A huge topic of interest for broadcasters today is how the new developments in Artificial Intelligence (AI) will affect local media. Broadcasting hasn’t changed much in the past 50 years and, as we know, change is hard. But saying “We have always done it this way” is not going to be a valid response in the new age of AI.
People hear “AI” and immediately think, the robots are coming to take our jobs! This actually isn’t totally incorrect; according to AI investor and expert Kai-Fu Lee, artificial intelligence may be able to replace 40-50% of jobs in the United States within 15 years (pg. 19 AI Superpowers, Lee). Jobs that consist only of data compilation and “keystrokes” are poised to be replaced by machines. But this is not entirely a bad thing. It will allow the human work force to do the work we were intended for: high-level decision making.
If you are in media and have attended any conferences in the past year, your buzzword bingo cards are full of phrases like “Let’s unpack that” and “swim-lanes,” as well as the requisite “data-driven approach.” So, let’s stay in our swim lane and unpack what it means to be “data-driven” in the AI age of media… in non-buzz talk.
The term data-driven has been beat to death. What it means simply, is to take the personal bias out of decision making. Speaking specifically to broadcasting, human bias or “going with your gut” when making decisions sometimes results in wonderful results. Many of us know the story of the reporter from a small market who stands out to her news director, moves up markets quickly and ends up on a national morning talk show. But as great as those stories are, there are many more unfortunate tales where a gut decision created major headaches and cost both stations and companies revenue.
Humans are a product of their environment. How we were raised, our values, the markets we have worked in — these all affect our decision-making skills. When we discuss being data-driven, we mean using the data on hand, not affected by human bias, to make more informed decisions.
Up until now in local news, a treasure trove of available data has been absent in the decision-making process: the content itself.
Using AI to truly understand the data that makes up your content will be crucial in the future of media. We can look to Netflix being built on this principle for validation of that fact: they receive massive amounts of data from their viewers and they use all of it to their advantage to deliver what their viewers want. When you use machine learning to rapidly decode content into data, you can compare that to viewership data, web listening and other third-party data sources to truly understand what content is resonating with your audience.
A great example is a TV station Transform worked with that wanted to know if they were showing an equal percentage of male & female faces on the screen in newscasts; not just the station talent, but with all video including interviewees and stock footage. Their gut instinct was that they were doing a very good job. The data proved otherwise, over 60% of the faces shown on the screen were male, leaving the newscasts very far off from gender parity.
So, what’s the good news? Fixing all this is simple. Integrating AI is quick and painless, it works brilliantly and it will arm you with the necessary data to do what you’re best at: making the informed decisions that will lead to greater success in your markets.