AI Control

  • Responding to and Recovering from AI System Incidents

    A significant portion of businesses lack clarity on how to halt or diagnose AI system failures, posing a growing risk of irreversible damage. ISACA research reveals most digital trust professionals cannot confidently intervene in AI emergencies or identify responsible parties for AI-induced harm. Experts stress the need for structured AI management, treating AI as “digital employees” with clear ownership and immediate override capabilities, rather than a purely technical issue. Effective governance and accountability are crucial for safe AI scaling.

    2026年4月20日
  • The AI Risks That Could Plunge Business into Chaos

    AI’s rapid integration into business creates a risk of systems exceeding human comprehension and control. As AI becomes more complex, unforeseen errors can emerge and propagate silently, leading to significant disruptions and compliance issues. Experts stress the imperative of establishing robust control mechanisms, including “kill switches,” and diligent oversight to manage AI’s unpredictable behavior, especially given the pressure for rapid deployment. A disciplined approach that embraces learning from failures is crucial for navigating this evolving landscape.

    2026年3月1日