It is often said that most people only know the little that they do about artificial intelligence through watching films about AI. Arguably, the most famous of all is Steven Spielberg’s A.I (1997), a film that tells the story of a humanoid AI boy that learns to love.

Movie buffs know that the film was originally developed by Stanley Kubrick, who worked on developing the movie for years, only to give the project to Spielberg on account of both AI and robotics of the time being too undeveloped to realize his vision.

Even today, some 25 years later, it is likely that AI and robotics still could not reach Kubrick’s vision of an extremely realistic human-like AI humanoid. But thanks to this and other movies like Ridley Scott’s Blade Runner (1982) and Ex Machina (2014), global audiences have been given a taste of the potential of AI, as well as a slightly dystopic vision of our future with artificial intelligence systems too.

But what is the reality surrounding AI? In this article, we will answer the question, how is AI used in filmmaking today?

AI in Film

There are several main avenues of development when it comes to artificial intelligence in film. The most obvious one is AI movie production. Other avenues include AI onscreen and AI marketing. Let’s start with AI movie production.

AI-assisted moviemaking is the term given to artificial intelligence enhanced movie production processes. AI-assisted filmmaking platforms offer production teams, directors, scriptwriters, etc., the opportunity to use powerful big data analytics tools to gain insights into aspects of their production.

The most obvious example is ‘Script Analysis’, a tool that allows these platforms to analyze and provide insights into a whole range of production elements including ‘genre recipe’, and ‘character analysis’ that includes actor suggestions, etc. Filmmakers can use the insights provided by the system as a guide on what potential audiences will see in their film on a scene-by-scene basis.

How is this done? Well, teams of data scientists and AI engineers start by creating sophisticated machine learning algorithms and AI models. They then turn these models into code so that they have the basic skeleton of the AI system.

Next, they need to begin training the system using increasingly larger and larger data pools. In the case of AI-assisted filmmaking systems, the engineers begin with basic data sets in order to train the system on the most basic understanding of what patterns it should be looking for in the data. The system is guided in terms of the accuracy of these insights while the data scientists both refine the model and scale up the volume of training data.

During this process, the AI system develops an increasing number of data points that allow it to gain an increasingly broader ‘perspective’ on what elements affect the accuracy of its insights. In effect, the process is the same as we humans undertake from when we are babies. This learning continues even as the system is being used by clients. The more learning the system does, the more accurate it becomes.

Today, AI-assisted moviemaking companies offer a wide range of accurate tools that help users to gain valuable data derived insights regarding their projects.

Onscreen Help: AI Actors and AI Enhancements

The second major avenue for artificial intelligence in film is the one that audiences really notice.

Last year, headlines were made the world over after a U.S film company announced that it was to make the first movie to star an AI actor. The film is currently still in production but is set to star an AI system developed by two Japanese data scientists.

The growth in the numbers and sophistication of AI actors is inevitable, particularly as they become increasingly ‘human-like’. However, their acceptance by human audiences is not. While it is likely that we will come to accept AI actors to some degree, as we have done computer-generated ones, their success is by no means assured.

As we have seen with CGI, there is almost certainly a limit to the audience size for AI lead movies. Only time will tell, but until AI systems are walking the red carpet at the Cannes Film Festival and living lives that give us lots to gossip about, it is very unlikely they will take the role of human actors.

Another example of this avenue of AI development is the development of systems that alter images. Everything from CGI to the touching up of damaged old film is already undergoing a revolution thanks to AI.

The benefits of the automation of these processes, which in the case of animating CGI characters, for example, are obvious. Not only does it mean a huge reduction in the time it takes to complete such tasks, which in turn offers huge cost savings, but it also takes the weight off the animators and allows them to focus more time on creating new and exciting characters.

In the case of film restoration, a relatively simple AI system is now capable of restoring silent films at a fraction of the cost. This means that it will now be possible to ‘restore’ thousands of silent pictures that would simply have not been otherwise due to the enormous restoration costs involved. Audiences everywhere will soon be able to watch 4k versions of long-forgotten classics, something that will greatly enrich the film-going audience.

AI Marketing

The world’s leading AI-assisted moviemaking companies and an increasing number of AI marketing platforms are developing tools that will allow producers and production companies to dramatically boost their return on investment in terms of their marketing budgets.

In a trend that was launched by Eli Roth with his film Green Inferno (2013), big data analytics are implemented into the marketing process to help direct market movies to their intended audiences.

So, for example, instead of traditional blanket marketing, AI systems help to create marketing campaigns that allow distributors to target advertisements to those most likely to see the film.

One example might be utilizing social media platforms to reach all people who either have liked, let’s say, Vin Diesel’s fan page or one or more of his previous films. These people are far more likely to go to see his latest film and, therefore, this approach allows distributors to streamline their advertising campaigns.

These are just a few examples of how AI is currently being used to help improve the films we get to watch. As these systems develop and become increasingly sophisticated, the insights that they offer are going to increase in accuracy, thereby increasingly helping the film professionals who bring them to our screens.