Reputational Rationality Theory

Dorison, C. (2023, March 29). 

PsyArXiv.com

https://doi.org/10.31234/osf.io/q27sj

Abstract

Traditionally, research on human judgment and decision making draws on cognitive psychology to identify deviations from normative standards of how decisions ought to be made. These deviations are commonly considered irrational errors and biases. However, this approach has serious limitations. Critically, even though most decisions are embedded within complex social networks of observers, this approach typically ignores how decisions are perceived by valued audiences. To address this limitation, this article proposes reputational rationality theory: a theoretical model of how observers evaluate targets who do (vs. do not) strictly adhere to normative standards of judgment and choice. Drawing on the dual pathways of homophily and social signaling, the theory generates testable predictions regarding when and why observers positively evaluate error-prone decision makers, termed the benefit of bias hypothesis. Given that individuals hold deep impression management goals, reputational rationality theory challenges the unqualified classification of response tendencies that deviate from normative standards as irrational. That is, apparent errors and biases can, under certain conditions, be reputationally rational. The reputational rewards associated with cognitive biases may in turn contribute to their persistence. Acknowledging the (sometimes beneficial) reputational consequences of cognitive biases can address long-standing puzzles in judgment and decision making as well as generate fruitful avenues for future research.

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Reputational rationality theory inverts this relationship. Reputational rationality theory is primarily concerned with the observer rather than the target.It thus yields novel predictions regarding how observers evaluate targets (rather than how targets shift behavior due to pressures from observers). Reputational rationality theory is inherently a social cognition model, concerned with—for example—how the public evaluates the politician or how the CEO evaluates the employee. The theory suggests that several influential errors and biases—not taking the value-maximizing risk or investing in the worthwhile venture—can serve functional goals once reputational consequences are considered.

As summarized above, prior cognitive and social approaches to judgment and decision making have traditionally omitted empirical investigation of how judgments and decisions are perceived by valued audiences—such as the public or coworkers in the examples above. How concerning is this omission? On the one hand, this omission may be tolerable—if not ignorable—if reputational incentives align with goals that are traditionally considered in this work (e.g., accuracy, optimization, adherence to logic and statistics). Simply put, researchers could safely ignore reputational consequences if such consequences already reinforce conventional wisdom and standard recommendations for what it means to make a “good” decision. If observers penalize targets who recklessly display overconfidence or who flippantly switch their risk preferences based on decision frames, then examining these reputational consequences becomes less necessary, and the omission thus less severe. On the other hand, this omission may be relatively more severe if reputational incentives regularly conflict with traditional measures or undermine standard recommendations.

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Conclusion

The challenges currently facing society are daunting. The planet is heating at an alarming pace. A growing number of countries hold nuclear weapons capable of killing millions in mere minutes. Democratic institutions in many countries, including the United States, appear weaker than previously thought. Confronting such challenges requires global leaders and citizens alike to make sound judgments and decisions within complex environments: to effectively navigate risk under conditions of widespread uncertainty; to pivot from failing paths to new opportunities; to properly calibrate their confidence among multiple possible futures. But is human rationality up to the task?

Building on a traditional cognitive and social approaches to human judgment and decision making, reputational rationality theory casts doubt on traditional normative classifications of errors and biases based on individual-level cognition, while simultaneously generating testable predictions for future research taking a broader social/institutional perspective. By examining both the reputational causes and consequences of human judgment and decision making, researchers can gain increased understanding not only into how judgments and decisions are made, but also how behavior can be changed—for good.

Foundation Models are exciting, but they should not disrupt the foundations of caring

Morley, Jessica and Floridi, Luciano

(April 20, 2023).

Available at SSRN: https://ssrn.com/abstract=

Abstract

The arrival of Foundation Models in general, and Large Language Models (LLMs) in particular, capable of ‘passing’ medical qualification exams at or above a human level, has sparked a new wave of ‘the chatbot will see you now’ hype. It is exciting to witness such impressive technological progress, and LLMs have the potential to benefit healthcare systems, providers, and patients. However, these benefits are unlikely to be realised by propagating the myth that, just because LLMs are sometimes capable of passing medical exams, they will ever be capable of supplanting any of the main diagnostic, prognostic, or treatment tasks of a human clinician. Contrary to popular discourse, LLMs are not necessarily more efficient, objective, or accurate than human healthcare providers. They are vulnerable to errors in underlying ‘training’ data and prone to ‘hallucinating’ false information rather than facts. Moreover, there are nuanced, qualitative, or less measurable reasons why it is prudent to be mindful of hyperbolic claims regarding the transformative power ofLLMs. Here we discuss these reasons, including contextualisation, empowerment, learned intermediaries, manipulation, and empathy. We conclude that overstating the current potential of LLMs does a disservice to the complexity of healthcare and the skills of healthcare practitioners and risks a ‘costly’ new AI winter. A balanced discussion recognising the potential benefits and limitations can help avoid this outcome.

Conclusion

The technical feats achieved by foundation models in the last five years, and especially in the last six months, are undeniably impressive. Also undeniable is the fact that most healthcare systems across the world are under considerable strain. It is right, therefore, to recognise and invest in the potentially transformative power of models such as Med-PaLM and ChatGPT – healthcare systems will almost certainly benefit.  However, overstating their current potential does a disservice to the complexity of healthcare and the skills required of healthcare practitioners. Not only does this ‘hype’ risk direct patient and societal harm, but it also risks re-creating the conditions of previous AI winters when investors and enthusiasts became discouraged by technological developments that over-promised and under-delivered. This could be the most harmful outcome of all, resulting in significant opportunity costs and missed chances to benefit transform healthcare and benefit patients in smaller, but more positively impactful, ways. A balanced approach recognising the potential benefits and limitations can help avoid this outcome. 

Many people in U.S., other advanced economies say it’s not necessary to believe in God to be moral

Janell Fetteroff & Sarah Austin

Pew Research Center

Originally published 20 APR 23

Most Americans say it’s not necessary to believe in God in order to be moral and have good values, according to a spring 2022 Pew Research Center survey. About two-thirds of Americans say this, while about a third say belief in God is an essential component of morality (65% vs. 34%).

However, responses to this question differ dramatically depending on whether Americans see religion as important in their lives. Roughly nine-in-ten who say religion is not too or not at all important to them believe it is possible to be moral without believing in God, compared with only about half of Americans to whom religion is very or somewhat important (92% vs. 51%). Catholics are also more likely than Protestants to hold this view (63% vs. 49%), though views vary across Protestant groups.

There are also divisions along political lines: Democrats and those who lean Democratic are more likely than Republicans and Republican leaners to say it is not necessary to believe in God to be moral (71% vs. 59%). Liberal Democrats are particularly likely to say this (84%), whereas only about half of conservative Republicans (53%) say the same.

In addition, Americans under 50 are somewhat more likely than older adults to say that believing in God is not necessary to have good values (71% vs. 59%). Those with a college degree or higher are also more likely to believe this than those with a high school education or less (76% vs. 58%).

A chart showing that Majorities in most countries say belief in God is not necessary to be moral.

Views of the link between religion and morality differ along similar lines in 16 other countries surveyed. Across those countries, a median of about two-in-three adults say that people can be moral without believing in God, just slightly higher than the share in the United States.

The info is here.

What Thomas Kuhn Really Thought about Scientific "Truth"

John Horgan

Scientific American

Originally posted 23 May 12

Here are two excerpts:

Denying the view of science as a continual building process, Kuhn held that a revolution is a destructive as well as a creative act. The proposer of a new paradigm stands on the shoulders of giants (to borrow Newton's phrase) and then bashes them over the head. He or she is often young or new to the field, that is, not fully indoctrinated. Most scientists yield to a new paradigm reluctantly. They often do not understand it, and they have no objective rules by which to judge it. Different paradigms have no common standard for comparison; they are "incommensurable," to use Kuhn's term. Proponents of different paradigms can argue forever without resolving their basic differences because they invest basic terms—motion, particle, space, time—with different meanings. The conversion of scientists is thus both a subjective and political process. It may involve sudden, intuitive understanding—like that finally achieved by Kuhn as he pondered Aristotle. Yet scientists often adopt a paradigm simply because it is backed by others with strong reputations or by a majority of the community.

Kuhn's view diverged in several important respects from the philosophy of Karl Popper, who held that theories can never be proved but only disproved, or "falsified." Like other critics of Popper, Kuhn argued that falsification is no more possible than verification; each process wrongly implies the existence of absolute standards of evidence, which transcend any individual paradigm. A new paradigm may solve puzzles better than the old one does, and it may yield more practical applications. "But you cannot simply describe the other science as false," Kuhn said. Just because modern physics has spawned computers, nuclear power and CD players, he suggested, does not mean it is truer, in an absolute sense, than Aristotle's physics. Similarly, Kuhn denied that science is constantly approaching the truth. At the end of Structure he asserted that science, like life on earth, does not evolve toward anything but only away from something.

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Kuhn declared that, although his book was not intended to be pro-science, he is pro-science. It is the rigidity and discipline of science, Kuhn said, that makes it so effective at problem-solving. Moreover, science produces "the greatest and most original bursts of creativity" of any human enterprise. Kuhn conceded that he was partly to blame for some of the anti-science interpretations of his model. After all, in Structure he did call scientists committed to a paradigm "addicts"; he also compared them to the brainwashed characters in Orwell's 1984. Kuhn insisted that he did not mean to be condescending by using terms such as "mopping up" or "puzzle-solving" to describe what most scientists do. "It was meant to be descriptive." He ruminated a bit. "Maybe I should have said more about the glories that result from puzzle solving, but I thought I was doing that."

As for the word "paradigm," Kuhn conceded that it had become "hopelessly overused" and is "out of control." Like a virus, the word spread beyond the history and philosophy of science and infected the intellectual community at large, where it came to signify virtually any dominant idea. A 1974 New Yorker cartoon captured the phenomena. "Dynamite, Mr. Gerston!" gushed a woman to a smug-looking man. "You're the first person I ever heard use 'paradigm' in real life." The low point came during the Bush administration, when White House officials introduced an economic plan called "the New Paradigm" (which was really just trickle-down economics).

The article is here.

Stolen elections: How conspiracy beliefs during the 2020 American presidential elections changed over time

Wang, H., & Van Prooijen, J. (2022).

Applied Cognitive Psychology.

https://doi.org/10.1002/acp.3996

Abstract

Conspiracy beliefs have been studied mostly through cross-sectional designs. We conducted a five-wave longitudinal study (N = 376; two waves before and three waves after the 2020 American presidential elections) to examine if the election results influenced specific conspiracy beliefs and conspiracy mentality, and whether effects differ between election winners (i.e., Biden voters) versus losers (i.e., Trump voters) at the individual level. Results revealed that conspiracy mentality kept unchanged over 2 months, providing first evidence that this indeed is a relatively stable trait. Specific conspiracy beliefs (outgroup and ingroup conspiracy beliefs) did change over time, however. In terms of group-level change, outgroup conspiracy beliefs decreased over time for Biden voters but increased for Trump voters. Ingroup conspiracy beliefs decreased over time across all voters, although those of Trump voters decreased faster. These findings illuminate how specific conspiracy beliefs are, and conspiracy mentality is not, influenced by an election event.

From the General Discussion

Most studies on conspiracy beliefs provide correlational evidence through cross-sectional designs (van Prooijen & Douglas, 2018). The present research took full advantage of the 2020 American presidential elections through a five-wave longitudinal design, enabling three complementary contributions. First, the results provide evidence that conspiracy mentality is a relatively stable individual difference trait (Bruder et al., 2013; Imhoff & Bruder, 2014): While the election did influence specific conspiracy beliefs (i.e., that the elections were rigged), it did not influence conspiracy mentality. Second, the results provide evidence for the notion that conspiracy beliefs are for election losers (Uscinski & Parent, 2014), as reflected in the finding that Biden voters' outgroup conspiracy beliefs decreased at the individual level, while Trump voters' did not. The group-level effects on changes in outgroup conspiracy beliefs also underscored the role of intergroup conflict in conspiracy theories (van Prooijen & Song, 2021). And third, the present research examined conspiracy theories about one's own political ingroup, and found that such ingroup conspiracy beliefs decreased over time.

The decrease over time for ingroup conspiracy beliefs occurred among both Biden and Trump voters. We speculate that, given its polarized nature and contested result, this election increased intergroup conflict between Biden and Trump voters. Such intergroup conflict may have increased feelings of ingroup loyalty within both voter groups (Druckman, 1994), therefore decreasing beliefs that members of one's own group were conspiring. Moreover, ingroup conspiracy beliefs were higher for Trump than Biden voters (particularly at the first measurement point). This difference might expand previous findings that Republicans are more susceptible to conspiracy cues than Democrats (Enders & Smallpage, 2019), by suggesting that these effects generalize to conspiracy cues coming from their own ingroup.

Conclusion

The 2020 American presidential elections yielded many conspiracy beliefs that the elections were rigged, and conspiracy beliefs generally have negative consequences for societies. One key challenge for scientists and policymakers is to establish how conspiracy theories develop over time. In this research, we conducted a longitudinal study to provide empirical insights into the temporal dynamics underlying conspiracy beliefs, in the setting of a polarized election. We conclude that specific conspiracy beliefs that the elections were rigged—but not conspiracy mentality—are malleable over time, depending on political affiliations and election results.

The research is here.

How Smart People Can Stop Being Miserable

Arthur C. Brooks

The Atlantic

Originally posted 23MAR 23

Here are some excerpts:

“Happiness in intelligent people is the rarest thing I know,” an unnamed character casually remarks in Ernest Hemingway’s novel The Garden of Eden. You might say that this is a corollary of the much more famous “Ignorance is bliss.”

The latter recalls phenomena such as:

• the Dunning-Kruger effect—in which people lacking skills and knowledge in a particular area innocently underestimate their own incompetence—and 

• the illusion of explanatory depth, which can prompt autodidacts on social media to excitedly present complex scientific phenomena, thinking they understand them in far greater depth than they really do.

The Hemingway hypothesis, however, is less straightforward. I can think of a lot of unhappy intellectuals, to be sure. But is intelligence per se their problem? Happiness scholars have studied this question, and the answer is—as in so many parts of life—it depends. The gifts you possess can lift you up or pull you down; it all depends on how you use them. Many people see intelligence as a way to get ahead of others. But to get happier, we need to do the opposite.

You might assume that intelligence—whether it be the conventional IQ kind, emotional intelligence, musical talent, or some other dimension along which a person can excel—raises happiness, all else being equal. After all, people with higher cognitive ability should logically have more exciting life opportunities than others. They should also acquire more resources with which to enhance their well-being.

In general, however, there is no correlation between general intelligence and life satisfaction at the individual level. That principle does mask a few wrinkles. In 2022, researchers at Weill Cornell Medicine and Fordham University looked at the association between well-being and various building blocks of neurocognitive ability: memory, processing speed, reasoning, spatial visualization, and vocabulary. The only components of intelligence that they found to be positively related to happiness were spatial visualization, memory, and processing speed—but those relationships were fleeting and age-related.

More interesting, the researchers also found a strongly negative association between happiness and vocabulary. To explain this, they offered a hypothesis: People with a large vocabulary “self-select more challenging environments, and as a result may encounter more daily stressors and reduced positive affect.” In other words, loquacious logophiles might have byzantine lives and find themselves in manifold precarious situations that lower their jouissance. (They talk themselves into misery.)

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I think there is a clear reason that something as valuable as intelligence, especially manifested in one’s ability to communicate, doesn’t necessarily lead to a higher quality of life.

One of life’s cruelest mysteries is why we are impelled to pursue rewards that bring success, but not happiness. Mother Nature drives us toward the four goals of money, power, pleasure, and prestige with the promise that these rewards will bring happiness. In truth, the correlation might be positive, but the causation is probably reversed: Happier people naturally get these rewards. But seek them for their own sake, for your own gain, and happiness will likely fall. Accordingly, if you aspire to use your cleverness for personal benefit—for the praise and admiration of others, or an advantage in work and dating—woe be unto you.

The smarter you are, the better equipped you should be to understand that well-being comes from faith, family, friendship, and work that serves others. Your intelligence is more likely to bring you happiness if you put it to use by chasing better ways to love and serve others, rather than elbowing others aside and hoarding worldly rewards.

In some ways, you can think of intelligence as a resource just like money or power. We know how to make the latter two sources of joy: Share them with others, and use them as a force for good in the world. To make smarts a fount of happiness, too, we can follow the same guide. Here are a couple of tangible proposals.

The article is paywalled here.

Is the world ready for ChatGPT therapists?

Ian Graber-Stiehl

Nature.com

Originally posted 3 May 23

Since 2015, Koko, a mobile mental-health app, has tried to provide crowdsourced support for people in need. Text the app to say that you’re feeling guilty about a work issue, and an empathetic response will come through in a few minutes — clumsy perhaps, but unmistakably human — to suggest some positive coping strategies.

The app might also invite you to respond to another person’s plight while you wait. To help with this task, an assistant called Kokobot can suggest some basic starters, such as “I’ve been there”.

But last October, some Koko app users were given the option to receive much-more-complete suggestions from Kokobot. These suggestions were preceded by a disclaimer, says Koko co-founder Rob Morris, who is based in Monterey, California: “I’m just a robot, but here’s an idea of how I might respond.” Users were able to edit or tailor the response in any way they felt was appropriate before they sent it.

What they didn’t know at the time was that the replies were written by GPT-3, the powerful artificial-intelligence (AI) tool that can process and produce natural text, thanks to a massive written-word training set. When Morris eventually tweeted about the experiment, he was surprised by the criticism he received. “I had no idea I would create such a fervour of discussion,” he says.

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Automated therapist

Koko is far from the first platform to implement AI in a mental-health setting. Broadly, machine-learning-based AI has been implemented or investigated in the mental-health space in three roles.

The first has been the use of AI to analyse therapeutic interventions, to fine-tune them down the line. Two high-profile examples, ieso and Lyssn, train their natural-language-processing AI on therapy-session transcripts. Lyssn, a program developed by scientists at the University of Washington in Seattle, analyses dialogue against 55 metrics, from providers’ expressions of empathy to the employment of CBT interventions. ieso, a provider of text-based therapy based in Cambridge, UK, has analysed more than half a million therapy sessions, tracking the outcomes to determine the most effective interventions. Both essentially give digital therapists notes on how they’ve done, but each service aims to provide a real-time tool eventually: part advising assistant, part grading supervisor.

The second role for AI has been in diagnosis. A number of platforms, such as the REACH VET program for US military veterans, scan a person’s medical records for red flags that might indicate issues such as self-harm or suicidal ideation. This diagnostic work, says Torous, is probably the most immediately promising application of AI in mental health, although he notes that most of the nascent platforms require much more evaluation. Some have struggled. Earlier this year, MindStrong, a nearly decade-old app that initially aimed to leverage AI to identify early markers of depression, collapsed despite early investor excitement and a high-profile scientist co-founder, Tom Insel, the former director of the US National Institute of Mental Health.

The info is here.

The Unchecked Rise of Psychological Testing Evidence in United States Courts.

King, C., & Neal, T. M. (2022, June 7).

https://doi.org/10.31234/osf.io/4hfd6

Abstract

Psychological testing, based on psychometric science, is often used in court to aid judges and juries in making legal decisions that profoundly affect people’s lives, such as eligibility for disability benefits, psychological damages, child custody, and whether and where someone will serve a criminal sentence. We provide a novel estimate of the pattern of psychological tests introduced as legal evidence throughout the entire history of United States case law, finding a sharp increase in this type of expert evidence in recent years. Although the law requires judges to screen evidence for relevance and reliability before allowing an expert to testify about it in court, legal challenges to psychological testing evidence are rare: across 28,824 judicial opinions citing psychological tests, just 479 involved a potential admissibility challenge (1.66%). This finding informs and raises questions for the public as well as legal and mental health professionals.

Discussion

Our results indicate that psychological testing evidence in U.S. courts has been increasing steadily in civil, family, and criminal cases over the past half-century, beginning roughly around the time that psychological testing emerged as a specialty in the field of psychology. Although we used a sizable sample, psychological testing evidence has undoubtedly occurred in many more cases than we could capture—with such evidence either not specified in written opinions, or judicial decisions not incorporated, for various reasons, into the large legal database we searched.

We also found evidence that legal professionals either rarely scrutinize psychological testing evidence, or admissibility decisions about such evidence are not typically deemed significant enough to warrant written explanations. This seems to be true irrespective of shifts in the strictness of admissibility standards over time. Potential challenge rates did, however, vary across individual psychological tests, and at least a third of the examined tests were challenged at least once. The two most commonly challenged types of tests provide a clue as to the type of case most likely to involve testing-related challenges: litigation concerning the civil commitment of certain convicted sex offenders. Nevertheless, the generally unchecked rise in psychological testing evidence, as suggested by this study, raises questions about the rigor of current admissibility standards, the functioning of the enforcers of those rules, and the seemingly broad deference afforded to mental health professionals’ highly varied test selections.

The research is here.

Advocates of high court reform give Roberts poor marks

Kelsey Reichmann

Courthouse News Service

Originally published 27 April 23

The final straw for ethics experts wondering if the leader of one of the nation’s most powerful bodies would uphold the institutionalist views associated with his image came on Tuesday as Chief Justice John Roberts declined to testify before Congress about ethical concerns at the Supreme Court. 

“You can't actually have checks and balances if one branch is so powerful that the other branches cannot, in fact, engage in their constitutionally mandated role to provide a check on inappropriate or illegal behavior,” Caroline Fredrickson, a distinguished visitor from practice at Georgetown Law, said in a phone interview. “Then we have a defective system.” 

Roberts cited concerns about separation of powers as the basis for declining to testify before the Senate Judiciary Committee on the court’s ethical standards — or lack thereof. Fredrickson said it was a canard that a system based on checks and balances would not be able to do just that. 

“It sort of puts the question to the entire structure of separation of powers and checks and balances,” Fredrickson said. 

For the past several weeks, one of the associate justices has been at the heart of controversy. After blockbuster reporting revealed that Republican megadonor Harlan Crow has footed the bill for decades of luxury vacations enjoyed by Justice Clarence Thomas, the revelations brought scrutiny on the disclosure laws that bind the justices and it called into question why the justices are not bound by ethics standards like the rest of the judiciary and other branches of government.

“For it to function, it relies on the public trust, and the trust of the other institutions to abide by the court's findings,” Virginia Canter, chief ethics counsel at Citizens for Responsibility and Ethics in Washington, said in a phone call. “If the court and its members are willing to live without any standards, then I think that ultimately the whole process and the institution start to unravel.” 

Many court watchers saw opportunity for action here on a call that has been made for years: the adoption of an ethics code.

“The idea that the Supreme Court would continue to operate without one, it's just ridiculous,” Gabe Roth, executive director of Fix the Court, said in a phone call. 

Along with his letter declining to testify before Congress on the court’s ethics, Roberts included a statement listing principles and practices the court “subscribes” to. The statement was signed by all nine justices. 

For ethics experts raising alarm bells on this subject, a restatement of guidelines that the justices are already supposed to follow did not meet the moment.

“It's just a random — in my view at least — conglomeration of paragraphs that rehash things you already knew, but, yeah, good for him for getting all nine justices on board with something that already exists,” Roth said. 

The info is here.