Our approach to understanding and addressing AI harms (www.anthropic.com)

As AI systems grow increasingly powerful and integrated into critical domains, Anthropic has outlined an evolving framework to better understand and address the diverse harms AI can cause. Moving beyond solely catastrophic risks, their approach assesses potential impacts across multiple dimensions—physical, psychological, economic, societal, and individual autonomy—while factoring in likelihood, scale, affected groups, and mitigation feasibility. This comprehensive perspective aims to bring nuance and proportionality to harm management, balancing safety with usefulness in real-world applications. Key technical implications include sophisticated pre- and post-launch evaluations such as red teaming and adversarial testing, dynamic enforcement policies, and detection strategies to prevent misuse like fraud or disinformation. The framework also informs feature development and behavior tuning. For instance, in enabling AI to interact with computer interfaces, they closely analyze risks around financial software and communication tools to craft targeted safeguards without sacrificing utility. Similarly, adjustments in Claude 3.7 Sonnet’s response boundaries have reduced unnecessary refusals by 45% while maintaining protections, reflecting a more calibrated tradeoff between responsiveness and safety, particularly for vulnerable populations. Anthropic emphasizes that this harm assessment approach is a continuously evolving effort, open to collaboration from the broader AI community. Recognizing that future AI capabilities will introduce unforeseen challenges, they commit to refining these frameworks and methods to responsibly steward AI’s societal impacts as the technology advances.