Self-Motivation
David Goggins
Former Navy Seal
Career Development
Bryan Cranston
Actor
Critical Thinking
Liv Boeree
International Poker Champion
Emotional Intelligence
Amaryllis Fox
Former CIA Clandestine Operative
Management
Chris Hadfield
Retired Canadian Astronaut & Author
Learn
from the world's big
thinkers
Start Learning

The biggest problem in AI? Machines have no common sense.

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

  • 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.

Quantcast