Eye on AI - January 4th, 2021
Welcome to Aigora's "Eye on AI" series, where we round up exciting news at the intersection of consumer science and artificial intelligence!
This week, we’ll be discussing AI predictive analysis in media, including a new AI that can accurately predict movie ratings that could reshape cultural analysis in media and the potential impacts of Facebook’s emerging news summary AI. Happy 2021!
New Movie Rating Prediction AI Could Unveil Nuanced Story Patterns
We begin with the intriguing article out of TechXplore, titled “New AI tool can predict in seconds what a movie will be rated,” which discusses how researchers were able to use an AI tool to accurately predict movie rating based entirely on script analysis.
“The AI tool created receives as input all the script, processes it through a neural network and scans it for semantics and sentiment expressed,” writes TechXplore contributor Shutianyi Li. “In the process, it classifies sentences and phrases as positive, negative, aggressive and other descriptors.”
‘Rating’ as it’s referred to here does not mean viewer rating, but the Motion Picture Association (MPA) content rating (i.e. G through NC-17). Studios bend over backwards to achieve a movie’s desired rating, spending millions on re-shoots and script development when it isn’t achieved. Movie studio’s could use this sort of AI to design scripts that match their desired movie rating before filming even begins.
Perhaps most interesting is the larger applications of this sort of technology. The same AI used to predict movie ratings could potentially be used to raise awareness about the varied details about story structure and social biases. For instance, if the algorithm was trained on data from consumer rating systems –– the Rotten Tomatoes database, for example –– it could conceivably reveal nuanced script patterns that lead to higher consumer ratings, such as the sex or race of the main characters, or the basic themes, periods, or shooting styles. Such information would paint a broader picture of the movie industry as a whole, including social prejudices –– even within specific regions –– and how movie scripts have evolved. This same algorithm could be used in television as well.
Of course, the prediction of a film’s consumer rating based solely on script analysis raises potential concerns. Such technology could lead to media companies to focus more on consumer appeal rather than artistic integrity (they’re already doing this, but largely without the help of AI). Sure, money moves the art world. But many would argue that art should move the market and not the other way around.
Facebook’s News Summary AI Raises Ethical Concerns
A similar concern is being raised over the announcement of Facebook’s news summary AI. In The Next Web (TNW) article “Facebook is reportedly developing AI to summarize news — what could go wrong?”, it was revealed that Facebook is currently at work developing a new algorithm that would summarize longer news stories automatically, which has many worried about potential misinformation.
“According to a report from BuzzFeed News, Facebook is testing an AI-powered tool called TL;DR (Too Long; Didn’t Read) to summarize news pieces, so you don’t even have to click through to read those articles,” writes TNW contributor Ivan Mehta. “.... There are already some similar tools such as the AutoTLDR bot on Reddit. However, given Facebook‘s sketchy history with news and publishers, there are many ways this could go wrong.”
There will obviously be a learning curve if Facebook’s AI comes to fruition (it was introduced as a concept last month). However, minor slip-ups in summarizing news stories could lead to major issues, which would only add to the news-based issues Facebook is already facing.
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