What impact is AI having? I'm of the view that we should be focussing more on aggregate outputs, relatively less on inputs or intermediate proxies.
- Inputs: time spent across different activities; money spent on tokens.
- Intermediate proxies: working papers; lines of code, commits & pull requests; self-reported speedup.
- Final outputs: total cyber exploits discovered; total math problems solved; algorithmic efficiency.
The disadvantage of inputs & intermediate proxies is that they're very hard to interpret -- totally possible that they move, but outputs don't, and vice versa. Lines of code could explode without value changing; and vice versa.
A disadvantage of final outputs is (1) it's harder to run experiments; (2) it's hard to attribute to whether the change is AI or not. But in some domains the trend-break is so large that it's *obviously* AI.
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