It's not that LLMs (I think that's what we are talking about when talking about AI) are not that useful. They are. But the most straightforward way to use them is to generate walls of text, which contain a lot of BS. In order to consume all this text and make sense of it, LLMs are used which reshuffle that BS into more BS but with less context. In the end, a human is presented with total BS that looks very plausible and if they don't critically evaluate it before forwarding to their higher-ups, they put their reputation at risk.
1. They are being forced to use it vs them organically adopting it
2. They are now have to do more work than before to get the same outcomes
3. The actual gains in productivity vs what’s being portrayed by the management & marketing material doesn’t add up
4. Their career growth and rewards (read income) now is being dictated on meeting the said productivity gains
5. There is a cognitive backlog that is building up. People know less and less about how things work.
6. But they are still responsible for the work in case AI fucks up.
7. They risk burnout because the mundane tasks that broke up the day, no longer exists. They have to churn out 8 hours of cognitive output which is the fastest way to burnout.
8. It is very clear that the adoption is being pushed down with the end goal of leaving people out of a job
9. And the management has quickly gone from “we’re all a family and we want to make the world a better place” to “fuck you plebe, make me millions or face starvation”. The amount of disrespect for employees from the management class in the last few years has been astounding.
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[ 8.3 ms ] story [ 121 ms ] threadI really only use it as a better search engine since outlook search is completely crap.
The Code it makes is too verbose. If I can do it in 7 lines, I don't need 60 thrown at me
2. They are now have to do more work than before to get the same outcomes
3. The actual gains in productivity vs what’s being portrayed by the management & marketing material doesn’t add up
4. Their career growth and rewards (read income) now is being dictated on meeting the said productivity gains
5. There is a cognitive backlog that is building up. People know less and less about how things work.
6. But they are still responsible for the work in case AI fucks up.
7. They risk burnout because the mundane tasks that broke up the day, no longer exists. They have to churn out 8 hours of cognitive output which is the fastest way to burnout.
8. It is very clear that the adoption is being pushed down with the end goal of leaving people out of a job
9. And the management has quickly gone from “we’re all a family and we want to make the world a better place” to “fuck you plebe, make me millions or face starvation”. The amount of disrespect for employees from the management class in the last few years has been astounding.
It seems there is a structural problem, since practitioners have to take responsibility when AI makes mistakes.
The best thing should be happened is that AI practically helps with the tasks of practitioners
Should not use energy to verify how AI works well without accident, it is that workers can use energy somewhere else, but it is yet coming.
Because there is currently a bottleneck in adopting AI models regarding whether the data is AI-ready. We must solve this part.
Then I expect the conflict to be resolved because AI is said to help me without actually threatening me at work.