A Verified Answer Isn't Knowledge, Argues a Northwestern Scientist
Verification Is Not Knowledge: Science needs more than answers
Jessica Hullman argues that the rush to let AI verify proofs and produce cures mistakes correctness for knowledge. Drawing on Bill Thurston, Terry Tao's cancer-treatment thought experiment, and arXiv's flood of papers whose authors can't defend their claims, she traces the problem to the Cold War-era "value-free ideal" that stripped ethical and social judgment from science. Verification, she contends, cannot replace the human accountability and criticism that make knowledge possible.
The value-free ideal distorts how we go about seeking truth, causing us to mistake verified results for knowledge.
- throw0101c
When Kepler published his models:
* https://en.wikipedia.org/wiki/Kepler%27s_laws_of_planetary_m...
People did not understand how or why they worked, but they switched over to them from the Ptolemaic (Tychonic, etc†) system anyway because the math was easier. It was only later (Newton, Einstein) that we understood the "why" and "how".
† https://tofspot.blogspot.com/2013/08/the-great-ptolemaic-sma...
- niemandhier
We all know Terry Tao, do you know Peter Scholz?
Fields medalist and as Tao listed as one of the most important mathematicians of our age.
Scholz is known to find
„precisely the correct and cleanest way to incorporate all the previously done work and find an elegant formulation for that — and then, because he found really the correct framework, go way beyond the known results“
In a way that man is the complement of an AI, he generates understanding rather than just proofs.
Maybe he is the right template for the mathematicians of the future.
https://www.quantamagazine.org/peter-scholze-and-the-future-...
- A_D_E_P_T
The article's perspective reminds me of math class when I was a kid. The teacher didn't want the right answer alone, she wanted to see how I got there. In an absolute sense, the right answer is the right answer with or without my understanding, but that's not how the class was graded. We're approaching a point where AI is to science as my old calculator is to elementary school math -- it's capable of leapfrogging to answers faster and more accurately than we can.
Thing is, though, verification is knowledge itself. And if we can get to a point where the important questions have answers, we can surely have the verifiers explain those to us in ways we can understand them.
- wqtz
Ahhh, epistemology... Does any academic researcher even care about these things anymore?
If you're in academia, you've probably noticed a major shift recently. Research production at an industrial scale through AI.
Grants have "always" been awarded to professors based on quantity multiplied by quality. Now, some professors are churning out 1–3 papers a month with the same group of co-authors. All the grant money goes to them. Grant givers are just only counting the numbers of papers being published.
The Industrial Revolution has hit academia, and some academics are busy arguing for the artisanal value of research while some are creating factories for research.
- My_Name
Surely the way forwards is to take the results obtained by brute force with AI, for example that certain conjectures are true or false, then to use that knowledge to further human understanding.
Knowing that something is true or false will at least stop humans wasting time trying to prove or disprove it, and allow them to find a more elegant proof, or investigate the implications of the true/false result.