Latest Turing Award winners again warn of AI dangers

Two trailblazing scientists who today received this year’s Turing Award for creating fundamental artificial intelligence training techniques are using the spotlight to shine concern on the dangers of rushing AI models out for public consumption.

University of Massachusetts researcher Andrew Barto and former DeepMind research scientist Richard Sutton warned that AI companies are not thoroughly testing products before releasing them, likening the development to “building a bridge and testing it by having people use it,” according to The Financial Times.

The Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize and was jointly awarded to Barto and Sutton for developing “reinforcement learning” — a machine learning method that trains AI systems to make optimized decisions through trial and error. Google’s senior vice president Jeff Dean describes the technique as “a lynchpin of progress in AI” and has remained “a central pillar of the AI boom” that led to breakthrough models like OpenAI’s ChatGPT and Google’s AlphaGo before that.

“Releasing software to millions of people without safeguards is not good engineering practice,” Barto told The Financial Times. “Engineering practice has evolved to try to mitigate the negative consequences of technology, and I don’t see that being practised by the companies that are developing.”