I’m surprised how often I hear well-informed people argue that modern AI models are still “just repeating things that are in the training data.” This is simply not true. Large language models routinely solve math problems they have never seen, write poems that have never been written, and program software algorithms that are not in the training set.
Of course, these outputs are similar to things seen in the training data — but in the same way that humans mostly only solve math problems that are similar to ones we have seen, write poems that only use familiar elements of language, and write computer programs based on strategies we learned from other programs.
This is not to say that AI models have reached or exceeded the limit of what humans can do. For instance, I am not aware of any AI models that have invented entirely new fields of research. Indeed, AI models are not yet competitive with most (if not all) experienced professionals. But in terms of everyday creativity — which involves copying, combining, and transforming known ideas — current AI models are quite capable.
Part of the confusion may come from the need to “un-bundle creativity” as I wrote about previously. We may not be used to viewing creativity on a spectrum from “somewhat creative” to “as creative as an experienced professional.”
Another reason for misunderstanding may simply be our natural resistance to the idea that some of the things that used to be uniquely human are no longer so. (Though some animal species also exhibit creative problem solving.)
We might also see generic or cliché outputs and mistakenly attribute them to a lack of creativity. In reality, these generic responses come from models that are specifically trained to be neutral and multi-purpose. By default, popular systems do not veer far off the beaten path — for the same reason that most corporations do not hire erratic geniuses as spokespeople. They are still capable of creativity if prompted.
Finally, we might unnecessarily conflate creativity with agency. Part of being an artist is being moved — knowing what you want to create. Chatbots are designed to be assistants, only responding when prompted, so they do not have this type of intrinsic agency. A human needs to specify the goal and the constraints. But this still leaves plenty of room for the AI model to create novel solutions.
If the definition of creativity requires capabilities to be uniquely human, then the word is useless in discussions about AI. If the definition requires equivalence to what humans can do, then the word is useless until (and if) we reach that point. To meaningfully discuss the impact of the technology now, we need to acknowledge the spectrum of creativity and the AI models’ very real capabilities for creative problem solving and artistic expression.