Working on “hard problems”?

Ben E Kuhn writes:

For some reason, a lot of smart college students end up with the idea that “solving hard technical problems” is the best thing they can do with their life. It’s a common refrain in Hacker News commentsjob ads and interview questions.School is a closed-world domain—you are solving crisply-defined puzzles (multiply these two numbers, implement this algorithm, write a book report by this rubric), your solution is evaluated on one dimension (letter grade), and the performance ceiling (an A+) is low. The only form of progression is to take harder courses. If you try to maximize your rewards under this reward function, you’ll end up looking for trickier and trickier puzzles that you can get an A+ on.

The real world is the polar opposite. You’ll have some ultra-vague end goal, like “help people in sub-Saharan Africa solve their money problems,” based on which you’ll need to prioritize many different sub-problems. A solution’s performance has many different dimensions (speed, reliability, usability, repeatability, cost, …)—you probably don’t even know what all the dimensions are, let alone which are the most important.

This is fascinating insight (obvious and hidden in plain sight). Whenever, I hear about the next hype cycle around the AI (and machine learning) out there to solve the “global problems”, I roll up my eyes. For the same reason, I found numerous publications around SMS delivery of healthcare in Africa with absolute zero insight on the efficacy metrics. It does wonders on the resume to show that you have been working with the less advantaged communities while failing to solve the meltdown issues in your own backyard. NHS is tottering towards insolvency propped up by the British taxpayer. The US healthcare (despite massive spending) has seen the maximum number of fatalities in the pandemic. What are the solutions? Simple. Decouple the politics from policy and create mechanisms for doctors to ensure well being.