Avoiding Side Effects By Considering Future Tasks. - Victoria Krakovna; Laurent Orseau; Richard Ngo; Miljan Martic; Shane Legg (NeurIPS, 2020)

REALab: An Embedded Perspective on Tampering. - Ramana Kumar; Jonathan Uesato; Richard Ngo; Tom Everitt; Victoria Krakovna; Shane Legg (CoRR, 2020)

Avoiding Tampering Incentives in Deep RL via Decoupled Approval. - Jonathan Uesato; Ramana Kumar; Victoria Krakovna; Tom Everitt; Richard Ngo; Shane Legg (CoRR, 2020)

Automating Supervision of AI Delegates. - Jaan Tallinn; Richard Ngo (The Cambridge Handbook of Responsible Artificial Intelligence, 2022)

The alignment problem from a deep learning perspective. - Richard Ngo (CoRR, 2022)

The Alignment Problem from a Deep Learning Perspective. - Richard Ngo; Lawrence Chan; Sören Mindermann (ICLR, 2024)

Computing Power and the Governance of Artificial Intelligence. - Girish Sastry; Lennart Heim; Haydn Belfield; Markus Anderljung; Miles Brundage; Julian Hazell; Cullen O'Keefe; Gillian K. Hadfield; Richard Ngo; Konstantin Pilz; George Gor; Emma Bluemke; et al. (CoRR, 2024)

On Defining Neural Averaging. - Su Hyeong Lee; Richard Ngo (CoRR, 2025)