A prominent researcher of machine learning and artificial intelligence is arguing that his field has strayed out of the bounds of science and engineering and into "alchemy." And he's offering a route back.
Ali Rahimi, who works on AI for Google, said he thinks his field has made amazing progress, but suggested there's something rotten in the way it's developed. In machine learning, a computer "learns" via a process of trial and error. The problem in a talk presented at an A.I. conference is that researchers who work in the field — when a computer "learns" due to a process of trial and error — not only don't understand exactly how their algorithms learn, but they don't understand how the techniques they're using to build those algorithms work either, Rahimi suggested in a talk presented at an AI conference covered recently by Matthew Hutson for Science magazine.
Back in 2017, Rahimi sounded the alarm on the mystical side of artificial intelligence: "We produce stunningly impressive results," he wrote in a blog. "Self-driving cars seem to be around the corner; artificial intelligence tags faces in photos, transcribes voicemails, translates documents and feeds us ads. Billion-dollar companies are built on machine learning. In many ways, we're in a better spot than we were 10 years ago. In some ways, we're in a worse spot." [Super-Intelligent Machines: 7 Robotic Futures]
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