Using causal models in heterogeneous information fusion to detect terrorists. - Paul K. Davis; David Manheim; Walter L. Perry; John Hollywood (WSC, 2015)

Categorizing Variants of Goodhart's Law. - David Manheim; Scott Garrabrant (CoRR, 2018)

Overoptimization Failures and Specification Gaming in Multi-agent Systems. - David Manheim (CoRR, 2018)

Oversight of Unsafe Systems via Dynamic Safety Envelopes. - David Manheim (CoRR, 2018)

Multiparty Dynamics and Failure Modes for Machine Learning and Artificial Intelligence. - David Manheim (Big Data Cogn. Comput., 2019)

Forecasting AI Progress: A Research Agenda. - Ross Gruetzemacher; Florian Dorner; Niko Bernaola-Alvarez; Charlie Giattino; David Manheim (CoRR, 2020)

Testing, tracing and isolation in compartmental models. - Simone Sturniolo; William Waites; Tim Colbourn; David Manheim; Jasmina Panovska-Griffiths (PLoS Comput. Biol., 2021)

Arguments about Highly Reliable Agent Designs as a Useful Path to Artificial Intelligence Safety. - Issa Rice; David Manheim (CoRR, 2022)

Modeling Transformative AI Risks (MTAIR) Project - Summary Report. - Sam Clarke; Ben Cottier; Aryeh Englander; Daniel Eth; David Manheim; Samuel Dylan Martin; Issa Rice (CoRR, 2022)

Building less-flawed metrics: Understanding and creating better measurement and incentive systems. - David Manheim (Patterns, 2023)

The Necessity of AI Audit Standards Boards. - David Manheim; Sammy Martin; Mark Bailey; Mikhail Samin; Ross Greutzmacher (CoRR, 2024)

Limits of Safe AI Deployment: Differentiating Oversight and Control. - David Manheim; Aidan Homewood (CoRR, 2025)