The Diminishing Returns of Focusing on the Right Thing

There was a recent thread on Hacker News about the search for the “cure for aging”:

The thought has recently occurred to me that we should all be working on the “aging problem”, until it’s solved, and then spending all our extra time on other pursuits. — b_emery

I’m sure you’ve heard (or expressed) a similar sentiment about other pressing Big Problems.

After all, why should we spend millions in tax dollars funding “useless”, or at the very least, non-vital research, when there are real problems to be solved? Why do we pay pure mathematicians to dream up infinite-dimensional spheres and Hilbert spaces, when that money could be better spent training engineers to build next-generation sustainable transportation?

This line of thinking may be noble in principle (“Let’s prioritize research that focuses on finding solutions to our most urgent real-world problems, instead of wasting resources on useless/unprofitable endeavours”), but it tends to lead to stagnation, not innovation.

Focusing on big problems is important, but there are diminishing returns to focusing on the right thing, possibly even negative returns. That is, focusing too much on solutions makes us less likely to find them.

While, improvements and advancements come from focused research, paradigm-shifting discoveries tend to come from unexpected places; often based on information that is initially discarded as not useful, even by experts.

By taking away funding from “useless” pursuits (like pure maths, arts, theoretical research) and focussing solely on the bottom line (“real-world problems”, what is profitable, what is immediately useful), we make great advancements less likely, not more.

This is why we can’t simply pour infinite money into “Finding the cure for x” and expect results; we can’t pour infinite money on engineers, while defunding basic research, and expect innovation.

Reminds me of the Louie bit where David Lynch instructs Louie to “Be funny: 3… 2… 1… Go”. — Well, that’s not how funny work. Achieving that level of mastery of his craft is 90% non-funny related activities (life experiences, personal growth, self-reflection etc.), and 10% actually focusing on “being funny” in itself.

What if the key to unlocking “disease x” comes from unrelated research in metabolism, what if the techniques needed to sort through the data come from an applied mathematician investigating economic trends? What if the technology required to model the problem in order to even ask the right question in the first place is developed by computer scientists modelling data for a social network? There’s just no way to know but to explore.

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