Structured dataset documentation shows little engagement with major reflexivity themes from FAccT literature, leading to a new codebook and extended datasheet questions.
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A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle
Canonical reference. 100% of citing Pith papers cite this work as background.
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Modeling recommender systems as control systems shows that time-optimized fairness interventions can improve overall long-term performance rather than merely trading off against utility.
Generative AI boosts attackers' ability to create harmful content at scale while also enabling defenders to detect threats, support users, and improve moderation processes.
A budget split intervention reduces gender skew in online ad delivery by incorporating users with unknown demographics alongside targeted inferred-gender groups.
Topic modeling of 6520 AI papers reveals divergent and sometimes contradictory conceptions of bias within the research community.
citing papers explorer
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Evaluating Structured Documentation as a Tool for Reflexivity in Dataset Development
Structured dataset documentation shows little engagement with major reflexivity themes from FAccT literature, leading to a new codebook and extended datasheet questions.
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Recommender Systems as Control Systems
Modeling recommender systems as control systems shows that time-optimized fairness interventions can improve overall long-term performance rather than merely trading off against utility.
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How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape
Generative AI boosts attackers' ability to create harmful content at scale while also enabling defenders to detect threats, support users, and improve moderation processes.
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Into the Unknown: Accounting for Missing Demographic Data when Mitigating Ad Delivery Skew
A budget split intervention reduces gender skew in online ad delivery by incorporating users with unknown demographics alongside targeted inferred-gender groups.
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Navigating the muddy waters of bias in artificial intelligence research: Understanding divergent meanings and conceptions
Topic modeling of 6520 AI papers reveals divergent and sometimes contradictory conceptions of bias within the research community.
- LLM Harms: A Taxonomy and Discussion