The AI Incident Database Catalogs AI Errors

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The threat Artificial Intelligence holds is unknown and many people are rightfully concerned about the potential harm that AI can cause. The AI Incident Databaseo help us as a society to think through how we should regulate AIs by tracking any problematic issue that has been raised by the actions (or inaction) of an AI. Anyone can submit an incident and anyone can explore the database. In time this should become a very informative resource for researchers and policy makers.

The AI Incident Database is dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment of artificial intelligence systems. Like similar databases in aviation and computer security, the AI Incident Database aims to learn from experience so we can prevent or mitigate bad outcomes.

You are invited to submit incident reports, whereupon submissions will be indexed and made discoverable to the world. Artificial intelligence will only be a benefit to people and society if we collectively record and learn from its failings.

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Using Machine Learning and Traffic Cameras to Replace Cops

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Mass surveillance is everywhere in modern cities. Cameras are on every corner monitoring all sorts of activities, which led one person to think about using them to see if traffic cameras can be used to replace traffic cops. The short answers is yes. Personally, I don’t see mass surveillance as a good thing but what I find really interesting about this isn’t the policing aspect but the data collection of how streets are used. In the example setup it was found that cars broke the laws quite a lot and endangered the lives of cyclists. Maybe we can use the technology to better understand how streets get used and what we can do to ensure traffic flows.

The Results
During a 10 day period in December 2017,

  • bike lane was blocked 40% of the time (57% weekdays 7am to 7pm)
  • bus stop was blocked 57% of the time (55% weekdays 7am to 7pm)

Keep in mind this is just one average block. This means if you are riding in a bike lane you are swerving blind in and out of the bike lane every other block. And if you are on a bus your commute just got longer.

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