This post is part of a series about Artificial Intelligence (AI) and its potential role in science communication. In this post (part 4), I talk about creativity and how it relates to AI.
In the previous posts, I’ve been talking about the computer Watson and how it helped create a trailer for the movie Morgan. Is this “cognitive movie trailer” evidence of AI creativity or the potential to mimic human creativity? In other words, can a human be replaced by a machine—in this case a trailer editor who uses skill and imagination to create something new?
Let’s first consider what creativity is. The dictionary defines creativity as the ability to make new things or think of new ideas. But is it a trait only exhibited by humans? Is it an attribute that some people have and others don’t? Is it an occasional mental state that we enter? Can one learn to be more creative? I’m not sure of the answers to all these questions, but perhaps it’s more helpful to ask what creativity is not. It’s not problem solving, which is a process whereby a “rule” or “algorithm” is applied to solve a problem. Being able to understand and apply a rule is different from discovering the rule.
In the case of the computer Watson, we can see that understanding what a movie trailer is and identifying the best scenes from the movie Morgan to use fall into the realm of problem solving and not creativity. A human stepped in to do the actual film editing, which additionally suggests that the “creative” aspect of putting together the trailer could only be done by a person with the requisite editing skills and imagination to sequence the clips and add other components such as music and text. However, I don’t think a human was essential to do the editing, once the scenes were selected.
A movie trailer template could have provided a guide with placeholders for media and text, much the way iMovie trailers are created. In this screenshot, you can see an iMovie trailer template, which guides the choice of video clips and text. Scenes are suggested, as are text titles that form a story. Such a template could have been used along with the ten selected scenes from Morgan to produce a finished trailer. However, such an ability by an AI could not be called creative. Although some decision-making would be involved in selecting which scene to go into each placeholder, those steps would be guided by a set of rules—in other words, problem-solving, not creativity. Also, templates would produce an assembly-line of movie trailers that all follow the same format—rather than a unique trailer with sequences, pacing, music, and other features individually selected by the editor using his or her knowledge, skill, and imagination.
I think we are a long way from machines that think and create like humans. However, we are at a point where AI can be used to enhance human skills and help us perform tasks involving vast amounts of information. Artificial intelligence systems are already at work aiding, for example, analysis of medical images, detection of suspicious charges to our credit cards, or automated telephone customer service. The real question is not whether AI can replicate human thinking or creativity but how AI can help humans create new things or think of new ideas faster and more efficiently.
This post is part of a series about Artificial Intelligence (AI) and its potential role in science communication. In the next and final post (part 5), I’ll discuss how AI might help scientists be better communicators.