"The danger of AI is not that it's going to rebel against us, it's that it's going to do exactly what we ask it to do"
But what happens when AI does exactly what we ask, yet not what we intend?
Working with AI isn't like working with a human, more like working with a weird force of nature.
► Consider this: You task an AI with assembling a robot from a pile of parts. 🤖🦾🦾🦿🦿
The goal? Get from point A to point B.
You'd expect the AI to build a robot with legs and walk, right?
But what if the AI decides to assemble itself into a tower and simply falls over to reach point B?
Technically, it did what you asked.
But is it what you intended?
The trick of working with AI becomes: How do we set up the problem so that it actually does what we want?
It's easy to accidentally give AI the wrong problem to solve, and often we don't realize that until something has gone horribly wrong.
► Take Amazon's resume-sorting algorithm, for instance. It was trained on example resumes of people they had hired in the past.
But what happened?
The AI learned to avoid the resumes of people who had gone to women's colleges or who had the word "women" somewhere in their resume.
The AI didn't know that it wasn't supposed to copy this particular thing that it had seen the humans do. And technically, it did what they asked it to do. They just accidentally asked it to do the wrong thing.
So, what's the takeaway from all this?
AI can be really destructive and not know it. It doesn't understand the consequences of its actions. It's up to us to avoid problems.
We have to learn what AI is capable of doing and what it's not, and to understand that. AI doesn't really understand what we're trying to ask it to do.
We must be prepared to work with the AI we have, not the super-competent, all-knowing AI of science fiction.
So, the next time you interact with AI, remember: it's not just about what you ask, but how you ask it.
After all, AI is only as smart as the tasks we give it.
(h/t to @westwoodpro)
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