21 citations · 26 across the 6 of their papers we have counts for
6 papers
Enabling the AI Revolution in Healthcare
Mona Singh, Katie Siek, David Danks +5
The transformative potential of AI in healthcare - including better diagnostics, treatments, and expanded access - is currently limited by siloed patient data across multiple syste…
Trustworthiness in Stochastic Systems: Towards Opening the Black Box
Jennifer Chien, David Danks
AI systems are increasingly tasked to complete responsibilities with decreasing oversight. This delegation requires users to accept certain risks, typically mitigated by perceived…
Future of Pandemic Prevention and Response CCC Workshop Report
David Danks, Rada Mihalcea, Katie Siek +3
This report summarizes the discussions and conclusions of a 2-day multidisciplinary workshop that brought together researchers and practitioners in healthcare, computer science, an…
Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation
Jennifer Chien, David Danks
Algorithmic harms are commonly categorized as either allocative or representational. This study specifically addresses the latter, focusing on an examination of current definitions…
Commercial AI, Conflict, and Moral Responsibility: A theoretical analysis and practical approach to the moral responsibilities associated with dual-use AI technology
Daniel Trusilo, David Danks
This paper presents a theoretical analysis and practical approach to the moral responsibilities when developing AI systems for non-military applications that may nonetheless be use…
Fairness Vs. Personalization: Towards Equity in Epistemic Utility
Jennifer Chien, David Danks
The applications of personalized recommender systems are rapidly expanding: encompassing social media, online shopping, search engine results, and more. These systems offer a more…