Superhuman artificial intelligence can improve human decision-making by increasing novelty.

How will superhuman artificial intelligence (AI) affect human decision-making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move decisions made by professional Go players over the past 71 y (1950 to 2021). To address the first question, we use a superhuman AI program to estimate the quality of human decisions across time, generating 58 billion counterfactual game patterns and comparing the win rates of actual human decisions with those of counterfactual AI decisions. We find that humans began to make significantly better decisions following the advent of superhuman AI. We then examine human players' strategies across time and find that novel decisions (i.e., previously unobserved moves) occurred more frequently and became associated with higher decision quality after the advent of superhuman AI. Our findings suggest that the development of superhuman AI programs may have prompted human players to break away from traditional strategies and induced them to explore novel moves, which in turn may have improved their decision-making.

Difficult climate-adaptive decisions in forests as complex social-ecological systems.

Climate change threatens the social, ecological, and economic benefits enjoyed by forest-dependent communities worldwide. Climate-adaptive forest management strategies such as genomics-based assisted migration (AM) may help protect many of these threatened benefits. However, such novel technological interventions in complex social-ecological systems will generate new risks, benefits, and uncertainties that interact with diverse forest values and preexisting risks. Using data from 16 focus groups in British Columbia, Canada, we show that different stakeholders (forestry professionals, environmental nongovernmental organizations, local government officials, and members of local business communities) emphasize different kinds of risks and uncertainties in judging the appropriateness of AM. We show the difficulty of climate-adaptive decisions in complex social-ecological systems in which both climate change and adaptation will have widespread and cascading impacts on diverse nonclimate values. Overarching judgments about AM as an adaptation strategy, which may appear simple when elicited in surveys or questionnaires, require that participants make complex trade-offs among multiple domains of uncertain and unknown risks. Overall, the highest-priority forest management objective for most stakeholders is the health and integrity of the forest ecosystem from which all other important forest values derive. The factor perceived as riskiest is our lack of knowledge of how forest ecosystems work, which hinders stakeholders in their assessment of AM's acceptability. These results are further evidence of the inherent risk in privileging natural science above other forms of knowledge at the science-policy interface. When decisions are framed as technical, the normative and ethical considerations that define our fundamental goals are made invisible.

A moral trade-off system produces intuitive judgments that are rational and coherent and strike a balance between conflicting moral values.

How does the mind make moral judgments when the only way to satisfy one moral value is to neglect another? Moral dilemmas posed a recurrent adaptive problem for ancestral hominins, whose cooperative social life created multiple responsibilities to others. For many dilemmas, striking a balance between two conflicting values (a compromise judgment) would have promoted fitness better than neglecting one value to fully satisfy the other (an extreme judgment). We propose that natural selection favored the evolution of a cognitive system designed for making trade-offs between conflicting moral values. Its nonconscious computations respond to dilemmas by constructing "rightness functions": temporary representations specific to the situation at hand. A rightness function represents, in compact form, an ordering of all the solutions that the mind can conceive of (whether feasible or not) in terms of moral rightness. An optimizing algorithm selects, among the feasible solutions, one with the highest level of rightness. The moral trade-off system hypothesis makes various novel predictions: People make compromise judgments, judgments respond to incentives, judgments respect the axioms of rational choice, and judgments respond coherently to morally relevant variables (such as willingness, fairness, and reciprocity). We successfully tested these predictions using a new trolley-like dilemma. This dilemma has two original features: It admits both extreme and compromise judgments, and it allows incentives-in this case, the human cost of saving lives-to be varied systematically. No other existing model predicts the experimental results, which contradict an influential dual-process model.

People Endorse Harsher Policies in Principle Than in Practice: Asymmetric Beliefs About Which Errors to Prevent Versus Fix.

Countless policies are crafted with the intention of punishing all who do wrong or rewarding only those who do right. However, this requires accommodating certain mistakes: some who do not deserve to be punished might be, and some who deserve to be rewarded might not be. Six preregistered experiments (N = 3,484 U.S. adults) reveal that people are more willing to accept this trade-off in principle, before errors occur, than in practice, after errors occur. The result is an asymmetry such that for punishments, people believe it is more important to prevent false negatives (e.g., criminals escaping justice) than to fix them, and more important to fix false positives (e.g., wrongful convictions) than to prevent them. For rewards, people believe it is more important to prevent false positives (e.g., welfare fraud) than to fix them and more important to fix false negatives (e.g., improperly denied benefits) than to prevent them.

How Can Debiasing Research Aid Efforts to Reduce Discrimination?

PUBLIC ABSTRACT: Scientists studying intergroup biases are often concerned with lessening discrimination (unequal treatment of one social group versus another), but many interventions for reducing such biased behavior have weak or limited evidence. In this review article, we argue one productive avenue for reducing discrimination comes from adapting interventions in a separate field-judgment and decision-making-that has historically studied "debiasing": the ways people can lessen the unwanted influence of irrelevant information on decision-making. While debiasing research shares several commonalities with research on reducing intergroup discrimination, many debiasing interventions have relied on methods that differ from those deployed in the intergroup bias literature. We review several instances where debiasing principles have been successfully applied toward reducing intergroup biases in behavior and introduce other debiasing techniques that may be well-suited for future efforts in lessening discrimination.

Communicating risk: How relevant and irrelevant probabilistic information influences risk perception in medical decision-making.

Patients rely on knowing potential risks before accepting medical treatments, but risk perception can be distorted by cognitive biases and irrelevant information. We examined the interactive effects of subjective processes, objective knowledge, and demographic characteristics on how individuals estimate risks when provided with relevant and irrelevant probabilistic information. Participants read medical scenarios describing potential adverse effects associated with declining and accepting preventative treatment, as well as the objective likelihood of experiencing adverse effects associated with one of these two courses of action. We found that the perceived negativity of outcomes influenced perceptions of risk regardless of whether relevant probabilities were available and that the use of affect heuristics to estimate risk increased with age. Introducing objective estimates ameliorated age-related increases in affective distortions. Sensitivity to relevant probabilities increased with greater perceived outcome severity and was greater for men than for women. We conclude that relevant objective information may reduce the propensity to conflate outcome severity with likelihood and that medical judgments of risk vary depending on exposure to relevant and irrelevant probabilities. Implications for how medical professionals should communicate risk information to patients are considered.

Investigating features that contribute to evaluations of intrusiveness for thoughts and memories.

What makes a thought feel intrusive? One possibility is that traumatic experiences are the primary cause of intrusive thoughts and memories. Another possibility is that experiences of intrusiveness arise from the features involved with re-experiencing. We investigated several features that may lead a thought to feel intrusive: task-congruence, repetition, and affective content. In Experiment 1, participants listened to popular song clips expected to become stuck in one's head. In Experiment 2, participants were cued to recall their own autobiographical memories. We found that both songs and autobiographical memories replaying mentally felt more intrusive when they were incongruent with the current task, cued repeatedly, and had negative emotional content. Additionally, even liked songs and positive autobiographical memories were evaluated as highly intrusive under some conditions. Based on these findings, we argue that intrusiveness is not limited to traumatic thoughts, but rather is a context-dependent evaluation influenced by a variety of features.

Improving the Accuracy of a Biohybrid for Environmental Monitoring.

Environmental monitoring should be minimally disruptive to the ecosystems that it is embedded in. Therefore, the project Robocoenosis suggests using biohybrids that blend into ecosystems and use life forms as sensors. However, such a biohybrid has limitations regarding memory-as well as power-capacities, and can only sample a limited number of organisms. We model the biohybrid and study the degree of accuracy that can be achieved by using a limited sample. Importantly, we consider potential misclassification errors (false positives and false negatives) that lower accuracy. We suggest the method of using two algorithms and pooling their estimations as a possible way of increasing the accuracy of the biohybrid. We show in simulation that a biohybrid could improve the accuracy of its diagnosis by doing so. The model suggests that for the estimation of the population rate of spinning Daphnia, two suboptimal algorithms for spinning detection outperform one qualitatively better algorithm. Further, the method of combining two estimations reduces the number of false negatives reported by the biohybrid, which we consider important in the context of detecting environmental catastrophes. Our method could improve environmental modeling in and outside of projects such as Robocoenosis and may find use in other fields.

Where the Blame Lies: Unpacking Groups Into Their Constituent Subgroups Shifts Judgments of Blame in Intergroup Conflict.

Whom do individuals blame for intergroup conflict? Do people attribute responsibility for intergroup conflict to the in-group or the out-group? Theoretically integrating the literatures on intergroup relations, moral psychology, and judgment and decision-making, we propose that unpacking a group by explicitly describing it in terms of its constituent subgroups increases perceived support for the view that the unpacked group shoulders more of the blame for intergroup conflict. Five preregistered experiments (N = 3,335 adults) found support for this novel hypothesis across three distinct intergroup conflicts: the Israeli-Palestinian conflict, current racial tensions between White people and Black people in the United States, and the gender gap in wages in the United States. Our findings (a) highlight the independent roles that entrenched social identities and cognitive, presentation-based processes play in shaping blame judgments, (b) demonstrate that the effect of unpacking groups generalizes across partisans and nonpartisans, and (c) illustrate how constructing packed versus unpacked sets of potential perpetrators can critically shape where the blame lies.

Social Cognitive Processes Underlying Normative Misperception of Sexual Judgments.

Acquaintance-initiated sexually aggressive behavior (SAB) is a widespread problem on college campuses, and intervention strategies thus far have not produced sustained reductions in SAB. Peer-related social norms and cognitive processes underlying sexual decision-making have separately been implicated in SAB. The present study integrates this work by examining the effect of perspective (self vs. typical college male referent) on college men's judgments of the justifiability of unwanted sexual advances, determining the cognitive processes underlying men's misperceptions, and evaluating rape-supportive attitudes (RSA) as a correlate of the implicated processes. College men attracted to women (n = 217) completed the Heterosocial Perception Survey-Revised, in which they judged the justifiability of a man's increasingly intimate sexual advances as a woman responds increasingly negatively. Participants completed the Heterosocial Perception Survey-Revised from their own perspective and from the typical college male perspective. Participants also completed questionnaires assessing RSA and demographics. Undergraduate men, and particularly those endorsing more RSA, greatly overestimated how much the typical college male perceives increasingly nonconsensual behavior as justified. Three cognitive processes were strongly implicated in this misperception. When responding from the self-perspective, RSA correlated significantly with all cognitive processes. These findings illustrate the utility of integrating work on social norms and cognitive processing to document the global effect of perspective on average justifiability ratings and the perspective effect on cognitive processes underlying the ratings. Future work should evaluate personalized normative feedback and cognitive-training approaches to target misperceptions of peers' sexual judgments, given the well-established relation between sexual misperception and SAB risk.

Debiasing Training Improves Decision Making in the Field.

The primary objection to debiasing-training interventions is a lack of evidence that they improve decision making in field settings, where reminders of bias are absent. We gave graduate students in three professional programs (N = 290) a one-shot training intervention that reduces confirmation bias in laboratory experiments. Natural variance in the training schedule assigned participants to receive training before or after solving an unannounced business case modeled on the decision to launch the Space Shuttle Challenger. We used case solutions to surreptitiously measure participants' susceptibility to confirmation bias. Trained participants were 19% less likely to choose the inferior hypothesis-confirming solution than untrained participants. Analysis of case write-ups suggests that a reduction in confirmatory hypothesis testing accounts for their improved decision making in the case. The results provide promising evidence that debiasing-training effects transfer to field settings and can improve decision making in professional and private life.

Do Evaluations Rise With Experience?

Sequential evaluation is the hallmark of fair review: The same raters assess the merits of applicants, athletes, art, and more using standard criteria. We investigated one important potential contaminant in such ubiquitous decisions: Evaluations become more positive when conducted later in a sequence. In four studies, (a) judges' ratings of professional dance competitors rose across 20 seasons of a popular television series, (b) university professors gave higher grades when the same course was offered multiple times, and (c) in an experimental test of our hypotheses, evaluations of randomly ordered short stories became more positive over a 2-week sequence. As judges completed repeated evaluations, they experienced more fluent decision making, producing more positive judgments (Study 4 mediation). This seemingly simple bias has widespread and impactful consequences for evaluations of all kinds. We also report four supplementary studies to bolster our findings and address alternative explanations.

The Binary Bias: A Systematic Distortion in the Integration of Information.

One of the mind's most fundamental tasks is interpreting incoming data and weighing the value of new evidence. Across a wide variety of contexts, we show that when summarizing evidence, people exhibit a binary bias: a tendency to impose categorical distinctions on continuous data. Evidence is compressed into discrete bins, and the difference between categories forms the summary judgment. The binary bias distorts belief formation-such that when people aggregate conflicting scientific reports, they attend to valence and inaccurately weight the extremity of the evidence. The same effect occurs when people interpret popular forms of data visualization, and it cannot be explained by other statistical features of the stimuli. This effect is not confined to explicit statistical estimates; it also influences how people use data to make health, financial, and public-policy decisions. These studies ( N = 1,851) support a new framework for understanding information integration across a wide variety of contexts.

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions.

Behavioral and neural correlates of increased self-control in the absence of increased willpower.

People often exert willpower to choose a more valuable delayed reward over a less valuable immediate reward, but using willpower is taxing and frequently fails. In this research, we demonstrate the ability to enhance self-control (i.e., forgoing smaller immediate rewards in favor of larger delayed rewards) without exerting additional willpower. Using behavioral and neuroimaging data, we show that a reframing of rewards (i) reduced the subjective value of smaller immediate rewards relative to larger delayed rewards, (ii) increased the likelihood of choosing the larger delayed rewards when choosing between two real monetary rewards, (iii) reduced the brain reward responses to immediate rewards in the dorsal and ventral striatum, and (iv) reduced brain activity in the dorsolateral prefrontal cortex (a correlate of willpower) when participants chose the same larger later rewards across the two choice frames. We conclude that reframing can promote self-control while avoiding the need for additional willpower expenditure.

The effect of introspection on judgment and decision making is dependent on the quality of conscious thinking.

That introspection may impair certain judgments and result in fabrication has been attributed to a distracting shift from more adaptive intuitive processing to more analytic and conscious processing. This phenomenon was studied in an experiment where participants made multidimensional visual choices. It was found that the effect of this shift on decision-making performance was dependent on the quality of the explanations during introspection, while the performance in silent conditions was not. Therefore, it appears that the effect of introspection on judgments is not only influenced by the thinking mode per se, but also by the individual's ability to approach the decision problem analytically.

Scarcity frames value.

Economic models of decision making assume that people have a stable way of thinking about value. In contrast, psychology has shown that people's preferences are often malleable and influenced by normatively irrelevant contextual features. Whereas economics derives its predictions from the assumption that people navigate a world of scarce resources, recent psychological work has shown that people often do not attend to scarcity. In this article, we show that when scarcity does influence cognition, it renders people less susceptible to classic context effects. Under conditions of scarcity, people focus on pressing needs and recognize the trade-offs that must be made against those needs. Those trade-offs frame perception more consistently than irrelevant contextual cues, which exert less influence. The results suggest that scarcity can align certain behaviors more closely with traditional economic predictions.

Using Nonnaive Participants Can Reduce Effect Sizes.

Although researchers often assume their participants are naive to experimental materials, this is not always the case. We investigated how prior exposure to a task affects subsequent experimental results. Participants in this study completed the same set of 12 experimental tasks at two points in time, first as a part of the Many Labs replication project and again a few days, a week, or a month later. Effect sizes were markedly lower in the second wave than in the first. The reduction was most pronounced when participants were assigned to a different condition in the second wave. We discuss the methodological implications of these findings.

Thinking in Black and White: Conscious thought increases racially biased judgments through biased face memory.

It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiments 1 and 2, university students formed impressions of Black and White housemate candidates. They judged the candidates either immediately (immediate decision condition), thought about their judgments for a few minutes (conscious thought condition), or performed an unrelated task for a few minutes (unconscious thought condition). Conscious thinkers and immediate decision-makers showed a stronger face memory bias than unconscious thinkers, and this mediated increased judgment bias, although not all results were significant. Experiment 3 used a new, different paradigm and showed that a Black male was remembered as darker after a period of conscious thought than after a period of unconscious thought. Implications for racial prejudice are discussed.

Young children heed advice selectively.

A rational strategy to update and revise one's uncertain beliefs is to take advice by other agents who are better informed. Adults routinely engage in such advice taking in systematic and selective ways depending on relevant characteristics such as reliability of advisors. The current study merged research in social and developmental psychology to examine whether children also adjust their initial judgment to varying degrees depending on the characteristics of their advisors. Participants aged 3 to 6 years played a game in which they made initial judgments, received advice, and subsequently made final judgments. They systematically revised their judgments in light of the advice, and they did so selectively as a function of advisor expertise. They made greater adjustments to their initial judgment when advised by an apparently knowledgeable informant. This suggests that the pattern of advice taking studied in social psychology has its roots in early development.