Demystifying the complexity of Artificial Intelligence
Publishers and studio executives are faced with using new technologies in their day-to-day business and creative decisions to keep pace with emerging markets, trends, and audience behavior. In recent years, the fastest growing technology of them all has been Artificial Intelligence. A simple definition of AI is “intelligence exhibited by machines (i.e., computers) instead of humans.” It may seem counterintuitive, or at least something that might require a data science background, to use a machine to make decisions, especially decisions traditionally driven by human emotion.
Entertainment and the arts have been driven by human emotion since the dawn of time. They still are. We watch and read what we like based on how it makes us feel. But with the advent of technologies that analyze data on our behavior, likes and dislikes, is there room for new science to supplement, or at least augment the creative decisions made by the entertainment industry based on data? Must the leaders in entertainment become a technocracy, a system of governance where decision-makers are selected on the basis of technological knowledge? Technocrats, no, but adopters, yes.
In truth, artificial intelligence and its subsets–machine learning, data analysis, neural networks and natural language processing–are very complex technologies. Teaching machines to think and decide like humans may have been the thing of science fiction a few decades ago, but it’s here now and its impact is significant. Its complexity should not preclude one from adopting the technology for personal use or business.
If you used Google Search to find this article, or a GPS-enabled map application to get you where you’re sitting, you benefited from the use of artificial intelligence. Your smartphone, your car, your bank, and your house all use artificial intelligence on a daily basis; sometimes it’s obvious what it’s doing, like when you ask Siri to give you directions to the nearest Sushi restaurant. And you didn’t require a degree in computer science.
One of the most profitable examples of technology in entertainment has been the use of recommendation engines for books, movies and music. AI drives these. (Here is a technical look at how Netflix guides subscriber viewing through AI recommendations) With massive amounts of data being collected, too much for human consumption, it takes high-speed computers to analyze and decide what the data it telling us. And the data is guiding us in what we should acquire; what is the market potential; what’s the best audience; and how we should position it.
Is there room for originality?
One of the beauties of artificial intelligence is that computers can be taught to think like you and your business thinks. You can liken it to the training of an editor, who is taught to look for what best serves the company criteria. If your publishing house has an affinity for books that impact social change or your studio thrives with producing high dramas with complex characters, AI can be trained to discovery, support and promote those proclivities.
AI is not some ghost in the machine. It is highly sophisticated technology that responds to the directives and goals of a business. You will need a data science team to build it and reap its benefits, but you personally won’t need a degree in computer science to understand and use it.