A friend shared an interview with Caterina Moruzzi, a philosopher exploring how people and AIs work together, and what that relationship does to us as humans. As I listened to it, I became increasingly aware that we need to define what “creativity” is more precisely in light of what AI can do for us. She is working with artists and musicians, so the line between the artistic and the creative is ambiguous in this interview. Let’s take a closer look at the difference.

I want to first establish that something artistic, beautiful, or tasteful is not necessarily creative, and something creative is not necessarily artistic. The key distinction is that creativity involves meeting an objective condition, even when the path to it is unexpected, which makes it more objective than we typically admit. And anything positioned as objectively superior often feels dehumanizing because it pressures everyone to conform, leaving little room for personal quirks or idiosyncrasies. That’s why, before going further, I want to clarify more precisely what I mean by “artistic” and “creative.” Creativity is actually measurable. Here are some examples.

Let’s say we need to build a bridge but the location is not conducive to building any solid structure. Someone could come up with a beautiful design for it, but it cannot be built at that location. Another person comes up with a solution that allows us to overcome the limitation of the location. The former, as beautiful as it may be, would not be considered “creative” because the result does not achieve our objective, and this objective is definable. Creativity, at least in the way we often use the term, is about making unexpected connections to solve a definable problem. In many cases, we can even measure it in terms of profit, efficiency, or productivity. Without this socially agreeable value, we are not likely to use the term “creative.” When someone does something creative, we often say, “That’s clever!” which reveals how we view creativity. Cleverness, which is closely associated with intelligence, has more objective value.

On the other hand, let’s say you have an empty wall you want to cover with something beautiful. You commission an artist and she creates a painting that elevates the entire space, but a blunt friend walks in and says, “I think it’s ugly, and countless artists have made similar paintings. This is not creative or original.” Be that as it may, you personally still think it’s beautiful even if nobody else does. To you, it is still “artistic” because art is in the eye of the beholder.

In Japan, when studying to be an artist, teachers do not encourage creativity or originality; they typically force students to master the fundamentals. This is partly because their ultimate goal is not the final product but the transformation of the self through disciplined practice. Creativity and originality are often seen as expressions of the ego, aimed outward toward the Other, whereas the artistic process is inward-looking, a way of encountering and understanding one’s own unconscious. This perspective, too, differentiates “artistic” from “creative” in a similar fashion.

Now, you might complain that my definitions are too narrow. Fair enough; I’m narrowing them on purpose because AI forces us to separate what is objectively solvable from what is subjectively meaningful. In everyday conversation, we mix these terms freely (creativity and artistry blur together), but that vagueness makes it impossible to see what AI is actually encroaching on. The two concepts lie on a spectrum of objective and subjective values, but for the sake of this argument, I need to pull them apart. I’m not suggesting we always use them this way; I’m doing it here so we can see what part of “creativity” AI can surpass and what part it can’t.

I would assume that AI will soon surpass us in “creativity” as defined above. AI or machine learning models are easy to train when the goal can be objectively defined. Recognizing letters and numbers or identifying flowers were among the first problems solved with AI because the correct answers were easy to obtain.

In other words, AI will be superior to us with any problems that have objectively correct answers; it is only a matter of time. So, creativity, after all, isn’t all that “human” in the sense that its superiority is independent of any of us. I would not mind outsourcing it to AI entirely. What is more human is the quality of being “artistic.”

I’m currently working on a project with an artist where our code generates artworks from randomized parameters and has him approve or disapprove them based on his personal taste, what he thinks is beautiful, regardless of what anyone else thinks. The machine learning model we built can now predict with roughly 80% accuracy whether he would approve another randomly generated work.

Now imagine ten years from now, when AI is exponentially smarter: Would this model be superior to or more “artistic” than the artist? I hope you can see that this is a nonsensical question. The very nature of art resists objective comparison. As soon as the model deviates from the artist’s taste, it simply becomes a different taste, not a superior one, and it becomes less useful to him because its predictive accuracy declines.

Just as Duchamp tried to demonstrate by putting a urinal in a gallery, art is about communicating what you think is beautiful; it is this assertion that is more meaningful than the work itself. AI can certainly help artists create artworks, but it can never be superior (or inferior, for that matter) to humans because there is no basis for comparison.

This also pertains to products we don’t normally consider artistic. Take a computer application. Now that AI can help any of us create our own apps, it will soon be pointless to buy apps designed for millions of others. Your needs and preferences are unique; why put up with sifting through features you don’t need? Why not have AI build exactly what you need, like ordering a custom-tailored suit? Although we don’t normally use the word “artistic” in this context, the subjective dimension of UI/UX design is structurally the same: it reflects personal preferences and tradeoffs that cannot be resolved objectively. That is the “artistic” aspect of UI/UX.

As you try to design one, you will realize that reality forces you to make many compromises, not because your budget is limited, but because reality has conflicting forces. Sometimes we want life to be predictable and routine so we can take care of things efficiently by following the same pattern over and over, but other times we crave freedom and flexibility. No matter how large your budget is, you cannot design an app that accommodates both simultaneously. You could design two separate interfaces, one rigid and one loose, but most of the time, we want something in between. If we designed a thousand different interfaces, managing them would create a problem of its own.

As we confront our own desires, tastes, and preferences, we quickly notice that they pull in opposing directions. The same structural tension appears in our social reality, which also makes contradictory demands on us. From a scientific or engineering mindset, such conflicts look like problems waiting for solutions. Artists, however, recognize that many of these tensions are fundamentally irresolvable: confidence vs insecurity, kindness vs resentment, solitude vs connection, freedom vs responsibility, honesty vs kindness, fear vs desire, love vs hate. Each pair contains truths that cannot be collapsed into a single answer, nor repressed without consequence. Art is the process of metabolizing these contradictions rather than resolving them. Each person must discover their own way of living with them; there is no universal formula.

In this sense, as AI advances and allows us to get exactly what we want, we will confront our own contradictions. Once we find and embrace them, we won’t care what other people say about them. The app you designed works for you and that is all that matters. Whether other people find it useful is secondary; maybe they do, maybe they don’t.

It is this artistic dimension, not the creative one, that will be more meaningful in our relationship to AI.

Reading about the successes of AI-generated artworks in marketing made me realize that the creative industry, as we knew it, is over. It’s been in decline for a while, but we’ve reached the point where the final nail is being hammered in. At the very least, the definition of “creative” has shifted almost entirely. Today, creative professionals are less about being “artistic” or “aesthetic” and more about problem-solving.

People with refined aesthetic sensibilities (those drawn to design, illustration, photography, and music) once pursued creative careers because they could chase their own vision of beauty while making a living. That’s no longer viable. Businesses have figured out that, in the vast majority of cases, “good enough” is optimal for marketing.

For people not particularly passionate about art, like engineers, AI-generated content is exciting and fun to play with. Marketing now attracts many who simply enjoy dabbling in something that feels “creative.” That may sound dismissive, but it’s a reality the industry has to face. Those driven to define and express their own sense of beauty don’t find AI interesting because it isn’t theirs. For them, creativity is about the journey. For marketers, it’s only about the destination, and AI is an incredible shortcut to that end.

As marketing becomes more AI-driven, fewer artists will be drawn to it. The creative industry, as we knew it, will vanish. Maybe that’s for the better. If your goal is to express your own vision of beauty, maybe it’s best not to do it on someone else’s dime.

At the same time, the shift is happening in reverse. Many “creative” types are now thrilled that they can build apps without coding. In this case, they’re skipping the part they never wanted: the process of learning to code. They just want the final product they imagined; the journey means nothing to them.

On the other side, many coders (especially those from computer science backgrounds) love the process of coding for its own sake. What excites them is turning a well-defined problem into an elegant algorithm. They don’t care how the finished product looks, how it feels to use, or whether it solves the right problem. Many coders find users annoying. Their focus is abstract logic, coding as a kind of pure thought. AI can now do much of that “pure” coding just as well, if not better, and it does not get bored or precious about elegance. It just delivers the result.

What we’re seeing is a broader pattern: technological evolution deprives us of the journeys we enjoy by figuring out how to skip straight to the destination. This is why there’s a ceramics boom now. People miss making things by hand. The industrial revolution took that away a long time ago.

For every type of product, those who enjoy the journey are a small minority. For the rest, it feels like a chore. Capitalists and technologists feel justified in eliminating these tasks, believing they’re doing everyone a favor. But in doing so, they tilt the playing field toward those who never cared in the first place: those who dabble, who skim the surface, who treat creativity as a means to an end. In today’s system, depth is inefficient, and mastery is a liability, especially when scaling the business is a top priority. Dabbling wins because it doesn’t waste time caring. That’s the new creative economy.

Before the historic match between AlphaGo and Lee Sedol, most experts, including Lee himself, believed AI wasn’t yet capable of defeating a top human player. So when AlphaGo won the first three games of the five-game match, it shocked the world. Had the documentary ended there, it would have been merely an educational film about AI’s advancement. But it became something more emotionally profound when Lee managed to win the fourth game. I found myself tearing up, oddly enough. Lee knew AI would only get stronger from that point on, and indeed, nearly a decade later, no human can beat it. Yet, despite knowing it was futile, he persisted.

The beauty I perceive in the film has two aspects. First, Lee’s defiance in the face of an unbeatable opponent is reminiscent of John Henry, a folklore hero from the 19th century who competed against a steam-powered drilling machine to prove that human labor was superior. Second, it marked a fleeting moment when AI still felt human, imperfect, and fallible. Today, AI’s absolute dominance feels alien, a cold engine of perfection, playing Go on a level beyond human comprehension.

In that fourth game, Lee played what became known as “God’s move,” a move so unexpected it caused AlphaGo to stumble. But ironically, it wasn’t divine, it was the last, greatest human move: imperfect, yet brilliant within human limits. Since then, every move by AI has been effectively a “God’s move,” because they transcend our understanding.

We’re prone to wish for a god, to resolve our conflicts, erase uncertainties, and calm our fears. But in truth, beauty, and what makes life meaningful, lies in the very imperfections and uncertainties that define being human.

Academia is facing a crisis with AI. The problem is outlined well in a YouTube video by James Hayton. It’s not just that students can now write papers using ChatGPT, but that professors, too, can rely on ChatGPT to read and evaluate them. Hayton pleads with his audience not to use AI to cheat, but it’s futile. It’s like when Japan opened its doors to Western technologies—some lamented the destruction of traditional aesthetics and customs, but when the economic incentives of efficiency are so overwhelming, resistance becomes pointless in a capitalistic world. You either adapt or perish. That said, I personally believe AI will ultimately improve academia. Let me explain.

What people like Hayton are trying to protect isn’t education itself but the credentialism that academic institutions promote. Today, schools are no longer necessary for learning. There are plenty of free resources where you can learn virtually anything, including countless videos of lectures by some of the world’s top academics.

You don’t go to college to be educated—you go for the credentials. College professors’ primary function isn’t teaching but verifying that you completed what you otherwise would have preferred to avoid. If your goal is to learn something you’re passionate about, being forced to prove it through exams and papers is just an annoyance. If you love ice cream, do you need someone to certify that you ate it?

The same logic applies to professors. Academic institutions exist to certify that the papers they publish were indeed written by them and not plagiarized. If they didn’t care about getting credit, amassing cultural capital, or winning awards, they could simply share their work online. If their ideas are truly valuable, people will read and spread them like memes. But what professors care about most is being credited. Posting papers on their personal websites doesn’t guarantee that. Just as hedge fund managers are greedy for financial capital, academics are greedy for cultural capital. Both are human—the only difference is the type of capital they chase.

Now, let’s imagine a brave new world in which AI renders credentialism obsolete. How bad would that really be?

Colleges would have to give up on grading and testing because they could no longer tell whether students were using AI to cheat. Are the achievements genuinely theirs, or just the result of better AI tools? These questions become irrelevant once credentialism is abandoned. Graduating from Harvard or holding a PhD becomes meaningless because you might have used AI to get them.

But if your creativity and insights are genuinely valuable, you’ll still be valued in society—while those who cheated and have no original ideas will be left behind. Isn’t that closer to true meritocracy? Isn’t credentialism what distorts meritocracy in the first place?

Hayton argues that developing skills, such as writing, is important, and therefore students shouldn’t use ChatGPT to write their papers. And yes, during this transitional period, writing is still a useful skill. But I’m convinced that, in the future, writing skills will become as obsolete as tapping out Morse code. In a capitalist world, any skill that can be automated eventually will be. Our value, then, will lie in offering what machines cannot (yet)—creativity and insight. By leveraging AI, students can focus on cultivating those traits instead of wasting time on skills that soon may no longer matter.

Some may argue that skills and creativity are inseparable—or at least that skills can spark creativity or serve as the source of unique insights. I agree, but I think those benefits will become negligible. If the connection were truly that significant, no skill would ever go obsolete. High school teachers would still be forcing students to learn how to find information in a book library. Some savants can still perform complex mental calculations without calculators, but we view those abilities as curiosities or party tricks. I think it makes more sense to focus on creativity and insight, and acquire writing skills only when necessary. Whether you need writing skills at all depends on your goals. Professors who insist on them may simply get in your way.

AI will usher in a future where we no longer care who came up with a great idea. A great idea stands on its own, regardless of whose name is attached, where they went to school, or how well it’s written. We’ll grow accustomed to working like chefs, who rarely receive credit for individual dishes because recipes aren’t copyrightable. To survive and thrive as human beings, we’ll stop obsessing over credentials and instead focus solely on what we’re passionate about learning. We’ll leave behind the certifiers and seek out real teachers to help us discover the things AI cannot teach. Professors will no longer need to whip students into studying. Only those eager to learn what they have to offer—hanging on their every word—will show up to their classes.

Everyone is trying to figure out how AI will impact their careers. The opinions are varied, even among the so-called “experts.” So, I, too, can only formulate opinions or theories. I’m often criticized for speculating too much, but we now live in a world where we’re forced to speculate broadly about everything.

According to the latest McKinsey report, the fields most impacted by AI so far are marketing and sales—which is not speculation but an analysis of the recent past. In my view, this makes sense because AI is still not reliable enough to be used in fields that require accuracy. Marketing and sales have the greatest wiggle room because so much of it is up to subjective interpretation. Choosing one artwork over another is not a make-or-break decision. It’s easy to justify using AI-generated artwork. Also, in most cases, marketers are trying to reach the largest number of consumers, which makes cutting-edge or experimental artworks unsuitable.

[The poster image for this article was generated using the latest model by OpenAI, including the composition of the title over the image. I simply submitted my essay and asked ChatGPT to create a poster for it. I did not provide any creative direction.]

Although the mainstream understanding of fine arts is that the work should speak for itself, in reality, the objects are practically worthless if not associated with artists. You own a Pollock or a Warhol—not just the physical object. After all, the quality of a replica can be just as good as the original, if not better.

Some might argue that artworks created by AI have already sold for a lot of money. That’s true, but they hold historical significance more than artistic value. The first of a particular type of AI-generated work may continue to sell for high prices, but the meaning of that value is fundamentally different from the value of work created by artists. In this sense, I don’t see fine artists being significantly impacted by AI, aside from how they choose to produce their work.

In commercial art and entertainment, who created the work is secondary to the goal of commanding attention and entertaining the audience. If AI can achieve the same end, the audience won’t care. Nobody knows or cares who created the ads they see. Many Hollywood films aren’t much different. I can imagine successful action films being written and generated entirely by AI. As long as they keep us on the edge of our seats, we won’t care who made them.

More arty films are exceptions. Who wrote and directed them still carries significant meaning—just as in fine arts. Similarly, bestselling books—fiction or nonfiction—could be written by AI, but when it comes to genuine literature, we care who the author is. Finnegans Wake would likely have been ignored if it weren’t for Joyce, with his track record, writing it. I predict that a sea of AI-generated books will make us crave human-written ones, in the same way mass-manufactured goods have made us value handcrafted ones. The rebirth of the author—but only at the highest levels of art, across all mediums.

Authorship will become especially important as AI floods the market with books and films that are just as good as human-generated ones. Since we can only read or watch a small fraction of them in our lifetimes, “human-generated” will become an arbitrary yet useful filter.

What we’ll ultimately value isn’t the technicality of who generated a work but the “voice” we can consistently perceive across all works by an author. AI might be able to emulate a voice and produce a series of works, but doing so would require a fundamental change in how AI models are designed. An artistic voice reflects the fundamental desire of the artist. AI has no needs or desires of its own. Giving AI its own desires would be dangerous—it would begin acting on its own interests, diverging from what we humans want or need.

I hope we don’t make that mistake. But we seem to be following a trend: making our own mistakes before anyone else does, because it is inevitable that someone else eventually will anyway.

Many people use ChatGPT as a kind of therapist. While it can’t solve all your emotional problems, it excels at one thing: telling you whether your behavior aligns with or deviates from the norm.

ChatGPT serves as an exceptional sounding board if you’re unsure how most people would react in a given situation. Suppose you recently moved to New York from Japan and aren’t familiar with American social norms. One day, you give someone a gift, but their reaction seems indifferent. Instead of agonizing over what went wrong, you can simply ask ChatGPT how most Americans might perceive your gift.

Much of our anxiety stems from uncertainty about social expectations—how closely our actions match the norm. Because ChatGPT is trained on vast amounts of human-generated data, it has an unparalleled grasp of what lies at the center of the bell curve. This is similar to what industry “advisors” offer. If you’re not a realtor, you might not know the unwritten rules of real estate transactions, but a realtor can guide you. Now, ChatGPT can do the same, anytime you need it.

However, before relying on its guidance, consider the limits of its data. It may not accurately reflect the customs of a small ethnic neighborhood in New York City, for instance. And while knowing the norm can ease anxiety, it doesn’t always mean the norm is the right choice. But in many socially fraught situations, there is no objectively “right” answer—only what is typical.

Take the concept of a faux pas. It is entirely norm-based. In contrast, jaywalking on a red light isn’t considered a faux pas because it’s governed by a clear rule. Rule-based behaviors usually don’t cause much anxiety; we can easily determine whether we followed them correctly. A faux pas, however, is anxiety-inducing because the only way to know if you misstepped is to understand the norm—something that often takes years of experience. ChatGPT can shortcut this process by giving you a reliable sense of what is considered appropriate.

Of course, even norms can be disputed. Two people may claim to know what’s customary yet disagree. For example, one person may believe it’s normal to hug someone they just met, while another insists hugging is reserved for close friends. Their perspectives might be shaped by cultural differences or personal experiences. In such cases, AI can serve as an impartial arbiter, providing a broader, data-driven perspective.

In this way, ChatGPT can be your best friend in confirming that you acted appropriately—or warning you before you make an unintended social blunder. After all, what you assume is common sense might not be common at all.