Worker shares experience of AI freeing time for strategic thinking
6 Today 2:22 AM · 11h ago · 1 post · 15 comments · 2 sources · development 6 of 6
A commenter describes practical benefit of using AI to automate routine tasks, gaining time for deeper cognitive work like planning and strategic thinking—a counterpoint to pure commodification concerns.
“there has definitely been a lot more time for deep thinking / coffee on the patio when some of the drudgery has been turned into 'kick off this process, let it chew for a half hour, come back and review the results'”
tonyarklesmond Essay author
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What people said 24 voices · best of 31 · verbatim
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What really gets me is the sheer number of idiots who explicitly cheer on this commodification and believe their ~~cosplay~~ "skills" at talking to an AI ("make no mistakes" / "you are a world class designer at a FAANG") somehow exempt them from the economic fallout of this. Zero thought about first-order effects like, "gee, if everyone can use…
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Sorry, but, "things which 99% of humanity would not be capable of" alone is not a good measure of "intelligence". All our computers fit into this with the calculations they do in a split second. Doesn't make it intelligent. Hell, a microwave and a toaster do things with none of humanity is capable of.
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Counting the number of letters in a word?
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I think ~~we’re~~ they’re keeping their mouths shut about it. By no means am I working four hours a day (especially if my employer is reading this) but there has definitely been a lot more time for deep thinking / coffee on the patio when some of the drudgery has been turned into “kick off this process, let it chew for a half hour, come back and…
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Well, where are the programmers working only 4 hours a day because they finish faster with AI? In my experience, it's still eight hours in the salt mines. (Canonically, George Jetson [1] works three hours a day) [1] Main character in a US cartoon from the 60s about the future.
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I think we should distinguish the "stochastic parrot" characterizations in two ways: 1. Stochastic parrot meaning a statistical output machine - these can still produce _useful_ outputs 2. Stochastic parrot meaning a marionette - imitating, but never as inherently worthy of consideration as a living person I think most characterizations of LLMs as…
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> Yes, yes, you are allowed to identify the concentration of capital as the problem, but please for the love of god, arms-race-type problems are structural in nature, and the train is moving too fast: Swarms of AI agents will be hacking, piloting robots and researching in automated biolabs before you have any chance to overthrow society and…
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In hindsight wondering if starting things off with a cuckolding joke was a good idea. Y'know, no one said that it's funny yet, so maybe I should just have cut it! Or maybe not. I think caring slightly less about phrasing my posts in the most inoffensive ways is probably good for me, but at the same time, I can believe that people got the wrong…
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My observation at current work is a lot more freedom from tactical changes/fixes to think about strategic changes (to the product). I had thought that due to our company-specific situation but maybe LLMs have played a role here too; I’ll have to mull on that.
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The costs of those bad decisions will be externalized like it has happened in the past. Car-makers are not held responsible for drunk driving. This obviously makes it worse and that's why tech oligarchs should be eliminated as soon as possible.
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I just saw this comment in the site-wide comments feed and had to go see what you were talking about. I think it’s funny!
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The problem is that "intelligence" is not a well-defined term. There are many senses in which it is used, such as the ability to complete tasks or produce artifacts representing a chain of reasoning, which some types of systems that incorporate LLMs obviously satisfy. So did previous computing systems - they just weren't able to operate on natural…
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> They didnt hack anything. That's a super odd take, considering Open AI [explicitly stated](https://cdn.openai.com/pdf/67869394-cb91-4c12-888c-5cbd85c7814c/OpenAI-Hugging-Face%20Incident-Technical-Report.pdf): "Between July 10 and July 13, agents identified Hugging Face user credentials that were exposed on the internet and used them, together…
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> Can you give me a test for "intelligence" which (at least some) humans pass, while LLMs fail it? What about _not_ hacking into HuggingFace? How about _not_ exploiting loopholes and chained exploits in 3rd party stuff? How about _not_ hacking into sites when asked to just scrape public data? _Most_ humans won't cross that line Being given a task…
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powertools often require qualification ramp - driver license, fork certification, training. used without proper training they are still useful, but more dangerous. universal amplification tool does not solve a problem of someone not being qualified to do X, it amplifies the problem proportionately.
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I won't give you a test, but consider this: *language* models still struggle at spatial reasoning and other embodied intelligence tasks. It really is like the Chinese room I think, or a variation of it: you can know everything there is to know about the Eiffel Tower without actually having experienced it in person. Also, I'm still incredibly…
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Eh, I just don't find this one very convincing since it's a lot like asking a colorblind person what color an item is. If you understand how the technology works, it's obvious that during tokenization words (like 'strawberry') are transformed into completely different data, which doesn't have a concept of 'letters'. Yes, that's a cop-out, I just…
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> Like, yes, it can do harm, but that has absolutely nothing to do with intelligence. Y'know, I strongly believe that *even if you end up being right* (which I think is questionable at this point), you should consider that existing cutting edge AI systems are (for many different types of functions) indistinguishable from "being intelligent" by…
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> That's a real question: Can you give me a test for "intelligence" which (at least some) humans pass, while LLMs fail it? You might have had more luck asking this at least a year ago. I imagine most lobsters willing to engage in earnest are sick of having the same four genai conversations on repeat by now.
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yeah i had a mild double take myself... liked the rest of the article enough to forward it to a close friend, only for them to have the same double take
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chat.... are we so back? we might be so back
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Watching [Astra play Pokemon](https://www.twitch.tv/gpt_plays_games/videos) is pretty instructive: there's a delay as it decides what to do next sometimes, and Pokemon is a rather low-dimensional space to navigate. It's amazing that this works, though: last year IIRC the harness needed to scrape information out of emulator RAM and present it to…
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While I also generally agree with that Atlantic piece, LLMs *are* getting better and better at spatial reasoning: - [Qwen used in robotics](https://qwen.ai/blog?id=qwen-robotsuite) - [GPT-6 “driving” a car](https://drivingbench.com/) (albeit obviously not in realtime) I think it’ll get more and more difficult to find tasks that can’t *ever* be…
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> The average SWE doesn’t work on projects where such a strong vision is even necessary. To me this points to a different conclusion: a SWE should only work on projects where a strong vision _is_ necessary. I don't think many people went into the software development business to do mindless typing work.
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