If you gaze too long into the metrics abyss… calamities, disasters, tragedies, etc all fade away, until all you can see are “quasi random experiments” and “exogenous variation”
I returned, and saw under the sun, that the retweets are not to the correct, nor the dunks to the stupid, neither yet followers to the witty, nor yet bannings to rulebreakers, nor yet blue checks to men of distinction; but time and chance happeneth to them all.
I'm increasingly convinced that a lot of smart academics are confused about AI because most of their worst experiences with it come from the classroom. But professors play two roles and are also supposed to spread knowledge.
In class, we test whether students learned something themselves. Sure, test them and do oral exams. That's what I'm planning to do as well. But in journals, we should publish true, original, important claims, whether AI-assisted or not.
There's a way of engaging with philosophy that amounts to just learning the positions espoused by a variety of historical figures without paying much attention to the arguments for and against those positions. I can't think of a less interesting approach to the history of ideas.
“Why didn’t you submit your homework on time?”
“Corner solutions are rarely optimal.”
“It says here you attended less than half of the lectures. Why?”
“Corner solutions are rarely optimal.”
“You did not appear for your maths final. Why?”
“Corner solutions are rarely optimal.”
Tried to ask my metrics prof some questions about my model on two hours of sleep. All knowledge about my model specifications and metrics in general fled my mind the moment I opened my mouth. Do not recommend