zkPass(@zkPass):What’s changing in data science isn’t really the role, it’s where the pain is. It used to be getting data into shape. Now anyone can generate analysis that looks convincing in minutes. The problem is none of it comes with any guarantee. You don’t know if the data was interpreted right, if the steps actually happened, or if the result maps to anything real. So the work didn’t disappear, it just moved. Less time doing analysis, more time second guessing it. The real bottleneck now is whether anything can be verified.

2026.05.14 15:22

What’s changing in data science isn’t really the role, it’s where the pain is. It used to be getting data into shape. Now anyone can generate analysis that looks convincing in minutes. The problem is none of it comes with any guarantee. You don’t know if the data was interpreted right, if the steps actually happened, or if the result maps to anything real. So the work didn’t disappear, it just moved. Less time doing analysis, more time second guessing it. The real bottleneck now is whether anything can be verified.

Lenny Rachitsky@lennysan

2026.05.13 18:33

Not enough people are talking about how much AI is impacting the role of data science. I was chatting with a DS friend, and he said that most of his team's work now is reviewing half-assed AI data analysis from PMs and engineers. And that 50% of the time, that analysis is wrong. The role is becoming less fun.