We hear about AI taking over our jobs. We hear about AI listening in on our conversations. We hear about AI becoming a substitute for our romantic partners. Here’s what the real AI experts Guru Banavar, (IBM), Toby Walsh, (The University of New South Wales), and Roman Yampolskiy (University of Louisville), say about the subject, and why a lot of what you think you know is probably wrong.

  1. Automation vs. AI. Put simply, AI is a machine that is capable of thinking, that can perform a task thought to be reserved for a human mind. Automation is simply a process of completing a task with little to no human intervention. Automation is not AI.
  2. Humanoid robots vs. computer. Although we often conjure an image of a humanoid-type robot when we think of AI, most AI is invisible, hidden in computer systems for customer service and speech recognition, for example.

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  3. Intelligence vs. consciousness. AI refers to intelligence, not consciousness. “Intelligence is the ability to solve problems in any domain,” said Roman Yampolskiy, director of the CyberSecurity Lab at the University of Louisville. “Consciousness is something people claim they have. It has no practical applications, it doesn’t do anything. In fact we can’t even detect it, so it is not a scientific concept.”
  4. AI is not all tech. AI is often blamed for job losses when it’s really just general technology that is the cause. “AI gets a disproportionate amount of focus,” said Toby Walsh, AI professor in Australia. “Extrapolate to the Hollywood dystopian view of robots destroying us. All of the blame is on AI, but it’s technology as a whole. All of technology, even the dumbest smart phone, changes our lives.”

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  5. The Terminator does not represent the future of AI. Many experts I spoke to mentioned that seeing a picture of the Terminator on every AI story was their biggest pet peeve when it came to popular opinion of AI. This scenario, while compelling, is unlikely to come to fruition.
  6. Misunderstanding of machine learning. According to Guru Banavar, the head of the team at IBM responsible for creating Watson, the AI system that mastered Jeopardy, most people don’t have a good understanding of what machine learning is. What it is, he says, is showing a system examples and having it extrapolate information from them. “We can teach a computer to recognize a car, but we can’t ask that same computer, ‘How many wheels does that car have?’ Or, ‘What kind of engine does it have?’ Can you ask anything else about what this car is made of or how it is made? None of those things are possible,” he said.”Those are all far away.”
  7. Underestimating what is already possible with AI. Worried about AI writing music? Or news stories? Too late, it’s already been done!

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