Two leading figures in artificial intelligence (AI), Andrew Barto and Richard Sutton, have been awarded the prestigious Turing Award for their pioneering work in developing reinforcement learning, a technique central to today’s AI advancements. The duo, who first developed the groundbreaking method in the 1980s, received the $1 million prize from the Association for Computing Machinery (ACM) for their contributions to the AI field.
In the 1980s, Barto and Sutton were seen as outliers, working on an idea that seemed too ambitious—getting machines to learn from experience like humans and animals do.
Now, decades later, the method they developed is a key part of modern AI and programs like ChatGPT. For their work, Barto and Sutton have been awarded the Turing Award, the top honor in computer science.
Barto, a professor emeritus at the University of Massachusetts, and Sutton, a professor at the University of Alberta, were recognized for their role in creating reinforcement learning, a technique that has helped power some of the world’s most influential AI models, including those at Google and OpenAI. Despite their accolades, both scientists are sounding the alarm on the rapid pace of AI development, warning against the unchecked release of powerful models without sufficient testing and safety measures.
Barto expressed concerns over the current AI boom, likening the release of untested software to building a bridge and letting people cross it before it’s fully evaluated, according to the Financial Times. “Releasing software to millions of people without safeguards is not good engineering practice,” he said.
Their win comes at a time when AI is rapidly transforming industries and attracting massive investments, with the sector expected to exceed $320 billion in spending this year alone. However, Barto and Sutton criticize the industry’s focus on commercialization over scientific progress, highlighting the risks of rushing to launch AI products before addressing their potential flaws.
Sutton dismissed the growing hype surrounding Artificial General Intelligence (AGI) as exaggerated, stressing that systems more intelligent than humans will emerge gradually through a better understanding of the human mind. Despite their reservations, both remain optimistic about AI’s potential to drive positive societal change, with Sutton emphasizing that “too much intelligence is not one of the world’s problems.”
