Examining expertise: Synthetic biology experts' perceptions of risk, benefit, and the public for research and applications regulation.

Scientific experts can play an important role in decision-making surrounding policy for technical and value-laden issues, often in contexts that directly affect lay publics. Yet little is known about what characterizes scientific experts who want lay public involvement in decision-making. In this study, we examine how synthetic biology experts' perceptions of risks, benefits, and ambivalence for synthetic biology relate to views of lay publics, deference to scientific authority, and regulations. We analyzed survey data of researchers in the United States, who published academic articles relating to synthetic biology from 2000 to 2015. Scientific experts who see less risk and are more deferent to scientific authority appear to favor a more closed system in which regulations are sufficient, citizens should not be involved, and scientists know best. Conversely, scientific experts who see more potential for risk and see the public as bringing a valuable perspective appear to favor a more open, inclusive system.

Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.

BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public. OBJECTIVE: This study reviews the existing survey research on the United States' public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings. METHODS: We conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups. RESULTS: This review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use. CONCLUSIONS: Americans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information.

Collateral damage from debunking mRNA vaccine misinformation.

Amid the COVID-19 pandemic, the scientific community has been understandably eager to combat misinformation about issues such as vaccine safety. In highly polarized information environments, however, even well-intentioned messages have the potential to produce adverse effects. In this study, we connect different disciplinary strands of social science to derive and experimentally test the novel hypothesis that although particular efforts to debunk misinformation about mRNA vaccines will reduce relevant misperceptions about that technology, these correctives will harm attitudes toward other types of vaccines. We refer to this as the "collateral damage hypothesis." Our study specifically examines a corrective message stating that "mRNA vaccines do not contain live virus," and our results offer some support for our hypothesis, with the corrective triggering increased societal risk perceptions of live vaccines. We also find that the effect is, predictably, most evident among those whose vaccine acceptance is low. Building on the theoretical grounding we outline, we test a "damage control" adjustment to the corrective message and present evidence supporting that it mitigates the collateral damage.

The state of GMOs on social media An analysis of state-level variables and discourse on Twitter in the United States.

This study analyzes the relationship between state-level variables and Twitter discourse on genetically modified organisms (GMOs). Using geographically identified tweets related to GMOs, we examined how the sentiments expressed about GMOs related to education levels, news coverage, proportion of rural and urban counties, state-level political ideology, amount of GMO-related legislation introduced, and agricultural dependence of each U.S. state. State-level characteristics predominantly did not predict the sentiment of the discourse. Instead, the topics of tweets predicted the majority of variance in tweet sentiment at the state level. The topics that tweets within a state focused on were related to state-level characteristics in some cases.

(Mis)informed about what? What it means to be a science-literate citizen in a digital world.

Science literacy is often held up as crucial for avoiding science-related misinformation and enabling more informed individual and collective decision-making. But research has not yet examined whether science literacy actually enables this, nor what skills it would need to encompass to do so. In this report, we address three questions to outline what it should mean to be science literate in today's world: 1) How should we conceptualize science literacy? 2) How can we achieve this science literacy? and 3) What can we expect science literacy's most important outcomes to be? If science literacy is to truly enable people to become and stay informed (and avoid being misinformed) on complex science issues, it requires skills that span the "lifecycle" of science information. This includes how the scientific community produces science information, how media repackage and share the information, and how individuals encounter and form opinions on this information. Science literacy, then, is best conceptualized as encompassing three dimensions of literacy spanning the lifecycle: Civic science literacy, digital media science literacy, and cognitive science literacy. Achieving such science literacy, particularly for adults, poses many challenges and will likely require a structural perspective. Digital divides, in particular, are a major structural barrier, and community literacy and building science literacy into media and science communication are promising opportunities. We end with a discussion of what some of the beneficial outcomes could be-and, as importantly, will likely not be-of science literacy that furthers informed and critical engagement with science in democratic society.

Deference and decision-making in science and society: How deference to scientific authority goes beyond confidence in science and scientists to become authoritarianism.

Deference to scientific authority theoretically captures the belief that scientists and not publics should make decisions on science in society. Few studies examine deference, however, and none test this central theoretical claim. The result is deference is often conflated with concepts such as trust in scientists and belief in the authority of science. This study examines two claims key to conceptualizing deference: that deference (1) predicts anti-democratic views of decision-making and (2) relates to but is distinct from beliefs of science as authoritative knowledge. Analyzing US nationally representative data, we find deference to scientific authority does predict anti-democratic views, and this is its distinct conceptual value: trust in scientists and belief in science as authoritative knowledge strongly relate to deference, but both predict pro-democratic views, unlike deference. We discuss how these findings highlight deference as vital for understanding perceptions of science and societal decision-making and how we can better develop the concept.

What Do We (Not) Know About Global Views of Human Gene Editing? Insights and Blind Spots in the CRISPR Era.

As research on human applications of CRISPR advances, researchers, advisory bodies, and other stakeholder organizations continue calling for global public discourses and engagement to shape the development of human gene editing (HGE). Research that captures public views and tests ways for engaging across viewpoints is vital for facilitating these discourses. Unfortunately, such research lags behind advances in HGE research and applications. Here, we provide the first review of nationally representative public-opinion surveys focused on HGE to discuss limitations and remaining gaps, illustrating how these gaps hinder interpretation of existing studies. Rigorous research with proper methods for capturing representative public opinion of HGE is limited, especially in countries outside of the United States and on a global scale. The result is severely restricted understanding of even the surface level of public views concerning HGE. We identify broad areas where we need more and better research capturing public views, and describe how future surveys can help collect insights necessary for discourse and decision making on HGE.

Engagement present and future: Graduate student and faculty perceptions of social media and the role of the public in science engagement.

Interest in public engagement with science activities has grown in recent decades, especially engagement through social media and among graduate students. Research on scientists' views of engagement, particularly two-way engagement and engagement through social media, is sparse, particularly research examining graduate students' views. We compare graduate students and faculty in biological and physical sciences at a land-grant, research-intensive university in their views on engagement. We find that both groups overwhelmingly believe that public input in decision-making around science issues is important, and hold largely pro-engagement attitudes. Graduate students, however, have somewhat more optimistic views of engagement through social media and on the appropriateness of discussing science controversy on social media. We discuss implications for graduate education and future engagement.

Distinguishing scientific knowledge: The impact of different measures of knowledge on genetically modified food attitudes.

The impact of knowledge on public attitudes toward scientific issues remains unclear, due in part to ill-defined differences in how research designs conceptualize knowledge. Using genetically modified foods as a framework, we explore the impacts of perceived familiarity and factual knowledge, and the moderating roles of media attention and a food-specific attitudinal variable (food consciousness), in shaping these relationships. Based on the differential effects on "negative attitudes" toward genetically modified foods, we provide further evidence that the measures of knowledge are separate concepts and argue against a one-dimensional view of scientific knowledge. We discuss implications for understanding the relationship between knowledge and science attitudes.

National Academies of Sciences, Engineering, and Medicine report on genetically engineered crops influences public discourse.

In May 2016, the National Academies of Sciences, Engineering, and Medicine (NASEM) released the report "Genetically Engineered Crops: Experiences and Prospects," summarizing scientific consensus on genetically engineered crops and their implications. NASEM reports aim to give the public and policymakers information on socially relevant science issues. Their impact, however, is not well understood. This analysis combines national pre- and post-report survey data with a large-scale content analysis of Twitter discussion to examine the report's effect on public perceptions of genetically modified organisms (GMOs). We find that the report's release corresponded with reduced negativity in Twitter discourse and increased ambivalence in public risk and benefit perceptions of GMOs, mirroring the NASEM report's conclusions. Surprisingly, this change was most likely for individuals least trusting of scientific studies or university scientists. Our findings indicate that NASEM consensus reports can help shape public discourse, even in, or perhaps because of, the complex information landscape of traditional and social media.