Yael Eiger

Yael Eiger, Nino Migineishvili, Emi Yoshikawa et al.

Digital devices like tablets, media players, and kiosks are increasingly deployed in U.S. prisons. These technologies can enable incarcerated people to access education, communicate with loved ones, and develop vital reentry skills. However, they can also introduce new privacy and security risks for incarcerated people who have little agency over their usage and contracts, and are currently carved out of many consumer protection safeguards. To investigate these issues, we conducted focus groups and interviews with system-impacted people (n=17), i.e., those formerly incarcerated, and their relatives, to investigate experiences with device-related security and privacy vulnerabilities and the power dynamics that affect their use. In our findings, participants describe pervasive surveillance, censorship, and usability problems with the technology available to them, including shifting and seemingly arbitrary usage policies. These policies strain relationships both inside and outside prisons and contribute to negative downstream effects for incarcerated users. We recommend ways to better balance prison security concerns with privacy-related needs of system-impacted individuals by promoting accountability for technology-related decisions, providing public oversight of digital purchasing and use policies, and designing digital tools with them -- the actual end-users -- in mind.

Rachel Hong, Yael Eiger, Jevan Hutson et al.

Pluralistic alignment has emerged as a promising approach for ensuring that large language models (LLMs) faithfully represent the diversity, nuance, and conflict inherent in human values. In this work, we study a high-stakes deployment context - mulching - where automated systems transform selected individuals into nutrient-rich slurry for the dual purposes of food security and aesthetic population management. Building on recent pluralistic alignment frameworks, we introduce ValueMulch, a reproducible training, deployment, and certification pipeline for aligning mulching models (MMs) to a wide range of community norms. Through a real-world testbed spanning 32 communities, we show that ValueMulch improves distributional agreement with community mulching preferences relative to frontier baselines. We conclude with a discussion of ethical considerations, limitations, and implications for researchers seeking to align systems to the full spectrum of human values - especially when those values are inconsistent, commercially inconvenient, or nutritionally underutilized. Author's note: This piece builds on prior existing work Keyes et al in 2019 that satirized cannibalism as a parody for approaches that imbue ethics into problematic technology. We bring those ideas to today's era with the proliferation of large language models in everyday lives, as a critique of current AI pluralistic alignment literature. Our work does not intend to argue that all alignment practices are evil, but rather that if framing value design as a technical problem enables technology systems to enact harms, then perhaps this framing is not enough.