In this essay, we argue that the applications of generative-AI technologies to science communication need careful consideration to ensure such uses are desirable, and socially and ethically acceptable. In early applications of GenAI in science communication, especially in public media, there has been swift and overwhelmingly negative response to news about its use. Drawing on existing literature about generative-AI in adjacent fields to science communication, and on the scholarship on the ethics of science communication, this article maps out the key ethical issues that the use of generative-AI technologies raise for science communication. Specifically, acknowledging that generative-AI is more than an output-producing technology but is a constellation of governance, infrastructure, data, human and computing operating systems, we argue that three dimensions of ethical concerns need to be explored: the communication of generative AI; the social and environmental of using generative AI technologies in science communication and the we tell about AI technology.

Mounting socio-environmental crises have prompted calls for post-normal sustainability science, emphasising complexity, uncertainty, and epistemic pluralism, and framing science communication as dialogical and reflexive. However, previous research has identified a gap between these ideals and actual practices, where conventional norms of objectivity and expert authority often prevail. Drawing on Irwin's (2021) framework of socio-technical orders of thinking, we analyse interviews with 12 leading Danish sustainability scientists. Our thematic analysis shows that scientists pragmatically navigate between first-order (expert-led), second-order (inclusive), and third-order (reflexive and power-aware) modes of thinking. While third-order thinking emerges as integral to sustainability science, traditional assumptions about authority and neutrality continue to shape scientists' communication practices. These findings invite science communication scholars to view sustainability science as a fertile ground for developing and testing pluralistic, reflexive, and power-aware communication models, while also learning from the situated practices of scientists who already navigate these complexities in context.

This article examines trust in science in England, focusing on variation across demographic and ideological groups. Using survey data from 11,173 respondents, we compare trust in two domains, medical doctors and scientists, to explore whether predictors operate similarly across these professional groups. We find higher education is associated with greater trust, while right-wing political orientation predicts lower trust. Religious affiliation also matters, with some faith groups reporting lower trust relative to the non-religious baseline. Gender differences emerge as well, particularly in trust in medical doctors. Respondents selecting 'Prefer not to say' on the religion item report significantly lower trust in both doctors and scientists, consistent with a broader privacy-motivated disclosure style. Our results highlight the importance of considering not just overall levels of trust in science, but variation across education, ideology, religion and gender, and they suggest that trust in doctors and trust in scientists, while related, are not interchangeable.

Storytelling is a growing topic in science communication research, highlighting the importance of learning from existing storytelling research from other disciplines. Storytelling research in cultural evolution has identified a number of cognitive biases in how we transmit information: stories are remembered and passed on more faithfully when they contain social and survival information, negative information or counterintuitive information. In this article, we review this cultural evolution literature and present findings from a set of interviews with science communication professionals. We asked science communicators about the potential benefits and risks that may come about when using cognitive biases within science communication storytelling. Science communicators reported already using some cognitive biases in their practice. Participants also expressed concerns about some tactics that might contradict objectives of science communication, threaten the integrity of science and science communication and risk the welfare of audiences. We map the benefits and risks reported using a thematic analysis.

The study examines the intersection of science and politics by analyzing the involvement of = 205 U.S. and = 174 German scientists in policy disputes during the COVID-19 pandemic. I investigate how scientists integrate themselves into policy disputes. Through a survey, I identify four groups of scientists with specific self-images regarding their roles in policy disputes: . Furthermore, the findings reveal differences in how these groups of scientists perceive the importance of science in policy-making: Particularly U.S.-based wish for science to direct policy-making. In addition, I find that pandemic researchers overwhelmingly do not support political causes by selectively communicating political advice. I present empirically evidence that pandemic researchers sought to clarify the relevance of research during the pandemic, but did not attempt to distort policy disputes dishonestly.

Genes are increasingly understood to influence behavior. Research-generally conducted among convenience samples- has suggested that genetic influences tend to be perceived as playing a greater role in positive (e.g. prosocial) behaviors than in negative (e.g. antisocial) behaviors. Several potential bases for this asymmetry have been explored previously. We examined, in a U.S. sample, whether an asymmetry in genetic attributions between prosocial and antisocial behavior would be observed, and if so, what might help to explain it. Results revealed that the asymmetry did occur and appeared to be robustly mediated by an asymmetry between how "natural" prosocial and antisocial behavior are perceived to be. Genetic attributions were also lower on average when the individual was described as African American, especially as an African American man. These findings provide further evidence that genetic attributions are endorsed selectively, in ways that appear to reflect pre-existing psychological motivations and views about human nature.

We describe a focus group study of public perceptions of "deepfake" technology, that is, digitally manipulated videos that show people saying or doing things they never really did. The study was designed to explore the relationship between degree of closeness to or familiarity with technology and attitudes toward it. We find that in this case, publics that are closer have more positive and nuanced attitudes. In such cases, at least, it appears that distance does not lend enchantment. We suggest why this may be the case and propose further related research designed to test the conclusions reached here.

A fair (public) representation of women is one of the most discussed questions of our time. The way in which media coverage (re)produces genders may affect individual and collective thinking and the perceptions of women in society. We analyse the representation of female scientists in German news media coverage of eight science-related risk issues and compare male and female experts regarding their relative scientific reputation, the number of references and the content of their statements. Our findings show that female scientific experts are less visible in German media coverage than their male colleagues and that they are underrepresented compared to the respective proportions in the relevant research areas. At the same time, our data relativize the extent of the gender visibility gap - after controlling for hierarchical position and scientific reputation, the differences become rather small. We find no evidence of discrimination against female scientific experts through journalistic selection routines.

Promising results reported in genetic therapy clinical trials and recent US Food and Drug Administration approvals have attracted media attention. This critical content analysis examines themes and narrative framings present in feature articles published in US news media sources following patients involved in first-in-human clinical trials of genetic therapies. Articles were collected through focused searches across US news websites and LexisNexis databases in the period from 01 January 2017 to 06 April 2022. Forty-three articles met inclusion criteria (n = 13 from database searches, n = 30 from external searches). Articles were diverse across genetic conditions, news sources, and media types. Three dominant themes emerged: (1) Impacts of Living with Genetic Condition, (2) Consequences of Receiving Gene Therapy Treatment, and (3) Risks of Gene Therapy. Narrative frames included hope and caution. Results are discussed in relation to how the value of patient narratives and content may be situated alongside the interests of different actors.

US conservatives are often seen as distrusting scientists, and liberals as more trusting. This article examines how alignment between an expert's field and individual political ideology affects claims perceptions. US adults ( = 1054) participated in a pre-registered (https://osf.io/9wnm2) online experiment, indicating their trust in five experts and evaluating the accuracy of four claims. Claims were attributed to experts from impact fields (focused on the consequences of industry and policy), production fields (industry-focused), scientists in general, or no source. Results show that liberals trust all experts more than conservatives and generally perceive claims as more accurate. However, the trust gap between liberals and conservatives is smaller for production experts. While no difference was found between the perceived accuracy of claims attributed to production versus impact experts, expert attribution increased some claims' perceived accuracy. These findings reveal some political-ideology preferences and that attributing a claim to an expert can improve its perception.

It is repeatedly observed that public engagement with science is more common among members of the public with a more privileged socio-economic profile; however little evidence on the mechanisms of this relationship exists. This article proposes one such mechanism in deference towards authority. Through Structural Equation Model on Eurobarometer 2021 data, I investigate if favoring expert guidance over public participation in decision-making on science-related issues mediates the relationship between people's socio-economic status and engagement with science. Results show that higher socio-economic status is associated with greater engagement but also with favor toward experts' deliberation. Preferring experts over public involvement in decision-making is also associated with more informative engagement and less general engagement. Nevertheless, this mediating role is rather weak. Moreover, the study examines how other perceptions of science relate to socio-economic status and engagement, emphasizing the broader social and structural factors that shape opportunities for participation.

This study used a survey ( = 1897) of United States- and Canada-based scientists in six scientific fields to explore correlates of perceived (a) public engagement goal importance and (b) personal goal prioritization. Building on the Integrated Behavioral Model, the results suggest that scientists' beliefs about the societal benefits of a goal (i.e. attitudes) are the most consistent predictors of goal importance ratings and personal goal prioritization. Other beliefs are also associated with personal goal prioritization, including beliefs about personal benefits, agency (i.e. self-efficacy), and to a lesser extent, social norms. The data further suggests that basic scientists have similar goals to applied scientists who were in the sample, and that there are few differences across the six fields studied. The conclusion is that proponents of specific behavioral goals may wish to focus on communicating the benefits of goals to scientists, more so than norms or efficacy.

Substantial minorities of the population report a low degree of trust in science, or endorse conspiracy theories that violate basic scientific knowledge. This might indicate a wholesale rejection of science. In four studies, we asked 782 US participants questions about trust in science, conspiracy beliefs, and basic science (e.g. the relative size of electrons and atoms). Participants were provided with the scientifically consensual answer to the basic science questions, and asked whether they accept it. Acceptance of the scientific consensus was very high in the sample as a whole (95.1%), but also in every sub-sample (e.g. no trust in science: 87.3%; complete endorsement of flat Earth theory: 87.2%). This quasi-universal acceptance of basic science suggests that people are motivated to reject specific scientific beliefs, and not science as a whole. This could be leveraged in science communication.

A large survey of American adults explored the complex landscape of attitudes toward artificial intelligence (AI). It explored the degree of concern regarding specific potential outcomes of the new advances in AI technology and correlates of these concerns. Key variables associated with the direction and intensity of concern include prior experience using a large language model such as Chat GPT, general trust in science, adherence to the precautionary principle versus support for unrestricted innovation, and demographic factors such as gender. By identifying these relationships, the paper offers insights into the American public's response to AI that can inform the development of policies aimed at either regulating or encouraging its advancement.

This qualitative study uses inductive thematic analysis to investigate how journalists and their readers perceive scientists. The data-driven approach was applied to 84 articles (reporting on the contested science issues of climate change, vaccines, or genetically modified organisms (GMOs)) and their associated comment sections. Two dominant groups were observed: the pro-science group (consisting of commentators and journalists) and the contra-science group (nearly exclusively commentators). The identified themes show that both groups represent scientists and their science in a particular and similar way across the three contested science topics. These representations are used to justify both support and opposition (e.g., each group refers to scientists' motives; however, they express this theme differently by either describing scientists' actions as born out of a desire to help or out of arrogance). Understanding how non-experts perceive scientists could help improve science communication, which may be the first step toward decreasing societal polarization over contested science.

Global challenges like biodiversity loss cannot be understood without essential knowledge about evolution. However, evolution is one of the most misunderstood concepts among the general public. Informal learning environments like natural history museums offer great potential for learning about evolution by showing the latest scientific findings in their exhibitions. But to date, there is a lack of evidence about museum visitors' understanding of evolution. Therefore, this study aims to identify which evolutionary key concepts and misconceptions are applied by visitors when asked to explain evolutionary scenarios. Using an online survey, visitors ( = 122) were asked to answer two open-response ACORNS items. Overall, respondents tended to use relatively few key concepts in their responses. Although museum visitors are considered a highly educated group, our surveyed visitors seem to have a poor understanding of evolution. The key concepts and misconceptions identified might help develop future exhibitions and educational programs/activities.

Scholars have increasingly turned to empathy to increase the effectiveness of participatory deliberations among individuals with diverse interests and values. However, because empathy is traditionally focused on in-group relations, deliberations in increasingly polarized contexts would benefit from ways to bridge across social groups. To address this, we apply the construct of empathy. Our study explores social empathy through participatory technology assessment forums and asks: how do we incorporate, measure, and understand social empathy in public deliberations on human genome editing technology? The analysis reveals that by considering social empathy, participatory deliberation forum designers can use "persona" character cards and other forum infrastructure to increase the effectiveness of deliberation across social groups among individuals with diverse interests and values. For future deliberations seeking to cultivate social learning, social empathy-when designed for, integrated in, and measured through deliberations-presents an important mechanism for attention.

Large language models (LLMs) have emerged as a novel form of media, capable of generating human-like text and facilitating interactive communications. However, these systems are subject to concerns regarding inherent biases, as their training on vast text corpora may encode and amplify societal biases. This study investigates overestimation bias in LLM-generated climate assessments, wherein the impacts of climate change are exaggerated relative to expert consensus. Through non-parametric statistical methods, the study compares expert ratings from the Intergovernmental Panel on Climate Change 2023 Synthesis Report with responses from GPT-family LLMs. Results indicate that LLMs systematically overestimate climate change impacts, and that this bias is more pronounced when the models are prompted in the role of a climate scientist. These findings underscore the critical need to align LLM-generated climate assessments with expert consensus to prevent misperception and foster informed public discourse.

While much research has revealed the prevalence of climate change misinformation on social media, there is no conclusive evidence about its impact on cultivating public misperceptions. Even less work has been done to examine how social media use may condition the relationships between cognitive orientations, such as epistemic and science populism beliefs, and climate change misperceptions. This study fills this gap by analyzing data from a national representative survey of 1405 US adults. Results confirmed the relationships between cognitive orientations and climate change misperceptions. While neither mainstream nor alternative social media use had a direct impact, both types of social media use conditioned the relationships between cognitive orientations and climate change misperceptions. This study's findings suggest that social media use's adverse impact on climate change misperceptions may have been overstated.

Recent research examines how the transformational experience of the COVID-19 pandemic reshapes trust in science, expertise and public institutions in its aftermath. This article extends this scholarship by asking how the transformation of societal norms about expertise induced by the pandemic experience shapes social movements that contest state expertise. Using interview data with participants from an ongoing environmental health mobilization in Rouyn-Noranda (Quebec, Canada), this article highlights how participants negotiate their precarious status as challengers of expertise in a post-COVID world. First, I examine the direct and indirect evidence of politicized expertise that participants draw on to motivate their distrust. Second, I show how participants negotiate the boundary between claims of COVID-related groups labeled as conspiracist and their own. Overall, this article contributes to better understanding how mobilized citizens navigate changing norms around trust in science.