Recent advances in AI have significantly changed people’s lives, yet sometimes their inherent risks deter adoption. Risk preference and perception in AI remain understudied. We surveyed 406 participants to explore how risk preferences, risk perceptions, and socioeconomic variables influence AI adoption in high-risk (autonomous vehicles) and low-risk (recommendation algorithms) contexts. Socioeconomic groups overall show different levels of risk aversion and seeking across scenarios. For high-risk autonomous driving, the risk aspects tend to be centralized. In contrast, the risk aspects of recommendation algorithms are more dispersed. These findings indicate a prevailing inclination among individuals toward caution regarding risks, highlighting the need for government policies that distinguish high- and low-risk AI. Regulations for autonomous vehicles should be strengthened to ensure safety and clarify liability, while those for recommendation algorithms should be expanded to enhance public risk awareness. This study aims to support policymakers toward more targeted AI risk management.

Abstract Misinformation is a complex and urgent sociotechnical problem that requires meaningful governance, in addition to technical efforts aimed at detection or classification and intervention or literacy efforts aimed at promoting awareness and identification. This review draws on interdisciplinary literature—spanning information science, computer science, management, law, political science, public policy, journalism, communications, psychology, and sociology—to deliver an adaptable, descriptive governance model synthesized from past scholarship on the governance of misinformation. Crossing disciplines and contexts of study and cases, we characterize: the complexity and impact of misinformation as a governance challenge, what has been managed and governed relative to misinformation, the institutional structure of different governance parameters, and empirically identified sources of success and failure in different governance models. Our approach to support this review is based on systematic, structured literature review methods to synthesize and compare insights drawn from conceptual, qualitative, and quantitative empirical works published in or translated into English from 1991 to the present. This review contributes a model for misinformation governance research, an agenda for future research, and recommendations for contextually‐responsive and holistic governance.

Abstract Privacy‐enhancing technologies that incorporate a socially meaningful conception of privacy, one that meets people's expectations and is ethically defensible, need to factor in contextual privacy norms and information governance as part of their design. This involves understanding what information handling practices users deem acceptable, what factors influence users' perceptions and behaviors, and how informational norms evolve. In this paper, we present GKC‐CI, a unifying framework for examining contextual privacy norms and information governance in a given context to help structure research inquiries around these questions.

Abstract Privacy expectations during disasters differ significantly from nonemergency situations. This paper explores the actual privacy practices of popular disaster apps, highlighting location information flows. Our empirical study compares content analysis of privacy policies and government agency policies, structured by the contextual integrity framework, with static and dynamic app analysis documenting the personal data sent by 15 apps. We identify substantive gaps between regulation and guidance, privacy policies, and information flows, resulting from ambiguities and exploitation of exemptions. Results also indicate gaps between governance and practice, including the following: (a) Many apps ignore self‐defined policies; (b) while some policies state they “might” access location data under certain conditions, those conditions are not met as 12 apps included in our study capture location immediately upon initial launch under default settings; and (c) not all third‐party data recipients are identified in policy, including instances that violate expectations of trusted third parties.

The prevalence of sites in which users can contribute content increases ordinary citizens' participation in emerging forms of knowledge sharing. This article investigates the practices associated with the roles of participants who actively contribute to the coproduction of knowledge in three online communities and how these roles differ in controversial and noncontroversial threads. The Measles, Mumps, and Rubella (MMR) vaccine was selected as a contentious scientific topic because of persistent belief about an alleged link between the vaccine and autism. Contributions to three online communities that engage mothers with young children were analyzed to identify participant roles. No consistent roles were evident in noncontroversial threads, but the role of mediator consistently appeared in controversial threads in all three communities. This study helps to articulate the roles played in online communities that engage in knowledge collaboration. The variety of roles in online communities has implications for both the study for practice and the design of information technologies.

Online trolling has become increasingly prevalent and visible in online communities. Perceptions of and reactions to trolling behaviors varies significantly from one community to another, as trolling behaviors are contextual and vary across platforms and communities. Through an examination of seven trolling scenarios, this article intends to answer the following questions: how do trolling behaviors differ across contexts; how do perceptions of trolling differ from case to case; and what aspects of context of trolling are perceived to be important by the public? Based on focus groups and interview data, we discuss the ways in which community norms and demographics, technological features of platforms, and community boundaries are perceived to impact trolling behaviors. Two major contributions of the study include a codebook to support future analysis of trolling and formal concept analysis surrounding contextual perceptions of trolling.