But I think there’s also a basic misunderstanding about what a T-shaped individual is and why they are sought after outside academia. It’s not because they can do a bit of everything, setting up the build system with one hand and designing the logo with the other. (That’s more what you’d call a jack of all trades.)
The reason T-shaped individuals are sought after in industry is that they are effective leaders. They understand enough about the problem domain(s) to identify meaningful problems and enough about the solution domain to help map out the solution space.
The reason you’d want more T-shaped people in machine learning research is that they will ask better research questions, not because they’ll design prettier logos.
> The reason T-shaped individuals are sought after in industry is that they are effective leaders. They understand enough about the problem domain(s) to identify meaningful problems and enough about the solution domain to help map out the solution space.
> The reason you’d want more T-shaped people in machine learning research is that they will ask better research questions, not because they’ll design prettier logos.
Author here---fully agree with you. Man, that example with the logos is going to haunt me now...I just did not want to bog down the article with too many technical details. Of course there's immense value in moving between disciplines...that's a whole other discussion to be had (because IMO, academia does not necessarily have the right incentives for this either; research between disciplines X and Y often tends to be dismissed as being 'not enough X for Y' or 'not enough Y for X')
But I think there’s also a basic misunderstanding about what a T-shaped individual is and why they are sought after outside academia. It’s not because they can do a bit of everything, setting up the build system with one hand and designing the logo with the other. (That’s more what you’d call a jack of all trades.)
The reason T-shaped individuals are sought after in industry is that they are effective leaders. They understand enough about the problem domain(s) to identify meaningful problems and enough about the solution domain to help map out the solution space.
The reason you’d want more T-shaped people in machine learning research is that they will ask better research questions, not because they’ll design prettier logos.