Contributing author: Rodney Thompson, Offering Manager, Max Engage with Watson
For quite some time, weather models from The Weather Company, an IBM Business, have used AI to continuously evaluate and adapt to improve weather forecasts. That means television stations—as an extension—have already utilized AI through the use of this weather data.
But let’s face it—this is only the beginning. With IBM and Watson being integrated into The Weather Company products, how far will AI in meteorology go?
AI is often referred to as “artificial intelligence” but a more accurate phrase might be “augmented intelligence.” Augmented intelligence is different from artificial intelligence in that it is built to use machines in a way that enhances the human worker. In other words, this type of AI is designed to add to what the television staff is doing, not replace it. Similar to the augmented intelligence that is already applied to weather models, there is still a human in the loop guiding the process and playing a critical role. Let’s break down AI’s role in the future of weather broadcasts, the new developments in weather technology, and how this will affect the role of meteorologists moving forward.
Lessons learned from test automation
Just like the meteorologist wondering if AI will replace them, I have experienced a similar transformation in my career. Before I transitioned to product management, I spent many years in software testing and QA leadership roles. When test automation roared into the industry at blazing speeds, we all thought the same thing: ”Is this going to replace my job?”
Many kept doing what they were doing, manually testing software while others jumped in with both feet to utilize test automation. Now that this initiative has reached maturity, I can share some interesting facts about how that played out.
First, automation eliminated the boring, repetitive tasks. Second, the people that learned how to automate became more valuable in the industry and earned significantly higher wages. Finally, automation didn’t eliminate our jobs; it allowed us to focus on the more important things so we could deliver more business value.
How will AI in broadcasting help the industry?
AI by itself is compelling, but it becomes useful when linked to the automation capabilities embedded in Max Engage with Watson. When content is published from a station, Watson rapidly evaluates the video’s engagement level. Is it getting views? Is the video engagement optimal for this period of time and weather scenario? This information is factored into what to do next, such as replacing a video that isn’t getting the expected engagement or changing the sequence of the video slightly and immediately reevaluating.
Even if AI makes content, the meteorologist still plays an essential role. They are now free to cover the main stories and add their local expertise while AI automation handles repetitive tasks. Time has always been a rare commodity for meteorologists and producing content for various platforms is a challenge. AI can help you focus on what you enjoy most—delivering your weather presentation—while the tech works in the background to distribute additional content across screens. You can almost think about it as a new digital staff member joining your team.
I know this phrase is thrown around a lot in our industry, but using technology to drive weather videos could be a game changer. This is much more sophisticated than the automation we do on the web today in which there isn’t an AI layer optimizing the process. Max Engage with Watson has helped television stations increase video engagement by more than a thousand percent.* Powering this approach with AI could yield similar results, going beyond what is humanly possible in terms of the number of videos produced and understanding what resonates best with the digital audience.
The future of broadcasting is here
Our mindset must change. We are no longer competing only with the station down the street. We’re also competing with new industry giants like Netflix who are fundamentally changing end-user expectations around personalization. What would the Netflix experience be without suggesting what to buy or watch next? The secret sauce isn’t video delivery; it’s the recommendation engine.
AI isn’t just one way to align with these new industry expectations, it might be the only way. Max Engage with Watson can help meteorologists drive more value for their station, keeping them relevant in a rapidly-changing world.
*Based on one leading U.S. broadcast station group using Max Engage. All client examples cited or described are presented as illustrations of the manner in which some clients have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual client configurations and conditions.