This argument style is always humorous. The intention is something like “so humans are as bad as AI” when the original question boils down to something like “why would I replace humans with AI?”.
> The intention is something like “so humans are as bad as AI” when the original question boils down to something like “why would I replace humans with AI?”
If AI really is at human level quality/error rate (I don't think it is for general tasks, but there are some areas where it is), then the answer is typically cost and speed/capacity.
Have outputs from engineers traditionally been measured in cost and speed?
Remember, we aren’t just talking about the product you create. While you would measure deliverables by cost and speed are we ignoring something else? Something that could potentially be more important than either of those metrics?
> Have outputs from engineers traditionally been measured in cost and speed?
Yes. How long it'll take and how much it'll cost are going to be among pretty much any customer's first questions.
They're not the only considerations, and could potentially be outweighed by other concerns even when quality is the same, but I think they are the main drives of AI adoption in industry. If error rate is the same, a $1/hr (amortized) camera and machine vision model capable of checking 300ft of material for defects per minute will likely be preferred to a $10/hr human QA capable of checking 30ft per minute, for instance.
My understanding of your argument is (paraphrasing):
> > People try to excuse AI issues/failure modes by saying humans have them too, but even if they're equally bad then what would be the whole point of replacing a human worker with AI?
To which my response is that speed and cost are also important factors, which can often give AI the edge in considerations when quality/error rate is equal.
If you meant something other than that, you may have to specify.
The entire purpose of automation is to remove a capacity limited human from a continuous workflow because the workflow is more capably achieved with fewer errors than the human
If I have a choice between a deterministic traffic light and a non-deterministic traffic light which one would I use?
And yes, before you say “this isn’t a comparison of non deterministic and deterministic tools, this is a comparison of two non-deterministic tools” think about what my next question might be.
I am unaware of any healthy human who confabulates things as arbitrarily and disastrously as a SOTA reasoning model. It is childish to say stuff like "lawyers always made up court cases" - no they didn't!
That is the entire industry of business consulting.
Boston consulting group Bain and MacKenzie make billions of years completely making shit up. same thing with Ernst and young and any of these organizations that make these “future of (insert market)” reports
Again, they never made up totally fictional citations or any otherwise immediately falsifiable statements. In fact it is the opposite problem: technically these reports are quite clean and up to finest MBA standards. The BS is ideological / methodological / social / delusionally optimistic strategizing, and so on. This BS involves the most powerful and haziest forms of human cognition. Consultants "making stuff up" really is not the same thing as a frontier SOTA LLM being unable to summarize a document without making up a few numbers.
Look, I don't spend most of my time online criticizing AI progress. But what does your response even mean? People hallucinating work and solutions isn't commonplace at all, right? What industry do you work in where people hallucinate with frequency?
I can't speak to GP's intention, but I've personally witnessed a guy on my team who was trying to position himself as the go-to technical dude. He was jockeying for a management role. When QA or customer support had questions about our products, he'd always have an answer. I would say that at least 50% of the time, his answer was completely fabricated nonsense. He'd wildly misrepresent projects that his teammates were working on. I also saw several incidents of cargo-cult programming from him. Bizarrely, this never bit him in the ass and now he's a middle manager at a FAANG. This experience leaves me without much hope for the future of software development as a career.