Machine-made art does not mean the end of human creativity

The Gray Area Incubator is mentioned here with words By: Khari Johnson

On Tuesday the creative collective Botnik Studios released an imitation Coachella poster with artists names generated by a recurrent neural network trained on thousands of band names.

In past weeks Botnik, an Alexa Accelerator graduate, has taught a predictive model to generate a top 10 trending hashtags list and used its predictive keyboards to write a Scrubs episode and a passage of the Trump tell-all Fire and Fury.

Like AI trained to draw based on photo captions that Microsoft researchers shared last week, Botnik raises questions about the use of AI for the creation of art and what that means for creatives.

Style transfers made popular by Prisma and followed by FacebookGoogle, and Algorithmia must have convinced more than one artist that AI is here to take their job, but AI isn’t just imitating the work of Picasso. It can also act as a framework and supply a space for creativity to exist.

Cynthia Hua, for example, is part of an tech-art incubator at Gray Area Foundation, an organization in San Francisco that in 2016 displayed art generated by Google’s DeepDream. She uses AI to generate imagery, and views computer-generated art produced by models fed an amalgam of thousands of images from different people as a kind of collective imagination.

Above: From Hua’s Particle Swarm collection

Some may use AI purely to imitate styles, but artist-technologists, Hua argues, engage with the question of how people can use machine learning in ways that are not meant purely to increase efficiency.

“Personally the kind of art I find most invigorating in the tech scene is the kind that doesn’t just try to replicate creative processes through art, it doesn’t just try to draw the way the Mona Lisa was drawn, but takes these new tools and try to ask if we can use these new tools in a way that makes people feel inspired and excited,” she said.

Machines will grow smarter and better able to imitate human creativity, but work by Hua and groups like NIPS for Creativity or Machine Learning for Art (ML4A) demonstrate that the use of neural networks for art doesn’t have to mean the end of creativity.

Seems like we’ve got a bit of time before AI models are able to understand the brilliance that is the Baroque Obama meme, stand-up comedy, or other forms of art that require humanity or imagination.

When considering the impact of AI in art, it’s worth remembering, as HP Tech Venture’s Andrew Bolwell reminded me at a panel discussion earlier this week, Garry Kasparov believed his battle with IBM’s Deep Blue led to better human chess players. Go player Lee Sedol apparently expressed similar sentiments in the AlhpaGo documentary now available on Netflix.

Botnik’s shenanigans are the latest reminder that art by neural nets and humans can produce unique results that don’t have to replace human ingenuity but can, like any other tool, augment human endeavors — to, as the DeepMind team puts it, “be a multiplier for human ingenuity.”

As you’ve likely heard said, AI is just getting started, but just as AI won’t kill all jobs, AI in art isn’t all bad. Just like AI in the workplace, AI in art can augment, not replace, human activity, and help humans discover new forms of expression.