Visions for the future of computing, such as those on Ubiquitous Computing or Tangible Interfaces, are highly cited and frequently used in teaching. Yet, we know little about the practical value of these visions for research on Human-Computer Interaction (HCI) or how HCI researchers engage with them individually and collectively. To address this gap, we conducted a survey with 172 HCI researchers. We identified key benefits and pitfalls as well as specific uses of visions by researchers. Researchers appreciate how visions guide us, drive us, and initiate new fields. Simultaneously, researchers acknowledge how visions create hype, restrict our creativity, and make us disregard real-world problems. Based on these insights, we derive tensions related to the pursuit of visions and discuss critical reading practices. Our paper offers a metascientific account of visions in the HCI field along with tools for critical reflection when engaging with them.
Drawing on infrastructure studies in HCI and CSCW, this paper introduces Protocol Futuring, a methodological framework that extends design futuring by foregrounding protocols—rules, standards, and coordination mechanisms—as the primary material of speculative inquiry. Rather than imagining discrete future artifacts, Protocol Futuring examines how protocol rules accumulate drift, jam, and other second-order effects over long temporal horizons. We demonstrate the method through a case study of Knowledge Futurama, a multi-team participatory workshop exploring millennial-scale knowledge preservation. Using a relay format in which teams inherited and reinterpreted partially formed designs, the workshop revealed how ambiguous handovers, adversarial reinterpretations, shifting cultural norms, and crisis dynamics transform protocols as they move across communities and epochs. The case shows how Protocol Futuring makes infrastructural politics and long-run consequences analytically visible. We discuss the method’s strengths, limitations, and implications for researchers investigating emergent sociotechnical systems whose impacts unfold over extended timescales.
Juniors enter as AI‑natives, seniors adapted mid‑career. AI is not just changing how engineers code–it is reshaping who holds agency across work and professional growth. We contribute junior–senior accounts on their usage of agentic AI through a three-phase mixed-methods study: ACTA combined with a Delphi process with 5 seniors, an AI-assisted debugging task with 10 juniors, and blind reviews of junior prompt histories by 5 more seniors. We found that agency in software engineering is primarily constrained by organizational policies rather than individual preferences, with experienced developers maintaining control through detailed delegation while novices struggle between over-reliance and cautious avoidance. Seniors leverage pre-AI foundational instincts to steer modern tools and possess valuable perspectives for mentoring juniors in their early AI-encouraged career development. From synthesis of results, we suggest three practices that focus on preserving agency in software engineering for coding, learning, and mentorship, especially as AI grows increasingly autonomous.
Computing's ubiquity and accumulation of capital have positioned modern tech giants to be key players in society's responses to crises. Fulfilling this potential, however, requires methods and incentives for the industry to meaningfully support communities (“community-industry partnerships”). This paper examines one such partnership: an effort to co-develop software with and for community health workers that began in 2020 with the COVID-19 pandemic. Our multi-year, ethnographic work explores how Agile development, the industry's standard development practice, delimits the possibilities of community participation. Analyzing the project's breakdowns, we find stakeholders aligned on goals but misaligned on three key tensions: whose expertise takes primacy, how disagreements are surfaced, and how accountability is enacted. We propose reimagining these tensions as guiding principles for stronger partnerships: yielding to community expertise, embracing disagreement as productive friction, and ensuring accountability through realignment. Our framework offers guidance for community-industry partnerships to enhance societal resilience, in crises and beyond.
In the future of work discourse, AI is touted as the ultimate productivity amplifier. Yet, beneath the efficiency gains lie subtle erosions of human expertise and agency. This paper shifts focus from the future of work to the future of workers by navigating the AI-as-Amplifier Paradox: AI's dual role as enhancer and eroder, simultaneously strengthening performance while eroding underlying expertise. We present a year-long study on longitudinal use of AI in a high-stakes workplace among cancer specialists. Initial operational gains hid "intuition rust'': the gradual dulling of expert judgment. These asymptomatic effects evolved into chronic harms, such as skill atrophy and identity commoditization. Building on these findings, we offer a framework for dignified Human-AI interaction co-constructed with professional knowledge workers facing AI-induced skill erosion without traditional labor protections. The framework operationalizes sociotechnical immunity through dual-purpose mechanisms that serve institutional quality goals while building worker power to detect, contain, and recover from skill erosion, and preserve human identity.Evaluated across healthcare and software engineering, our work takes a foundational step toward dignified human-AI interaction futures by balancing productivity with preservation of human expertise.
This paper examines how infrastructures organize time in ways that unevenly distribute burden, access, and opportunity across communities. We draw on two ethnographic cases: eviction case filings in Atlanta, part of the state’s legal and housing governance infrastructure, and a sexual healthcare intervention in Chicago, situated within the city’s public health services. We advance HCI’s engagement with temporality by demonstrating how infrastructures sediment layers of political, social, and technical decisions over time. We conceptualize infrastructures as stratified formations where earlier allocations of power become materially and procedurally embedded, configuring present-day experiences of public systems. We define \emph{temporal arrangements} as the patterned ways infrastructures shape and allocate time, producing unequal demands on who waits, who moves, and who must continually adjust. We describe two temporal arrangements—\emph{compression} and \emph{gaps}—to show how systems structure and constrain access to care, support, and basic services. By linking inherited infrastructural logics to everyday temporal burdens, we offer HCI a framework for examining how inequities persist through time.
While generative AI promises to democratize creativity, we lack empirical understanding of how creative professionals begin using these systems. Through a 10-week longitudinal study following one artist's self-directed exploration, we ask three case-bounded questions: what interaction patterns emerged? What dynamics characterized sustainable co-creation for this artist? How might we evaluate successful integration in this case? Our findings from this case study reveal: (1) physical environments and material practices drove digital interaction; (2) specific temporal patterns emerged (short prompt bursts, consolidation periods, multi-day resurfacing cycles) and (3) productive discomfort and sustained tension marked successful sessions. These patterns suggest alternative design spaces worth exploring. We contribute: (1) four empirically-grounded design patterns (park-and-resurface, warm-up modes, affect-to-action bridges, comfort controls) that could be prototyped and tested; and (2) speculative provocations that challenge efficiency-first paradigms. This case study demonstrates that some users may benefit from approaches orthogonal to current design paradigms.