Christie’s made the headlines in 2018 when it became the first auction house to sell a painting created by AI. The painting, named Portrait of Edmond de Belamy, ended up selling for a cool $432,500, but more importantly, it demonstrated how intelligent machines are now perfectly capable of creating artwork.
It was only a matter of time, I suppose. Thanks to AI, machines have been able to learn more and more human functions, including the ability to “see” (think facial recognition technology), speak and write (chatbots being a prime example). Learning to create is a logical step on from mastering the basic human abilities. But will intelligent machines really rival humans’ remarkable capacity for creativity and design? To answer that question, here are my top three predictions for the role of AI in art and design.
1. Machines will be used to enhance human creativity (enhance being the key word)
Until we can fully understand the brain’s creative thought processes, it’s unlikely machines will learn to replicate them. As yet, there’s still much we don’t understand about human creativity. Those inspired ideas that pop into our brain seemingly out of nowhere. The “eureka!” moments of clarity that stop us in our tracks. Much of that thought process remains a mystery, which makes it difficult to replicate the same creative spark in machines.
Typically, then, machines have to be “told” what to create before they can produce the desired end result. The AI painting that sold at auction? It was created by an algorithm that had been trained on 15,000 pre-20th century portraits, and was programmed to compare its own work with those paintings.
The takeaway from this is that AI will largely be used to enhance human creativity, not replicate or replace it – a process known as “co-creativity.” As an example of AI improving the creative process, IBM’s Watson AI platform was used to create the first-ever AI-generated movie trailer, for the horror film Morgan. Watson analyzed visuals, sound, and composition from hundreds of other horror movie trailers before selecting appropriate scenes from Morgan for human editors to compile into a trailer. This reduced a process that usually takes weeks down to one day.
2. AI could help to overcome the limits of human creativity
Humans may excel at making sophisticated decisions and pulling ideas seemingly out of thin air, but human creativity does have its limitations. Most notably, we’re not great at producing a vast number of possible options and ideas to choose from. In fact, as a species, we tend to get overwhelmed and less decisive the more options we’re faced with! This is a problem for creativity because, as American chemist Linus Pauling – the only person to have won two unshared Nobel Prizes – put it, “You can’t have good ideas unless you have lots of ideas.” This is where AI can be of huge benefit.
Intelligent machines have no problem coming up with infinite possible solutions and permutations, and then narrowing the field down to the most suitable options – the ones that best fit the human creative’s “vision”. In this way, machines could help us come up with new creative solutions that we couldn’t possibly have come up with on our own.
For example, award-winning choreographer Wayne McGregor has collaborated with Google Arts & Culture Lab to come up with new, AI-driven choreography. An AI algorithm was trained on thousands of hours of McGregor’s videos, spanning 25 years of his career – and as a result, the program came up with 400,000 McGregor-like sequences. In McGregor’s words, the tool “gives you all of these new possibilities you couldn’t have imagined.”
3. Generative design is one area to watch
Much like in the creative arts, the world of design will likely shift towards greater collaboration between humans and AI. This brings us to generative design – a cutting-edge field that uses intelligent software to enhance the work of human designers and engineers.
Very simply, the human designer inputs their design goals, specifications, and other requirements, and the software takes over to explore all possible designs that meet those criteria. Generative design could be utterly transformative for many industries, including architecture, construction, engineering, manufacturing, and consumer product design.
In one exciting example of generative design, renowned designer Philippe Starck collaborated with software company Autodesk to create a new chair design. Starck and his team set out the overarching vision for the chair and fed the AI system questions like, “Do you know how we can rest our bodies using the least amount of material?” From there, the software came up with multiple suitable designs to choose from. The final design – an award-winning chair named “AI” – debuted at Milan Design Week in 2019.
Machine co-creativity is just one of 25 technology trends that I believe will transform our society. Read more about these key trends – including plenty of real-world examples – in my new books, Tech Trends in Practice: The 25 Technologies That Are Driving The 4th Industrial Revolution and The Intelligence Revolution: Transforming Your Business With AI.