The AI-Generated Search for Creativity is About to Explode

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We are about to experience a huge boost in creativity thanks to the supercharged relationship between humans and artificial intelligence, believes internet blogger Jon Radoff.

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Even if we don’t fully understand how it works, it is the ease of communicating with large language models like Chat GPT, which will propel society’s ability to become more “efficient at creativity.”

“We are moving towards a new phase in human civilization: one that involves not only enhancing our own creativity with computers, but working alongside a network of generative models and agents that will help along the path of discovery,” writes Radoff, a self-described adventurer and entrepreneur, blogging about gaming and AI at Metavert Meditations on Substack.

These systems will not only be collaborators, he says. AI will help us “filter through the vast ocean of data, information and applications and practices” of all the creativity that happened of the past.”

He prophesizes an acceleration in the ease of integrating, linking and combining creative content (so-called “composability”) and an exponential scaling-up in the number of creative actors.

“Rather than think of creativity as something unique to [human] genes or our brains, or divinely inspired, or based on some other vital magic — it may be helpful to think of creativity as a search,” he suggests.

“If the universe is a nearly-infinite number of possibilities, parameters and variables—then perhaps creativity is about applying efficient processes towards this search for effective solutions.”

This search is one that results in all manner of discoveries, he says, not only scientific discoveries, but engineering problem-solving and the production of artistic works and cultural products.

Searching the entire variable-space (let’s call that the multiverse of possibilities) would be impractical since it would require infinite computation and therefore infinite time and energy.

A better means of conducting this search is what we might call intelligence, Radoff suggests.

“As we continue to scale-up the number of minds, network with each other, and create better algorithms for conducting the search, we will produce useful outputs: the kind we call creative,” he says.

Radoff also talks about the concept of “emergence,” which is already well known to game makers. Emergence is the idea that from a set of simple underlying rules, complex systems may emerge. As more inputs are available to the system, it is possible for the game to become far more complex.

For example, what made roleplaying games like Dungeons & Dragons so compelling is that the “emergent complexity” came from the ability for players to add their own creativity and storytelling to the experience. A game like Minecraft gave players the ability to shape the structure of the world, build custom servers, and invent mods that affected the experience of other players.

Multiuser dungeons, virtual worlds, and then massively multiplayer online role playing games added even more emergent complexity: they scaled-up the number of players and their network of social interactions.

He thinks that the simple interface of ChatGPT is a gateway to ever increasing complexity that meshes human-machine creativity.

“Much of the recent excitement in artificial language is that the natural-language interfaces ‘just work.’ And while these systems make mistakes (itself a quality we attribute to humans more than machines) it is a universal interface that allows us to interact with them efficiently.”

Good games, he adds in a side note, are usually those that don’t overwhelm the player with this complexity within the basic rules — otherwise the game becomes too hard to learn.

But when the learning curve is balanced with complexity that’s more emergent in nature, it often makes for long-term fun as players continuously learn new forms of interaction with the environment.