Public Understanding of Science最新文献

The motivated reception of science in line with one's preexisting convictions is a well-documented, pervasive phenomenon. In two studies (N = 743), we investigated whether this bias might be stronger in some people than others due to dispositional differences. Building on the assumptions that motivated science reception is driven by perceived threat and suspicion and higher under perceived ambiguity and uncertainty, we focused on traits associated with such perceptions. In particular, we tested the impact of conspiracy mentality and victim sensitivity on motivated science reception (as indicated by ascriptions of researchers' trustworthiness and evidence credibility). In addition, we explored the role of broader personality traits (generalized mistrust and ambiguity intolerance) in this context. None of the investigated dispositions modulated the motivated science reception effect. This demonstrates once again, that motivated science reception is a ubiquitous challenge for the effective dissemination of science and everyone seems to be at risk of it.

This research explored the strategic beliefs that people have about science and the extent to which it can explain moral and immoral behaviors. Although people do not believe that science is able to explain certain aspects of their mind, they might nevertheless accept a scientific explanation for their immoral behaviors if that explanation is exculpatory. In a first study, participants reflected on moral and immoral deeds that they performed or that other people performed. Participants were somewhat skeptic that science can account for people's behavior-except for when they reflected on the wrongdoings that they committed. Two further studies suggest that strategic belief in science arises because it enables external attributions for the behavior, outside of the wrongdoers' control. Implications are discussed for science understanding and communication.

Given the importance of public engagement in governments' adoption of artificial intelligence systems, artificial intelligence researchers and practitioners spend little time reflecting on who those publics are. Classifying publics affects assumptions and affordances attributed to the publics' ability to contribute to policy or knowledge production. Further complicating definitions are the publics' role in artificial intelligence production and optimization. Our structured analysis of the corpus used a mixed method, where algorithmic generation of search terms allowed us to examine approximately 2500 articles and provided the foundation to conduct an extensive systematic literature review of approximately 100 documents. Results show the multiplicity of ways publics are framed, by examining and revealing the different semantic nuances, affordances, political and expertise lenses, and, finally, a lack of definitions. We conclude that categorizing publics represents an act of power, politics, and truth-seeking in artificial intelligence.

Initiatives that collect and share genomic data to advance health research are widespread and accelerating. Commercial interests in these efforts, while vital, may erode public trust and willingness to provide personal genomic data, upon which these initiatives depend. Understanding public attitudes towards providing genomic data for health research in the context of commercial involvement is critical. A PRISMA-guided search of six online academic databases identified 113 quantitative and qualitative studies using primary data pertaining to public attitudes towards commercial actors in the management, collection, access, and use of biobank and genomic data. The presence of commercial interests yields interrelated public concerns around consent, privacy and data security, trust in science and scientists, benefit sharing, and the ownership and control of health data. Carefully considered regulatory and data governance and access policies are therefore required to maintain public trust and support for genomic health initiatives.

The governance of artificial intelligence (AI) is an urgent challenge that requires actions from three interdependent stakeholders: individual citizens, technology corporations, and governments. We conducted an online survey (N = 525) of US adults to examine their beliefs about the governance responsibility of these stakeholders as a function of trust and AI ethics. Different dimensions of trust and different ethical concerns were associated with beliefs in governance responsibility of the three stakeholders. Specifically, belief in the governance responsibility of the government was associated with ethical concerns about AI, whereas belief in governance responsibility of corporations was related to both ethical concerns and trust in AI. Belief in governance responsibility of individuals was related to human-centered values of trust in AI and fairness. Overall, the findings point to the need for an interdependent framework in which citizens, corporations, and governments share governance responsibilities, guided by trust and ethics as the guardrails.

Scientism proposes science to be an all-powerful human enterprise, able to answer not only all practical but also philosophical or moral questions. We are taking a psychological approach to scientism, studying uncritical trust in science and uncritical trust in scientists as a part of a unique attitudinal tendency. Our novel measure assesses both kinds of trust through short Thurstone scales allowing us to establish a clear threshold for endorsing scientism, thus effectively delineating it from science enthusiasm, which previous instruments were unable to do. We built and refined a novel scale through five stages in which we consulted relevant literature, experts, and laypeople. We demonstrated that uncritical trust in science and scientists are interrelated, yet distinct constructs. As expected, these two subscales positively correlated with dogmatism, scientific knowledge, and overclaiming, but not with knowledge overestimation. The results suggest the new instrument is reliable, valid, and suitable for the lay public.

Photography plays an important role in science communication. This study investigates the photographic portraits of scientists in the news media in China from 1949 to 2022. The data consist of 1,071 photographs published in People's Daily, the most influential newspaper in China. The photographs are analysed according to a framework based on previous studies on the visual representation of scientists. Analysis shows an overall image of scientists that demonstrates distinctive 'Chinese' features, such as the prominence of group photos and governmental honours. Diachronically, the visual image of scientists evolved from the early farmer scientists acclaimed in midst of political struggle to social elites and stars celebrated as China's hope for indigenous innovation. The study enriches our understanding of the visual representation of scientists in China, and sheds light on the influence of culture, politics and social positioning of science and technology on the image of scientists created by the media.

Politicization is frequently employed as an analytic concept to explain the relationships between politics and media coverage of climate change. However, relatively few works explore how different notions of politicization are mobilized by actors in media discourses themselves. This article does so via a framing analysis of climate change coverage in Canadian newspapers. I investigate how different relationships between science and politics are conceived and associated with varying positions on climate change. In particular, I examine a supposition in science and technology studies that the media remains committed to deficit models and thus uncritically reproduces the authority of science. Scientistic discourses exist but among a diversity of politicization framings. A key finding is that the strongest appeals to scientific neutrality are associated with climate skepticism. This casts light on the nuanced, strategic "politics of politicization" in climate change debates. A more fine-grained and reflexive approach to politicization discourses can help identify productive interventions.

As societal discussion on the public opinion of science and technology ignites over and over again, understanding where such opinions are rooted is increasingly relevant. A handful of prior studies have suggested personality traits as a root of science and technology attitudes. However, these report mixed findings, and employ small student or convenience samples. This leaves considerable uncertainty regarding personality traits' relation to attitudes toward science and technology. If in fact stable psychological predispositions play a role, this has considerable implications for science policy and science communication. This article investigates the relationship between the big five personality traits and science attitudes in Germany and the Netherlands. Findings indicate that personality traits are related to science attitudes but only very weakly so, among them openness to experience and negative emotionality are most notably related to science attitudes, whereas extraversion, in contrast to prior studies, shows no relation to science and technology attitudes.

To examine how different features of corrective messages moderate individuals' attitudes toward misinformation on social media, a 2 (misinformation source credibility: high vs low) × 2 (corrective message source: algorithmic vs peer correction) × 2 (correction type: factual elaboration vs simple rebuttal) between-subjects experiment was conducted. To reduce perceived credibility and respondents' attitudes toward the misinformation, peer corrections were more effective than algorithmic corrections for misinformation from a source with lower credibility; for misinformation from a highly credible source, the superiority effect of peer corrections was still significant on perceived credibility but not on respondents' attitudes toward the misinformation. For the fact-checking tendency, we did not find a robust effect about how different features of corrective messages interacted. Our findings provide important insights into message design in combatting misinformation on social media.