Bias in AI is the ultimate snowball effect, the result of compounding decisions over time. It can originate in early data selection, annotation practices or the objectives chosen during development.

Artificial intelligence (AI) systems tend to take on human biases and amplify them, causing people who use that AI to become more biased themselves, finds a new study by UCL researchers.

Companies will need to have an overall AI governance strategy to monitor and track AI behavior, measure fairness, and detect bias across their growing AI portfolios. - Vinod Bijlani , HPE 6.

The most alarming thing about AI isn’t its newness: It’s that it repeats an age-old mistake in medicine, continuing to use flawed, incomplete data to shape decisions on patient care.

New AI benchmarks could help developers reduce bias in AI models, potentially making them fairer and less likely to cause harm. The research, from a team based at Stanford, was posted to the arXiv ...