Now you see me, now you don't: an exploration of religious exnomination in DALL-E.

Artificial intelligence (AI) systems are increasingly being used not only to classify and analyze but also to generate images and text. As recent work on the content produced by text and image Generative AIs has shown (e.g., Cheong et al., 2024, Acerbi & Stubbersfield, 2023), there is a risk that harms of representation and bias, already documented in prior AI and natural language processing (NLP) algorithms may also be present in generative models. These harms relate to protected categories such as gender, race, age, and religion. There are several kinds of harms of representation to consider in this context, including stereotyping, lack of recognition, denigration, under-representation, and many others (Crawford in Soundings 41:45-55, 2009; in: Barocas et al., SIGCIS Conference, 2017). Whereas the bulk of researchers' attention thus far has been given to stereotyping and denigration, in this study we examine 'exnomination', as conceived by Roland Barthes (1972), of religious groups. Our case study is DALL-E, a tool that generates images from natural language prompts. Using DALL-E mini, we generate images from generic prompts such as "religious person." We then examine whether the generated images are recognizably members of a nominated group. Thus, we assess whether the generated images normalize some religions while neglecting others. We hypothesize that Christianity will be recognizably represented more frequently than other religious groups. Our results partially support this hypothesis but introduce further complexities, which we then explore.

Moral universals: A machine-reading analysis of 256 societies.

What is the cross-cultural prevalence of the seven moral values posited by the theory of "morality-as-cooperation"? Previous research, using laborious hand-coding of ethnographic accounts of ethics from 60 societies, found examples of most of the seven morals in most societies, and observed these morals with equal frequency across cultural regions. Here we replicate and extend this analysis by developing a new Morality-as-Cooperation Dictionary (MAC-D) and using Linguistic Inquiry and Word Count (LIWC) to machine-code ethnographic accounts of morality from an additional 196 societies (the entire Human Relations Area Files, or HRAF, corpus). Again, we find evidence of most of the seven morals in most societies, across all cultural regions. The new method allows us to detect minor variations in morals across region and subsistence strategy. And we successfully validate the new machine-coding against the previous hand-coding. In light of these findings, MAC-D emerges as a theoretically-motivated, comprehensive, and validated tool for machine-reading moral corpora. We conclude by discussing the limitations of the current study, as well as prospects for future research.

Addressing climate change with behavioral science: A global intervention tournament in 63 countries.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

Exploring intellectual humility through the lens of artificial intelligence: Top terms, features and a predictive model.

Intellectual humility (IH) is often conceived as the recognition of, and appropriate response to, your own intellectual limitations. As far as we are aware, only a handful of studies look at interventions to increase IH - e.g. through journalling - and no study so far explores the extent to which having high or low IH can be predicted. This paper uses machine learning and natural language processing techniques to develop a predictive model for IH and identify top terms and features that indicate degrees of IH. We trained our classifier on the dataset from an existing psychological study on IH, where participants were asked to journal their experiences with handling social conflicts over 30 days. We used Logistic Regression (LR) to train a classifier and the Linguistic Inquiry and Word Count (LIWC) dictionaries for feature selection, picking out a range of word categories relevant to interpersonal relationships. Our results show that people who differ on IH do in fact systematically express themselves in different ways, including through expression of emotions (i.e., positive, negative, and specifically anger, anxiety, sadness, as well as the use of swear words), use of pronouns (i.e., first person, second person, and third person) and time orientation (i.e., past, present, and future tenses). We discuss the importance of these findings for IH and the value of using such techniques for similar psychological studies, as well as some ethical concerns and limitations with the use of such semi-automated classifications.

Social and moral psychology of COVID-19 across 69 countries.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

Polarization and trust in the evolution of vaccine discourse on Twitter during COVID-19.

Trust in vaccination is eroding, and attitudes about vaccination have become more polarized. This is an observational study of Twitter analyzing the impact that COVID-19 had on vaccine discourse. We identify the actors, the language they use, how their language changed, and what can explain this change. First, we find that authors cluster into several large, interpretable groups, and that the discourse was greatly affected by American partisan politics. Over the course of our study, both Republicans and Democrats entered the vaccine conversation in large numbers, forming coalitions with Antivaxxers and public health organizations, respectively. After the pandemic was officially declared, the interactions between these groups increased. Second, we show that the moral and non-moral language used by the various communities converged in interesting and informative ways. Finally, vector autoregression analysis indicates that differential responses to public health measures are likely part of what drove this convergence. Taken together, our results suggest that polarization around vaccination discourse in the context of COVID-19 was ultimately driven by a trust-first dynamic of political engagement.

Attention and counter-framing in the Black Lives Matter movement on Twitter.

The social media platform Twitter platform has played a crucial role in the Black Lives Matter (BLM) movement. The immediate, flexible nature of tweets plays a crucial role both in spreading information about the movement's aims and in organizing individual protests. Twitter has also played an important role in the right-wing reaction to BLM, providing a means to reframe and recontextualize activists' claims in a more sinister light. The ability to bring about social change depends on the balance of these two forces, and in particular which side can capture and maintain sustained attention. The present study examines 2 years worth of tweets about BLM (about 118 million in total). Timeseries analysis reveals that activists are better at mobilizing rapid attention, whereas right-wing accounts show a pattern of moderate but more sustained activity driven by reaction to political opponents. Topic modeling reveals differences in how different political groups talk about BLM. Most notably, the murder of George Floyd appears to have solidified a right-wing counter-framing of protests as arising from dangerous "terrorist" actors. The study thus sheds light on the complex network and rhetorical effects that drive the struggle for online attention to the BLM movement.

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning.

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

The Development and Validation of the Epistemic Vice Scale.

This paper presents two studies on the development and validation of a ten-item scale of epistemic vice and the relationship between epistemic vice and misinformation and fake news. Epistemic vices have been defined as character traits that interfere with acquiring, maintaining, and transmitting knowledge. Examples of epistemic vice are gullibility and indifference to knowledge. It has been hypothesized that epistemically vicious people are especially susceptible to misinformation and conspiracy theories. We conducted one exploratory and one confirmatory observational survey study on Amazon Mechanical Turk among people living in the United States (total N = 1737). We show that two psychological traits underlie the range of epistemic vices that we investigated: indifference to truth and rigidity. Indifference manifests itself in a lack of motivation to find the truth. Rigidity manifests itself in being insensitive to evidence. We develop a scale to measure epistemic vice with the subscales indifference and rigidity. The Epistemic Vice Scale is internally consistent; has good convergent, divergent, and discriminant validity; and is strongly associated with the endorsement of misinformation and conspiracy theories. Epistemic vice explains additional variance in the endorsement of misinformation and conspiracy theories over and above demographic and related psychological concepts and shows medium to large effect sizes across outcome measures. We demonstrate that epistemic vice differs from existing psychological constructs, and show that the scale can explain individual differences in dealing with misinformation and conspiracy theories. We conclude that epistemic vice might contribute to "postfactive" ways of thinking. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13164-021-00562-5.

Stewardship of global collective behavior.

Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our social systems, with poorly understood functional consequences. This gap in our knowledge represents a principal challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a "crisis discipline" just as medicine, conservation, and climate science have, with a focus on providing actionable insight to policymakers and regulators for the stewardship of social systems.

Moral reasoning is the process of asking moral questions and answering them.

Reasoning is the iterative, path-dependent process of asking questions and answering them. Moral reasoning is a species of such reasoning, so it is a matter of asking and answering moral questions, which requires both creativity and curiosity. As such, interventions and practices that help people ask more and better moral questions promise to improve moral reasoning.

The Nietzschean precedent for anti-reflective, dialogical agency.

Nietzsche anticipates both the anti-reflective and the dialogical aspects of Doris's theory of agency. Nietzsche's doctrine of will to power presupposes that agency does not require reflection but emerges from interacting drives, affects, and emotions. Furthermore, Nietzsche identifies two channels through which dialogical processes of person-formation flow: sometimes a person announces what she is and meets with social acceptance of that claim; sometimes someone else announces what the person is, and she accepts the attribution.

Development and validation of a multi-dimensional measure of intellectual humility.

This paper presents five studies on the development and validation of a scale of intellectual humility. This scale captures cognitive, affective, behavioral, and motivational components of the construct that have been identified by various philosophers in their conceptual analyses of intellectual humility. We find that intellectual humility has four core dimensions: Open-mindedness (versus Arrogance), Intellectual Modesty (versus Vanity), Corrigibility (versus Fragility), and Engagement (versus Boredom). These dimensions display adequate self-informant agreement, and adequate convergent, divergent, and discriminant validity. In particular, Open-mindedness adds predictive power beyond the Big Six for an objective behavioral measure of intellectual humility, and Intellectual Modesty is uniquely related to Narcissism. We find that a similar factor structure emerges in Germanophone participants, giving initial evidence for the model's cross-cultural generalizability.

Placebo Effects and Informed Consent.

The concepts of placebos and placebo effects refer to extremely diverse phenomena. I recommend dissolving the concepts of placebos and placebo effects into loosely related groups of specific mechanisms, including (potentially among others) expectation-fulfillment, classical conditioning, and attentional-somatic feedback loops. If this approach is on the right track, it has three main implications for the ethics of informed consent. First, because of the expectation-fulfillment mechanism, the process of informing cannot be considered independently from the potential effects of treatment. Obtaining informed consent influences the effects of treatment. This provides support for the authorized concealment and authorized deception paradigms, and perhaps even for outright deceptive placebo use. Second, doctors may easily fail to consider the potential benefits of conditioning, leading them to misjudge the trade-off between beneficence and autonomy. Third, how attentional-somatic feedback loops play out depends not only on the content of the informing process but also on its framing. This suggests a role for libertarian paternalism in clinical practice.

Functional outcome in TBI I: neuropsychological, emotional, and behavioral mediators.

Literature exists to suggest that the severity of traumatic brain injury (TBI) is positively associated with the severity of functional impairment. However, potential mediators of this relationship have not been studied systematically. In the present study, we evaluated a model hypothesized to explain the relationship between TBI severity and functional impairment in 87 patients with moderate-to-severe TBI, studied longitudinally. Using structural equation modeling, we found that only neuropsychological status (but not emotional or behavioral difficulties) consistently mediated the relationship between TBI severity and functional outcome at 12-months post-injury. These findings suggest that, of the factors examined here, neurocognitive compromise plays the most prominent role in mediating post-TBI adaptive functioning in moderate-to-severe TBI, which has important implications for post-injury interventions.

Functional outcome in TBI II: verbal memory and information processing speed mediators.

Following traumatic brain injury (TBI), patients often report memory difficulties, as well as reduced information processing speed. However, it remains unclear the extent to which these deficits contribute to functional impairment. In the present study, we compared the relative contribution of verbal memory and information processing speed to functional impairment at 12-month post-injury, in 87 patients with moderate-to-severe TBI. Employing structural equation modeling, we found that information processing speed, but not verbal memory functions, significantly mediated the relationship between TBI severity and post-TBI adaptive functioning. These findings suggest that despite the pervasive memory complaints among patients with TBI, it is the impact of neurotrauma on frontal systems that appears to be primarily responsible for patients' difficulties in social and occupational functioning.