The responsible AI (RAI) community has introduced numerous processes and artifacts---such as Model Cards, Transparency Notes, and Data Cards---to facilitate transparency and support the governance of AI systems. While originally designed to scaffold and document AI development processes in technology companies, these artifacts are becoming central components of regulatory compliance under recent regulations such as the EU AI Act. Much of the existing literature has focussed primarily on the design of new RAI artifacts, or an examination of their use by practitioners within technology companies. However, as RAI artifacts begin to play key roles in enabling external oversight, it becomes critical to understand how stakeholders---particularly stakeholders situated outside of technology companies who govern and audit industry AI deployments---perceive the efficacy of RAI artifacts. In this study, we conduct semi-structured interviews and design activities with 19 government, legal, and civil society stakeholders who inform policy and advocacy around responsible AI efforts. While participants believe that RAI artifacts are a valuable contribution to the RAI ecosystem, many have concerns around their potential unintended and longer-term impacts on actors outside of technology companies (e.g., downstream end-users, policymakers, civil society stakeholders). We organized these beliefs into four barriers that help explain how RAI artifacts may (inadvertently) reconfigure power relations across civil society, government, and industry, impeding civil society and legal stakeholders' ability to protect downstream end-users from potential AI harms. Participants envision how structural changes, along with changes in how RAI artifacts are designed, used, and governed, could help re-direct the role and impacts of artifacts in the RAI ecosystem. Drawing on these findings, we discuss research and policy implications for RAI artifacts.

Calls for engagement with the public in Artificial Intelligence (AI) research, development, and governance are increasing, leading to the use of surveys to capture people's values, perceptions, and experiences related to AI. In this paper, we critically examine the state of human participant surveys associated with these topics. Through both a reflexive analysis of a survey pilot spanning six countries and a systematic literature review of 44 papers featuring public surveys related to AI, we explore prominent perspectives and methodological nuances associated with surveys to date. We find that public surveys on AI topics are vulnerable to specific Western knowledge, values, and assumptions in their design, including in their positioning of ethical concepts and societal values, lack sufficient critical discourse surrounding deployment strategies, and demonstrate inconsistent forms of transparency in their reporting. Based on our findings, we distill provocations and heuristic questions for our community, to recognize the limitations of surveys for meeting the goals of engagement, and to cultivate shared principles to design, deploy, and interpret surveys cautiously and responsibly.

People are increasingly introduced to each other offline thanks to online platforms that make algorithmically-mediated introductions between their users. Such platforms include dating apps (e.g., Tinder) and in-person gig work websites (e.g., TaskRabbit, Care.com). Protecting the users of these online-offline systems requires answering calls from prior work to consider 'post-digital' orientations of safety: shifting from traditional technological security thinking to consider algorithm-driven consequences that emerge throughout online and offline contexts rather than solely acknowledging online threats. To support post-digital safety in platforms that make algorithmically-mediated offline introductions (AMOIs), we apply a mixed-methods approach to identify the core harms that AMOI users experience, the protective safety behaviors they employ, and the prevalence of those behaviors. First, we systematically review existing work (n=93), synthesizing the harms that threaten AMOIs and the protective behaviors people employ to combat these harms. Second, we validate prior work and fill gaps left by primarily qualitative inquiry through a survey of respondents' definitions of safety in AMOI and the prevalence and implementation of their protective behaviors. We focus on two exemplar populations who engage in AMOIs: online daters (n=476) and in-person gig workers (n=451). We draw on our systematization and prevalence data to identify several directions for designers and researchers to reimagine defensive tools to support safety in AMOIs.

This paper presents a comparative legislative analysis that critically examines the precursors and implementation of online safety legislation on societies in the Global South, using the Caribbean as a focal case study. The online communities that we engage with foster greater human connections, serve as platforms to promote business services, and have become central in public discourse worldwide. Consequently, governance has emerged as a vital approach to maintain healthy digital environments and address the rise of socio-technical harms flowing from online communities. This study employs a two-tiered analytical approach to scrutinize the legislative frameworks established in the Caribbean and to surface variations in policy priorities, approaches to regulation, levels of enforcement, and identify power dynamics that impact the execution of said regulation. The findings of this work shed light on the need for additional work in social computing that delves into the societal ramifications of existing governance structures, rather than solely focusing on efforts to inform and develop new legislation. Through the lens of the Caribbean's case study, this paper provides valuable insights for policymakers and stakeholders in the region seeking to optimize the impact of online safety laws on their societies while highlighting contextually appropriate governance solutions that acknowledge the unique cultural, political, and socioeconomic contexts of the Global South.

Online harassment is a global problem. This article examines perceptions of harm and preferences for remedies associated with online harassment with nearly 4000 participants in 14 countries around the world. The countries in this work reflect a range of identities and values, with a focus on those outside of North American and European contexts. Results show that perceptions of harm are higher among participants from all countries studied compared to the United States. Non-consensual sharing of sexual photos is consistently rated as harmful in all countries, while insults and rumors are perceived as more harmful in non-U.S. countries, especially harm to family reputation. Lower trust in other people and lower trust in sense of safety in one’s neighborhood correlate with increased perceptions of harm of online harassment. In terms of remedies, participants in most countries prefer monetary compensation, apologies, and publicly revealing offender’s identities compared to the U.S. Social media platform design and policy must consider regional values and norms, which may depart from U.S. centric-approaches.

Little is known about non-Western social media users’ motivations for adopting behaviors that protect them against pervasive threats to their privacy, security, and personal well-being. Drawing on Rogers’ Protection Motivation Theory (PMT), this survey study explores Caribbean people’s (N=551) perceptions of safety threats and the factors contributing to their intention to adopt protective behaviors. Our analysis revealed that prior victimization was associated with increased perceptions of vulnerability and severity of harms, which, in turn, influenced elevated safety protection behaviors. For harassment-related harms in particular, participants’ trust in social media sites increased their intention to adopt protective behaviors. We observe significant country-to-country differences, which we contextualize through interviews with experts throughout the region. Our findings provide a new understanding of users’ mental models, behaviors, and attitudes with respect to online safety. We conclude by discussing theoretical and practical implications and outline opportunities for the design of inclusive and culturally-aware safety tools.

Social media platforms aspire to create online experiences where users can participate safely and equitably. However, women around the world experience widespread online harassment, including insults, stalking, aggression, threats, and non-consensual sharing of sexual photos. This article describes women's perceptions of harm associated with online harassment and preferred platform responses to that harm. We conducted a survey in 14 geographic regions around the world (N = 3,993), focusing on regions whose perspectives have been insufficiently elevated in social media governance decisions (e.g. Mongolia, Cameroon). Results show that, on average, women perceive greater harm associated with online harassment than men, especially for non-consensual image sharing. Women also prefer most platform responses compared to men, especially removing content and banning users; however, women are less favorable towards payment as a response. Addressing global gender-based violence online requires understanding how women experience online harms and how they wish for it to be addressed. This is especially important given that the people who build and govern technology are not typically those who are most likely to experience online harms.

Chatbots or conversational recommenders have gained increasing popularity as a new paradigm for Recommender Systems (RS). Prior work on RS showed that providing explanations can improve transparency and trust, which are critical for the adoption of RS. Their interactive and engaging nature makes conversational recommenders a natural platform to not only provide recommendations but also justify the recommendations through explanations. The recent surge of interest inexplainable AI enables diverse styles of justification, and also invites questions on how styles of justification impact user perception. In this article, we explore the effect of “why” justifications and “why not” justifications on users’ perceptions of explainability and trust. We developed and tested a movie-recommendation chatbot that provides users with different types of justifications for the recommended items. Our online experiment ( n = 310) demonstrates that the “why” justifications (but not the “why not” justifications) have a significant impact on users’ perception of the conversational recommender. Particularly, “why” justifications increase users’ perception of system transparency, which impacts perceived control, trusting beliefs and in turn influences users’ willingness to depend on the system’s advice. Finally, we discuss the design implications for decision-assisting chatbots.

Abstract Virtual Private Networks (VPNs) can help people protect their privacy. Despite this, VPNs are not widely used among the public. In this survey study about the adoption and usage of VPNs, we investigate people’s motivation to use VPNs and the barriers they encounter in adopting them. Using data from 90 technologically savvy participants, we find that while nearly all (98%; 88) of the participants have knowledge about what VPNs are, less than half (42%; 37) have ever used VPNs primarily as a privacy-enhancing technology. Of these, 18% (7) abandoned using VPNs while 81% (30) continue to use them to protect their privacy online. In a qualitative analysis of survey responses, we find that people who adopt and continue to use VPNs for privacy purposes are primarily motivated by emotional considerations, including the strong desire to protect their privacy online, wide fear of surveillance and data tracking not only from Internet service providers (ISPs) but also governments and Internet corporations such as Facebook and Google. In contrast, people who are mainly motivated by practical considerations are more likely to abandon VPNs, especially once their practical need no longer exists. These people cite their access to alternative technologies and the effort required to use a VPN as reasons for abandonment. We discuss implications of these findings and provide suggestions on how to maximize adoption of privacy-enhancing technologies such as VPNs, focusing on how to align them with people’s interests and privacy risk evaluation.

Abstract Smartphone users are often unaware of mobile applications’ (“apps”) third-party data collection and sharing practices, which put them at higher risk of privacy breaches. One way to raise awareness of these practices is by providing unobtrusive but pervasive visualizations that can be presented in a glanceable manner. In this paper, we applied Wogalter et al.’s Communication-Human Information Processing model (C-HIP) to design and prototype eight different visualizations that depict smartphone apps’ data sharing activities. We varied the granularity and type (i.e., data-centric or app-centric) of information shown to users and used the screensaver/lock screen as a design probe. Through interview-based design probes with Android users (n=15), we investigated the aspects of the data exposure visualizations that influenced users’ comprehension and privacy awareness. Our results shed light on how users’ perceptions of privacy boundaries influence their preference regarding the information structure of these visualizations, and the tensions that exist in these visualizations between glanceability and granularity. We discuss how a pervasive, soft paternalistic approach to privacy-related visualization may raise awareness by enhancing the transparency of information flow, thereby, unobtrusively increasing users’ understanding of data sharing practices of mobile apps. We also discuss implications for privacy research and glanceable security.

Traditionally, recommender systems are built with the goal of aiding users' decision-making process by extrapolating what they like and what they have done to predict what they want next. However, in attempting to personalize the suggestions to users' preferences, these systems create an isolated universe of information for each user, which may limit their perspectives and promote complacency. In this paper, we describe our research plan to test a novel approach to recommender systems that goes beyond "good recommendations" that supports user aspirations and exploration.

Every day, we are confronted with an abundance of decisions that require us to choose from a seemingly endless number of choice options. Recommender systems are supposed to help us deal with this formidable task, but some scholars claim that these systems instead put us inside a "Filter Bubble" that severely limits our perspectives. This paper presents a new direction for recommender systems research with the main goal of supporting users in developing, exploring, and understanding their unique personal preferences.