- Joined
- Sep 20, 2018
- Messages
- 7,127
- SL Rez
- 2006
Hackers competed to find AI harms. Here’s what they found. - The Washington Post
As AI chatbots and image generators go mainstream, their flaws and biases have been widely catalogued. We know, for example, that they can stereotype people of different backgrounds, make up false stories about real people, generate bigoted memes and give out inaccurate answers about elections. We also know they can overcorrect in an attempt to counter biases in their training data. And we know they can sometimes be tricked into ignoring their own restrictions.
What’s often missing from these anecdotal stories of artificial intelligence going rogue is a big-picture view of how common the problem is ― or to what extent it’s even a problem, as opposed to an AI tool functioning as intended. While it doesn’t claim to answer those questions definitively, a report released Wednesday by a range of industry and civil society groups offers some fresh perspective on the myriad ways AI can go wrong.
The report details the results of a White House-backed contest at last year’s Def Con hacker convention, which I wrote about last summer. The first-of-its-kind event, called the Generative Red Team Challenge, invited hackers and the general public to try to goad eight leading AI chatbots into generating a range of problematic responses. The categories included political misinformation, demographic biases, cybersecurity breaches and claims of AI sentience.














