Politics of Adversarial Machine Learning

This is a 2020 research paper (not a software tool) that synthesizes Science and Technology Studies (STS) with machine learning security. While intellectually significant in its niche, it lacks a technical moat, codebase, or active community engagement on GitHub. Its value is purely academic and policy-oriented, presenting zero competition to frontier lab engineering, though its findings may inform their safety/alignment policies.