That is true. Take, for example, movies. Cinema studious with big budgets are usually very risk averse, simply due to the cost of failure being so high. So they have to make sure they can turn a profit. But how can you make sure any given thing will be profitable? Well, that is a prediction, and to predict anything, you need data to base that prediction on. Predictions are based on past events. And so they make sequel after sequel. They make things that have been proven to work. New things, by virtue of being new, don’t have tons of data (past examples) for them to make good predictions and so they avoid new things. This results in the homogenization of art. Homogenization induced by Capital, has Capital only sees value in profit, and thus, for Capital, only predictably profitable art is given the resources to flourish.
Machine Learning made images art the epiphany of this. All output is based on previous input. The machine is constructed to not deviate too much from the training data (loss function). And thus struggles to do things it does not have much data on, like original ideas.
I think that what we’re likely to see are parallel worlds of art. The first and biggest being the homogenous, public and commercial one which we’re seeing now but with more of it produced by machines, and the other a more intimate, private and personal one that we discover by tuning back into our real lives and recognising art that has been made by others who are doing the same.
That’s kind of already a thing. Just without the AI. Like in the example above, Capital wants predictable profit. Therefore only the most widely appealing, proven to be profitable art will get significant budgets. Creative and unique ideas are just too risky, and therefore delegated to the indie space, where, should any ever become successful, Capital is willing to help… Under the condition they get all the money (Think, for example, how Spotify takes most of the revenue made by the songs they distribute).
By “Capital” I mean those who own things necessary to produce value.
Yes, the example of films is a really good one that most people can clearly see. Among other reasons, I personally refuse to watch most franchises, sequels, reboots and crossovers because I find them extremely patronising.
While I’m disappointed that capital has crushed the opportunity to make a living from the arts for the vast majority of us I also think that this process is increasingly alienating creative people and pushing them to give up making work that ingratiates itself with a superficial, mundane and homogenous culture. For example more and more of the musicians I know are deciding not to release their music on Spotify, YT music et al because they see no point in it and feel insulted by it. Their creative paradigm is no longer shaped by satisfying these algorithms (values) and so they now have more creative latitude. I think this is necessary for art that has human value.
There are some experimental private funding models gradually emerging to support this but in the meantime I think it’s better for all of us if artists are willing to be poor than willing to sell out.
That is true. Take, for example, movies. Cinema studious with big budgets are usually very risk averse, simply due to the cost of failure being so high. So they have to make sure they can turn a profit. But how can you make sure any given thing will be profitable? Well, that is a prediction, and to predict anything, you need data to base that prediction on. Predictions are based on past events. And so they make sequel after sequel. They make things that have been proven to work. New things, by virtue of being new, don’t have tons of data (past examples) for them to make good predictions and so they avoid new things. This results in the homogenization of art. Homogenization induced by Capital, has Capital only sees value in profit, and thus, for Capital, only predictably profitable art is given the resources to flourish.
Machine Learning made images art the epiphany of this. All output is based on previous input. The machine is constructed to not deviate too much from the training data (loss function). And thus struggles to do things it does not have much data on, like original ideas.
That’s kind of already a thing. Just without the AI. Like in the example above, Capital wants predictable profit. Therefore only the most widely appealing, proven to be profitable art will get significant budgets. Creative and unique ideas are just too risky, and therefore delegated to the indie space, where, should any ever become successful, Capital is willing to help… Under the condition they get all the money (Think, for example, how Spotify takes most of the revenue made by the songs they distribute).
By “Capital” I mean those who own things necessary to produce value.
Yes, the example of films is a really good one that most people can clearly see. Among other reasons, I personally refuse to watch most franchises, sequels, reboots and crossovers because I find them extremely patronising.
While I’m disappointed that capital has crushed the opportunity to make a living from the arts for the vast majority of us I also think that this process is increasingly alienating creative people and pushing them to give up making work that ingratiates itself with a superficial, mundane and homogenous culture. For example more and more of the musicians I know are deciding not to release their music on Spotify, YT music et al because they see no point in it and feel insulted by it. Their creative paradigm is no longer shaped by satisfying these algorithms (values) and so they now have more creative latitude. I think this is necessary for art that has human value.
There are some experimental private funding models gradually emerging to support this but in the meantime I think it’s better for all of us if artists are willing to be poor than willing to sell out.