AI chess vs. AI art - why are they perceived differently?
Introduction
AI is fast developing in many fields, with very different results. In chess, it became a useful tool and learning aid. In art, it has caused confusion, legal issues, and ethical concerns. Chess AI is seen as a partner by many chess players. AI art is often seen as a threat. So, what are the underlying reasons for the application of AI in these domains diverging so differently in public opinion?
(Note: I’m discussing the use of chess AI as an analytical tool. Of course, it can be misused for cheating in competitions, which is a separate ethical issue. Generally, though, this doesn’t seem to be a massive issue at the highest levels of chess, while it’s easier to detect at lower levels.)
History of AI in Chess
AI in chess began in the mid-1900s with programs built to study logic and decision-making. In a pivotal moment in 1997, IBM’s Deep Blue beat world champion Garry Kasparov.
That moment kicked off the modern use of engines in training and analysis. Now, engines like Stockfish and AlphaZero help players find better moves and explore new lines. AI didn’t replace players. It helped them improve.
Players compete still, with AI assisting preparation rather than dominating public play. One thing is clear: the wider chess community has little interest in watching two robots play each other, despite it being at levels far beyond that of human play.
AI chess evaluations have become a standard feature in all modern chess coverage. Commentators and broadcasts regularly show engine assessments to help viewers understand positions.
History of AI in Art
AI-generated art, on the other hand, started as a research project. Early systems like AARON in the 1970s were created by artists experimenting with code as an art project itself.
But, with the recent AI boom, tools like Midjourney, DALLE and Stable Diffusion have arrived which use massive datasets that are often built from copyrighted material scraped online without permission.
Instead of helping artists, these tools now seem to be replacing them. They generate countless images without crediting original creators, while artists’ works and styles may be used in the datasets. However, they receive no attribution or compensation.
We (art regard) have, and still are, speaking to a lot of artists, and harms such as loss of commissions, false accusations of AI use, and a general feeling of being used are mentioned time and time again.
Similarities
There are a few key similarities between AI in chess and art. Both use large-scale computation and pattern recognition trained on countless chess games or artworks to perform tasks that previously required human intuition. Both can produce results that surprise humans, and both are often seen as impressive advances, from a technical standpoint.
Differences
However, the systems operate in fundamentally different domains. Chess exists as a game with fixed rules, defined boundaries, and objective win conditions. Art operates without boundaries, incorporates culture, emotion, and human experience, and relies on subjective reception.
Chess AI functions within this closed system where every position has concrete solutions. It processes the mathematical certainty of chess and outputs moves with value measured by effectiveness toward victory. Art AI operates in an open system where evaluation happens through human connection, cultural context, and non-quantifiable responses.
The implementation paths also diverged. Chess AI developed through decades of collaboration between players, programmers, and the chess community. Art AI emerged from tech companies without partnership from the art community, leading to one-sided development and a feeling of being used or sold out by big tech.
Chess players maintain control over when and how they use AI tools. The engines analyze when requested and provide options players may accept or reject. Art AI enters creative spaces without invitation, processes artists’ work without consent, and creates outputs that compete in the same markets.
The economics differ too. Chess AI enhances player skill but doesn’t replace players in tournaments or exhibitions. Chess players still earn income through competition, teaching, and content creation—often using AI to enhance these activities. Art AI directly threatens artist income by generating work that replaces commissions and erodes market value for human-created art.
Chess players use AI voluntarily as a tool. Artists often have no choice. AI tools generate work in their style without consent. This creates tension, not collaboration.
So Why Are They Perceived Differently?
Some of the similarity in perception comes from novelty, as both technologies seemed revolutionary when they appeared. But the underlying reasons for differences in how they are viewed are, at their core, structural.
Chess AI is seen as additive. It makes players better and reveals new ideas in a transparent way. It’s used mostly by the people it’s meant to help: chess players.
AI art is seen as subtractive. It bypasses the artist, takes their work as training data, and automates the output. It’s often used by people with little or no artistic background, and, as mentioned by artists themselves, it replaces commissions or devalues original art. The economic and creative costs fall heavily on artists, while the benefits go mostly to tech developers, platforms, and paid, usually commercial, consumers of art who now get a hefty discount.
Conclusion
The difference in perception comes down to trust, control, and context. One application of AI is used to assist and evolve chess with the support of its community, while the other seems to steal from and exploit the community it is claiming to have joined.
AI art tools have disrupted artistic labor without building relationships with artists. Chess got a tool. Art got an identity crisis.
