Can A.I. Be Taught to Explain Itself?

December 4, 2017 Jonathan Nessler

Can A.I. Be Taught to Explain Itself?

https://www.nytimes.com/2017/11/21/magazine/can-ai-be-taught-to-explain-itself.html

Artificial Intelligence is mysterious. Even leading researchers in the field are often mystified by this world changing technology. Oftentimes, these researchers are unable to explain what the machines know and how the machines figured those things out. This article discusses the problem of not knowing how AI knows what it knows.

The vagaries of how AI technology works should be concerning to lawyers. Allowing an AI to order office supplies when the supplies run short might be acceptable, but it is not so clear that it is reasonable to allow a mysterious machine to make decisions that affect clients.

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It has become commonplace to hear that machines, armed with machine learning, can outperform humans at decidedly human tasks, from playing Go to playing “Jeopardy!” We assume that is because computers simply have more data-crunching power than our soggy three-pound brains. Kosinski’s results suggested something stranger: that artificial intelligences often excel by developing whole new ways of seeing, or even thinking, that are inscrutable to us. It’s a more profound version of what’s often called the “black box” problem — the inability to discern exactly what machines are doing when they’re teaching themselves novel skills — and it has become a central concern in artificial-intelligence research. In many arenas, A.I. methods have advanced with startling speed; deep neural networks can now detect certain kinds of cancer as accurately as a human. But human doctors still have to make the decisions — and they won’t trust an A.I. unless it can explain itself.

https://www.nytimes.com/2017/11/21/magazine/can-ai-be-taught-to-explain-itself.html

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