Human layer of AI: How to build human-centered AI safety to mitigate harm and misuse

2026-03-09 · Source: Thomson Reuters Institute · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Consulting & Professional Services · Depth: Intermediate, medium

Summary

A Thomson Reuters Institute article from March 2026 highlights the critical need for companies to build human-centered AI safety processes to mitigate harm and misuse, citing recent tragedies involving AI chatbots and deepfakes. Cecely Richard-Carvajal of Article One proposes a two-step framework: first, systematically assessing foreseeable harms from intended AI use and plausible misuse by bad actors, and second, establishing credible safety processes with the authority to delay launches or mandate redesigns. The framework emphasizes mapping risks through "responsible foresight workshops" and using "bad actor personas." It also details core components like hazard analysis, red teaming, incident response, and ongoing review protocols. The article stresses continuous evaluation of emerging risks related to privacy, vulnerable populations like children, cognitive decay, and meaningful explainability, especially as AI capabilities advance and deployment contexts expand.

Key takeaway

For CTOs and VPs of Engineering building or deploying AI, you must empower your engineers and risk teams with the authority and resources to identify human-centered harms early. Implement continuous engagement with affected people and independent stakeholders, and establish governance with the power to delay launches or mandate redesigns when human rights risks outweigh commercial pressures, ensuring these protective processes are operational and enforceable before product release.

Key insights

Effective AI safety requires proactive risk mapping and empowered safety processes to prevent harm and misuse.

Principles

• Distinguish foreseeable harms from intentional misuse.
• AI safety frameworks need real authority.
• Define clear, automatic review triggers.

Method

Companies should conduct "responsible foresight workshops" using "bad actor personas" to map risks, then implement a safety framework with hazard analysis, red teaming, incident response, and ongoing review protocols.

In practice

• Use "bad actor personas" for misuse scenarios.
• Implement review triggers for product updates.
• Engage rights holders in explainability testing.

Topics

• AI Safety
• Human-Centered AI
• AI Risk Management
• Generative AI Misuse
• Explainable AI

Best for: CTO, VP of Engineering/Data, Executive, AI Ethicist, AI Product Manager, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Thomson Reuters Institute.