Comment by wordpad
3 days ago
Depends on what they're trying to incentivise.
It's quite possible they aren't trying to measure performance but are literally just trying to increase token consumption to feed the bubble and hype.
Plus pressure employees may find new unique use cases for AI.
It's like if your goal is inflation, you give out tons of money and as long as its spent, you achieve your goal.
I would guess they are trying to maximize training data
If I was being rewarded for using more tokens, I would feed LLM output back into the model. That's probably not very useful training data.
I personally know two people who are doing exactly that after a mandate rolled out at their work, the measurement is "tokens spent" and since they weren't finding many cases that required a lot of tokens they simply started to run agent loops feeding each other.
Absurdly wasteful but Goodhart's Law almost never fails.
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