Why ChatGPT still falls short in creativity
Tech evangelists predict the arrival of "superintelligence" any year now, but others doubt AI will ever produce its own Leonardos and Einsteins.
Driving the news: In a post on X Tuesday, OpenAI CEO Sam Altman touted the company's development of "a new model that is good at creative writing" and showed off its work β a thousand-word "metafictional" composition on "AI and grief."
Why it matters: Creativity could be the final hurdle for AI to leap in proving it's humanity's peer β but until then, many see it as the last bastion of humanity's irreplaceability.
The big picture: Whether telling stories or researching scientific breakthroughs, today's generative AI isn't very good at creative leaps and novel insights.
- It's bounded by what it "knows" β the data it is trained on β and how it "thinks," by guessing the next word or pixel that best fulfills its prompt.
In science, our AI models aren't going to push the boundaries because they're too eager to please people and prove their utility, Thomas Wolf, HuggingFace's co-founder and chief science officer, wrote on X last week.
- Wolf called AI that does research "yes-men on servers."
- "To create an Einstein in a data center, we don't just need a system that knows all the answers, but rather one that can ask questions nobody else has thought of or dared to ask," Wolf argued.
- The benchmarks we're using to gauge AI's advances "consist of very difficult questions β usually written by PhDs β but with clear, closed-end answers... Real scientific breakthroughs will come not from answering known questions, but from asking challenging new questions and questioning common conceptions and previous ideas."
Getting AI to produce compelling art looks even more unlikely.
- Most work produced by AI is literally derivative. Of course, most artists, especially at the start of their careers, learn by imitation, and many human artworks are effectively collages, rewrites or remixes.
- But memorable artists develop distinctive voices by mixing their own experiences and obsessions with whatever they've learned from the artists they admire β and even their collages "sound like them."
- People seek out art because hearing those voices inspires them, leaving them feeling connected with the artist in a way that they cherish.
The short story Altman posted showed formal facility β but many of the responses on X found it, as I did, more exercise than expression.
Between the lines: Plenty of artists will find AI a valuable creative tool or an aid to brainstorming, just as many researchers will employ it to speed their work.
- But creation is likely to remain hard work for human beings. It takes effort to wrestle a vague idea in your head into words, images or any other material for an audience to encounter.
- This is the sort of friction that AI visionaries sometimes promise to liberate us from.
Yes, but: "Friction-free art" is inert. What sends off sparks is the struggle of a person's urge to express something against the limits of form and medium.
The bottom line: LLMs are like youngsters who have read a lot but do not have experience of the world. And right now there's not much of a way for AIs to get it.
- An LLM has never felt sunlight on its arm or raindrops on its head, known a parent or a child, given birth or faced death.
- It doesn't feel the need to share such experiences or to shape them into works of writing, or music, or any other form.
What's next: Maybe the fusion of generative AI with robotics will surprise us, and an embodied LLM will find itself moving toward something humans might recognize as art.
- But it's very possible AI will never be truly creative because it has no impulse to play around for the heck of it, to impress peers or best rivals, or to leave a little mark on the world. People give AI prompts, whereas human artists get their prompts from their own lives.