The power that AI filmmaking solutions give production companies to see into the future cannot be understated. In effect, AI is a magic wand that can help filmmakers steer clear of dissatisfied audiences, and with them, possible financial disaster.
Artificial intelligence driven big data analytics has already scored a number of big hits.
A 2018 study showed that “half the money earned from profitable ventures in recent times came from the top 6% of movies and half the money lost came from the bottom 6%.” To put this into perspective, the global movie business loses hundreds of millions a year on movie ‘flops’. Cats (2019), for example, only managed to recoup about $10.9 million of its $100 million budget, something which would have certainly hit the studio’s finances hard.
With yearly losses like these, it is no surprise to hear that several big studios including Warner Bros and Fox have already signed deals with artificial intelligence moviemaking companies to help them minimize their exposure to risk.
AI-assisted filmmaking has already achieved prediction accuracies in the mid to high 80% when it comes to predicting the box office revenues of upcoming releases. Several of the top AI-assisted moviemaking companies are now offering a service that predicts viewing figures for online video on demand platforms too. Along with these services, artificial intelligence can help filmmakers with everything from casting choices to direct marketing.
Most importantly, AI has helped level the playing field in a number of ways for productions of all sizes. Eli Roth’s The Green Inferno (2013) was described as the “make or break moment for the future of independent film” due to the production’s use of machine learning big data analytics to market the film to its target audience. It worked. The film took in $12.9 from a total budget of $8 million.
Despite these and other successes, the movie business has been slow to embrace AI, largely because of unfounded fears of mass job losses. But in an era of the huge losses in income due to the COVID-19 pandemic, which has also helped dramatically speed up the switch from cinemas to online viewing, it is clear that the movie industry has no choice but to embrace AI to turn things around by enabling it to reconnect with its audiences.
The AI-driven Global Movie Business in 2040
What would the global movie industry look like 20 years from now were it to comprehensively embrace artificial technology solutions today?
The most obvious answer is that it will still be a healthy industry that remains popular with all age groups and demographics.
Moviegoers would still be heading to cinemas in large numbers to see the films that they want to see, as well as watching and interacting with them (VR interactive movies) at home via online streaming services.
Interactive movies are certain to spawn new culture of small, private cinema rooms similar to those now used to service karaoke parties. This will inevitably provide huge new revenue streams to movie theatres as well as leading to a huge growth in small ‘local’ interactivity-focused cinemas. Interactivity is certain to dramatically boost audience numbers, and indeed, might eventually replace 2D movies altogether, however, this is a topic for another article.
The important point is that AI will allow the movie business to remain relevant to both young and old people and to all demographics. Age group is a vital factor for long term success as it is only by constantly attracting younger generations that any artform can continue to thrive.
Movies are currently locked in a battle with changing behavioral habits and shortening attention spans that have resulted from our interaction with smart phones and tablets. Many young people who have grown up with these devices no longer want to sit through a two to three hour film, and if they do, need to be constantly entertained by rapid-paced drama or action scenes. This factor alone has huge implications in terms of the types of movies that get made.
Catering to a wide demographic range is arguably the most challenging problem that movies face. Compounding this problem is the fact that the movie business is a very reactive industry, it nearly always lags behind social changes.
Overcome in recent years by a wave of movements that aim to prevent negative or stereotypical portrayals of minority groups, along with their desire to see better representation in terms of employment within the industry, Hollywood has, almost more offensively, simply tried to ensure that more actors from certain backgrounds ‘get their faces up onscreen’ in what are frequently superficial characterizations.
The richness of the cultural diversity of minority groups in the United States could spawn hundreds of fresh and interesting movies, and many new genres with them. Just consider the Blaxploitation movie genre of the 70s or the transgressive cult films of the same era and you can see what an enormous wealth of characters, stories, and different perspectives there are out there waiting to get represented onscreen. And most importantly for the movie business, there are the audiences are ready and waiting to watch them.
Artificial intelligence solutions coupled with big data analytics will overcome the problem that has stifled these and so many other promising genres for generations. It will allow for the true celebration of cultural diversity that has the power to make the movies we get to see rich and culturally relevant once more.
This represents the golden goose for a truly long lasting and healthy film industry, namely, that underrepresented groups are not bought off with superficial representations, but rather get to see their real cultures and stories celebrated onscreen.
Were there to be a mass adoption of AI today, the most obvious result would be the almost obliteration of the box office flop. The industry would then be able to invest these sums of money into more movies. As its confidence grew in AI’s ability to accurately predict how much a particular film would make at the box office or through online streaming deals, an accuracy that will only get better and better the more these systems are used, the industry would be able to take bigger chances on the type of films it made.
Since the medium and small sized studios would also be using AI, thanks to its low cost of access, audience viewing habits and numbers would quickly be mapped out so that markets for specific genres of all sizes would become clear.
Very quickly after mass adoption, these systems would learn how many people like watching, for example, low budget horror movies ($50,000 or less), and more specifically, what audiences liked and disliked about each one. With this information, the system could accurately predict how profitable a new low budget horror movie would be.
These insights would allow all kinds of production companies to greenlight specific numbers of films per year in order to meet the needs of their particular audience segment. An obvious example of where this has been done in the past, though based more on ‘hunches’ than accurate analysis of data, is the Christmas movie. Each year, a very small number of Christmas movies are made and scheduled for an late December release with the knowledge that there will be a definite appetite for them.
The bottom line is that with accurate insights from ever increasing pools of data, AI would have the power to outline specific market sizes, factor in the number of rival productions currently being filmed, etc., and help target market these films to specific individuals via social media, all of which would empower production companies to minimize risk and be profitable, no matter how small they were.
An Inevitable Outcome
The most promising aspect regarding the mass adoption of AI-assisted filmmaking practices would be the inevitability of this outcome.
Even if the major studios were to ignore the smaller markets and to simply hang onto their additional profits, independent or smaller studios will still continue to make these types of smaller budget films.
These studios will still utilize AI to understand their market, even though their films might not make it into cinemas, as they would still need insights regarding distribution via online streaming platforms. As previously stated, the use of AI systems would allow them to map out all the potential markets for whatever types of films they are analyzing.
Once a market has been identified and mapped, the profitability of making movies for that segment would become clear. These reliable profits mean healthy production companies, no matter what their size.
This removal of risk and clear understanding of audience numbers and preferences will turn the clock back and result in more diversity in terms of the films being produced. Most importantly, it will very quickly reverse the current ‘good movie education problem’, where young audiences become educated to enjoy a very narrow range of movies. This process, which is well underway now, results from the lack of diversity in our cinemas and the inevitable relationship that young viewers form with the narrow range of movies that they see.
Expanding the diversity of films available is the only solution to this problem. Allowing individuals to experiment to see which kind of film they enjoy will allow them to develop a passion for film and also guarantee a diversity in audience viewing preferences that have made film such a rich and varied artform in the past.
AI needs support in order to develop however. While it seems certain that the damage caused by the COVID 19 pandemic will speed up the implantation of AI movie production aids, the longer that it takes for these solutions to be fully adopted, the larger the chance that uninspired audiences turn their back on movies forever.
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