How Artificial Intelligence Transforms Media – One of the most complicated games in the world is the game Go, and AI first attempted the challenge of playing Go and playing Go at the world championship level in 2016. The game AlphaGo was the first version that successfully beat a world-class human player. A year later a successor version of Alphago called AlphaGo Master actually beat the world champion at Go.
And those versions of AI involved an extraordinary amount of input of prior human games for the system to learn and understand how it was that the game Go is played. Within a single year after that, a further successor version called AlphaGo Zero beat AlphaGo a hundred games to zero. And so the importance of that is it took all of human history to get to 2016, where AI for the first time could play at a championship level, a year later it beats the world champion, and a year after that the version that beat the world champion is beat by a successor version of AI 100 games to zero. And that tells you something about how fast improvements are occurring in the AI space.
So, in the area of media AI is changing how media is produced and it’s changing how media is consumed. On the site of media production one sees AI being utilized in things ranging from the creation of news to, for example, an automated insights or Taotao in China is both using AI to be able to actually write news stories.
A perfect example of those would either be sports results occurring in real time, stock market stories as earnings are announced, or in the case of an LA earthquake details about the earthquake within minutes of the time of the earthquake occurred, where the entirety of the news story is actually being written by AI and without any human participation. Whether this content is embraced by people similarly one has in the case of Tatyarao 120 million daily users and a recommendation engine that is providing to those users the content that is most likely to be interesting to them.
And again when one thinks about the fundamentally transformative nature of how this type of content which was unimaginable a generation ago and not acceptable executed 10 years ago is now being delivered at scale, it creates a sense of how with accelerating change that’s likely to even more fundamentally transform the creation and delivery of news content.
We can see the same thing in other areas of media. For example, there was recently a Lexus commercial that was written by IBM’s Watson and with a storyline that is somewhat amazing when again one considers that it was written by AI. The script it created had a human designer of a new Lexus vehicle who watches as his car leaves the warehouse.
There’s then effectively a subplot where the car is gonna be stolen and destroyed, and the car saves itself by using its automatic break. And what’s amazing about that is that one computer wrote a story that is touching to people about how another computer saves itself. And again this is occurring in the just beginning infancy of the technology.
In yet another example recently Warner Music signed a music deal for 20 albums with a basically a German algorithm that creates that music not being written by people but being written by AI for a human audience. So, one other area where it is likely that AI is gonna have a fundamental and transformative effect on news and media and the consumption of media is in the area that is known as deepfakes.
Deepfakes are essentially a portmanteau word that is a combination of on the one hand deep learning and on the other hand fakes and you put those things together and it becomes a deepfake. A deepfake in practice is essentially a synthetic combination of existing images and source images, such of image or video, such that the output will appear to be a person who is saying or doing something that they actually never did.
The process uses something called a generative adversarial network. And the generative adversarial network utilizes a process of that whose output to you know to an audience makes it appear that let’s say a celebrity or a news anchor is saying something but that thing was never said by that person. And the quality of those productions is getting better, and better, and better, and already only five or six years after the technology was invented, it’s at a level that is close to good enough or good enough to fool an observer.
The consequences of that over time for purposes both good and bad are likely to be profound. As an example of a good use of it, the global superstar footballer David Beckham was in an anti-malaria video where as a speaker of English he was able to state the desired message in English but he was also able to through the use of deepfakes provide an identical message in six languages that he doesn’t actually speak. Malaria isn’t just any disease. It’s the deadliest disease that’s ever been. …..
So that’s an example of using the technology for good but that same technology could be used in exactly the same way for malign purposes. And media companies in every level from news organizations to news aggregators, to consumers themselves are gonna have to become a lot more sophisticated about what this technology is, how it’s used and its implications.
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