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20242026
most citedUnequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CY20261 cited

Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI

Holli Sargeant, Mackenzie Jorgensen, Arina Shah +3

Uncertainty in artificial intelligence (AI) predictions raises pressing legal and ethical questions for AI-assisted decision-making. This article examines two uncertainty-based alg…

cs.CY2026

Prompt Governance? On Governing Technologies Governed by Natural Language

Anna Neumann, Holli Sargeant, Jatinder Singh

Generative artificial intelligence (GenAI) is increasingly operated by natural language instructions (prompts). Across the pipeline, stakeholders designate various forms, e.g. end-…

cs.CY2025

Large Language Models' Complicit Responses to Illicit Instructions across Socio-Legal Contexts

Xing Wang, Huiyuan Xie, Yiyan Wang +7

Large language models (LLMs) are now deployed at unprecedented scale, assisting millions of users in daily tasks. However, the risk of these models assisting unlawful activities re…

cs.CY2025

Formalising Anti-Discrimination Law in Automated Decision Systems

Holli Sargeant, MÃ¥ns Magnusson

Algorithmic discrimination is a critical concern as machine learning models are used in high-stakes decision-making in legally protected contexts. Although substantial research on…

cs.CL2025

Topic Classification of Case Law Using a Large Language Model and a New Taxonomy for UK Law: AI Insights into Summary Judgment

Holli Sargeant, Ahmed Izzidien, Felix Steffek

This paper addresses a critical gap in legal analytics by developing and applying a novel taxonomy for topic classification of summary judgment cases in the United Kingdom. Using a…

cs.HC2024

Modulating Language Model Experiences through Frictions

Katherine M. Collins, Valerie Chen, Ilia Sucholutsky +6

Language models are transforming the ways that their users engage with the world. Despite impressive capabilities, over-consumption of language model outputs risks propagating unch…