‘It almost doubled our workload’: AI is supposed to make jobs easier. These workers disagree::A new crop of artificial intelligence tools carries the promise of streamlining tasks, improving efficiency and boosting productivity in the workplace. But that hasn’t been Neil Clarke’s experience so far.

  • RagingNerdoholic@lemmy.ca
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    1 year ago

    Well, would you look at that, it’s playing out exactly the same as every other technological advancement ever. Instead of using it to reduce employee workloads and maintain an equilibrium of output, it exploits them by brute-forcing increased productivity with no changes to compensation and the capitalists hoard even more of the profits for themselves.

    • Peanut@sopuli.xyz
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      1 year ago

      Exactly what I keep saying when people start blaming the tools being used for automation. Productivity is up and up and up, but none of that has been given back to the workers in the past fifty years. If I try to find dialogue on that issue, I run into a mountain of blatant propaganda defending the continued robbery of the middle and lower classes.

      • RagingNerdoholic@lemmy.ca
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        1 year ago

        Temporarily embarrassed millionaires will lick the boots of capitalism in the naive hope of pulling themselves up by the straps

    • _finger_@lemmy.world
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      1 year ago

      Also the amount of work that it puts on IT, implementing new tech and not providing/approving the training (which only goes so far)

  • cerevant@lemmy.world
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    1 year ago

    In medicine, when a big breakthrough happens, we hear that we could see practical applications of the technology in 5-10 years.

    In computer technology, we reach the same level of proof of concept and ship it as a working product, and ignore the old adage “The first 90% of implementation takes 90% of the time, and the last 10% takes the other 90%”.

  • ShittyBeatlesFCPres@lemmy.world
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    1 year ago

    I really wish MBA programs and journalism schools would start teaching that technology doesn’t progress linearly (much less exponentially) forever. “Look what it can do today! Imagine in 5 years!” Is there still low-hanging fruit to pick? Because if not, it might be as good as it’s gonna be for awhile.

    There’s obviously exceptions where things have gotten steadily better for a very long time. But often, it’s a punctuated equilibrium situation around major scientific advancements. And way more often, business realities pause advancement. (Like maybe OpenAI’s next giant leap forward will have to wait on chip suppliers to expand capacity.)