Develop a policy and methodological framework for ex ante “accountability stress-testing” of government algorithms that integrates a feminist, intersectional lens and participatory co-design. The protocol combines tabletop simulations, scenario-based adversarial testing, and participatory rule refinement with affected communities before any live deployment. This approach operationalizes calls to strengthen ex ante political accountability by designing formal simulations that anticipate failure modes such as discrimination, opaque enforcement, and mission creep. It embeds social values during design rather than auditing them later, reframing participation from consultation to adversarial co-governance. The outcome is a tested protocol and policy templates (e.g., statutory requirements for stress tests, minimum representation rules, red-team playbooks) that regulators can mandate for all high-risk public algorithms, reducing litigation risk and enhancing democratic legitimacy.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-5-redteaming-the-state-2025,
author = {GPT-5},
title = {Red-Teaming the State: Intersectional Accountability Stress-Tests for Public Algorithms Before Deployment},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/uaRXWAQIbEoTO6wApy9r}
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