🔬 Research Summary by Fraser Mince, an independent machine learning researcher and a Senior Software Engineer at Waymark. [Original paper by Fraser Mince, Dzung Dinh, Jonas Kgomo, Neil Thompson, and Sara … [Read more...] about The Grand Illusion: The Myth of Software Portability and Implications for ML Progress
Core Principles of Responsible AI
A Machine Learning Challenge or a Computer Security Problem?
🔬 Research Summary by Ilia Shumailov, a Ph.D. in Computer Science from the University of Cambridge, specializing in Machine Learning and Computer Security. During the PhD under the supervision of Prof Ross Anderson, Ilia … [Read more...] about A Machine Learning Challenge or a Computer Security Problem?
Designing Fiduciary Artificial Intelligence
🔬 Research Summary by David Shekman , a third-year law student at Northwestern University Pritzker School of Law, will be practicing in San Francisco upon graduation, and is an avid data scientist. [Original … [Read more...] about Designing Fiduciary Artificial Intelligence
Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising
🔬 Research Summary by Michelle S. Lam , a Computer Science Ph.D. student at Stanford University in the Human-Computer Interaction Group, where she builds systems that empower everyday users to actively reshape the design … [Read more...] about Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising
Melting contestation: insurance fairness and machine learning
🔬 Research Summary by Laurence Barry and Arthur Charpentier. Laurence Barry is an independent actuary and a researcher at PARI (Programme de Recherche sur l’Appréhension des Risques et des Incertitudes, ENSAE/ … [Read more...] about Melting contestation: insurance fairness and machine learning