AI Mania Is Eviscerating Global Decision-Making | Hacker News Reader

AI Mania Is Eviscerating Global Decision-Making

ludic.mataroa.blog

88 pointsbertman13 comments

This matches my experience. Leadership gives us a weekly "AI is amazing, it's world changing, we're using it for everything". Every project using AI is at least six months late. My team gets praised for using it effectively but we're the team that turned it off. We had an SLA violation because Copilot hallucinated a service we don't have that it claimed was down and we can't convince ops that the service literally doesn't exist. Any amount of time AI could have saved me has been swallowed up tenfold by everyone else having access to it and I hate what work has become.

I work at F500 company and this is not my experience at all. We are rolling out claude to basically everyone in my division and people are doing pretty amazing things with it and the uptake is high. Building “skills” around specific workflows has been very useful. We have regular training where we meet to share “skills”. Its exciting. Its not all rainbows but the impact and growth potential is very clear to me. This blog seems to reflect a 2024-ish state of affairs.

Agree. It’s good and exciting. It is so strong at information retrieval. Much enterprise work is finding, categorising, slicing, summarising info.

Querying SQL, searching Sharepoint, AWS/Azure CLI, log analysis… etc. Amazing.

ABAC/RBAC, data labelling, scoped tokens, Purview all v helpful in managing risk.

What gives you basis to believe and accept that all of the above is exhaustive, complete and devoid of fakes? That "finding" finds ALL what exists and NONE of what does not exist? Ditto for categorising, summarising and labeling?

There is no fundamental guarantees provided by LLM architecture, so to assert anything of sorts would require manually executing the operation and comparing the results. And why not asserting the correctness is not negligence or fraud?

I am not saying it is impossible, but so far I have not found any explanations that would close this huge gap in logic for me. LLMs themselves "admit" the gap cannot be explained rationaly.

It's wild how different this person's experience has been from mine. I guess I could see how a team of people would see lower (or no) productivity gains than an individual when it comes to using LLMs. My theory is, as teams scale, doing work faster is always a coordination problem and that coordination gets harder as you add more workers, so each worker has more and more of their productivity stripped as pure overhead. This happens with LLM "workers" as well, except an LLM cannot effectively supervise itself whereas a human worker can, so adding an LLM adds the overhead penalty to the human operator. And human operators begin to drown in that overhead, and their own personal productivity suffers.

Of course not everybody is like that. But I totally believe him that he's met people who lose all reason when confronted with AI. I've met them too. We've all read articles about leaderboards to waste as many tokens as possible, companies burning through insane AI budgets in a month, the ridiculous scale of investments by AI companies. I've seen many articles explaining how they're never going to get that money back.

Nobody is denying it's a useful tool, but there are absolutely people completely losing their minds over it. Often people who don't really understand it, but do control a lot of money.

I don't necessarily buy this view as plausible other than the fact that in my experience the majority of large companies are dysfunctional politically and technically.

"All of the AI projects we have observed as a team are failing. Every single one – we have seen 0% success in a year and a half, not only amongst projects we have been asked to participate in2, but even within projects that we have observed in passing while doing totally unrelated work."

Sounds like a skill issue

I don’t know if you intended it, but that was a good pun

another world-is-ending chicken screaming

just don't use AI

don't use computers

go run a farm or something

stop complaining and stop using

just enough with your AI hate

if it's not for you, fine, go do something else

The article is about how being seen as negative on AI is getting people fired, even if their grievances are legitimate. It's not really about AI itself, it's about the decision making around it.

Crazy how deep the misunderstandings run - Software companies today are like horse breeders when the car hit the streets in the early 1900s. ,Everything will change over the next years with LLMs’ is a resonable and risk adverse stance for someone (like a CEO) who’s job it is to secure the long term future of a company. Searching for the new ways around writing software is the number one job for C-lebel execs, as the danger of your competition figuring this out is absolutely real. So one thing you do is letting your company throw money at many different ways of trying to make using AI successful and learning as much and as fast as possible. And no - not using AI will jot solve your problem. ,Just use horses, right now that’s the best option!’ - I feel this is what the author wants to say - is not addressing the problem the CEOs have. Therefore I fear the misunderstandings will continue…

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