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Comment by elil17 | Hacker News Reader

Until you realize they’re dumb. I don’t think people are so naive that they’ll ignore clearly dumb robots that they work with every day.

I do think people will make those mistakes with robots they’re not that familiar with.

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Experience suggests that people are all too willing to unthinkingly follow instructions just because "the computer said so".

https://theweek.com/articles/464674/8-drivers-who-blindly-fo...

I would say GPS is in the zone of having such a low error rate that people can't process it right. If, as an example, GitHub Copilot added a security vulnerability in one in ten thousand lines of code, that would be a disaster because no one would double check it's work. Currently Copilot adds a security vulnerability in one in ten lines of code (made up number), so people with even a tad of experience using it know not to blindly trust it.

I don't mean to dismiss the issue of over-trust in computer systems - I think it's a very serious issue, and one that needs to be addressed across a lot of disciplines.

People have certainly done some dumb things in the GPS vein. That said, if you're taking confident navigation directions from either a person or a computer, it can be hard to make a split-second decision that something "doesn't seem right." (Obviously some of the more extreme cases still shouldn't happen.)

> People have certainly done some dumb things

This sentence doesn't need to be continued. It's already the ultimate state of affairs since forever.

That's true if your only goal is to generate truthful text. But if you're trying to generate useful text, continuing the sentence is necessary.

Maybe that'll be the next step once LLMs get very good at generating truthful text :)

Challenge the assertions of of a shiny-confident-robot and you will be challenged right back with, according to what shiny-confident-robot?

And no, first hand observation doesn't count, because that's mere anecdote.

It's an anecdote which is meant to illustrate a widely observed behavior among many humans: we're better at accounting for frequent errors than we are at accounting for rare ones. This is well established in the field of human reliability analysis (HRA). Take a look at the HRA method HEART (https://www.epd.gov.hk/eia/register/report/eiareport/eia_224...). There are three different error producing conditions (EPCs) related to rare failures (EPCs 1, 3, and 12 in table 1.3).

As for my argument that people who frequently work with this technology aren't going to be so susceptible to "shiny-confident-robot" - that is based on my first hand observation. But the counterargument (people trust LLMs too much) is not based in data either. The Pearce, et. al paper everyone cites about security vulnerabilities didn't look at how much people trust the code, just how frequently it gives wrong answers (https://arxiv.org/pdf/2108.09293.pdf). An actual user study (n=20) showed that Copilot users engage critically with the tool by examining and testing suggestions, comparing multiple suggestions, and crosschecking it against documentation (https://arxiv.org/pdf/2206.15000.pdf).

They're not dumb. They're management consultants!

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