Why "AI Incidents"?
Intelligent systems are currently prone to unforeseen and often dangerous failures when they are deployed to the real world. Much like the transportation sector before it (e.g., FAA and FARS) and more recently computer systems, intelligent systems require a repository of problems experienced in the real world so that future researchers and developers may mitigate or avoid repeated bad outcomes.
What is an Incident?
The initial set of more than 1,000 incident reports have been intentionally broad in nature. Current examples include,
- An autonomous car kills a pedestrian
- A trading algorithm causes a market "flash crash" where billions of dollars transfer between parties
- A facial recognition system causes an innocent person to be arrested
You are invited to explore the incidents collected to date, view the complete listing, and submit additional incident reports. Researchers are invited to review our working definition of AI incidents.
Current and Future Users
- Current Users include system architects, industrial product developers, public relations managers, researchers, and public policy researchers. These users are invited to use the Discover application to proactively discover how recently deployed intelligent systems have produced unexpected outcomes in the real world. In so doing, they may avoid making similar mistakes in their development.
- Future Uses will evolve through the code contributions of the open source community, including additional database summaries and taxonomies.
When Should You Report an Incident?
When in doubt of whether an event qualifies as an incident, please submit it! This project is intended to converge on a shared definition of "AI Incident" through exploration of the candidate incidents submitted by the broader community.