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Drago Indjic
Drago Indjic

Drago Indjic

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From Where Humans Meet Machines: Intuition, Expertise and Learning by MIT IDE

Brynjolfsson: You’re not a big fan of human decision making, I see.

Kahneman: For a job like underwriters, a simple algorithm can do just as well.

From Where Humans Meet Machines: Intuition, Expertise and Learning by MIT IDE

d 15%, but in fact, they disagreed… people can make that are different than biases. Help us understand that a little bit.

Kahneman: At an insurance company, we measured what is technically called noise, and we did that in the following way: We constructed a series of six completely realistic cases that were given to 50 of their underwriters. We wanted to determine how much variability there was in their funding decisions. We expected differences between 10% and 15%, but in fact, they disagreed about 56% of the time. That’s a lot of noise.

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Proof of Value

Ivan Bjelajac

From liquid exchangeable tokens to unique non-fungible tokens — a 360 spin?

Nejc Novak, LL.M. (UCL)

Where Humans Meet Machines: Intuition, Expertise and Learning

MIT IDE