Stevie Chancellor

Knowledge-based institutions, such as libraries and archives, are ripe venues for knowledge gaps, defined as systemic disparities in content coverage or participation. The core problem is not that knowledge gaps exist, but that they often further disempower already marginalized communities. By reinforcing systemic inequity, knowledge gaps are matters of justice. In this paper, we draw on critical scholarship about knowledge exclusion and take a design lens to a pressing instantiation: knowledge gaps on Wikipedia. We present findings from a two-day Wikipedia expert workshop focused on how knowledge gaps manifest in editors’ interactions with platform policy. Our core contribution is an empirically grounded argument that a more inclusive Wikipedia is one in which editors can acquire the skills to invoke, bend, and even break the platform policies that dictate encyclopedic content. To make this argument, we synthesize author testimony into (1) a problem space articulating contributing factors and (2) a two-dimensional solution space where policy engagement can be at odds with policy adherence. To illustrate this inclusive Wikipedia future, we present speculative prototypes along the engagement-adherence matrix. Finally, we discuss the epistemic implications of our work, returning to formative philosophies on knowledge inclusion and justice.

Context collapse—the flattening of multiple audience types into one on social media platforms—has been a crucial concept in social computing for over 15 years. It has been instrumental in informing and framing research, driving empirical experimentation, and shaping platform design interventions. However, the concept has not evolved alongside rapidly changing social media platforms and new forms of user engagement, and is itself conceptually ambiguous. In this paper, we retheorize context collapse by developing a grammar of its dimensions and potential applications for modern platforms. We introduce three dimensions of context for social media: the user, the platform, and the data/interaction. We then review well-known context collapses using our grammar and propose three novel examples of collapses on social media platforms. Our retheorization provides a necessary refresh of the concept of context collapse, aligning it with today’s social media platforms and offering a context grammar to enable more robust theorization and generative design potential.

Inclusion is important for meeting effectiveness, which is in turn central to organizational functioning. One way of improving inclusion in meetings is through feedback, but social dynamics make giving feedback difficult. We propose that AI agents can facilitate feedback exchange by being psychologically safer recipients, and we test this through a meeting system with an AI agent feedback mediator. When delivering feedback, the agent uses the Induced Hypocrisy Procedure, a social psychological technique that prompts behavior change by highlighting value-behavior inconsistencies. In a within-subjects lab study (n = 28), the agent made speaking times more balanced and improved meeting quality. However, a field study at a small consulting firm (n = 10) revealed organizational barriers that led to its use for personal reflection rather than feedback exchange. We contribute a novel sociotechnical system for feedback exchange in groups, and empirical findings demonstrating the importance of considering organizational barriers in designing AI tools for organizations.

As AI systems are increasingly adopted in high-stakes domains such as healthcare, autonomous driving, and criminal justice, their failures may threaten human safety and rights. Human oversight of AI systems is therefore critically important as a potential safeguard to prevent harmful consequences in high-risk AI applications. The global regulatory and policy landscape for AI governance remains understandably fragmented and diverse. While frameworks like the European AI Act require human oversight for high-risk AI systems, there is currently a lack of well-defined methodologies and conceptual clarity to operationalize such oversight effectively. Independent of policy and regulation, poorly designed oversight can create dangerous illusions of safety while obscuring accountability. This interdisciplinary workshop aims to bring together researchers from various disciplines, including AI, HCI, psychology, law, and policy, to address this critical gap. We will explore the following questions: (1) What are the greatest challenges to achieving effective human oversight of AI systems? (2) How can we design AI systems that enable meaningful human oversight? (3) How do we assign responsibilities to and support the various stakeholders involved in oversight? Through talks and interactive group discussions, participants will identify oversight challenges; examine stakeholder roles; discuss supporting tools, methods, and regulatory frameworks; and establish a collaborative research agenda. Our central goal is to further a roadmap that enables effective human oversight for the responsible deployment of AI in society.

Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design workshops with 21 participants diagnosed with mental illness about their interactions with social media platforms. We find that users develop cause-and-effect explanations, or folk theories, to understand their experiences with algorithmic curation. These folk theories highlight a breakdown in algorithmic design that we explain using the framework of entanglement, a phenomenon where there is a disconnect between users' actions and platform outcomes on an emotional level. Participants' designs to address entanglement and mitigate harms centered on contextualizing their engagement and restoring explicit user control on social media. The conceptualization of entanglement and the resulting design recommendations have implications for social computing and recommender systems research, particularly in evaluating and designing social media platforms that support users' mental well-being.