Inside the Incident is a new video series where Andrew Burt talks with Sean McGregor, founder and executive director of the AI Incident Database, about real-life AI incidents in the news. In our second episode, we break down an incident where a security robot's navigation system led it straight into a fountain, and what it reveals about the challenges of autonomous AI today.
Agency comes with responsibility. This security robot was given autonomy to patrol public spaces and make navigation decisions independently. Sound familiar? That's exactly what we're doing when we deploy AI agents to make decisions without human oversight. The fundamental challenge hasn't changed, however, the scale and complexity have increased.
Edge cases are everywhere. The robot wasn't trained to recognize a fountain as a hazard. When we evaluate AI systems in controlled environments, we often miss how they'll behave in unpredictable real-world scenarios. If your organization is deploying AI agents, ask yourself: have you accounted for unintended scenarios?
AI governance isn't starting from zero. This incident took place in 2017. Many of today's biggest AI governance challenges—bias, privacy, safety, autonomous decision-making—have precedents. Organizations that learn from past incidents, both successes and failures, gain a significant advantage in managing current risks.
As agentic AI deployment accelerates, companies need governance systems that can handle autonomous decision-making at scale. The question isn't whether edge cases will occur; it's whether you'll catch them before they become incidents.
Want to discuss how Luminos helps companies scale AI governance? Book a demo with our team.
