Counterfactuals and the logic of causal selection

Quillien, T., & Lucas, C. G. (2022, June 13)

https://doi.org/10.31234/osf.io/ts76y

Abstract

Everything that happens has a multitude of causes, but people make causal judgments effortlessly. How do people select one particular cause (e.g. the lightning bolt that set the forest ablaze) out of the set of factors that contributed to the event (the oxygen in the air, the dry weather. . . )? Cognitive scientists have suggested that people make causal judgments about an event by simulating alternative ways things could have happened. We argue that this counterfactual theory explains many features of human causal intuitions, given two simple assumptions. First, people tend to imagine counterfactual possibilities that are both a priori likely and similar to what actually happened. Second, people judge that a factor C caused effect E if C and E are highly correlated across these counterfactual possibilities. In a reanalysis of existing empirical data, and a set of new experiments, we find that this theory uniquely accounts for people’s causal intuitions.

From the General Discussion

Judgments of causation are closely related to assignments of blame, praise, and moral responsibility.  For instance, when two cars crash at an intersection, we say that the accident was caused by the driver who went through a red light (not by the driver who went through a green light; Knobe and Fraser, 2008; Icard et al., 2017; Hitchcock and Knobe, 2009; Roxborough and Cumby, 2009; Alicke, 1992; Willemsen and Kirfel, 2019); and we also blame that driver for the accident. According to some theorists, the fact that we judge the norm-violator to be blameworthy or morally responsible explains why we judge that he was the cause of the accident. This might be because our motivation to blame distorts our causal judgment (Alicke et al., 2011), because our intuitive concept of causation is inherently normative (Sytsma, 2021), or because of pragmatics confounds in the experimental tasks that probe the effect of moral violations on causal judgment (Samland & Waldmann, 2016).

Under these accounts, the explanation for why moral considerations affect causal judgment should be completely different than the explanation for why other factors (e.g.,prior probabilities, what happened in the actual world, the causal structure of the situation) affect causal judgment. We favor a more parsimonious account: the counterfactual approach to causal judgment (of which our theory is one instantiation) provides a unifying explanation for the influence of both moral and non-moral considerations on causal judgment (Hitchcock & Knobe, 2009)16.

Finally, many formal theories of causal reasoning aim to model how people make causal inferences (e.g. Cheng, 1997; Griffiths & Tenenbaum, 2005; Lucas & Griffiths, 2010; Bramley et al., 2017; Jenkins & Ward, 1965). These theories are not concerned with the problem of causal selection, the focus of the present paper. It is in principle possible that people use the same algorithms they use for causal inference when they engage in causal selection, but in practice models of causal inference have not been able to predict how people select causes (see Quillien and Barlev, 2022; Morris et al., 2019).

The research is here.

The Selective Laziness of Reasoning

Trouche, E., Johansson, P., Hall, L., & Mercier, H. 

(2016). Cognitive science, 40(8), 2122–2136.

https://doi.org/10.1111/cogs.12303

Abstract

Reasoning research suggests that people use more stringent criteria when they evaluate others' arguments than when they produce arguments themselves. To demonstrate this "selective laziness," we used a choice blindness manipulation. In two experiments, participants had to produce a series of arguments in response to reasoning problems, and they were then asked to evaluate other people's arguments about the same problems. Unknown to the participants, in one of the trials, they were presented with their own argument as if it was someone else's. Among those participants who accepted the manipulation and thus thought they were evaluating someone else's argument, more than half (56% and 58%) rejected the arguments that were in fact their own. Moreover, participants were more likely to reject their own arguments for invalid than for valid answers. This demonstrates that people are more critical of other people's arguments than of their own, without being overly critical: They are better able to tell valid from invalid arguments when the arguments are someone else's rather than their own.

From the Discussion

These experiments provide a very clear demonstration of the selective laziness of reasoning. When reasoning produces arguments, it mostly produces post-hoc justifications for intuitive answers, and it is not particularly critical of one’s arguments for invalid answers. By contrast, when reasoning evaluates the very same arguments as if they were someone else’s, it proves both critical and discriminating.

The present results are analogous to those observed in the belief bias literature (e.g., Evans et al., 1983). When participants evaluate an argument whose conclusion they agree with, they tend to be neither critical (they accept most arguments) nor discriminating(they are not much more likely to reject invalid than valid arguments). By contrast, when they evaluate argument whose conclusion they disagree with, they tend to be more critical (they reject more arguments) and more discriminating (they are much more likely to reject invalid than valid arguments). The similarity is easily explained by the fact that when reasoning produces arguments for one’s position, it is automatically in a situation in which it agrees with the argument’s conclusion.

Selective laziness can be interpreted in light of the argumentative theory of reasoning (Mercier & Sperber, 2011). This theory hypothesizes that reasoning is best employed in a dialogical context. In such contexts, opening a discussion with a relatively weak argument is often sensible: It saves the trouble of computing the best way to convince a specific audience, and if the argument proves unconvincing, its flaws can be addressed in the back and forth of argumentation. Indeed, the interlocutor typically provides counter-arguments that help the speaker refine her arguments inappropriate ways (for an extended argument, see Mercier, Bonnier, & Trouche, unpublished data). As a result, the laziness of argument production might not be a flaw but an adaptive feature of reasoning. By contrast, people should properly evaluate other people’s arguments, so as not to accept misleading information—hence the selectivity of reasoning’s laziness.

The research is here.

In short: We make better judges for others, and better defense attorneys for ourselves (paraphrasing an old saying).

South Dakota Governor Kristi Noem may have "engaged in misconduct," ethics board says

CBS News

Originally posted 23 AUG 22

A South Dakota ethics board on Monday said it found sufficient information that Gov. Kristi Noem may have "engaged in misconduct" when she intervened in her daughter's application for a real estate appraiser license, and it referred a separate complaint over her state airplane use to the state's attorney general for investigation.

The three retired judges on the Government Accountability Board determined that "appropriate action" could be taken against Noem for her role in her daughter's appraiser licensure, though it didn't specify the action.

The board's moves potentially escalate the ramifications of investigations into Noem. The Republican governor faces reelection this year and has also positioned herself as an aspirant to the White House in 2024. She is under scrutiny from the board after Jason Ravnsborg, the state's former Republican attorney general, filed complaints that stemmed from media reports on Noem's actions in office. She has denied any wrongdoing.

After meeting in a closed-door session for one hour Monday, the board voted unanimously to invoke procedures that allow for a contested case hearing to give Noem a chance to publicly defend herself against allegations of "misconduct" related to "conflicts of interest" and "malfeasance." The board also dismissed Ravnsborg's allegations that Noem misused state funds in the episode.

However, the retired judges left it unclear how they will proceed. Lori Wilbur, the board chair, said the complaint was "partially dismissed and partially closed," but added that the complaint could be reopened. She declined to discuss what would cause the board to reopen the complaint.

The info is here.

Dual use of artifcial-intelligence-powered drug discovery

Urbina, F., Lentzos, F., Invernizzi, C. et al. 

Nat Mach Intell 4, 189–191 (2022). 

https://doi.org/10.1038/s42256-022-00465-9

The Swiss Federal Institute for NBC (nuclear, biological and chemical) Protection —Spiez Laboratory— convenes the ‘convergence’ conference series set up by the Swiss government to identify developments in chemistry, biology and enabling technologies that may have implications for the Chemical and Biological Weapons Conventions. Meeting every two years, the conferences bring together an international group of scientific and disarmament experts to explore the current state of the art in the chemical and biological fields and their trajectories, to think through potential security implications and to consider how these implications can most effectively be managed internationally.  The meeting convenes for three days of discussion on the possibilities of harm, should the intent be there, from cutting-edge chemical and biological technologies.  Our drug discovery company received an invitation to contribute a presentation on how AI technologies for drug discovery could potentially be misused.

Risk of misuse

The thought had never previously struck us. We were vaguely aware of security concerns around work with pathogens or toxic chemicals, but that did not relate to us; we primarily operate in a virtual setting.  Our work is rooted in building machine learning models for therapeutic and toxic targets to better assist in the design of new molecules for drug discovery. We have spent decades using computers and AI to improve human health—not to degrade it. We were naive in thinking about the potential misuse of our trade, as our aim had always been to avoid molecular features that could interfere with the many different classes of proteins essential to human life. Even our projects on Ebola and neurotoxins, which could have sparked thoughts about the potential negative implications of our machine learning models, had not set our alarm bells ringing.

(cut)

Broader effects on society

There is a need for discussions across traditional boundaries and multiple disciplines to allow for a fresh look at AI for de novo design and related technologies from different perspectives and with a wide variety of mindsets. Here, we give some recommendations that we believe will reduce potential dual-use concerns for AI in drug discovery. Scientific conferences, such as the Society of Toxicology and American Chemical Society, should actively foster a dialogue among experts from industry, academia and policy making on the implications of our computational tools.

A pdf is here.

Tackling Implicit Bias in Health Care

J. A. Sabin

N Engl J Med 2022; 387:105-107

DOI: 10.1056/NEJMp2201180

Implicit and explicit biases are among many factors that contribute to disparities in health and health care. Explicit biases, the attitudes and assumptions that we acknowledge as part of our personal belief systems, can be assessed directly by means of self-report. Explicit, overtly racist, sexist, and homophobic attitudes often underpin discriminatory actions. Implicit biases, by contrast, are attitudes and beliefs about race, ethnicity, age, ability, gender, or other characteristics that operate outside our conscious awareness and can be measured only indirectly. Implicit biases surreptitiously influence judgment and can, without intent, contribute to discriminatory behavior. A person can hold explicit egalitarian beliefs while harboring implicit attitudes and stereotypes that contradict their conscious beliefs.

Moreover, our individual biases operate within larger social, cultural, and economic structures whose biased policies and practices perpetuate systemic racism, sexism, and other forms of discrimination. In medicine, bias-driven discriminatory practices and policies not only negatively affect patient care and the medical training environment, but also limit the diversity of the health care workforce, lead to inequitable distribution of research funding, and can hinder career advancement.

A review of studies involving physicians, nurses, and other medical professionals found that health care providers’ implicit racial bias is associated with diagnostic uncertainty and, for Black patients, negative ratings of their clinical interactions, less patient-centeredness, poor provider communication, undertreatment of pain, views of Black patients as less medically adherent than White patients, and other ill effects.1 These biases are learned from cultural exposure and internalized over time: in one study, 48.7% of U.S. medical students surveyed reported having been exposed to negative comments about Black patients by attending or resident physicians, and those students demonstrated significantly greater implicit racial bias in year 4 than they had in year 1.

A review of the literature on reducing implicit bias, which examined evidence on many approaches and strategies, revealed that methods such as exposure to counterstereotypical exemplars, recognizing and understanding others’ perspectives, and appeals to egalitarian values have not resulted in reduction of implicit biases.2 Indeed, no interventions for reducing implicit biases have been shown to have enduring effects. Therefore, it makes sense for health care organizations to forgo bias-reduction interventions and focus instead on eliminating discriminatory behavior and other harms caused by implicit bias.

Though pervasive, implicit bias is hidden and difficult to recognize, especially in oneself. It can be assumed that we all hold implicit biases, but both individual and organizational actions can combat the harms caused by these attitudes and beliefs. Awareness of bias is one step toward behavior change. There are various ways to increase our awareness of personal biases, including taking the Harvard Implicit Association Tests, paying close attention to our own mistaken assumptions, and critically reflecting on biased behavior that we engage in or experience. Gonzalez and colleagues offer 12 tips for teaching recognition and management of implicit bias; these include creating a safe environment, presenting the science of implicit bias and evidence of its influence on clinical care, using critical reflection exercises, and engaging learners in skill-building exercises and activities in which they must embrace their discomfort.

The info is here.

Meta-Analysis of Inequality Aversion Estimates

Nunnari, S., & Pozzi, M. (2022).

SSRN Electronic Journal.

https://doi.org/10.2139/ssrn.4169385

Abstract

Loss aversion is one of the most widely used concepts in behavioral economics. We conduct a large-scale interdisciplinary meta-analysis, to systematically accumulate knowledge from numerous empirical estimates of the loss aversion coefficient reported during the past couple of decades. We examine 607 empirical estimates of loss aversion from 150 articles in economics, psychology, neuroscience, and several other disciplines. Our analysis indicates that the mean loss aversion coefficient is between 1.8 and 2.1. We also document how reported estimates vary depending on the observable characteristics of the study design.

Conclusion

In this paper, we reported the results of a meta-analysis of empirical estimates of the inequality aversion coefficients in models of outcome-based other-regarding preferences `a la Fehr and Schmidt (1999). We conduct both a frequentist analysis (using a multi-level random-effects model) and a Bayesian analysis (using a Bayesian hierarchical model) to provide a “weighted average” for α and β. The results from the two approaches are nearly identical and support the hypothesis of inequality concerns. From the frequentist analysis, we learn that the mean envy coefficient is 0.425 with a 95% confidence interval of [0.244, 0.606]; the mean guilt coefficient is, instead, 0.291 with a 95% confidence interval [0.218, 0.363]. This means that, on average, an individual is willing to spend € 0.41 to increase others’ earnings by €1 when ahead, and € 0.74 to decrease others’ earnings by €1 when behind. The theoretical assumptions α ≥ β and 0 ≤ β < 1 are upheld in our empirical analysis, but we cannot conclude that the disadvantageous inequality coefficient is statistically greater than the coefficient for advantageous inequality. We also observe no correlation between the two parameters.

The research is here.

Medial and orbital frontal cortex in decision-making and flexible behavior

Klein-Flügge, M. C., Bongioanni, A., & 

Rushworth, M. F. (2022).

Neuron.

https://doi.org/10.1016/j.neuron.2022.05.022

Summary

The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.

Summary

Neural systems that represent the value of the environment exist in many vertebrates. An extended subcortical circuit spanning the striatum, midbrain, and brainstem nuclei of mammals corresponds to these ancient systems. In addition, however, mammals possess several frontal cortical regions concerned with guidance of decision-making and adaptive, flexible behavior. Although these frontal systems interact extensively with these subcortical circuits, they make specific contributions to behavior and also influence behavior via other cortical routes. Some areas such as the ACC, which is present in a broad range of mammals, represent the distribution of opportunities in an environment over space and time, whereas other brain regions such as amFC and dmPFC have roles in representing structural associations and causal links between environmental features, including aspects of the social environment (Figure 8). Although the origins of these areas and their functions are traceable to rodents, they are especially prominent in primates. They make it possible not just to select choices on the basis of past experience of identical situations, but to make inferences to guide decisions in new scenarios.

The info is here.

Truth by Repetition … without repetition: Testing the effect of instructed repetition on truth judgments

Mattavelli, S., Corneille, O., & Unkelbach, C.

Journal of Experimental Psychology

Learning Memory and Cognition

June 2022

Abstract

Past research indicates that people judge repeated statements as more true than new ones. An experiential consequence of repetition that may underly this “truth effect” is processing fluency: processing statements feels easier following their repetition. In three preregistered experiments (N=684), we examined the effect of merely instructed repetition (i.e., not experienced) on truth judgments. Experiments 1-2 instructed participants that some statements were present (vs. absent) in an exposure phase allegedly undergone by other individuals. We then asked them to rate such statements based on how they thought those individuals would have done. Overall, participants rated repeated statements as more true than new statements. The instruction-based repetition effects were significant but also significantly weaker than those elicited by the experience of repetition (Experiments 1 & 2). Additionally, Experiment 2 clarified that adding a repetition status tag in the experienced repetition condition did not impact truth judgments. Experiment 3 further showed that the instruction-based effect was still detectable when participants provided truth judgments for themselves rather than estimating other people’s judgments. We discuss the mechanisms that can explain these effects and their implications for advancing our understanding of the truth effect.

(Beginning of the) General Discussion 

Deciding whether information is true or false is a challenging task. Extensive research showed that one key variable that people often use to judge the truth of a statement is repetition (e.g., Hasher et al. 1977): repeated statements are judged more true than new ones (see Dechêne et al., 2010). Virtually all explanations of this truth effect refer to the processing consequences of repetition: higher recognition rates than new statements, higher familiarity, and higher fluency (see Unkelbach et al., 2019). However, in many communication situations, people get to know that a statement is repeated (e.g., it occurred frequently) without prior exposure to the statement. Here, we asked whether repetition can be used as a cue for truth without prior exposure, and thus, in the absence of experiential consequences of repetition such as fluency. 

Conclusion 

This work represents the first attempt to assess the impact of instructed repetition on truth judgments. We found that the truth effect was stronger when repetition was experienced rather than merely instructed in three experiments. However, we provided initial evidence that a component of the effect is unrelated to the experience of repetition. A truth effect was still detectable in the absence of any internal cue (i.e., fluency) induced by the experienced repetition of the statement and, therefore, should be conditional upon learning history or naïve beliefs. This finding paves the way for new research avenues interested in isolating the unique contribution of known repetition and experienced fluency on truth judgments.

The research is here.

This research has multiple applications to psychotherapy, including how do patients know what information about self and others is true, and how much is due to repetition or internal cues, beliefs, or feelings.  Human beings are meaning makers, and try to assess how the world functions based on the meaning projected toward others.

Too cynical to reconnect: Cynicism moderates the effect of social exclusion on prosociality through empathy

B. K. C. Choy, K. Eom, & N. P. Li

Personality and Individual Differences

Volume 178, August 2021, 110871

Abstract

Extant findings are mixed on whether social exclusion impacts prosociality. We propose one factor that may underlie the mixed results: Cynicism. Specifically, cynicism may moderate the exclusion-prosociality link by influencing interpersonal empathy. Compared to less cynical individuals, we expected highly cynical individuals who were excluded to experience less empathy and, consequently, less prosocial behavior. Using an online ball-tossing game, participants were randomly assigned to an exclusion or inclusion condition. Consistent with our predictions, the effect of social exclusion on prosociality through empathy was contingent on cynicism, such that only less-cynical individuals responded to exclusion with greater empathy, which, in turn, was associated with higher levels of prosocial behavior. We further showed this effect to hold for cynicism, but not other similar traits typically characterized by high disagreeableness. Findings contribute to the social exclusion literature by suggesting a key variable that may moderate social exclusion's impact on resultant empathy and prosocial behavior and are consistent with the perspective that people who are excluded try to not only become included again but to establish alliances characterized by reciprocity.

From the Discussion

While others have proposed that empathy may be reflexively inhibited upon exclusion (DeWall & Baumeister, 2006; Twenge et al., 2007), our findings indicate that this process of inhibition—at least for empathy—may be more flexible than previously thought. If reflexive, individuals would have shown a similar level of empathy regardless of cynicism. That highly- and less-cynical individuals displayed different levels of empathy indicates that some other processes are in play. Our interpretation is that the process through which empathy is exhibited or inhibited may depend on one’s appraisals of the physical and social situation. 

Importantly, unlike cynicism, other similarly disagreeable dispositional traits such as Machiavellianism, psychopathy, and SDO (Social Dominance Orientation) did not modulate the empathy-mediated link between social exclusion and prosociality. This suggests that cynicism is conceptually different from other traits of a seemingly negative nature. Indeed, whereas cynics may hold a negative view of the intentions of others around them, Machiavellians are characterized by a negative view of others’ competence and a pragmatic and strategic approach to social interactions (Jones, 2016). Similarly, whereas cynics view others’ emotions as ingenuine, psychopathic individuals are further distinguished by their high levels of callousness and impulsivity (Paulhus, 2014). Likewise, whereas cynics may view the world as inherently competitive, they may not display the same preference for hierarchy that high-SDO individuals do (Ho et al., 21015). Thus, despite the similarities between these traits, our findings affirm their substantive differences from cynicism. 

The research is here.