Ethics and Society Newsletter #6: Building Better AI: The Importance of Data Quality

Ethics Practices in AI Development: An Empirical Study Across Roles and Regions

arXiv:2508. 09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks posed by these technologies.

Let's talk about biases in machine learning! Ethics and Society Newsletter #2

The crucial human component in computing and AI

The MIT Ethics of Computing Research Symposium brought together experts and researchers working at the heart of ethical and social impact in technology.

Can Data Work be Reparative?

arXiv:2606. 09408v1 Announce Type: cross Abstract: We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and benchmarking online safety systems.

Improving verifiability in AI development

We’ve contributed to a multi-stakeholder report by 58 co-authors at 30 organizations, including the Centre for the Future of Intelligence, Mila, Schwartz Reisman Institute for Technology and Society, Center for Advanced Study in the Behavioral Sciences, and Center for Security and Emerging Technologies. This report describes 10 mechanisms to improve the verifiability of claims made about AI systems.

AI Policy @🤗: Response to the U.S. NTIA's Request for Comment on AI Accountability