AIReview of the Artificial Intelligence Industry 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pitfalls of outsourcing our problems for technology to solve rather than addressing the causes, and of allowing outdated predictive modeling to go unchecked.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 University’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.
“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.
Stanford notes, however, that the technology is moving faster than expected, and the organizers of the AI100 felt there were issues to discuss prior to the next scheduled session. The reports that resulted from those workshops paint a picture of the potential pitfalls of outsourcing our problems for technology to solve rather than addressing the causes, or allowing outdated predictive modeling to go unchecked. Together, they provide an intermediate snapshot that could guide discussions at the next full meeting, said Altman.
“The reports capture the cyclical nature of public views and attitudes toward AI,” said Peter Stone, professor of computer science at the University of Texas in Austin who served as study panel chair for the last report, and is now chair of the standing committee. “There are times of hype and excitement with AI, and there are times of disappointment and disillusionment – we call these AI winters.”
This longitudinal study aims to encapsulate all the ups and downs – creating a long-term view of artificial intelligence.
Alexa Doesn’t Care about You
Although artificial intelligence is widespread in healthcare apps, participants in the workshop debating AI’s capacity to care concluded that care itself isn’t something that can be encoded in technology. Based on that, they recommend that new technologies be integrated into existing human-to-human care relationships.
