Generative AI and Human Creativity: Both Can't Flourish

As an arts journalist and practitioner, I've been immersed in creative process and creative economies for decades. What I've learned there gives me sincere concern when it comes to the future of human creativity, on individual and collective levels – because I also see generative AI proliferating. 

AI is problematic with respect to labor rights, the ethics of intellectual property, and environmental impact. Those are all very real issues, and I think about them often. Yet my focus here is, again, on individual creativity and collective creative economies. 

To ground this discussion, I think one understanding is key, one that I'll say until I'm blue in the face: generative AI uses what has already been made. It's a glorified search engine and aggregator, nothing more and nothing less. 

It “relies on data…and learn[s] how something ‘should’ sound or look by analyzing huge amounts of existing work,” explains Milan Ehrhardt. As one concerning potential of many, the result of that process could be severe depreciation of how we make and collectively refine art.

Generative AI versus the solo creative act

The aggregation of what has already been created is what makes generative AI unique. Mohammed Randeree rhetorically asks:

Would we criticise a writer for using a spellchecker? Would we shame a musician for using a digital synthesizer instead of a traditional piano? Would we devalue an architect’s blueprint because it was rendered using AutoCAD instead of hand-drawn?"

Yet this argument misses that fundamental uniqueness of generative AI. It is not simply a tool to assist in creative process – like spellcheck, a synthesizer, or AutoCAD – but a new kind of creative assemblage. Rather than something new, it is a hodgepodge of what has already been made – held together by digital duct tape (quality can leave something to be desired…in this writer’s humble opinion, the final result can just come off shoddy and artificial). It is not just a calculator, as some argue. 2+2 = 4 anywhere and anytime. Creativity, however, comes in adding different numbers and getting different results. 

Creators, at least honest and observant ones, recognize that such assemblage is where the art is really made: in structure, composition, transition, editing. The raw materials – the notes, the shapes, the colors, the steps – that’s just the start. Learning how to go from start to finish, how to work in and through creative process, takes time and effort. Like any human endeavor, it doesn’t just happen. It is learned, refined, and crafted.  

Randeree points out that generative AI can allow writers to produce an article in minutes "rather than spending hours crafting an article from scratch.” Yet here’s the crux of the thing: hours spent crafting an article from scratch is how one learns to write. Did this writer love her freshman writing seminar, the constant revisions my professor asked me for and the tense hours in which I implemented them? Not at all. 

Yet I daresay that because of all that, and similar hours spent struggling over writing, I can write (perhaps passably, at least). And I wouldn’t trade that away. 

Yes, it takes time. Yes, it can be incredibly challenging. When we bypass such invested time and struggle, however, what do we lose? Nothing less than the ability to create, in my estimation. 

Generative AI vs collective creativity and its evolution

Even more concerning to me is this question: what happens when more and more of us don’t learn to write – or paint, or compose music, et cetera, et cetera – because we instead opt for the digital duct-tape? What happens to our individual abilities to engage with creative process and make something with it? What then happens to creativity and creative output more collectively? 

Here's my sense of it: art does not advance and evolve, but only stagnates.

Art movements throughout time – Rococo, Baroque, what have you – happened because artists worked, struggled (yes, again that is part of it), and inspired each other. Over time, those artists made new things – new things part of collective evolutions. Artmaking happens individually, but also in communities as well as a wider cultural milieu. Those are the structures in which art and art movements happen. 

I see the increasing use of generative AI as a true threat to that process – and thus the advancement of art as a human phenomenon. Personally, I am not willing to sacrifice that for the sake of ease and efficiency.

Creativity is inefficient, messy, and human

That’s often where arguments for AI lie: efficiency, in saving time and money. What used to take hours to create can now be made in minutes. And who wouldn’t want that? I like saving time as much as the next person. That’s only logical and rational.

Here’s the thing, however: creativity isn’t necessarily efficient, logical, or rational. Ehrhardt, in a rather even-handed analysis of AI and creativity, concedes as much. Art is human, and “humans are full of contradictions. We change our minds, get struck by random ideas, and sometimes discover breakthroughs by mistake or frustration,” he explains. 

Many of our world’s greatest classics took a long, winding, and sometimes torturous road into being. Process can go from extremes of high inspiration to severe creative block. “Mistakes” can be incredibly fruitful. And there’s no predicting any of that. Art expresses our humanity, and humans aren’t always efficient, logical, or predictive. We can’t always predict or fully understand ourselves. 

Yet that waywardness offers a unique reward; in an analysis arguably even more pro-AI than Ehrhardt’s, mind you, Daniel Kim argues that “there’s a magic to creative self-expression; it’s joyful, it’s thrilling, it’s play.” And that's before we get to the magic of what it produces.

Sure, sometimes the world calls for a level of predictability and rationality – so let’s look at this issue through that lens. By currently available evidence, will AI negatively impact human creativity and creative economies? Kim claims that it will not have that “thawing effect”. Yet that effect is already at hand. 

People are already getting laid off because "AI can design that.” Artists are losing commissions. Creatives in various industries are seeing work that would have once been theirs go to a machine. That’s even before we get into the fact that AI may well be sourcing from their work without compensating or crediting them. 

In a broader view, if we apply a value of efficiency to art, we may very well lose entire art forms. I’ll point to concert dance here (and I acknowledge my bias as a dancer, dance critic, and ardent enthusiast); it’s notoriously expensive to create and almost impossible to fund through ticket sales alone. Most dance companies therefore rely on individual donors and nonprofit grants to fill that fiscal gap. 

A cold, calculating market perspective would scoff in the face of that environment. Is that enough to wave goodbye to an entire artform, to let it dwindle away simply because it is inefficient and impractical? I, for one, would sorely mourn it. 

It all surfaces the important question: what do we lose when efficiency is our sole focus? What do we sacrifice on its altar? Not anything I'm willing to. I hope I’ve given you pause before you might be. 

Works Cited

Kim, Daniel. “Dethroning Creativity: Why Does AI Art Make Us Feel So Icky?” Seen and Unseen. 14 March 2023.

Ehrhardt, Milan. “The Human Touch: Why AI Will Never Fully Replace Human Creativity.” Medium. 13 February 2025.

Randeree, Mohammed. “AI, Creativity, and the Need for a Cultural Shift in Thinking.” Medium. 3 April 2025.