The European Union (EU) has spearheaded the regulation of artificial intelligence (AI) with the AI Act, which regulates AI systems based on the risks they pose to fundamental rights and other protected values. AI systems that pose unacceptable risks are prohibited, high-risk AI systems must comply with mandatory requirements, and minimal risk AI systems are encouraged—but not required—to adopt voluntary standards. Motivated by concerns that the AI Act may not reflect the public's opinions, we investigate how laypeople (N=1,421) assess 48 different AI systems concerning their risk and regulation. We find that people believe all 48 AI systems pose moderate levels of risk and should be regulated (albeit without outright prohibitions). Our findings challenge the AI Act's tiered approach, showing that people might support horizontal regulation requiring minimal standards for AI systems, and provide implications for developers seeking to develop AI aligned with public expectations.
Financial institutions are required by their governments to detect and deter criminal activity, commonly known as Anti-Money Laundering (AML). AML professionals use a constellation of software tools to facilitate this work; The design of these tools and the way they fit together can impact the effectiveness of an investigation and the amount of effort required. We conducted 15 semi-structured interviews of AML professionals and analyzed their responses using reflexive thematic analysis. The results reveal a breadth of socio-technical challenges that financial institutions face in implementing an AML system. Many AML systems fail to address all aspects of an institution’s workflow and lack necessary data leading users to follow manual processes and workarounds. These shortcomings provide opportunity for the use of ML/AI— based technologies. These results inform design considerations for AML systems, and add financial institutions to the empirical literature around designing and deploying collaborative systems for enterprise settings.
Artificial intelligence (AI) technologies are increasingly adopted into everyday life, with most investment and development concentrated in the U.S. In response to rapid AI integration and scant federal guidelines, U.S. states have formed AI committees charged with studying AI-related societal trade-offs. We analyzed the 18 existing state-level AI committee reports to understand how policymakers discuss AI-related benefits and risks. We then compared the risks surfaced by policymakers to an established taxonomy of AI risks aggregated from literature and examined how policymakers’ concerns align---or misalign---from those of HCI scholars. These insights provide important mileposts for shaping currently ongoing policy initiatives and future research. Our findings reveal important gaps: while committees invoke responsible AI, their framings often omit broader socio-technical concerns emphasized in HCI. We discuss opportunities for HCI to support socio-technical perspectives, employ participatory design, and close the gap between research and policy.
Biometric payment, i.e., biometric authentication implemented in digital payment systems, can reduce memory demands and streamline payment for older adults. However, older adults' perceptions and practices regarding biometric payment remain underexplored. We conducted semi-structured interviews with 22 Chinese older adults, including both users and non-users. Participants were motivated to use biometric payment due to convenience and perceived security. However, they also worried about loss of control due to its password-free nature and expressed concerns about biometric data security. Participants also identified desired features for biometric payment, such as lightweight and context-aware cognitive confirmation mechanisms to enhance user control. We outline recommendations for more accessible and informative digital financial services that better support older adults.
How do communities sustain public spaces when formal infrastructure fails? In Stanley, UK a post-industrial town facing infrastructural neglect and climate-related flooding, residents sustain their environment through micro-acts that formal participation metrics fail to capture. Through surveys, interviews and a diary study conducted in partnership with Wear Rivers Trust, a charity advancing Nature-based Solutions (NbS), we examine how communities perceive and enact care under conditions of environmental precarity and low institutional trust. We found that care practices are embedded in daily routines and social ties, shaped by both pride and frustration, and sustained through informal networks. We contribute: (1) empirical insights into everyday civic care as emotional, negotiated, and place-based; and (2) a framework of six design dimensions, embeddedness, visibility, reciprocity, autonomy with support, coordination without formalization, and frustration as data --- to guide HCI/CSCW in developing respectful, lightweight, and situated systems that amplify rather than replace community capacities.
Entrepreneurs in resource-constrained communities often lack time and support to translate ideas into actionable business plans. While generative AI promises assistance, most systems assume high digital literacy and overlook community infrastructures that shape adoption. We report on the community-centered design and deployment of BizChat, an AI-powered business planning tool, introduced across four workshops at a feminist makerspace in Pittsburgh. Through log data (N=30) and interviews (N=10), we examine how entrepreneurs build resilience through collective AI literacy development—encompassing adoption, adaptation, and refusal of AI. Our findings reveal that while BizChat lowered barriers to accessing capital by translating ideas into "business language," this ease raised questions about whether instant AI outputs undermine sensemaking essential to planning. We show how peer support helped entrepreneurs navigate this tension. We contribute design implications, including productive friction, communal scaffolds, and co-optability, for strengthening resilience amid technological change.
Mobile money (MoMo) services have increased access to financial services in low- and middle- income countries (LMICs). However, requirements to register SIM cards with a government-issued identification have left around 18% of users, most without IDs, banking under a third-party’s name. Through interviews with 72 urban and rural residents in Kenya and Tanzania, this study provides the first in-depth assessment of how third-party SIM cards are acquired and the challenges and workarounds that arise when using them for MoMo. We document how third-party SIM users use various intermediaries---friends, family, agents, and strangers---to access services and the effects of ID and account misuse by both third-party SIM users and intermediaries. We further outline the personal and systemic challenges that lead to the lack of IDs for SIM registration and discuss how digitization, now underway in both Kenya and Tanzania, should be approached to effectively address these barriers.