How Technology is Changing the Future of Broadcasting
Over the decades, few industries have outpaced broadcasting in embracing advances in technology, from new audio or video formats to simple automation systems that have dramatically reduced human error in the final product that reaches the viewer. Now as artificial intelligence finds its way into many industries, there are new opportunities – and challenges – for broadcasters.
Much of the new technology embraced by broadcasters literally meets the eye, in the form of gee-whiz advancements that can isolate a given football player on a given play or track the shape of a golf shot while it’s in the air.
For a prime example, look no further than this year’s reboot of the USFL, which will take many of the advancements we’ve grown used to in sports broadcasts and ramp them up to levels previously unseen. Sky cams? The USFL will use two instead of one … as well as drones. That player who’s ‘mic’ed up?’ How 20th century. On USFL broadcasts, 32 players will be mic’ed, plus coaches and officials. It will be a different viewing experience for sure.
Technology and AI, though, are beginning to impact broadcasting in many more ways that aren’t apparent on your screen or speaker. In many ways this is more evolution than revolution, as broadcasters have long used various forms of automation to remain in compliance with regulations and broadcast standards. This technical monitoring, which might range from meeting loudness standards to compliance with closed caption rules, is being transformed by ever more sophisticated technology that stops errors before they go live, and helps broadcast engineers more intelligently monitor current statuses (reducing false alerts and alarms, for one).
The anomalies that trigger those alarms in the first place are much less likely to occur in an AI-monitored environment, where performance can be tracked much faster and across a much wider range of data points than a human can. And as an added bonus, much of the work happens in the cloud, reducing the need for rack space.
Those same types of advancements are improving operational workflows far beyond engineering, though. AI-based monitoring systems, for just one example, make it possible to quickly search video archives for instances of a certain word or name, whether in the audio or shown onscreen. Imagine the difference that could make to a news-gathering organization in the event of breaking news involving a celebrity or political leader.
Broadcasting by its nature involves a continuous stream of fragmented content that might vary widely in its nature and technical quality. Viewed through that lens, it’s easy to understand the appeal of AI, which shines in making sense out of large amounts of unstructured data.
The need for these new efficiencies in broadcasting has perhaps never been greater, as the industry continues to evolve to remain competitive with non-traditional entertainment sources including streaming services and other OTT, or over-the-top, providers. What might have been a single radio or TV station a couple of decades ago in all likelihood now incorporates additional sideband channels and any number of digital platforms including website and social media. That’s a lot more content to be produced, and all in the face of greatly increased competition for ad revenues. Any improvement that brings greater efficiency without additional human capital is likely to be welcome.
All this is not to say that the advent of AI is without its pitfalls. Traditional broadcasting is unique in its role as a holder of public trust, and questions persist about the lack of transparency and possible biased outcomes of AI use. Look no further than the often-debated perceptions of bias across social media to understand the potential for things to go in the wrong direction.
As the industry gathers for the National Association of Broadcasters (NAB) Show in Las Vegas this week, attendees will find an entire section dedicated to bringing AI and other technology to content production, business strategy