You should be skeptical when it comes to hyped-up AI. Here’s why.

These questions can help us think more critically about new developments in artificial intelligence.

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  • The media often exaggerate and overhype the latest discoveries in artificial intelligence.
  • It's important to add context to new findings by asking questions: Is there a demo available? How narrow was the task the computer performed?
  • A more robust approach to artificial intelligence involves solving problems in generalized situations rather than just laboratory demonstrations.
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Machines probably aren’t interested in global takeover. Here’s why.

What most people worry about when it comes to artificial intelligence likely comes from science-fiction fantasy.

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  • When someone says they fear artificial intelligence, what are they imagining? Robots taking over the world is the stuff of science-fiction fantasy.
  • Despite decades of beating humans at the game of Go, AI has never developed the desire to take over actual territory. The reality is that machines are not resourceful and have no interest in us.
  • Although AI plays an increasingly important role in our lives, we have a ways to go before deep learning and machines are solving all of our problems.
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The biggest problem in AI? Machines have no common sense.

Correlation doesn't equal causation — we all know this. Well, except robots.

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  • There are a lot of people in the tech world who think that if we collect as much data possible, and run a lot of statistics, that we will be able to develop robots where artificial "intelligence" organically emerges.
  • However, many A.I.'s that currently exist aren't close to being "intelligent," it's difficult to even program common sense into them. The reason for this is because correlation doesn't always equal causation — robots that operate on correlation alone may have skewed algorithms in which to operate in the real world.
  • When it comes to performing simple tasks, such as opening a door, we currently don't know how to encode that information — the varied process that is sometimes required in differing situations, i.e. jiggling the key, turning the key just right — into a language that a computer can understand.

Gary Marcus is the author of Rebooting AI: Building Artificial Intelligence We Can Trust.