Artificial Intelligence is often a phrase people flinch at, it’s almost treated like a dirty word. In some people it inflicts imagery of robots taking over the world and mass automation, so understandably one industry that is particularly concerned about the AI effect is the creative industry. If AI can be creative and make better art, write more interesting scripts or create tuneful music then where does that leave the industry? I went to the Beyond Conference to understand this a bit more.

The Beyond Conference is the R&D conference for the creative industries. This year was my first Beyond Conference and I had no idea what to expect. I have a lot of hands-on experience with immersive technology so to see how VR can be used within creative industries through some of the applications at the innovation showcase was brilliant yet somewhat expected. What really surprised me, was just how much AI can add to creative practices. When I consider the uses of AI in creative industries, I think more about how venues can use data to increase footfall, increase spending per head or to better understand their audience. What I wasn’t expecting to learn was how AI can better help the audience understand the work of creatives. 

We know that machine learning can help producers understand their audience but what I was pleased to discover was how AI can also help the audience understand the works of the producer. Take for example, who use AI to bring characters like Macbeth to life, or the Final Project who integrate voice recognition and natural language processing with UHD video media to allow for people to connect with role models or historical figures. Their work has helped to immortalise Holocaust survivors by providing a new and innovative way for people to experience history.

Not only can AI help the audience better understand the works of individuals, but it can also become a creative tool. Reeps100 uses his work to explore the evolution of technology and the human voice through mesmerising performances such as a beatbox battle with a machine. Another example is Jake Elwes, who injects data sets with stunning images of drag queens to produce hypnotic artwork and investigates what it means to collaborate creatively with an unpredictable algorithm. Instead of viewing machine learning as a threat to creativity, perhaps people could view it as an instrument that compliments creative processes. 

The use of Artificial Intelligence still raises a lot of ethical questions and has a way to go with regards to regulation and good practice, but going to an event like this really did highlight the positive sides of AI. I suppose a large takeaway from this conference for me is that we don’t really know what it means to be creative as humans. Surely our own creativity is limited by our personal experience of life. When we create, are we not combining elements from our lives or inspiration taken from other creatives? A generative model such as deep learning technology can learn to mimic the data it has been trained on to create something similar. So can it ever really create something anything truly new or unique when it uses a compilation of existing data from various sources. To understand whether AI could be more creative than humans I therefore believe we would need to better understand what makes humans creative in the first place.