In his 1983 memoir “Adventures in the Screen Trade,” Oscar-winning screenwriter William Goldman famously observed that in Hollywood “nobody knows anything.”
By that he meant no one involved in making movies really knows what will work and what will bomb ahead of release. “Every time out it’s a guess and, if you’re lucky, an educated one,” he wrote.
Were he alive today, Goldman might be shocked by just how possible it’s become to change this.
“Artificial Intelligence and Media,” the new 18-page special report from Variety Intelligence Platform (VIP), explores how the transformation of the movie, music and other media and entertainment industries over the past two decades, from ones based primarily on production and distribution of physical media via analog channels to ones based on digital formats and platforms, has yielded a torrent of consumer usage, preference and behavior that can be harnessed and applied across a plethora of entertainment-related functions.
Available algorithms can analyze film scripts and generate surprisingly accurate models for how a resulting film will likely perform in various territories.
Similarly, music recordings can be analyzed to measure hit potential. Given the right kind of data, A.I. systems can even identify which emerging artists are likely to produce a breakout hit within the next few months.
Combined with ever-growing computing capacity and advances in the computer science of artificial intelligence, Big Data can be plumbed to discover deep patterns and relationships among the attributes of millions of movies, TV shows and songs a human brain couldn’t hope to recognize or measure.
A.I. tech is also finding its way into writers’ rooms and recording studios as an aide to invention. It is even being put to use to create original music, visual art and news articles with little or no human input.
Given the financial stakes involved in creating media, it is increasingly unrealistic to expect A.I. will remain just a neat little aide, as its applications will only expand upon themselves the same way its algorithms are in a constant state of self-improvement. The big question: For how much longer can art remain a human-controlled operation?
Read on to learn about:
How A.I. was applied to tasks throughout its initial development phase and what machine learning, deep learning, and generative networks mean within the context of A.I.
A.I.'s earliest media applications and how it is currently being used to generate the hit potential for media across multiple sectors
How further development and usage of A.I. for media creation will complicate and redefine how works are both financed and copyrighted