Arvind Narayanan Profile picture
Princeton CS prof and Director @PrincetonCITP. Coauthor of "AI Snake Oil" and "AI as Normal Technology". https://t.co/ZwebetjZ4n Views mine.

Jun 21, 2021, 6 tweets

A student who's starting grad school asked me which topics in my field are under-explored. An important question! But not all researchers in a community will agree on the answers. If they did, those topics won't stay under-explored for long. So how to pick problems? [Thread]

It's helpful for researchers to develop a "taste" for problems based on their specific skills, preferences, and hypotheses about systemic biases in the research community that create blind spots. I shared two of my hypotheses with the student, but we must each develop our own.

Hypothesis 1: interdisciplinary topics are under-explored because it requires researchers to leave their comfort zones. But collaboration is a learnable skill, so if one can get better at it and find suitable collaborators, rich and important research directions await.

Hypothesis 2 (for computer science research): work that brings accountability to the tech industry's claims is pursued less than research that responds to the industry's needs. The reasons are, of course, funding, prestige, and other such incentives.

These hypotheses have guided me for most of my career, not just in picking research topics but in the way I conduct research — e.g. nurturing collaborations; learning from civil society organizations and investigative journalists who do critical tech accountability work.

Some researchers stay within a topic and develop deep expertise over decades. That's a perfectly valid way to do things. I've instead found it fruitful to evolve a strong taste and research style while migrating relatively frequently between topics. This way is worth considering!

Share this Scrolly Tale with your friends.

A Scrolly Tale is a new way to read Twitter threads with a more visually immersive experience.
Discover more beautiful Scrolly Tales like this.

Keep scrolling