This post marks my transition from a full-time AI researcher to a full-time urban science student. When I wrote my response to the 'What attracted you to this program?' question in the application form for the course, I was surprised to find that I had many thoughts about the mixing of the 'hard' and 'soft' sciences. I figure it will also be fun to look back on this post and see what has changed after finishing my urban science course.

I used to find the term social science oxymoronic. Not that I felt either humanities or sciences were inferior to the other, but that I thought the two were mutually exclusive. I enjoyed my share of visual arts, literature and cinematography, as well as a healthy dose of math and science (staples of the Singaporean education).

Recurrent words, symbols and themes in literature, the mise-en-scène, cuts and pacing in cinematography - these invoke raw feelings that do not necessarily have to be dissected to be impactful. On the other hand, math and science classes taught calculus, geometry, reactions and patterns and trends, dictated by gradients and formulas and rules (although I must say that I fully agree with Paul Lockhart’s A Mathematician’s Lament!).

One of the books that changed my mind about this was Poor Economics by Abhijit Banerjee and Esther Duflo.

Here's a link to the TED talk by Esther Duflo on Poor Economics.

A primary theme of the book was the use of Randomized Controlled Trials (RCTs) for understanding the effects of aid measures on the poor. RCTs have been traditionally employed for clinical and scientific trials. But Banerjee and Duflo demonstrated that RCTs could be used to shed light on the ‘soft’ psychological factors influencing the success of aid measures.

It was fascinating to see how traditional scientific techniques and sociological investigations could be complementary and lead to new innovations.