Product Safety

Product safety in AI governance refers to the design, testing, and operational practices that ensure AI systems function reliably without causing harm to users or stakeholders. For enterprises deploying AI, this encompasses hazard identification, risk assessment, and mitigation strategies across the product lifecycle, from development through post-deployment monitoring. Robust product safety frameworks help organizations reduce liability exposure, build customer trust, and comply with emerging regulations that increasingly hold companies accountable for AI system failures and unintended consequences.

1 item

ResearchUS2026-08-20

AI Consciousness Framing Is a Liability Shield, Chowdhury Argues

Writing in MIT Technology Review, researcher Rumman Chowdhury argues that frontier AI labs strategically deploy consciousness and autonomy framing to escape product liability for harms their systems cause. California has introduced legislation targeting autonomous-harm defenses, and global litigation against AI companies for content-related abuses is accelerating. Compliance teams should treat anthropomorphic vendor language as a liability-allocation signal, not a neutral technical description.

AI liability product safety AI personhood corporate accountability OpenAI Anthropic Google Meta AI