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 idea of separating a person's consciousness and transferring it to another medium-'mind upload'-is being actively discussed in science, philosophy, and science fiction. Mind upload technologies are currently also being developed by private companies in Silicon Valley, and similar technological developments have received significant funding in the EU. Mind upload has important existential and ethical implications, yet little is known about how ordinary people actually feel about it. The current paper aims to provide a thorough moral psychological evaluation about various cognitive factors that explain people's feelings and reactions towards the use of mind upload technology. In four studies (including pilot) with a total of 952 participants, it was shown that biological and cultural cognitive factors help to determine how strongly people condemn mind upload. Both experimental manipulations in a laboratory and cross-sectional correlative online study designs were employed. The results showed that people who value purity norms and have higher sexual disgust sensitivity are more inclined to condemn mind upload. Furthermore, people who are anxious about death and condemn suicidal acts were more accepting of mind upload. Finally, higher science fiction literacy and/or hobbyism strongly predicted approval of mind upload. Several possible confounding factors were ruled out, including personality, values, individual tendencies towards rationality, and theory of mind capacities. Possible idiosyncrasies in the stimulus materials (whether consciousness is uploaded onto a computer, chimpanzee, artificial brain, or android; and whether the person's body physically dies during the process) were ruled out. The core findings inform ongoing philosophical discussions on how mind upload could (or should) be used in the future, and imply that mind upload is a much more salient topic for the general population than previously thought.

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Artificial intelligences (AIs) are widely used in tasks ranging from transportation to healthcare and military, but it is not yet known how people prefer them to act in ethically difficult situations. In five studies (an anthropological field study, n = 30, and four experiments, total n = 2150), we presented people with vignettes where a human or an advanced robot nurse is ordered by a doctor to forcefully medicate an unwilling patient. Participants were more accepting of a human nurse's than a robot nurse's forceful medication of the patient, and more accepting of (human or robot) nurses who respected patient autonomy rather than those that followed the orders to forcefully medicate (Study 2). The findings were robust against the perceived competence of the robot (Study 3), moral luck (whether the patient lived or died afterwards; Study 4), and command chain effects (Study 5; fully automated supervision or not). Thus, people prefer robots capable of disobeying orders in favour of abstract moral principles like valuing personal autonomy. Our studies fit in a new era in research, where moral psychological phenomena no longer reflect only interactions between people, but between people and autonomous AIs.

AbstractThe idea of sex with robots seems to fascinate the general public, raising both enthusiasm and revulsion. We ran two experimental studies (Ns = 172 and 260) where we compared people’s reactions to variants of stories about a person visiting a bordello. Our results show that paying for the services of a sex robot is condemned less harshly than paying for the services of a human sex worker, especially if the payer is married. We have for the first time experimentally confirmed that people are somewhat unsure about whether using a sex robot while in a committed monogamous relationship should be considered as infidelity. We also shed light on the psychological factors influencing attitudes toward sex robots, including disgust sensitivity and interest in science fiction. Our results indicate that sex with a robot is indeed genuinely considered as sex, and a sex robot is genuinely seen as a robot; thus, we show that standard research methods on sexuality and robotics are also applicable in research on sex robotics.

Collecting data is one of the bottlenecks of Human-Computer Interaction (HCI) and user experience (UX) research. In this poster paper, we explore and critically evaluate the potential of large-scale neural language models like GPT-3 in generating synthetic research data such as participant responses to interview questions. We observe that in the best case, GPT-3 can create plausible reflections of video game experiences and emotions, and adapt its responses to given demographic information. Compared to real participants, such synthetic data can be obtained faster and at a lower cost. On the other hand, the quality of generated data has high variance, and future work is needed to rigorously quantify the human-likeness, limitations, and biases of the models in the HCI domain. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

Artificial intelligences (AIs) are widely used in tasks ranging from transportation and healthcare to military. Many tasks carried out by autonomous AIs have consequences for human well-being, but it is still unclear how people would prefer them to act in ethically difficult situations. In six studies with data from two cultures (five quantitative experiments, n = 1569, and a qualitative anthropological field study, n = 30), we presented people with hypothetical situations where a human or an advanced robot nurse is ordered to forcefully medicate an unwilling patient. We measured moral acceptance, perceived trust, and allocation of responsibility relating to the nurse's decision of either following orders to forcefully medicate the patient, or disregarding orders to protect the patient's autonomy. Our participants were aversive to robot nurses who forcefully medicated the patient, and preferred robot nurses who respected patient autonomy by disobeying orders. Under certain conditions, the decision to respect patient autonomy was more acceptable for robot nurses than for human nurses. Thus, our results suggest that people prefer robots that are capable of disobeying orders in favor of abstract moral principles such as valuing personal autonomy. These findings were relatively robust against manipulating the nurse's perceived reputation and character, and whether or not the patient lived or died afterwards. We also found that moral judgment is distinct from evaluations of trust and responsibility. In general, our participants did not trust robot nurses or hold them responsible for their actions; on the other hand human nurses who forcefully medicated a patient were morally condemned but also trusted. It seems that Moral Psychology of Robotics is a new and increasingly relevant sub-field of moral psychology that requires extensive attention.

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 behavior change. To help scholars better understand the social and moral psychology behind public health behavior, 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 individual differences 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.