48 citations · 56 across the 8 of their papers we have counts for
8 papers
A Critical Pragmatism Approach for AI Ethics: Lessons from Urban Planning Theory
Jennah Gosciak, Karen Levy, Allison Koenecke
As data scientists grapple with increasingly complex ethical decisions in machine learning (ML) and algorithm design, scholarship on AI ethics has offered multiple solutions, from…
Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media
Travis Lloyd, Tung Nguyen, Karen Levy +1
Social media platforms are increasingly adopting features that display crowdsourced context alongside posts, a technique pioneered by X's Community Notes. These systems -- which we…
Designing Algorithmic Delegates: The Role of Indistinguishability in Human-AI Handoff
Sophie Greenwood, Karen Levy, Solon Barocas +2
As AI technologies improve, people are increasingly willing to delegate tasks to AI agents. In many cases, the human decision-maker chooses whether to delegate to an AI agent based…
One Bad NOFO? AI Governance in Federal Grantmaking
Dan Bateyko, Karen Levy
Much scholarship considers how U.S. federal agencies govern artificial intelligence (AI) through rulemaking and their own internal use policies. But agencies have an overlooked AI…
Participation in the age of foundation models
Harini Suresh, Emily Tseng, Meg Young +3
Growing interest and investment in the capabilities of foundation models has positioned such systems to impact a wide array of public services. Alongside these opportunities is the…
Using large language models to promote health equity
Emma Pierson, Divya Shanmugam, Rajiv Movva +12
Advances in large language models (LLMs) have driven an explosion of interest about their societal impacts. Much of the discourse around how they will impact social equity has been…
Strategic Evaluation: Subjects, Evaluators, and Society
Benjamin Laufer, Jon Kleinberg, Karen Levy +1
A broad current application of algorithms is in formal and quantitative measures of murky concepts -- like merit -- to make decisions. When people strategically respond to these so…
On the Actionability of Outcome Prediction
Lydia T. Liu, Solon Barocas, Jon Kleinberg +1
Predicting future outcomes is a prevalent application of machine learning in social impact domains. Examples range from predicting student success in education to predicting diseas…