Snapshot of artificial intelligence reveals challenges

A periodic review of the artificial intelligence industry revealed the potential pitfalls of outsourcing our problems for technology to solve rather than addressing the causes, and of allowing outdated predictive modeling to go unchecked. As part of Stanford's ongoing 100-year study on artificial intelligence, known as the AI100, two workshops recently considered the issues of care technologies and predictive modeling to inform the future development of AI technologies. A Stanford-led artificial intelligence index called the AI100 periodically assesses the state of AI technology and makes predictions for the next century. (Image credit: Tricia Seibold) "We are now seeing a particular emphasis on the humanities and how they interact with AI," said Russ Altman , Stanford professor of engineering and the faculty director of the AI100. The AI100 is project of the Stanford Institute for Human-Centered Artificial Intelligence. After the first meeting of the AI100, the group planned to reconvene every five years to discuss the status of the AI industry. The idea was that reports from those meetings would capture the excitement and concerns regarding AI technologies at that time, make predictions for the next century and serve as a resource for policymakers and industry stakeholders shaping the future of AI in society.