Beyond the Algorithm: Why Human Creativity Remains Irreplaceable in the Age of AI
Artificial intelligence is generating poetry, images, songs, and content that make us pause and wonder: Did a machine just come up with that? As tools like ChatGPT, Midjourney, and others become more integrated into our daily lives, the boundary between human and machine creativity is blurring.
In a conversation between Mo Gawdat, former Chief Business Officer of Google X, and entrepreneur Steven Bartlett on The Diary of a CEO podcast, they go straight into the heart of this debate. Together, they explore the question: Can AI be creative?
Their answer is an enphatic yes. But as seductive (or scary) as that claim might be, it rests on a limited understanding of creativity, one that risks ignoring its deeper, systemic nature. In this post, I explore why creativity remains, at its core, a deeply human and socially embedded process, and why we should be careful not to outsource our role in it, even as AI dazzles us with its generative powers.
The Podcast View: Creativity as Novel Combination
During the show, Steven Bartlett offers a simple but compelling definition of creativity, proposing that it is rooted in novelty and synthesis: “Creativity, as far as I'm concerned, is like taking a few things that I know and combining them in new and interesting ways.”
To illustrate his point, he recounts asking ChatGPT to generate paradoxical yet true statements, and after checking some of the outputs on Google, he is convinced that the content produced by Chat GPT wasn’t pulled from any existing source, Bartlett concludes that “That’s the algorithm of creativity.”
He extends the argument to Midjourney, an AI art tool that generates images based on textual prompts: “It’s done what an artist would do—it’s taken a bunch of references that the artist has in their mind and merged them together to create this piece of quote-unquote art.”
Mo Gawdat echoes this sentiment, suggesting that what we call ingenuity, human creativity, is itself algorithmic: “Look at all of the possible solutions you can find to a problem, take out the ones that have been tried before, and keep the ones that haven’t been tried before. Those are creative solutions. He explicitly states that creativity is "an algorithmic way of describing a good solution that’s never been tried before,” and today we can get there with a prompt.
This view essentially equates creativity with computation. If creativity is simply the recombination of prior inputs in novel ways, then it becomes a kind of algorithm, a process of input, manipulation, and output that can, in theory, be replicated by machines. This mirrors a broader, long-standing metaphor in Western thought: the idea of the mind as a machine. Since the Enlightenment and especially since the rise of computer science, we’ve increasingly understood thinking in mechanistic terms: brains as processors, thoughts as data, learning as programming. This metaphor has deeply shaped our institutions, especially education. Schools often reward convergent thinking, standardization, and correct answers over ambiguity, exploration, and value-making. In such systems, creativity becomes a technical skill, a way of optimizing solutions rather than a socially situated, meaning-making process. When we view creativity as computation, we risk narrowing our understanding of it to something that can be efficiently taught, measured, and now, even outsourced to AI.
A Different Lens: Systemic Creativity as a Human Process
While the podcast offers a compelling account of what AI can do, I'd like to offer a different view, one that I explored in my Master's Thesis about systemic creativity. I would like to argue that this view is incomplete, because it strips creativity of its social, cultural, and systemic dimensions.
To understand creativity more fully, we can turn to the psychologist Mihaly Csikszentmihalyi’s systems model of creativity. According to this model, creativity is not simply about generating original ideas. It’s about bringing valuable novelty into existence within a social and cultural context that can recognize and adopt it.
Creativity, in this view, emerges through the interaction of three components:
The Domain
A structured body of symbolic knowledge (like mathematics, painting, storytelling, or engineering) that contains the rules, symbols, and conventions of a particular culture. The domain preserves tradition, and it defines what counts as meaningful or creative within its boundaries.The Individual
A person who learns the rules of the domain, internalizes them, and introduces novel variations. Creative individuals are often rule-breakers, divergent thinkers, or problem-finders, but their originality is always rooted in the structure of the domain they inhabit.The Field
The community of experts, peers, critics, publishers, curators, and educators who serve as gatekeepers. They evaluate whether a novelty is worth preserving, promoting, or integrating into the domain. This selection process is social and value-laden. It determines what counts as creative in the first place.
In this model, creativity is not the product of a lone genius (or a lone algorithm). It is a relational process, a dance between novelty and tradition, individual insight and collective judgment. A new idea only becomes creative when it is accepted by the field and integrated into the domain.
This systemic understanding of creativity does not align the the pervasive metaphor of the mind as a machine, but it fits well with the understanding that the mind works like an ecosystem, as it is a dynamic, interdependent, and evolving network of influences. In this view, the mind is not an isolated processor of information, but a node within a larger web of culture, history, language, values, and human relationships. Just as biodiversity in an ecosystem fosters resilience and innovation, creativity emerges from the richness of interactions across individuals, disciplines, communities, and traditions. The ecosystem metaphor invites us to see creativity not as a private act of genius, nor a programmable output, but as a collective, evolving process shaped by context and care. It is a view that holds space for uncertainty, nurtures difference, and recognizes that what becomes "creative" depends not only on what is produced, but who engages with it, how it is received, and what values it ultimately serves.
Why This Matters
From the systemic perspective, AI can indeed simulate the individual’s role. It ingests domain knowledge (in massive volumes), generates countless permutations, and produces outputs that appear new. But AI is not embedded in a field. It lacks intrinsic goals, values, or the cultural literacy to understand what its outputs mean within a specific domain. More importantly, it cannot evaluate the worth of its own creations or persuade others to do so. That task still falls to us.
AI can think new, but only humans can choose what is accepted and integrated into our domains. It is the human field (artists, researchers, teachers, editors, communities) that decides which AI-generated content becomes part of our evolving culture.
We should, of course, recognize that AI can be a powerful co-creator. It can push boundaries, challenge norms, and surface unexpected insights. But creativity in the systemic sense is not just about novelty, it is about meaning, value, and transmission. These are profoundly human responsibilities.
In a world increasingly enchanted by artificial intelligence, there is a real danger that we start to equate novelty with creativity, and in doing so, abdicate our role in the creative process. If machines generate infinite variations and we passively consume them, we risk becoming spectators rather than participants in our cultural evolution.
The challenge before us is not to deny AI’s creative capacities, but to reclaim our own.
We must remember that the power of creativity lies not only in the making, but in the valuing, selecting, and preserving of what is made. That is a human, cultural, and systemic act. The need for human judgment, taste, and meaning-making has never been more vital.
In Conclusion: Creativity Is Still Ours
Yes, AI can generate original content, it can astonish, provoke, and even move us. But we should not confuse output with creativity. We should not forget that creativity is not a product, it is a process, and one that unfolds within a deeply human system of meaning and value.
To create is to contribute to a living culture. To select, to shape, to share. And that is our responsibility. As AI continues to evolve, let’s not forget that the field still belongs to us.