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Dee Smith of Strategic Insight Group sits down with Raoul Pal to discuss the confluence of behavioral economics and technology. The principles of behavioral economics combined with machine learning and algorithms can lead to amazing results, but what happens when human bias bleeds into the very algorithms we believe protect us from it? This video is excerpted from a piece published on Real Vision on September 7, 2018 entitled “Modern Manipulation: Behavioral Economics in a Technological World.”

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Technology, Incentives & Cognitive Bias (w/ Dee Smith & Raoul Pal)

For the full transcript:
There is an emerging narrative that is claiming that computer programs do have
biases, and the biases are based on the people who write programs.
One of the interesting topics in that, of course, confirmation bias is one of the most deadly of the
behavioral economic biases that we look to find information that confirms what we already
believe, instead of finding information that could falsify it, which is what scientific method is based
on, is that you could try to falsify. You don’t try to verify.
That the whole American adventure in Iraq based on the intelligence finding that there were
weapons of mass destruction, which was in large part based on ignoring evidence that there
weren’t. It was simply selective use of intelligence, which is confirmation bias. It can be incredibly
problematic. But it’s something that is so, there’s some kind of a switch that flips and you decide,
oh, it’s an aha moment. I see it, I got it, I understand it now. Let me find all these things that tell me
I’m right.
RAOUL PAL: Because humans are so delusional. I mean, I fall into that bias all the time, as
everybody does. And this is why the machine is so powerful and why we have to be actually truly
concerned. Not flippantly concerned, but truly concerned, because there is no bias. And it’s the
massive ability to process data in ways that the human brain can’t.
We can process incredible data. Everything we’re seeing now and all the colors. Machines are
nowhere near that, nowhere near our cognitive abilities in certain ways. We cannot process a
fixed amount of, a fixed type of data in the quantity that machines can without a bias, because we
need patterns to fill in the blanks.

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