Collabra-Psychology最新文献

As healthcare artificial intelligence (AI) systems advance, their capacity for bias (e.g., as a function of patient protected characteristics) increases as well and these limitations are often left undisclosed by developers. Here, the question arises - do supportive motivational messaging designed to increase buy-in inspire healthcare AI developers to transparently communicate about bias in their technology? Computer science students (Study 1: N=271; Study 2: N=209) were randomly assigned to receive a brief communication framed in either an autonomy-supportive (choice promoting) or controlling (judging and pressuring) way, emphasizing either personal benefits (gaining profit) of transparency or legal implications of non-transparency. Results showed that while communication type was not associated with behavioral intention to engage in an educational course on transparent communication about bias, both internal (self-directed) and external motivations were associated with greater intention to take a course to build transparency-congruent technology skills, as well as greater ethical voice - intention to speak up in the service of positive transparency-consistent cultural change, and lower antagonism - i.e., a lower critical perspective regarding the need for transparency. Findings suggest that universities and workplaces should provide students and developers with a broadly supportive motivational climate, rather than providing a singular brief training.

It is commonly claimed that curiosity, agency, and choice enhance learning and memory in children. However, the few studies that have investigated this in young children reveal mixed effects on memory. To test this, in Experiment 1, children aged 4-7 years watched short cartoon clips and then viewed one of two endings: either in an "active" condition, where they made choices about which ending to view, or a "yoked" condition, where choices were made for them. A surprise memory test conducted 6-8 days later showed no significant difference between conditions in either recognition or binding tasks. In Experiment 2, a within-subject design was employed to control for individual differences. Again, no significant differences were found between conditions. Bayes factor analyses provided evidence supporting the null hypothesis in this child-friendly, cartoon-based paradigm. While our findings suggest that, under these specific task conditions, the agency does not enhance memory in 4- to 7-year-olds, further research is needed to clarify whether different task structures, feedback, or age groups might reveal more robust effects. Potential boundary conditions and developmental implications are discussed.

Studies assessing children's use of race in social judgment have often focused on White participants and usually include targets of only one or two racial backgrounds. They have also employed a wide range of methods, making comparisons across studies difficult. In this paper, we recruited a large sample of children ages 4- to 6-years-old (N = 666) belonging to the United States' four largest racial/ethnic groups (Black, Latine, Asian, and White) in five geographic regions (Durham, NC; Honolulu, HI; Long Beach, CA; New Haven, CT; Seattle, WA) to broadly examine children's race-based social judgments (including measures of racial attitudes, interpersonal distance, resource allocation, and status perception). Overall, children demonstrated consistent ingroup biases in the attitudes, resource allocation, and interpersonal distance measures, but did not systematically associate their ingroup with higher status. When analyzed separately by participant race, White children tended to show these effects at above chance rates, sometimes significantly more than children in other racial groups. Results for Black, Latine, and Asian children were more variable across measures.

Habits pose a fundamental puzzle for those aiming to understand human behavior. They pervade our everyday lives and dominate some forms of psychopathology but are extremely hard to elicit in the lab. In this Registered Report, we developed novel experimental paradigms grounded in computational models, which suggest that habit strength should be proportional to the frequency of behavior and, in contrast to previous research, independent of value. Specifically, we manipulated how often participants performed responses in two tasks varying action repetition without, or separately from, variations in value. Moreover, we asked how this frequency-based habitization related to value-based operationalizations of habit and self-reported propensities for habitual behavior in real life. We find that choice frequency during training increases habit strength at test and that this form of habit shows little relation to value-based operationalizations of habit. Our findings empirically ground a novel perspective on the constituents of habits and suggest that habits may arise in the absence of external reinforcement. We further find no evidence for an overlap between different experimental approaches to measuring habits and no associations with self-reported real-life habits. Thus, our findings call for a rigorous reassessment of our understanding and measurement of human habitual behavior in the lab.