Andrey F.: That's really interesting, because those are quite diverse activities and they are not typically things that economists actually study in their PhD. What is the advantage of an economist looking at this type of problem, as opposed to let's say in the case of logistics for Amazon? You would think that there is a person in operations research or in the case of search engine design, you'd think that there is a computer scientist focusing on machine learning, that would be the appropriate person. What is the economists' perspective on this?
Greg L.: Yes. I think what economists bring to the table is really a good idea of how we think about economic remodeling. If you think about the case of logistics, Amazon does have many highly talented operations research professionals working in these kinds of questions. The way Pat described this to me is you have to know what to optimize. In order to know what to optimize, you have to know what the economic trade-offs are that Amazon is making by, say, delivering things in one day relative two days.
Economists would sit there and think, "One day delivery attracts customers a little bit better. People like one day delivery. In the long run, this may make a big difference to Amazon's growth trajectory, versus the standalone retail store that we're used to every day." Economist are very good at thinking of those trade-offs and then working out how one might think about quantifying things.
The key difference that Lewis is highlighting is the way that economists approach research questions, and the way they go about answering them. Later in that same interview, there is a good bit about how machine learning won't replace economic modelling, which should be required knowledge for computer scientists. Well worth a read (albeit a long one).
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