I am currently surrounded by hyperventilating corporate and country level leadership who are fully swept up and captured by the AI craze.
I have seen some wild failure modes from people who are outsourcing their thinking to LLM. Amendments to clauses that don't make English sense. Multi-paragraph long replies in emails that say nothing specific to the issue at hand. Responding to questions with "AI says this" (but I asked you, not the LLM). Leadership wants us to embrace AI but there is no product for the layperson, it feels like everything is front end + generic prompts + $LLM_API_key. People want to make customer service bots that have access to personal data.
I feel like software devs are so lucky in that at least people in your field can see an LLM for what it is and harness (no pun intended) it appropriately. As a lay user, no such luck. Leadership and purse strings are far removed from IC work and don't understand why an AI product wouldn't work, they've heard otherwise in their circles, you had better make it work so that they can claim to have delivered an AI transformation this year.
Enter Zitron.
Zitron is a woo-pushing grifter (his product: his stance on AI). Even without examining his reasoning or the accuracy of his predictions, Zitron is hard to listen to. Mostly, he shouts out a constant barrage of bare assertions that his research is thorough and irrefutable and the doom is coming and ever "AI booster" who disagrees with him is an idiot, all the while without actually spending time arguing his point.
But Zitron feels like one of the few people actually pushing back against this craze.
I would very much like a better argument for a position that I support, please and thank you.
I'm surprised this happens between workers within the same knowledge domain. If you're a software dev asking another software dev for an opinion on code, can't you just... talk shop?
In my experience this sort of thing happens all the time when something has to cross between different knowledge domains and the sender doesn't apply their mind in order to co-operate on the issue at hand.
In the pre-LLM past, the sender would add no value, acting as a simple email forwarder, and they would blame you for the delays caused by your inevitable clarificatory questioning. But I always had a defence, which is that your email had no inputs and I had to ask questions to clarify.
Now, though? With LLMs, they just run whatever it is (contract, memo, policy) through whatever LLM they have available and paste the output in an email, giving them the appearance of having done work and added value to the project.
But their LLM outputs don't make sense, or don't apply to our organisation, or is a fluffy and abstract "right answer" with no connection to the specific concerns of the business. Parsing it is a chore, and takes time.
And since now I am the only one actually taking that time, I become the visible cause of the delay.
It's infuriating. Any tips on how to deal with this would be greatly appreciated.
The motive appears to be to get tax credits as opposed to becoming a full-on patent troll, though with how quickly China is speedrunning their version of capitalism I would not be surprised if it turns into patent trolling.
Their behaviour overall is really giving me mixed feelings, because the Bambu A1 I have is an absolutely amazing machine for the price, and I've been casually in this since the Printrbot days.
As a layman, this too strikes me as the problem underlying the "confidently wrong" problem.
The author proposes ways for an AI to signal when it is wrong and to learn from its mistakes. But that mechanism feeds back to the core next token matcher. Isn't this just replicating the problem with extra steps?
I feel like this is a framing problem. It's not that an LLM is mostly correct and just sometimes confabulates or is "confidently wrong". It's that an LLM is confabulating all the time, and all the techniques thrown at it do is increase the measured incidence of LLM confabulations matching expected benchmark answers.
I saw a post on this subject in the android subreddit back in 2019 [0] and it was clear that everyone had already accepted by then that the market was too small to sustain this. I too loved Sony's series of compact phones - the XZ1 Compact is still one of the best phones I've ever used.
It is only going to get worse. Most of us who were young adults when the iPhone was announced are in our 40s now, and presbyopia is a real thing. In a few years my daily QOL will be better served by a bigger phone and I suspect many people around my age are feeling the same thing. The "small electronic accessory I bring around" niche will be filled by smartwatches.
> Congratulations: you have successfully turned your cool idea into a chore.
The article gave me a vague, off-topic sense of unease but your comment crystallised the feeling for me.
I really wish less emphasis is placed on this kind of blue-sky, "strategic" thinking, and more placed on the "chores". Legwork, maintenance, step-by-step execution of a plan, issue tracking, perspective shifting etc. are all, in my opinion, critically important and much more deserving of praise and respect than so-called "strategic" thinking.
Which, IME, most people can't do anyway! After they've talked their big talk you suggest that there's a practical, on-ground problem and they look at you accusingly, like you're sabotaging their picture. And I'm like, no, my friend; reality is sabotaging your picture, it's just the two of us here and you're not losing any face by me pointing that out, and also if you were an actual strategic thinker you'd have taken my on-ground problem into account already...
This might come from childhood and problematic praise patterns. You can grow to both crave praise and surprise, but at the same time when you get it not really value it. You might be interested to do impressive work as play when you don’t know how it will pan out, but if you don’t feel like it is interesting enough then you are demotivated.
I think it is important to be able to strategise, especially if you can delegate parts of the work. If you cannot delegate, there needs to be a balance with capacity for grunt work. One way to address it perhaps is learning to get in the zone and enjoy ongoing work as a process. Unfortunately, sometimes it is hard to snap out of big picture view and get to it.
I’ve found the best strategies are the ones you can abandon. clearly defined tactics and an appropriate application of people and resources require a quarterback with an ability to audible.
It’s possible to make no mistakes and still lose, it’s when people get offended about something they are wrong about that creates a tolerance for Pyrrhic victories.
I played around with the website. I will take the author's advice to not take it seriously.
Many of the changes are active voice to passive voice. It might sound more polite, but in reality comes off as sneering or condescending.
For e.g., if I've already told you something, I usually change communication channels to a more casual one (pick up the phone, pop my head up, walk over, go on a chat channel) and say: "hey, that question you had, it's already addressed in my email, see this bit over here...".
I would not, as the website suggests, say any of this:
- "There seems to be a disconnect here as this information has already been provided."
- "The information has not changed since the last time it was communicated."
- "As indicated prior."
If you did this to me, I would think you are a jerk.
I have seen some wild failure modes from people who are outsourcing their thinking to LLM. Amendments to clauses that don't make English sense. Multi-paragraph long replies in emails that say nothing specific to the issue at hand. Responding to questions with "AI says this" (but I asked you, not the LLM). Leadership wants us to embrace AI but there is no product for the layperson, it feels like everything is front end + generic prompts + $LLM_API_key. People want to make customer service bots that have access to personal data.
I feel like software devs are so lucky in that at least people in your field can see an LLM for what it is and harness (no pun intended) it appropriately. As a lay user, no such luck. Leadership and purse strings are far removed from IC work and don't understand why an AI product wouldn't work, they've heard otherwise in their circles, you had better make it work so that they can claim to have delivered an AI transformation this year.
Enter Zitron.
Zitron is a woo-pushing grifter (his product: his stance on AI). Even without examining his reasoning or the accuracy of his predictions, Zitron is hard to listen to. Mostly, he shouts out a constant barrage of bare assertions that his research is thorough and irrefutable and the doom is coming and ever "AI booster" who disagrees with him is an idiot, all the while without actually spending time arguing his point.
But Zitron feels like one of the few people actually pushing back against this craze.
I would very much like a better argument for a position that I support, please and thank you.
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