Data people should strive to be folk singers, not rock stars

In early 2020, just before COVID-19 put a halt to in person events like this, I was invited to speak at the "Data for the Greater Good" meetup in New York. This vibrant community is open to all people interested in using data to tackle tricky social problems, and the organizers do a fantastic job.

For better or worse, they let me talk about whatever I wanted, so I thought this would be a great opportunity to share some vague ideas that I've been having lately around the ways that data scientists in our field actually create positive change vs the ways that people typically assume they do. In practice, they tend to more closely resemble the collaborative, organic, bottom-up approach that folk musicians take in their creative process instead of the common "rock star" stereotype.

The full video of the talk, which digs into this analogy a bit more uses it as a vehicle for telling some stories about data at GlobalGiving, is below. Development Guild, one of the sponsors for the evening, also wrote up a great blog post summary.

In addition, I spent probably more time than I needed to thinking of different musical examples of the kinds of creativity that I wanted to highlight. Of course, none of these made the final cut for the event, but I had too much fun not to share them. Eventually I'll write up some annotations for all the detailed reasons why I included each one, but in the meantime, here's the spotify playlist: