In my conversation, Eesha Iyer, an economist-data scientist, discusses how machine learning and artificial intelligence have changed what is possible. We are seeing a transition both from static inferential models common in economics for decades to dynamic, interactive systems that adjust in real-time.
We are also seeing a revamping of the workflow with AI systems clearing up time to do rudimentary programming tasks. Trivial programming tasks that once took quite a bit of a data scientist’s time are easier than ever, so now the key issue is becoming, What kinds of questions should we ask of the data? Qualitative and social science thinking are crucial for this new space. For Eesha, gone are the days when data scientists were technical workers spending hours writing code. In the current era, the question becomes how to formulate relevant research avenues to explore. For this, social scientists are more useful than ever.
In our conversation, we explore the implications all this has on the field of data science. She also advises how to learn data science in this shifting landscape. I hope you enjoy.
