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How much did photography "steal" painter jobs ?
(sh.itjust.works)
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this post was submitted on 01 Aug 2023
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It sure did have a big impact, comparable to what some people expect to happen soon with AI.
However, I think your framing misses the main point of why many artists today are wary about AI: They are not just being replaced, their own work is used as a building block for the tools that will replace them; and they were not asked for permission and don't even get any compensation for that.
If you have a basic understanding how AI works then this argument doesn't hold much water.
Let's take the human approach: I'm going to look at all the works of popular painters to learn their styles. Then I grab my painting tools and create similar works.
No credit there, I still used all those other works as input and created by own based on them.
With AI it's the same, just in a much bigger capacity. If you ask AI to redraw the Mona Lisa you won't get a 1:1 copy out, because the original doesn't exist in the trained model, it's just statistics.
Same as if you tell a human to recreate the painting, no matter how good they are, they'll never be able to perfectly reproduce the original work.
I’m just adding on to this.
Scale here comes in multiple layers, including the capacity/speed at which these technologies can be deployed, as well as the breadth of domains/fields/applications they touch upon, not to mention the unintended consequences when at scale. It’s not only they are much faster, cheaper, but they come almost all at once and have the potential to affect so many fields. Heck, “GP” means general purpose in GPT. Plus the effects of scale can be extremely unpredictable that we should not underestimate (disinformation campaigns now come much cheaper and easier, trust erodes even further).
I don’t know much about history so please correct me, but photography “replacing” painting may be quite specific, that painters could probably have adapted or switched to another professions. I think one commenter stated that the transition was “smoother”. In the case of these generative techs, this affects the livelihood of a whole bunch more of people (possibly both in absolute and per-capita number) that will need to grapple with what they’re going to do with their life, and have to do it fast.
One branch of the arguments I’ve been seeing is about capability comparison, sometimes even anthropomorphizing tech/companies. While I find that interesting and valuable intellectually, I personally think the conversations need to be more about the labor aspects.
Learning takes time and people need to eat. In the name of progress, society sometimes forgets or brushes over the “casualties” it leaves behind. I think many would benefit from this tech, but let’s hope they have a meal on their table doing so.
We don’t want a dystopian where they use these techs to generate the illusions of enjoying a feast over a big hotpot, while in reality it’s just a can of tomato soup for a family of 5.