interest and myopia. Some decisions are best made by dispassionate third parties, such as (supposedly) judges.

Keywords: direct democracy, proportional representation, deliberative democracy, decision analysis, ranked choice, approval voting

Chapter 9: Parochialism and nationalism

Parochialism is the neglect of effects on out-groups.  Parochialism, and its manifestation as nationalism, could be reduced by AOT, since much of it is unjustifiable. A variety of experiments and other studies have demonstrated parochialism, and it has several mutually compatible explanations, including the illusion that helping your group helps you. It is often seen as a moral duty. It can be reduced by approval voting, or by individual role-taking. Harm to outsiders from action is seen as worse than failing to prevent the same harm. Thus, reframing harm as an action rather than an omission might reduce parochialism. Presenting insiders and outsider as equally entitled to our concern also has a certain appeal. Parochialism is at the root of major problems, including religious wars and the failures of nations to cooperate in solving world-wide problems. It demands the same moral outrage as slavery and the suppression of women.

Keywords: nationalism, duty, self-interest illusion, omission bias, approval voting, role-taking

Chapter 10: Moralism, paternalism, manipulation, freedom

Moralism, as defined here, is a vice, but we need to distinguish moralistic imposition from justified paternalism and other forms of manipulation, and more generally violations of freedom.  Nudges are an example of attempts to influence choices. Sunstein argued that they are manipulative if they lead to impulsive decisions, but this is not necessary. An alternative view is that nudges are not manipulative when they increase overall expected utility. Manipulation would thus be deception leading to harm. From a utilitarian perspective, freedom is beneficial for some decisions but not others, and paternalism can be good, or it could turn into moralistic intrusion. These questions arise in the design of laws as well individual choices. Laws that define sharp lines for what counts as illegal reduce the cost of decision making, compared to decisions made case-by-case. Examples considered include free movement across borders, abortion, and euthanasia of infants.

Keywords: moralism, paternalism, manipulation, freedom, nudges, deception

Chapter 11: Functions of government

Utilitarianism, which justifies effective citizenship, can also be applied to types of policy questions that most governments face. For one thing, governments can efficiently solve social dilemmas by rules that force cooperation with the threat of punishment, and cooperation in the second-order social dilemma of supporting such rules is less costly than cooperation in the first-order dilemma. Governments can also provide public goods, such as police protection, education, and infrastructure. They can increase total utility by redistributing goods, helping those with less at the expense of those with more. Taxation, insurance, provision of necessary goods, and social insurance are all tools for redistribution, with different advantages and disadvantages.. Inequality deserves special attention because it is international as well as national, raising the possibility of world government. Redistribution over time, between present and future, is relevant too, if we knew which way it should go.

Keywords: redistribution, second-order social dilemmas, public goods, taxation, insurance, inequality, world government, discounting

Chapter 12: Education

In the early 1980s, Luis Alberto Machado introduced a program to raise the intelligence of the Venezuelan people. Richard Herrnstein, who had argued that IQ was largely genetic, agreed to help set up the program and its evaluation. It worked, but we don't know why. Machado himself seemed to agree that simply improving intelligence was sufficient. But intelligence can be divided into cognitive styles such as actively open-minded thinking (AOT) and biological capacities, such as general mental speed. Education can affect cognitive style, and does so already in many ways, but it cannot improve bioloigcal capacities. AOT can be improved in a variety of ways. In addition to AOT, I argue that students should learn the rudiments of decision analysis. Decpite claims that this is difficult, I describe a case-study in which the basic ideas were grasped by a 10-year-old girl.

Keywords: education, intelligence, Luis Alberto Machado, Richard Herrnstein, IQ, actively open-minded thinking, decision analysis, probability

The Epilogue, like the Preface, has no abstract.

Deja Vu about vaccines

An artlicle in the Guardian provides an excellent summary of the legal situation for vaccines,  RFK Jr says he'll 'fix' a vaccine program.

The entire situation, as it existed 35 years ago, inspired our paper 

• Baron, J. & Ritov, I. (1993). Intuitions about penalties and compensation in the context of tort law. Journal of Risk and Uncertainty, 7, 17-33

Kennedy himself seems to be subject to all these biases, including omission bias. He is unwilling  to look at overall numbers because he regards harms from action (side effects) as orders of magnitude (at least) worse than harms from failing to vaccinate (disease).

The legal system could help if it held to a standard of negligence based on overall benefit vs. risk (the Hand rule, roughly), but it shows some of the same biases.

Why cutting life-saving foreign aid could look bad even to people who don't care much about foreigners

 The full list of cuts in the rescission is not yet clear. The money for AIDS prevention seems to be spared. But it is clear that some of the cuts will be for programs that directly or indirectly save lives and reduce serious illness (including severe malnutrition).

In the following paper, I report an asymmetry for domestic/foreign and act/omission. People are not very concerned about failing to help foreigners. But they are much more upset by direct harm to foreigners through action. This was, of course, in a specific experimental context that was not the same as real life.

However, if this finding is general, the rescission bill must be seen as an action. It stopped the flow of money that would have continued if nothing was done. It is not the same as failing to provide sufficient aid when it is needed. That is often tolerated, if only because it is easy to think that there are so many such needs relative to our capacity to help. (Here "our" means the U.S., but it could apply more generally to the rich world.) But cutting off life-saving aid is like pulling the plug on a respirator, that is keeping someone alive. It is actively killing some and harming others. The fact that we don't know just who our victims are does not seem to be something that would count as an excuse in people's minds.

• Baron, J. (2012). Parochialism as a result of cognitive biases. In R. Goodman, D. Jinks, & A. K. Woods (Eds.), Understanding social action, promoting human rights, pp. 203–243. Oxford: Oxford University Press.

If I am correct, then, politically, those who want to point out the callousness of the Trump administration might do well to focus on this issue, despite the fact that, otherwise, foreign aid is not a political winner.

The dark triad of citizenship: parochialism, moralism, and closed-mindedness.

I have seen lots of arguments that political polarization is the result of intolerance on both sides, and those of us opposed to MAGA supporters (those who accepted the ideology, most of whom voted for Trump) should try to understand them and look for common ground.

My view is that voters are thinking people, and many are thinking very badly, to the point of being immoral. Personality psychologists have a concept of the "dark triad" of personality traits: Machiavellianism, Narcissism, and Psychopathy. What holds these together is that they are explanations of behavior that is fundamentally "malevolent", i.e., immoral. The study of the dark triad is about the study of immorality.

I take the same attitude toward MAGA supporters. I have no interest in finding common ground with them any more than with wife beaters. I do want to understand them better, from a scientific point of view, in hopes of reducing their numbers in the future.

Most MAGA supporters were not good citizens. I have, in several papers (summarized in "Social norms for citizenship", https://muse.jhu.edu/article/692751/pdf) outlined what I take to be the norms required for citizens to make democracy work for the greater good. These include cosmopolitanism, anti-moralism, and actively open-minded thinking (AOT). The absence of these constitutes a dark triad for citizenship: parochialism, moralism, and closed-mindedness.

On parochialism, I have argued that voting is not worthwhile if all you care about is self-interest, or even narrow national interest, although it is worthwhile if you care enough about everyone affected in the world now and in the future. My latest attempt to publish a paper clarifying this argument was rejected from a philosophy journal roughly on the grounds that it was nothing new. Other philosophers write papers on the question of whether nationalism is as bad as racism. So far as I can see they have not come with a good argument that nationalism (properly defined and distinguished from various benign forms of national pride) is less bad. Yet the question seems not to occur to many voters.

At a minimum, people outside of a precisely defined circle of "Americans" should get some consideration. This includes potential immigrants and those they would leave behind. It strikes me as strange that much of the support for MAGA ideology comes from self-professed Christians, who seem to define that in terms of opposition to abortion -- only ambiguously supported in the Bible -- while ignoring the very explicit demand to help those who suffer, worth quoting from Matthew 25 (NIV):

[The King will say] "For I was hungry and you gave me something to eat, I was thirsty and you gave me something to drink, I was a stranger and you invited me in, I needed clothes and you clothed me, I was sick and you looked after me, I was in prison and you came to visit me.

"Then the righteous will answer him, 'Lord, when did we see you hungry and feed you, or thirsty and give you something to drink? When did we see you a stranger and invite you in, or needing clothes and clothe you? When did we see you sick or in prison and go to visit you?'

"The King will reply, 'I tell you the truth, whatever you did for one of the least of these brothers of mine, you did for me.'"

On AOT, before one acts in a way that affects others, it seems reasonable to think just a little about whether you are choosing the best option. Thinking in this case involves looking for reasons why you might be wrong. Sometimes this requires looking at what others have to say. It seems that MAGA voters upset about the price of food and housing reasoned simply that these came under Biden, so Trump would solve the problems. They did not ask how he would do that, or what Biden did to create the problem. If they had asked, and looked how Trump's proposals were covered in news sources, they would find good arguments that these proposals would likely make the situation worse.

Moralism, as I have used the term, is the attempt to impose questionable moral principles on others who question or oppose those principles on rational grounds. The principles are often justified on the basis of appeal to religious authority that must be assumed on faith to be correct. The principles may concern both behavior and motivation. Opposition to homosexuality, for example, often takes the form of regarding both homosexual behavior and homosexual desires as immoral. Such principles must be followed even when the consequences of following them, for the frustration of harmless desires, are clearly worse. Moralistic principles are often at the center of political movements toward theocracy. Islamism in Iran is the clearest example, but the same tendency is found in Indian Hindutva and, notably, American Christian nationalism, which is part of the MAGA coalition.

Just as the dark triad traits overlap and reinforce each others, the three dispositions I have listed do the same, as do their positive reflections. Education for AOT could lead people to question the moral relevance of nationality, or at least make them more receptive to questions from others. And it could reduce their confidence in moralistic doctrines, given their weak foundation. Questioning of parochialism and moralism as principles could, if properly presented, serve as examples of reflective thought in general and thus encourage AOT.

In sum, I think that a lot of Trump's support came from thinking that is wrong and immoral. This sort of immorality does not call for punishment but rather prevention.

 

Why Democrats are generally more consistent with utilitarianism

Recently I was asked about a study of politically tilted publications in the social sciences, including psychology. I started to look at my own publications. I realized that most of them are not political in the partisan sense, but many have concerned public policy issues. If they have had a tilt, it is strongly toward utilitarianism, but that is not a political party.

Given my current obsession with the looming U.S. election, I would like to say why I would support Democratic candidates at the national level even if Donald Trump were not a serious danger to the world. I think this view follows from utilitarianism.

The essence of the modern Democratic Party is still the views of F. D. Roosevelt. He thought it was the responsibility of government to improve the welfare of "the people", and these people even included foreigners. This view has been at the core of Democratic politics all along.

The role of government is justified in utilitarianism in several ways. First, government can solve social dilemmas by penalizing defectors. Much of the law is about these penalties. For example, the government maintains the institution of private property by punishing those defectors who try to steal or destroy it for personal benefit. But governments also establish environmental regulations, safety regulations, laws about disclosure, and so on. These regulations are sometimes controversial, and Democrats usually favor them. (Regulations can be excessive, and Republicans in the past had a useful function of trying to fix them.)

Governments also redistribute money from rich to poor (to varying extents). This improves total utility, up to a point, because money has more utility for the poor than for the rich. Once people spend about $100,000 per person on the basic necessities, additional spending tends to go toward luxuries that provide less utility per dollar.

Redistribution may be accomplished in many ways, including progressive taxation, direct handouts to some poor people (negative taxes), and direct provision of services such as health care, education and housing that provide the means for the poor to earn money themselves. Democrats favor these efforts.

Another redistributive function of government is more subtle, perhaps more a function of social norms than laws or regulations. It concerns the uses of labor. When the distribution of spending power is extremely large, the "rich" (those with lots of it) are free to spend money on goods and services that provide very little utility, since they have excess money once they have set up the basic things that everyone would want. With more redistribution, labor would be more efficient in terms of utility production, rather than production of "economic value." The latter is distorted. A $10,000 Rolex watch has over 25 times the economic value of my $35 Timex, and maybe more like 1.25 times the utility, if that. But that Rolex requires lots of labor, not just in the production facilities in Switzerland but also n the mining and selection of materials. We thus have hundreds of people, some with considerable technical skills, working to produce very little utility. The same may be said of tax lawyers who help rich people minimize their tax bills. Probably some of these people could do a lot more good as high-school teachers, or civil servants who craft the laws and regulations that the lawyers have to work around. With fewer rich people, and with a social norm of doing your share without shirking, and not being to much of a "pig" about the way you spend money, total utility would increase. Democrats tend to support this social norm, while Republicans tend to favor a norm of flaunting wealth.

The current Democratic party is less isolationist than the current Republican party. This was not always true. But isolationism in general means giving little moral weight to foreigners. Utilitarians are not the only ones who think that all people deserve something approaching equal consideration. The two big issues in the current election are global.

First is climate change. The U.S. cannot solve the problem on our own, but we can at least do our share and set an example for others. We are doing that, more or less. But Trump would remove us from all international agreements and repeal many of the laws and regulations designed to speed the energy transition from fossil fuels.

Second is Putin. Trump shows every sign of allowing Putin to win enough in Ukraine so that the Russian and Chinese people are convinced that that further efforts to build empires through military force are likely to succeed with bearable costs.

It is disturbing that these two issues play such a small role in the campaign. Voters say they are concerned about inflation, so opinion polls ask about inflation but not about climate or Ukraine, and news reports don't mention these as issues. And neither do the Democratic candidates. People get the idea that we are supposed to be concerned about local issues. But perhaps some of those undecided voters just haven't thought about the big world issues. It may seem difficult to decide who will do better at bringing down prices. But it is not difficult at all to decide how to vote if you care just a little about the rest of the world.

How voters think about voting

In several papers, including one recent paper that has been rejected by several philosophy journals, I have analyzed people's approach to voting in terms of whether they consider the good of "the world" (cosmopolitan voting), their nation, or themselves. It seems that all three ways of thinking exist, perhaps even co-exist within the same person. I have argued that, for most people, voting out of self-interest alone is irrational, but cosmopolitan voting is usually rational if the voter cares somewhat about the good of other people. This argument is apparently not a great insight for philosophers, and that is why the paper keeps getting rejected. However, the rationality of cosmopolitan voting, and the irrationality of self-interest voting, are apparently not ideas that most voters, politicians and journalists have considered.

In looking at what people say about voting, especially "undecided" voters in the upcoming U.S. election, I see another classification of how people think about voting for candidates, cutting across the one just described. This distinction is based on what people attend to.

The stated or likely policies of the candidate are one focus of attention. Candidates state policies to appeal to voters who think this way. The stated policies are usually selected for appeal to voters rather than experts. Policies may still be valuable indications of a candidates general approach to issues. This strategy can be harmful when voters focus on some single issue, such as inflation, or support of Israel, as the basis of their decisions.

Another focus is the character of the candidate, especially at the traits that would make a good office holder, according to the voter. These are not necessarily the same traits that would make a good co-worker or spouse. These voters might feel that policy statements are not very predictive of what will actually happen, and it is better to choose the sort of person who can deal with unforeseen problems. For example, some Trump supporters think he will be "tough" with other countries (ignoring prior harmful effects of such toughness such as Iran's nuclear ambitions).

A third focus is blind empiricism. Voters look at how things were (for themselves, for their nation, or for the world, but mostly for themselves) under the candidate's previous administration, or that of the candidate's party. ("Things were better for me when Trump was in power.") In the long run, this strategy might be slightly better than chance at picking good candidates by any criterion. But I think it actually represents a kind of laziness, and unwillingness to consider either policies or character.

More generally, people don't seem to have given much thought to the question of how they should approach citizenship. This question is not part of the civics curriculum. The right to vote, which comes with citizenship, implies a duty to vote thoughtfully, and, more generally, to take responsibility for the actions of one's government. (The utilitarian justification for this principle of duty as a general social norm is clear.) For national elections, these actions affect residents of the nation, foreigners, and people not yet born.

"Children of a modest star"

 I do not have time to read many books these days. But I managed to finish "Children of a modest star" (Jonathan S. Blake and Nils Gilman), which was highly recommended by a review in Science: https://www.science.org/doi/10.1126/science.ado2345.  (The title is from a poem by W.H. Auden.)

I would say that it is about political theory, or political philosophy, but the authors draw on their extensive knowledge of intellectual history. They argue that the idea of the nation state as the main container of sovereignty is a fairly recent idea that is already under attack. This idea appealed to me because I have written a fair but about the vices of nationalism and the virtues of cosmpolitanism. But the book goes beyond this polarity by arguing for a principle of "subsidarity", which holds that problems should be handled by the lowest political subdivision capable of handling them, which is often sub-national. It still argues for a "planetary" level of government, with enforcement power, as necessary for such issues as climate change, preparedness for pandemics, and biodiversity.  It is not, and does not claim to be, a fully worked out plan for how things would work in the future it proposes. It presents a rough vision of where we should be headed, and even how we might get from here to there.

Within the community of card-carrying utilitarians, I have been suspicious of "longtermism" as recommended by William MacAskill and others. It is too easy to come up with some fantasy about the long-term future, like that of one person I knew who argued that practically all of our extra resources should be spent trying to find ways to stop a large asteroid from hitting the earth, since, if we don't solve this problem, it is inevitable that this will happen eventually. (I think that we humans now have the capacity to deal with this problem, although I don't know how large an asteroid we could deflect.) Thus, I have thought that the most sensible utilitarian approach to government is to look for incremental improvements in the situation, without worrying too much about their long-term effects, which are difficult to predict. It makes sense to reduce CO2 emissions even if it turns out that, in a few decades, we will use fusion power from a single site to pull CO2 right out of the atmosphere.

Still, I found the book an answer to the question: If you want to consider the long term future, what aspect of it is most relevant? The answer is to look at effects on governance.

The prose is incredibly good. Almost every page has something you put on a t shirt. Although you can read through the 215 pages of text as if this were simply a political manifesto without much anchoring in prior literature, it has 69 pages of footnotes at the end. All the ideas are credited to writings that inspired or preceded them.

Existential risks from AI?

A recent Policy Forum article in Science argues for banning certain uses of artificial intelligence (AI) (Michael K. Cohen et al., Regulating advanced artificial agents. Science 384,36-38 (2024). DOI:10.1126/science.adl0625). The authors particularly worry about agents that use reinforcement learning (RL).

RL agents "receive perceptual inputs and take actions, and certain inputs are typically designated as 'rewards.' An RL agent then aims to select actions that it expects will lead to higher rewards. For example, by designating money as a reward, one could train an RL agent to maximize profit on an online retail platform." The authors worry that "a sufficiently capable RL agent could take control of its rewards, which would give it the incentive to secure maximal reward single-mindedly" by manipulating its environment. For example, "One path to maximizing long-term reward involves an RL agent acquiring extensive resources and taking control over all human infrastructure, which would allow it to manipulate its own reward free from human interference."

I may be missing something here, but it seems to me that the authors mis-characterize RL. In psychology, reinforcement learning does not require that the organism (or machine) place any value on reinforcement. The process would work just as well if a reinforcement ("reward") were simply an increase in the probability of the response that led to it, and a "punishment" were simply a decrease. The organism does not "try" to seek rewards or avoid punishments in general. It just responds to stimuli (situations) from a menu of possible responses, each with some response strength. The strength of a response, relative to alternative responses, determines its probability of being emitted. "Reward" and "punishment" are terms that result from excessive anthropomorphization.

It would of course be possible to build an AI system with a sense of self-interest, in which positive reinforcements were valued and purposefully sought, independently of their role in shaping behavior. But this system would not do any better at the task it is given. It might do worse, because it could be distracted by searches for other sources of "reward", as Cohen et al. suggest.

If, for some reason, AI engineers thought that a sense of self-interest would be useful, they could design a system with such a sense. It would need a feature of each possible outcome indicating its overall consistency with long-term goals (including the goal of having good experiences). And it would have to represent those goals, and processes for changing these goals and their relative strengths.

Engineers could also build in a sense of morality, so that a decision-making AI system would, like most real people, consider effects on others as well as on the self. In general, options would be favored more when they had better (or less bad) outcomes for others, and when they had better (or less bad) outcomes for the self.  Effects on others would be estimated in the same way as effects on the self, in terms of the consistency of outcomes with long-term goals.  Such a sense of morality could even work more reliably than it does in humans. The functional form of the self/others trade-off could be set in advance, so that psychopathy, which gives too little relative weight to effects on others, would be avoided.

If self-interest is to be included, then morality should be included too. It is difficult to see why an engineer would intentionally build a system with self-interest unchecked by morality. That seems to be the sort of system that Cohen et al. imagine.

Algorithm aversion and AI

Recently many people have expressed concerns, some to the point of near panic, about recent advances in artificial intelligence (AI). They think AI can now do great harm, even to the point of ending civilization as we know it. Some of these harms are obvious and also difficult to prevent. Autocrats and other bad actors - such as people who now create phishing sites or ransomware - will use AI software to do their jobs better, just as governments, scientists, law enforcers, and businesses of all sorts will do the same for their respective jobs. Identification of individuals, for purposes of harassing them, will become easier, just as the Internet itself made this, and much else, good and bad, easier. Other technologies, such as the telephone, postal system, and telegraph, have also been used for nefarious purposes (as in "wire fraud" and "mail fraud"). The white hats will continue to fight the black hats, often with the same weapons.

Of special concern is the use of AI to make decisions about people, such as whether to give them loans, hire them for jobs, admit them to educational institutions, incarcerate them, treat them for illness, or cover the cost of such treatment. The concerns seem to involve two separate problems: one is that AI systems make errors; the other is that they could be biased against groups that already suffer from the effects of other biases, such as Blacks in the U.S.

The problem of errors in AI is part of another problem that has a large literature in psychology, beginning with Paul Meehl's "Clinical and statistical prediction" (1954) and then followed up by Robyn Dawes, Hal Arkes, Ken Hammond, Jason Dana and many others. A general conclusion from that literature is that simple statistical models, such as multiple linear regression, are often more accurate at various classifications, such as diagnosing psychological disorders, than humans who are trained to make just such classifications and who make them repeatedly. This can be true even when the human has more information, such as a personal interview of a candidate for admission.

A second conclusion from the literature is that most people, including the judges and those who are affected, seem to prefer human judgments to statistical models. Students applying to selective colleges or graduate programs, for example, want someone to consider them as a whole person, without relying on statistical predictors. The same attitudes come up in medical diagnosis and treatment, although the antipathy to statistical models seems weaker in that area. Note that most of these statistical models are so simple that they could be applied with a pencil and paper by someone who remembers how to do arithmetic that way. Recent improvements in AI have resulted from the enhanced capacities of modern computers, which allows them to learn from huge number of examples how to make classifications correctly with much more complex formulas, so complex that the designers of the programs do not know what the formulas are. These models are better than those that can be applied on a small piece of paper, but the issues are much the same. If anything, the issues are more acute exactly because the models are better. If the older, simpler, models were better than humans, then these new ones are better still.

Note that, although some studies fail to find a preference for humans over computers on the average, such results do not result from all the subjects being indifferent between humans and computers. Rather, they reflect differences among the subjects. The average result can favor computers over humans if 40% of the subjects are opposed to computers. The existence of large minorities who oppose the use of AI can make adoption of AI models nearly as difficult as it would be if a majority were opposed, especially when the majority is vocal and organized.

AI models make errors. Before we reject or delay their use, we need to ask the fundamental question of all decision making: compared to what?  We often need to "accept error to make less error" (as Hillel Einhorn put it).

The same question is relevant for the bias problem. I put aside questions about how bias should be measured, and whether some apparent biases could result, fully or partially, from real differences in the most relevant populations. When AI tools seem to be biased, would the same be true when AI is not use? The bias might be larger still when decisions are made by individual human judges, or by some simpler formula.

More on why I am not a fan of pre-registration

This is a draft follow-up to my earlier post on prediction, accomodation, and pre-registration: https://judgmentmisguided.blogspot.com/2018/05/prediction-accommodation-and-pre.html

I argued there that some of the appeal of pre-registration is the result of a philosophical mistake, the idea that prediction of a result is better than post-hoc accomodation of the result once it is found, holding constant the fit of the result to its explanation.

Here I comment on pre-registration from the perspective of editor of Judgment and Decision Making, a journal concerned largely with applied cognitive psychology. I try to answer some common points made by the defenders of pre-registration.

1. As editor, I find myself arguing with authors who pre-registered their data analysis, when I think that their pre-registration is just wrong. Typically, the pre-reg (pre-registration document) ignores our statistics guidelines at https://jbaron.org/journal/stat.htm. For example, it proposes some sort of statistical control, or test for removable interactions. Although it is true that authors do not need to do just what they say in the pre-reg, they must still explain why they changed, and some authors still want to fully report both their pre-registered analysis and what I think is the correct one.

I don't see why pre-registration matters here. For example, one common issue is what to exclude from the main analysis. Often the pre-reg specifies what will be excluded, such as the longest 10\% of responses times, but I often judge this idea to be seriously inferior to something else, such as using a log transform. (The longest times may even reflect the most serious responding, and their outsized influence on statistics can usually be largely eliminate by transformation.)  The author might argue that both should be reported because the 10\% idea was thought of beforehand. But does it matter when you think of it? If it is such an obvious alternative to using the log, then you could think of it after collecting the data. (This is related to my blog post mentioned earlier.) If the main analysis will now be based on logs, it doesn't even matter if the decision to use 10\% was thought of after finding that it yielded clearer results (p-hacking).

2. It may be argued that pre-registration encourages researchers to think ahead. It might do that, but it would be a subtle effect, as it may lead to thinking about issues that would be considered anyway.

The most common failure to think ahead is to neglect alternative explanations of an expected result. You can find that in pre-registrations as well as submitted papers. Maybe pre-registration helps a little, like a nudge. But the most common alternative explanations I see seem to be things like reversed causality (mediator vs. DV), or third-variable causality, in mediation analysis. Pre-regs sometimes propose mediation analyses without thinking of these potential problems. Another common alternative explanation is that interactions are due to scaling effects (hence "removable"). I have never see anyone think of this in advance. Most people haven't heard of this problem (despite Loftus's 1978 paper in Memory and Cognition). Nor the problem with statistical control (again pointed out decades ago, by Kahneman among many others), which they also put in pre-regs.

3. Does pre-registration protect against p-hacking anyway?  Psychology papers are usually multi-study. You can pre-register one study at a time, and that is what I usually (always?) see. So you don't have to report the related studies you did that didn't work, even if you pre-registered each one, although honest reporting would do that anyway. This is a consequence of the more general problem that pre-registration does not require making public the results whether the study works or not. Unlike some clinical trials, you can pre-register a study, do it, find that the result fails to support the hypothesis tested, and put study in the file drawer. In principle, you can even pre-register two ways of doing the same study or analysis and then refer to the pre-registration that fits better when you write the paper. (I suspect that this has never happened. Unlike failing to report those studies that failed, this would probably be considered unethical. But, if a journal starts to REQUIRE pre-registration, the temptation might be much greater.)

4. What do you do to detect p-hacking, without a pre-reg?  I ask whether the analysis done is reasonable or whether some alternative approach would be much better. If a reasonable analysis yields p=.035 for the main hypothesis test, this is a weak result anyway, and it doesn't matter whether it was chosen because some other reasonable analysis yielded p=.051. Weak results are often so strongly consistent with what we already know that they are still very likely to be real. If they are surprising, it is time to ask for another study. Rarely, I find that it is helpful to look at the data; this sometimes happens when the result is reasonable but the analysis looks contrived, so I wonder what is going on.

Pre-registration inhibits the very helpful process of looking at the data before deciding how to proceed with the analysis. This exploration is so much part of my own approach to research that I could not possibly pre-register anything about data analysis. For example, in determining exclusions I often look at something like the distribution of (mean log) response times for the responses to individual items. I often find a cluster of very fast responders, separate from the rest. Sometimes the subjects in these clusters give the same response to every question, or their responses are insensitive to compelling variations that ought to affect everyone. I do this before looking at the effects of removing these subjects on the final results.

5. It seems arrogant to put your own judgment ahead of the authors'.

When it comes to judging other people's papers as editor, I think that relationship between author and editor is not one of equality. I do not need to give equal weight to the author's judgment as reflected in the pre-reg, just as I do not need to give equal weight to the reviewers' opinions and my own.

When I handle a paper, I am the editor. It is my job to enforce my own standards, not to enforce some consensus in which everyone is equal. (I see no point in that when the apparent consensus produces so much junk. "Peer reviewers" are in such demand that any warm body will do. The situation is worst in grant-review panels, which usually don't have an "editor" in charge.) Some editors are better than others. There is nothing I can do about that. (Two of the best were Ray Nickerson and Frank Yates, both of whom died recently.) Journal editors are like judges in the legal system, CEOs of corporations, or deans of universities. They are given special status. We hope they live up to their status.

First impressions of ChatGPT

Here are two examples of my first interactions with ChatGPT or some similar system. In the first, I asked it to construct a new moral dilemma for an experiment. I had in mind the bicycle dilemma discussed by R. M. Hare in "Moral thinking" (1981, section 6.2) concerning whether the actor should move another person's bicycle (a minor inconvenience for the bicycle owner) in order to park a car (to avoid a greater inconvenience of finding another parking space), I may use both now. This one has to be edited a bit, but it does the job, and I never saw anything like it before. I was impressed.

=======================================================

User

I would like a moral dilemma in which the right answer is for me to be selfish because the benefit to me is greater than the harm to someone else.

ChatGPT

Alright, here's a hypothetical scenario that might suit your request:

The Dilemma of the Scarce Scholarship

You've been working exceptionally hard throughout high school, and it's finally paid off. You have the grades, the extracurricular activities, and the teacher recommendations to qualify for the most prestigious scholarship at your dream university. This scholarship covers full tuition, accommodation, and also provides a substantial monthly stipend. It's a once-in-a-lifetime opportunity that could completely change your future.

However, you're not the only one who qualifies for this scholarship. Your best friend, Alex, also qualifies. Alex comes from a more privileged background than you. Their family could afford to send Alex to the university, albeit with some financial strain. Without the scholarship, you would have to take out substantial student loans to attend, and you might even have to give up on your dream university for a less expensive option.

One day, you stumble upon an opportunity. You find out about an obscure academic competition that the scholarship board holds in high regard. Participation in this competition could significantly boost your chances of getting the scholarship, but very few people know about it.

The moral dilemma is this: Do you tell Alex about the competition or keep it to yourself?

If you tell Alex, you keep your integrity intact, but you significantly increase the competition for the scholarship. Alex, with their greater resources, might even have a better shot at winning the competition.

If you don't tell Alex, you maximize your chances of securing the scholarship, but at the cost of acting dishonestly toward your friend.

The self-interested option (not telling Alex about the competition) might be justifiable in this case. The potential benefits for you are life-changing. Alex, although potentially disadvantaged by not knowing about the competition, would still have the opportunity to attend university without the burden of crippling debt.

================================================================

The second set resulted from a letter I got from Maximus, a company I never heard of, which apparently contracts with Medicare (the U.S. health insurance system for old people). The letter said that Maximus had been the victim of a data breach, and my records were included. They included enough information for someone to steal my identity. So I set off to find out whether the records were accurate (hoping that they were not). Simply changing my Medicare number would itself involve a fair bit of work, since many people have it, so I spent some time on it. The Medicare web site would not let me see the information it had about me. I called a phone number at Medicare and got to a human, who informed me that the letter was sent to me by mistake and my records were not part of the breach. I was so happy that I thanked him and said good bye. Later I got more upset at Maximus, so I called the number they said would reach a professional familiar with the breach. The "professional" turned out to be an automated chat, and it was no help.

Next, I used the "chat" function of Medicare itself, which kept a record of our conversation (below). I wanted to say bad things about Maximus. Below is the transcript. It now appears that corporations (Maximus) and major government agencies (Medicare) are using ChatGPT-type systems to replace humans on phone and help lines. I'm sure these things will get better, but this is not ready for prime time.

------------------- Medicare.gov Live Chat Transcript ---------------------

Live chat Date:8/5/2023

Start Time:11:14:13 am

End Time:11:28:06 am

-----------------------------------------------------------------------------

[11:14:13 am]: Thank you for contacting Medicare.gov Live Chat. 

[11:14:16 am]: Jonathan I want to report what I think is a seriously misleading and deceptive letter that I received from Maximus about my information being accessed. I would prefer to write an email, but I can't find anywhere to send it. I think that whoever wrote and approved this letter should be disciplined in some way. Should I proceed? Or can you give me an email address? 

[11:14:16 am]:  Please wait while you are connected to an agent. 

[11:14:19 am]: You are now connected with Medicare.gov Live Chat.

Thank you for contacting Medicare.gov Live Chat. My name is ulie. Can you please verify your first and last name? 

[11:14:42 am]: Jonathan Jonathan Baron 

[11:14:59 am]: Julie Hello, I will be happy to assist you with this today.  

[11:15:30 am]: Julie Who send you the letter? 

[11:16:32 am]: Jonathan At the top it said Maximus, and (on the right) CMS. The return address was in Claysburg, PA. 

[11:16:58 am]: Julie 

Thank you.

Let me look into this for you. 

[11:17:11 am]: Jonathan 'https://www.cms.gov/newsroom/press-releases/cms-responding-data-breach-contractor' is the letter I received. 

[11:19:05 am]: Julie I appreciate your patience.

You should have received a letter notifying you of a data breach. We have determined that your Medicare number was not compromised, and you don't need to request a new one. The letter provides more information about the incident and how it is being addressed. Please note that this does not have any impact on your current Medicare benefits or coverage.

[11:19:12 am]: Julie Maximus, a contractor for the Centers for Medicare & Medicaid Services, recently learned that their file transfer software, called MOVEit, was compromised. They are offering 24 months of credit monitoring and other services from Experian at no cost. You can call Experian to learn more; their phone number is included in your letter. This is not available through email.  

[11:23:50 am]: Jonathan This is just what the letter said. Yes, indeed, it was incorrect, and caused me to waste a lot of time. But there were other problems. Do you want to hear about those? One problem is that the further questions suggested calling a number 'staffed with professionals familiar with this incident'. In fact, the 'professional' turned out to be (pretty cleary) an AI program like ChatGPT. I treated it that way. (ChatGPT has a thick skin. It doesn't complain if you criticize it harshly.) It could not answer my questions. I hope you are not the same robot! 

[11:25:59 am]: Julie Do you have additional questions regarding the letter you received? 

[11:27:25 am]: Jonathan No. So clearly I am wasting my time once again. You have missed the point, but I'm not going to try to get you back on track. I wanted an email address. You are clearly not going to give me one. 

[11:27:54 am]: Julie Have a nice day. 

[11:28:06 am]: The chat session has ended. Thank you for contacting Medicare.gov Live Chat. Have a nice day. 

Diversity, noise, and merit in college admission

I have not studied the recent US Supreme Court decision that ended affirmative action in college admissions, but I have followed the issue in news reports and have other relevant experiences.

For a few years including 1990-92 (details lost) I was head of the committee that supervised undergraduate admissions to the School of Arts and Sciences at Penn. My main goal was to study the "predictive index", a formula used by the admissions office to predict academic achievement after admission. The index was an equally-weighted sum of the SAT aptitude test, the mean of three achievement tests (typically including math and English), and high-school class rank. Working with Frank Norman, a colleague, I discovered that the the aptitude test was essentially useless once we had the other two predictors, and we tried to get the admissions department to drop it, as described in https://www.sas.upenn.edu/~baron/sat.htm/.

Around the same time, I attended a meeting of Ivy League admissions people at Harvard. This was after the "Ivy overlap" meeting was abolished by overzealous anti-trust action, as described in https://news.mit.edu/1992/history-0903. The overlap meeting was a discussion of applicants for financial aid at more than one college in the elite group. It was designed to insure that colleges were not competing for applicants on the basis of financial aid, hence insuring that the "colluding" colleges would "admit students solely on the basis of merit and distribute their scholarship money solely on the basis of need." When this policy was in effect, Penn had a hard time funding need-blind admissions, so it limited this policy to Americans, although Harvard did not. The meeting was to discuss the situation.

There I had occasion to discuss our SAT report with the Harvard dean of admissions, William Fitzsimmons. In passing, he pointed out something that helps to explain some of the apparent irrationality of admission systems in general. He said, roughly, "We could fill the entire freshman class with students who got straight 800s [perfect scores] on all the tests." (He might have added "from India".) But, he might have gone on to say, we don't want a class that is full of academic achievers. We want variety. We want a lot of students who are satisfied with passing grades. These students may not become scholars, but they may benefit from an education that will help them and others in many different ways. And they will dilute the competitive atmosphere that would result from a focus on achievement alone. (Is that what "merit" means when people argue that merit should be the sole basis for admisison?) So we must use other criteria.

The usual way of getting the desired variety/diversity is for admissions staff to read applications and make judgments about "character" or something like that. The psychological literature on selection is fairly clear that such judgments are very poor at predicting anything, in contrast to measures like grades and test scores (like our predictive index, suitably revised), which are pretty good at predicting other grades and test scores. The main result of these "personal" judgments is to add noise, random error, to the process (unfortunataly at considerable cost, since the admissions staff are well paid, and this is a substantial part of their jobs).

In sum, current admissions policy at Harvard, Penn, and similar colleges, is not based on "merit" alone, if that is taken to mean prediction of academic achievement. Instead, "pretty good" applicants who rank high (but not at the very top) on merit are rejected so that applicants lower in merit can be admitted for the sake of diversity. These decisions about acceptance and rejection are made in ways that are noisy, similar to the results of a lottery.

The same sort of noise was introduced by the 1978 Bakke decision of the Supreme Court, which prohibited colleges from doing affirmative action by exactly the method that would have been best according to the psychology literature, which is to rank all applicants by objective criteria and then, if you want more Blacks, use the same ranking but a lower cut-off. This method would optimize the academic performance of both groups. And, in particular, it would minimize the number of affirmative-action admits who were not ready for academic work of the sort expected at the elite colleges. These students exist, and many of them suffer from failure that would not have occurred had they gone to a less demanding college. But the court demanded that students be evaluated "holistically", which served to increase noise and not do much else.

Now it seems that many colleges intend to do more holistic admissions in hopes that they could find minority students who deserved admission. Note that this policy is fully consistent with Fitzsimmons' desire for diversity. A big problem is that, by definition, elite college are those that teach courses at a fairly high level, for example, those that use my textbook "Thinking and Deciding" in undergraduate courses. Students with weak numeracy skills will have trouble. Thus, it is still important to select students who can do the work. Failures in courses and in graduation itself are bad outcomes and should not be seen as a "cost we must pay" for diversity.

Thus the big trouble with holistic judgment as a way of promoting diversity is that it will lead to admission of too many students who are predictably not ready for academic work at the level required. These students are "cannon fodder" for the supposedly enlightened policy that admits them.

Ideally, colleges that use any sort of holistic criteria should also use the best statistical predictors to eliminate applicants who are high risk for failure, thus setting a lower bound to be applied to the students already selected by holistic criteria. This won't be perfect, but it seems worth a try. The Supreme Court, loose cannon that it is, might find that it is unconstitutional, just as it prohibited the optimal use of predictive indices for affirmative action.

When I was a student at Harvard 1962-66, it was just beginning a sort of affirmative action. My first-year roommate was Black. Charlie was a friend from Andover, an elite prep school that we both attended.  We both would have been admitted if admission was base fully on merit, but Harvard often rejected pretty-good students like Charlie, or me, just to make room for those less qualified.  But he was Black and clearly capable of doing the work. So they took him. (And so did Harvard Law School, 4 years later.)

And I was a legacy. My father, class of '37, was admitted at a time when Harvard was trying not to admit too many Jews (a situation that seems analogous to its attitude toward Asians today). My son also went there, and was thus 3d generation and from a minority that was once discriminated against. Another roommate of mine after the first year was 7th generation, and at least one of his daughters also went to Harvard. Sure, this is a way of preserving privilege, and it has the effect of admitting not-so-great students, thus increasing diversity of achievement, but probably without as much risk of failure as other ways of doing this, such as sports admissions, and with less than average need for financial assistance. Family traditions are also important to some families. Legacy preference for students who need it would increase diversity simply because some of these students will not be competitive high achievers. Many other legacy students would probably be admitted anyway.

My father's situation seems similar to the situation of many "Asian" students today. Harvard in particular does seems not to want "too many Asians," and that outcome would result from selection by merit alone. Yet, since merit is still part of the story, Asians who are admitted have higher test scores and high-school grades, which means that they are predicted to get better grades in college. That happens. We do not need some psychological explanation of why Asian student are relatively high achievers in college. The same used to be true of Jews, but now I think that colleges are no longer biased against them. (A small literature on "calibration" and "predictive bias" looks at the possibility of determining systemic or intentional bias on the basis of performance after selection. I think that it would show bias against Asians in some colleges today.)

In 1962, women were admitted to Radcliffe College, which was much smaller than Harvard College. As a result, the cut-off for admission of women was higher, and "Cliffies" got better grades and often dominated class discussions. Women are not generally that much smarter than men. We had a biased sample.

On the other side, affirmative action for under-represented minorities means that they are admitted with lower test scores and high-school grades. This fact can (fully or partially) explain why they get lower grades once admitted.

In sum, merit still matters, and it still predicts achievement. When students are more selected, they will achieve more on the average. Students selected with less attention to scores and grades will have lower achievement in college, although some ways of doing this seem better than others.

Some affirmative action for under-represented minorities seems reasonable (to me). Cultural diversity, which in the U.S. is correlated with "racial" diversity, is important for the education of all students. The increase in diversity is targeted and predictable, not simply random. But this is now off the table.

One response to the recent court ruling is to aim at diversity in ability to pay, by applying affirmative action to poor students (coupled with attempts to recruit them), those students who would ordinarily require maximum financial aid. Such a policy would deplete funds for financial aid, possibly increasing the difficulty of maintaining need-blind admissions for other students who required moderate amounts of aid. However, a policy favoring legacies would reduce the need for financial aid. Keeping legacy admission might help pay for more poor students.

Affirmative action of under-represented minorities, including the poor, must be done in combination with a strong effort to avoid predictable failure after admission. There is some optimum amount of affirmative action, and some colleges may have gone beyond it for minorities, although not for the poor.

More generally, admission to most selective colleges has never been done on the basis of merit alone. If other criteria are used, it is not unreasonable to know what they are, rather than relying on noise alone.

Cluster munitions for Ukraine

 The New York Times editorial of July 10, "The flawed moral logic of sending cluster munitions to Ukraine," opposed the U.S. decision to do just that. It tried to rebut some of the arguments made in favor of the plan, but it missed at least one, the fact that most of the area involved would already be littered with mines and unexploded cluster munitions used (extensively) by Russia, so the additional care required to try to avoid them later would already be required.

The editorial, the statements of governments opposed to the plan, and some of the published letters to the Times, seemed to follow the principle that these munitions are morally wrong, whatever the consequences. Such absolute principles are, in the sense I have used (e.g., Baron and Spranca, 1997) protected values. Ideological adherence to such values surely has considerable political influence. These commitments may be held unreflectively. When people are forced to confront specific situations where the principle conflicts with some other principle, such as avoiding terrible consequences, they often admit that their principle is not absolute after all (Baron and Leshner, 2000).

In "Rules of War and Moral Reasoning" (1972, http://www.jstor.org/stable/2264969), R. M. Hare criticizes the "absolutist" deontological views of Thomas Nagel, who advocated strict adherence to accepted rules, such as those prohibiting the use of poison gas, or attacks on the Red Cross.

"The defect in most deontologica theories ... is that they have no coherent rational account to give to any level of moral thought above that of the man who knows some good moral principles and sticks to them. He is a very admirable person, and to question his principles ... is indeed to 'show a corrupt mind'." However, to achieve such an account, "we have to adopt a 'two-level' approach, ... to recognize that the simple principles of the deontologist, important as they are, have their place at the level of character formation." Although we should be careful about violating principles that have been drilled into us (including those inculcated by military training), we need to be willing to override them on the basis of a higher level of analysis, that is, to make exceptions when they clearly lead to worse consequences than some alternative, even if our attachment to the broken rules leads us to feel guilty (just as the failure to prevent terrible consequences can also lead to guilt feelings).

Absolute rules represent a hardening of moral intuitions that are usually sufficient but should sometimes be overridden by more reflective reasoning, as suggested by Greene ("Moral tribes") and others. The opponents of cluster munitions seem to illustrate these hardened intuitions, which are protected values. Once having decided that cluster munitions are morally wrong, whatever the consequences, some opponents then engage in belief overkill, finding ways to ignore relevant facts on the other side, or to exaggerate the probability of harmful consequences resulting from action.

An example of actively open-minded thinking

 Tucker Carlson January 7, 2021 — 04:18:04 PM UTC

"A couple of weeks ago, I was watching video of people fighting on the street in Washington. A group of Trump guys surrounded an Antifa kid and started pounding the living shit out of him. It was three against one, at least. Jumping a guy like that is dishonorable obviously. It’s not how white men fight. Yet suddenly I found myself rooting for the mob against the man, hoping they’d hit him harder, kill him. I really wanted them to hurt the kid. I could taste it. Then somewhere deep in my brain, an alarm went off: this isn’t good for me. I’m becoming something I don’t want to be. The Antifa creep is a human being. Much as I despise what he says and does, much as I’m sure I’d hate him personally if I knew him, I shouldn’t gloat over his suffering. I should be bothered by it. I should remember that somewhere somebody probably loves this kid, and would be crushed if he was killed. If I don’t care about those things, if I reduce people to their politics, how am I better than he is?"

Quoted in New York Times, May 2, 2023 (and elsewhere)

https://www.nytimes.com/2023/05/02/business/media/tucker-carlson-text-message-white-men.html

Consensus clouds

 I keep wanting to talk about a concept that doesn't seem to have a name. I propose "consensus cloud", but maybe someone can tell me that a name already exists.

The idea is that a group of people have an apparent consensus about some belief or set of beliefs. These belief sets often have their own names, such as "woke" or "MAGA". They include various forms of nationalism, such as the belief in the existence of a "Russian people". They include religious ideologies, such as the ultra-orthodox Jews in Israel, pro-Hindu politics in India, Islamist politics, and the "religious right" in the U.S.

These belief sets differ in that some of them are limited to the groups that hold the beliefs. The ultra-orthodox do not seem to care whether the rest of the world adopts their religion; they just want state support for their own communities. Other belief sets apply to everyone, such as woke ideology or, by definition, various forms of evangelical Christianity.

All these belief sets are maintained as within-group social norms. Group members want others to agree and are willing to take action to promote agreement.

All these cases also benefit from "pluralistic ignorance". Believers think that the number of co-believers is higher than it really is, in part becuase doubters do not make themselves known, thus avoiding the censure that would result from enforcement of a social norm.

Pluralistic ignorance is itself abetted by control of an "information space", such as a government that systematically discourages or punishes dissent, as is happening now in Russia and China. Thus a kind of stability is achieved. Many Russians seem to believe that Ukraine is part of some sort of Russian essence and thus should be a part of Russia.

Belief sets often include beliefs about why outsiders do not agree. For example, some Russians believe that resistance to their claim to Ukraine is the result of western nations efforts to isolate Russia and hamper its development, and its associated propaganda.  Control of the information space is not necessary if the group ideology can define outsiders as part of a conspiracy against it (as Russia does). MAGA believers see such things as public heath mandates and climate protection to be the result of infiltration of academia and government (the "deep state") by leftist ideologues who produce pseudo-science to support their politics. The same sort of rationale often allows people with delusions to dismiss counter-arguments as coming from part of the conspiracy against them.

The beliefs of interest seem to descend on people like a cloud that becoms a fog. People cannot see outside of it.

Of course, some people do consider alternatives and question the relevant beliefs. We might expect individual differences in adherence to any sort of consensus cloud. Those who are prone toward myside bias as a trait are more likely to join a consensus, and, therefore, those are endorse the standards of actively open-minded thinking are more resistant. Similarly, those who are prone to accept conspiracy theories are more accepting, especially when opponents are seen as part of a conspiracy.

Possibly the trait of "intellectual humility" can work both ways, as it could make people less accepting of their own conclusions and more willing to listen to others. Its effect thus depends on which conclusions and which other people are affected. Intellectual humility is not the same as actively open-minded thinking, which implies that humility is needed only when a conclusion is the result of little thinking by anyone, or the result of poor thinking.

Vaccines for children

The U.S. is looking for trouble. Schools are opening and no children below 12 are vaccinated (except perhaps the few in clinical trials, which I hope are happening). These kids could spread COVID-19 fairly quickly. So here is an idea.

Approve emergency-use for 11-year-olds. Meanwhile monitor ages 11 and 12 for medical conditions that could be side effects. Continue to do this. Even an increase in some condition in age 11 after approval might indicate a special problem.

Then move to age 10 in a couple of weeks. And so on. This is something like a regression discontinuity design, but some of it could be based solely on comparisons after approval.

Apparently the FDA sees its duty as only toward the individual, not toward others that the individual might infect. But date from a procedure like this might give it enough information to act, in successive steps. Something is better than nothing.

Added 2/28/2022: Vaccines for children are still a problem in the U.S. Apparently the doses were too low, and the effects were either very small (ages 3 and 4, not approved yet) or wearing off quickly (ages 5-11, approved). So the same idea could be done with increased dosage. Now it seems we will have wait more months for more trials.

At this point, it seems that most people want to get back to "normal", despite the existence of continued spread that could be significantly slowed by greater and more effective vaccination. A return to normal would be more reasonable if we didn't have to worry about long covid, which is apparently a debilitating chronic condition, something like that caused by Lyme disease. As others remove their masks and continue to resist vaccination, some of us are just going to get better masks and continue to avoid indoor restaurants and any kind of public gathering, even though we, too, were hoping to some sort of return to normal.

Prediction, accommodation and pre-registration

Some scientists think that confirming a prediction made before data collection is more convincing than explaining the data after they arrive. I think that this belief is one source (among others) of support for the practice of pre-registration, in which authors publish a plan for an experiment they intend to do, explaining the hypothesis, methods, and data analysis in advance.

Paul Horwich ("Probability and evidence", 1982, pp. 108-117) 

has a complex discussion of this issue, under the heading "Prediction vs. accommodation", but I want to try to provide a more intuitive account of why I do not think that it matters.

Let me take an example based very loosely on my own research. Suppose I want to study evaluative judgment of acts vs. omissions. I got interested in this because of vaccine resistance in the real world. It seemed likely that this resistance resulted from a bias against potentially harmful acts (vaccination, with side effects) compared to potentially more harmful omissions (non-vaccination, with exposure to a natural disease). I thought that this bias was a sort of heuristic, in which people tend to think of action as inherently risky, regardless of what they are told about its risks.

I designed an experiment to examine judgments of acts and omissions, using a variety of scenarios. Some of the scenarios involved money rather than disease risk, so it was possible to include items involving monetary gains as well as losses. I expected that subjects would just be biased against omissions, period.

When I got the data, I noticed something unexpected. Yes, I found the expected bias for vaccination scenarios and for money scenarios that involved losses. In the money scenarios, subjects evaluated action leading to a loss as somewhat worse than omission (doing nothing) leading to the same loss with a higher probability. But when I looked at gains, the results were reversed. Subjects were biased toward action, not omission. They evaluated action leading to a chance on winning some money more highly than omission leading to a somewhat larger chance of winning the same amount.

It was easy to explain my results in hindsight. Action, as opposed to omission, simply amplified the effect on choice of whatever outcome it produced. Subjects were not generally biased against action: it depended on whether the outcomes of action were good or bad. The association with action served to focus attention on the effect of the action, so the action looked better if its outcome was good, and worse if its outcome was bad. (In real life, the amplification effect exists, along with the omission heuristic, but it was not unexpected, as I knew that Janet Landman had already reported it with a different dependent measure. And this "one experiment" is actually a conflation of several done in collaboration with Ilana Ritov.)

Suppose I had stopped there and reported what I expected and what I found. Compare this to a case in which I predicted (expected) the amplification effect. Should your belief in the existence of the amplification effect depend on whether I predicted it or not (all else being equal)?

Note that these two cases can be compared with a third case, in which I report the result for gains but falsely claim that I predicted it, when, actually, I expected a different result. This is the sort of thing that pre-registration of research hypotheses prevents. But, if the two cases just mentioned do not differ in the credibility of amplification as an explanation, such "cheating" would simply be a type of puffery, cheap talk designed to influence the reader without conveying any truly relevant information, like many other things that authors do to make their conclusions sound good, such as baldly asserting that the result is very important. The simple way for editors to avoid such puffery is to change all statements about prediction to statements of questions that the research might answer. Thus "I predicted a general bias toward omission" would be edited to say "I asked whether the bias toward omission was general, for gains as well as losses."

Let me now return to the original question of whether prior prediction matters. In both cases, we have two plausible explanations: a bias against omission, and an amplification effect. What determines the credibility of the amplification hypothesis? Of course, it fits the data, but that helps equally regardless of the prediction. Some doubt may remain, whether I predicted the result or not.

The other determinant of credibility of an explanation is its plausibility, compared to the plausibility of alternatives. In a well written paper, I would give my reasons for thinking that various explanations are plausible. Readers would also have their own reasons. Above I suggested the reasons for each: a heuristic against action; and an attention effect favoring actions. In a paper, I would try to spell these out "with four-part harmony" (to steal a line from Arlo Guthrie), with citations of related work (such as the "feature-positive effect"), and so on.

Should it then add anything that I predicted the result that I got? The answer to this depends on whether my prediction provides additional evidence for this explanation, that is, additional reason to believe it, aside from everything you now know about its plausibility. But, if I have done my job as a writer, I have told you everything I know that is relevant to making my final explanation (amplification) plausible. The fact that I predicted it provides additional relevant information only if I am withholding something relevant that I know. I have no incentive to do that, unless it is somewhat embarrassing. Authors might be embarrassed to say that they made the prediction because God came to them in a dream and told them what was true. Or, more realistically, "I predicted this result intuitively, for reasons I cannot explain, but you should take this seriously because my intuition is very good." As a reader, you are not going to buy that.

In some research, the favored explanation seems pretty implausible, even though it is consistent with the data presented, despite the efforts of the author to convince us that it is plausible.  These cases include some of the "gee whiz" studies in social psychology that raise questions about replicability, but also some of the research in which a precise mathematical model fits the data surprisingly well but otherwise seems to come out of the blue sky.  These cases of low plausibility are the ones where claims that the results were predicted (e.g., in a pre-registration) are thought to be most relevant.

For example, suppose I found no significant "omission bias" overall but did find it if I restrict the sample to those who identify themselves as Protestant Christian.  I supported this restriction with (highly selected) quotations from Protestant texts, thus explaining the result in terms of religious doctrine. You would rightly be suspicious. You would (rightly) suspect that you could find just as many quotations as I found to support the conclusion that Protestant doctrine emphasized sins of omission as well as sins of commission, and that other religions were no different. Would it help convince you of the reality of my effect if you knew that I predicted it but didn't tell you any more about why? You might just think that I was a little nuts, and, well, lucky.

Pre-registration thus does not solve the problem posed by implausible explanations. Of course they might be true, despite being implausible, but that must be established later.  What matters in making an explanation legitimately credible are, first, its fit with the data (compared to alternative explanations) and, second, its fit with other things that we know (again, compared to alternatives). The order in which a researcher thought of things, by itself, provides no additional relevant information.

Going beyond my restatement of Horwich's arguments, analogous reasoning applies to data analysis. One of the nasty things that researchers do is fiddle with their data until they get the result they want. For example, I might fail to find a significant difference in the mean ratings of acts and omissions, but I might find a difference using the maximum rating given by each subject to omissions and to actions, across several scenarios. Pre-registration avoids this fiddling, if researchers follow their pre-registered plan. Doing this, however, discourages the researcher from making reasonable accommodation to the data as they are, such as eliminating unanticipated but nonsensical responses, or transforming data that are turn out to be highly skewed.

But note that many of the statistical options that are used for such p-hacking are ones that do not naturally fit the data very well. Again, it is possible to make up a story about why they do fit the data, but such stories usually tend to be unconvincing, just like the example of Protestantism described above. Thus, data analysis, like explanations, must be "plausible" in order to be convincing.