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Friday, September 13, 2019

Build AI we can Trust

A long time question.   Its the old problem of  'common sense' reasoning, and it usually a step above common sense .... maybe call it 'light reasoning' , as the article below suggests.  Humans often omit that kind of reasoning too,  say the kind you can do in your head, or need to write a few lines on a piece of paper.   We sometimes do one-level analogies, but rarely more.   But surely we should expect that capability of a machine.  And often a question requires a determination of risk in context to determine a useful and correct answer.

How to Build Artificial Intelligence We Can Trust    By The New York Times

Exploring the universe with artificial intelligence.
We are relying on artificial intelligence more and more, but it hasn't yet earned our confidence.

Artificial intelligence has a trust problem. We are relying on A.I. more and more, but it hasn't yet earned our confidence.

Tesla cars driving in Autopilot mode, for example, have a troubling history of crashing into stopped vehicles. Amazon's facial recognition system works great much of the time, but when asked to compare the faces of all 535 members of Congress with 25,000 public arrest photos, it found 28 matches, when in reality there were none. A computer program designed to vet job applicants for Amazon was discovered to systematically discriminate against women. Every month new weaknesses in A.I. are uncovered.

The problem is not that today's A.I. needs to get better at what it does. The problem is that today's A.I. needs to try to do something completely different.

In particular, we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets — often using an approach known as deep learning — and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality.  ....  "

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