In his recent essay in the Wall Street Journal, Bill Gates proposed to “fix the world’s biggest problems” through “good measurement and a commitment to follow the data.” Sounds great!
Unfortunately it’s not so simple.
Gates describes a positive feedback loop when good data is collected and acted on. It’s hard to argue against this: given perfect data-collection procedures with relevant data, specific models do tend to improve, according to their chosen metrics of success. In fact this is almost tautological.
As I’ll explain, however, rather than focusing on how individual models improve with more data, we need to worry more about which models and which data have been chosen in the first place, why that process is successful when it is, and – most importantly – who gets to decide what data is collected and what models are trained.
Take Gates’s example of Ethiopia’s commitment to health care for…
View original post 529 more words