Lately, one reads a lot of statements with the preamble “Artificial intelligence presents opportunities and challenges…” But is this the right way to frame the conversation? Because if we’re talking about creative professionals and their industries, it is probably more accurate to say that generative AI presents clear threats and some opportunities. Although we are trying to predict future outcomes, and many expectations about AI (good or bad) may not come to pass, if generative AI is an existential threat to potentially millions of creative professionals while offering opportunities for a few, then it is wrong to begin the discussion as if opportunity and challenge are balanced forces.
Take, for example, the tentative agreement reached between the Writers Guild of America (WGA) and the motion picture producers, which includes the following provisions regarding the use of artificial intelligence:
- AI can’t write or rewrite literary material, and AI-generated material will not be considered source material under the MBA, meaning that AI-generated material can’t be used to undermine a writer’s credit or separated rights.
- A writer can choose to use AI when performing writing services, if the company consents and provided that the writer follows applicable company policies, but the company can’t require the writer to use AI software (e.g., ChatGPT) when performing writing services.
- The Company must disclose to the writer if any materials given to the writer have been generated by AI or incorporate AI-generated material.
- The WGA reserves the right to assert that exploitation of writers’ material to train AI is prohibited by MBA or other law.
These conditions prove the point in that they primarily seek to mitigate the threat of AI while opening a narrow and conditional window for the opportunity to use AI. Safeguards like these are necessary because it can be assumed that producers and show runners will be tempted by the prospect of paying fewer writers to “collaborate” with generative AI to produce scripts. But even if that approach were to prove effective (and there are reasons to think it would not), a writers’ room of, say, two instead of ten is not necessarily an opportunity. And perhaps not even for the show runners for very long.
Thinking solely about the U.S. economy, those laid-off writers would represent eight middle-class jobs lost—eight people who would curtail, if not cut off, their entertainment expenditures while they take the “opportunity” to ply their skills in other fields that may also be shedding jobs due to AI. If AI were to reduce the workforce in the entertainment industry alone, it would suck but could potentially fall within the principle of creative destruction. But if AI decimates work across multiple sectors at the same time, then products, including TV shows and movies, will lose customers, thereby nullifying those short-term savings gained by laying off those eight writers.
Meanwhile Creative Work Would Start to Suck
Beyond considering whether generative AI is an opportunity in cold, economic terms, it is hard to imagine outcomes that do not either diminish the cultural value of creative expression itself or trigger a rebellion against AI-generated material and dash the ambitions of the tech developers. In this regard, the “democratization of creativity” is a woefully ignorant goal as well as a dishonest talking point.
The promise that generative AI will “democratize creativity” should be read in the same light as Big Tech’s promise to “democratize information,” which has proven disastrous for democracy. Just as searching the web for “information” does not make the individual a journalist, instructing a generative AI to render ideas into expression does not make the individual an artist. And just like we continue to founder in a sea of disinformation, there is no broad, social value in “democratized” art any more than there is a market for children’s drawings tacked to a million refrigerators. If everyone is an artist then nobody is, and the value of creative expression diminishes accordingly.
That the creative process can be reduced to an algorithm which can learn how to write, draw, paint, etc. cannot be wholly denied when generative AIs are already doing these things and will presumably get better at doing them. However, the expectation that generative AI can or should displace artists may be the apotheosis of the TechBros’ enduring cynicism about the value of individual creators. In the trenches of the “copyright war,” creative professionals have been accused of being self-important, greedy, rent-seeking, whiners unwilling to get real jobs. And now that Big Tech is releasing tools that promise to obviate the need for creators, the newest hashtag claims that professional artists enjoy a #CreativityPrivilege that will finally be disrupted. In this context, generative AI can be seen as tech’s nuclear strike in the copyright war to prove once and for all that “original expression” is an illusion and, therefore, that any rights associated with original expression are a mythical construct that must be abandoned.
This impliedly jealous relationship with artists is an extension of the problem that the tech-utopian, anti-copyright crowd has never quite understood what artists do or why they do it. For instance, artistic output is not solely the result of interest plus training. Many great artists never receive formal training, and many need to escape formal training to find their own voices. Every artist will eventually, if not continually, go through a process of learning and unlearning various “rules” to make the craft their own. It may be a cliché to think of the artist as suffering or broken, but it is certain that the artist is sensitive to the world in a way that she is moved to respond through expression. And these are just some of the unpredictable human qualities that no computer can emulate with the math of probability outcomes.
Although it is plausibly argued that a creative-minded individual might have a disability which AI can help overcome, citing this hypothetical to justify the “democratization” narrative comes with a few caveats including: 1) enabling the few does not justify displacing the many; 2) if AI devastates the professional, creative ecosystem, the newly enabled artist can only be a hobbyist among millions of other hobbyists; and 3) if anyone believes the billion-dollar investments in generative AI were made with the intent to help someone with cerebral palsy become a painter, I’m calling billion-dollar bullshit. That may be a positive effect, but it is not the purpose of these machines.
Could the Models Simply Fall Down?
If generative AIs were to displace enough professional artists, it is possible that entropy will demand that the models exhaust their capacity for new outputs—let alone outputs that are of any interest or value. If we remove, say, one million working artists from the equation over the next few years, what will continue to feed the training models? Is the “sum of all human output” as of today sufficient to enable a generative AI to produce infinite, relevant expressions indefinitely? Maybe. But not necessarily.
Because artists are people who respond to the world through expression, timeliness and context matter a great deal. There are many reasons–from aesthetics to subject matter–why theater of the 19th century or television programs of the 1980s or ad campaigns of the 1960s are anachronistic to a contemporary audience. Yes, certain works endure or become freshly relevant as remakes because human experience is, in part, cyclical. But it is the artist’s sensitivity to the contemporary world that makes those connections, and the process of synthesizing that into creative expression is often instinctual as much as it is intellectual.
Yes, artists recycle and build upon prior works, but the relevance of a new expression at a given time and place requires a connection with audience that, again, is not merely the result of a probability outcome. This anticipates the likelihood that a lot of AI-generated work will be good enough but not necessarily good—a concern that directly affects the market for commercial art where many creators make a living.
For example, the stock music market for commercial use is built on a network of composers with the skills to produce a variety of tracks based on familiar and, often popular, music. If generative AI can adequately produce similar tracks by cutting out the human composer, the market for many composers is in peril. But again, if AI were to kill off or dramatically reduce new, human composition, it is conceivable that the “composition machine” might eventually fizzle out as it tries to burn the same fuel over and over.
No doubt, artificial intelligence will seed new opportunities, though I maintain that these are in fields other than the production of creative work. If the digital revolution in the creative market has taught us anything, it is that these technologies are generally an opportunity for owners of the tech at a tremendous cost to professional creators. Without the right safeguards, AI could exacerbate this trend in ways that will cost everyone.
Photo by: robcaven
