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Why would you be absolutely no fan of a sure technological improvement? Is it because of the personal threat to professionals? Not commenting personally on you

Why would you be absolutely no fan of a sure technological improvement? Is it because of the personal threat to professionals? Not commenting personally on you here, but I am very surprised at programmers' lack of nose for opportunities and how, after realizing GPT could do coding even before replacing retail and industry jobs, coders are completely on the defense. Is it a threat to job availability and security? Yes, but programmers have long been to other professionals (doctors even?) what AI is now to them (I was a coder too). Well, tough luck, the world changes and fast, better to try to create and carve out a new job or business idea for yourself than stand on denial of something that, good or bad, could either make or break humanity, but humanity has no say on the inexorable progress of ideas. This actually is science right here, don't tech people embrace science, or only when the collateral damage is elsewhere and not on them?

rf15 4y ago
The technology's hype precedes it whenever you try to engage with it. On the surface, it looks a lot like the bitcoin hype, and if you remember IBM Watson you might get the idea that nothing much will come of it. So for me, I will keep using it, but I have nothing but disdain for the people worrying about AI overtaking the world, claiming this will revolutionise everything/etc.. Especially since this technology is almost good enough to tempt lay people to believe the statistically related words to your query would mean anything. In fact, iirc this has already happened and e.g. caused a suicide.
zelphirkalt 4y ago
I think many are not actually against usage of these kinds of ML models in general, but against what is done using them right now: Code laundering, violation of licenses, intransparency, training on personal data, no responsible person to talk to, no way of having data removed, that one does not want in the model or the model to train from, and more. Any of these can lead to dystopia. When we use computer vision to identify benign or malignant tumors, we might cost someone a job, but at least what that model was trained on can be known and we are not leaking personal data in the model and probably there is no violation of licenses or similar to the data that was used to train the model. The model is very limited in output. The consequences are kind of simple to monitor or predict, because the model can only be used in its specialized area of use. With the new crop of ML models the situation is different. Lawmakers were asleep while these things became popular and there is no knowing, how it will all pan out, because the output is of a more general nature, that can touch any subject, any area of expertise. No one knows what they have been trained on and whether there is anything in that training data, that should not have been used, and there is no simple way (that I know of) to operate out any such data after training the model.

rf15 4y ago

The technology's hype precedes it whenever you try to engage with it. On the surface, it looks a lot like the bitcoin hype, and if you remember IBM Watson you might get the idea that nothing much will come of it. So for me, I will keep using it, but I have nothing but disdain for the people worrying about AI overtaking the world, claiming this will revolutionise everything/etc.. Especially since this technology is almost good enough to tempt lay people to believe the statistically related words to your query would mean anything. In fact, iirc this has already happened and e.g. caused a suicide.

zelphirkalt 4y ago

I think many are not actually against usage of these kinds of ML models in general, but against what is done using them right now: Code laundering, violation of licenses, intransparency, training on personal data, no responsible person to talk to, no way of having data removed, that one does not want in the model or the model to train from, and more. Any of these can lead to dystopia. When we use computer vision to identify benign or malignant tumors, we might cost someone a job, but at least what that model was trained on can be known and we are not leaking personal data in the model and probably there is no violation of licenses or similar to the data that was used to train the model. The model is very limited in output. The consequences are kind of simple to monitor or predict, because the model can only be used in its specialized area of use. With the new crop of ML models the situation is different. Lawmakers were asleep while these things became popular and there is no knowing, how it will all pan out, because the output is of a more general nature, that can touch any subject, any area of expertise. No one knows what they have been trained on and whether there is anything in that training data, that should not have been used, and there is no simple way (that I know of) to operate out any such data after training the model.