Comment by ryandrake
1 year ago
Imagine if your compiler just randomly and non-deterministically compiled valid code to incorrect binaries, and the tool's developer couldn't really tell you why it happens, how often it was expected to happen, how severe the problem was expected to be, and told you to just not trust your compiler to create correct machine code.
Imagine if your calculator app randomly and non-deterministically performed arithmetic incorrectly, and you similarly couldn't get correctness expectations from the developer.
Imagine if any of your communication tools randomly and non-deterministically translated your messages into gibberish...
I think we'd all throw away such tools, but we are expected to accept it if it's an "AI tool?"
Imagine that you yourself never use these tools directly but your employees do. And the sellers of said tools swear that the tools are amazing and correct and will save you millions.
They keep telling you that any employee who highlights problems with the tools are just trying to save their job.
Your investors tell you that the toolmakers are already saving money for your competitors.
Now, do you want that second house and white lotus vacation or not?
Making good tools is difficult. Bending perception (“is reality”) is easier and enterprise sales, just like good propaganda, work. The gold rush will leave a lot of bodies behind but the shovelmakers will make a killing.
I feel like there's a lot of motivated reasoning going on, yeah.
If you think of AI like a compiler, yes we should throw away such tools because we expect correctness and deterministic outcomes
If you think of AI like a programmer, no we shouldn't throw away such tools because we accept them as imperfect and we still need to review.
> If you think of AI like a programmer, no we shouldn't throw away such tools because we accept them as imperfect and we still need to review.
This is a common argument but I don't think it holds up. A human learns. If one of my teammates or I make a mistake, when we realize it we learn not to make that mistake in the future. These AI tools don't do that. You could use a model for a year, and it'll be just as unreliable as it is today. The fact that they can't learn makes them a nonstarter compared to humans.
Edsgar Dijkstra!
If the only calculators that existed failed at 5% of the calculations, or if the only communication tools miscommunicated 5% of the time, we would still use both all the time. They would be far less than 95% as useful as perfect versions, but drastically better then not having the tools at all.
Absolutely not. We'd just do the calculations by hand, which is better than running the 95%-correct calculator and then doing the calculations by hand anyway to verify its output.
Suppose you work in a field where getting calculations right is critical. Your engineers make mistakes less than .01% of the time, but they do a lot of calculations and each mistake could cost $millions or lives. Double- and triple-checking help a lot, but they're costly. Here's a machine that verifies 95% of calculations, but you'd still have to do 5% of the work. Shall I throw it away?
Unreliable tools have a good deal of utility. That's an example of them helping reduce the problem space, but they also can be useful in situations where having a 95% confidence guess now matters more that a 99.99% confidence one in ten minutes- firing mortars in active combat, say.
There's situations where validation is easier than computation; canonically this is factoring, but even division is much simpler than multiplication. It could very easily save you time to multiply all of the calculator's output by the dividend while performing both a multiplication and a division for the 5% that are wrong.
edit: I submit this comment and click to go the front page and right at the top is Unsure Calculator (no relevance). Sorry, I had to mention this
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