The Broadcast Landscape in 2023: Predictions & Analysis

Thursday, 26 January 2023

Uncovering Opportunities in a Slowly Evolving Industry

It is always difficult to make predictions, especially in an industry where the pace of change is slow. One reasonably certain prediction is that by the end of the year, things will be largely the same with some micro advances in some areas. It is those advances that I will try to focus on in this post, along with some thoughts gathered along the way.

How Data Will Change the Broadcast News Industry

Data-driven workflows will become increasingly important in broadcast newsrooms in 2023. Data can be used to better understand the audience and tailor stories to their interests.

Data can also be used to track viewership and engagement with these stories, allowing news teams to quickly and easily identify, which stories are resonating with the audience and which are not.

Data-driven workflows will also allow live graphics to create a two way conversation with a viewer over social media, injecting a new lease of life into the linear broadcasting format. The engagement is far higher when viewers feel involved and with the rising power of FAST channels, I predict that linear broadcasting will be back in fashion.

Balancing Morals and Efficiency: The Use of AI in Newsrooms

Automation will also become a major tool for broadcast newsrooms in 2023. Although studio galleries have used automation for some time, the newsrooms haven’t. This new breed of AI powered automated systems can be used to assist and research in the production of stories from thousands of online sources and formats and present curated results.

The explosive arrival of OpenAI with its developments around GPT is another step forward that cannot be ignored. While there are moral dilemmas around the use of AIs in newsrooms, I tend to view them as a tool to augment humans, not replace them.

imagine/: “a yorkshire mining village girl with a dirty face but dramatic lighting and a city behind which is full of smog”

What about the use of synthetic media? You can see from this set of images generated by midjourney, from a simple sentence AI can generate incredible photorealistic imagery in minutes. Now, in some ways this can save time hunting through stock libraries for generic images to put on video walls, etc. On the other hand… The camera never lies until it does.

How can we juggle this moral dilemma? I suspect that we simply won’t.

AI is likely to be restricted to speech to text, translation and a few GPT-3 applications for suggesting and augmenting stories. Imagery may very well be a step to far this year.

The interface to the story

With the proliferation of devices across all demographics of society, delivering content has become more of a challenge. Now we are not making TV for a screen in the living room, we are making content for all sorts of devices, in many different aspect ratios and sizes.

To solve this challenge we don’t need to start with a solution, we need to work backwards from the viewers experience. None of the interfaces people view content on are consistent.

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Here is the same story viewed on all the social platforms…

This is something that we rarely consider, somehow we think all these platforms have it sorted out. They haven’t, so we have to. This is something we explored in the IBC Accelerator last year in the “News Studio of the future”. You can see it here:

As we spoke about in that project, one place AI and ML can be of help is in story versioning. One version of a story can no longer satisfy all ages or platforms, so story versioning is also going to be an exciting new development. Effectively finding ways to fork a story for different demographics and social platforms through versions.

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Breaking a story into its component DNA pieces can facilitate story versions built to a users preferences

It could be that it is built into a single story, that is written to be segmented, or different versions automatically generated into the long and short versions using machine learning. Essentially one size does not fit all anymore and newsrooms will learn to adapt the content to that philosophy.

The Impact of Too Many Apps on Employee Productivity

The average team member uses 9.4 different applications for their daily work, that’s not an efficient use of money, resources or time. We need to use more consolidated and automated solutions that can also help to streamline workflows such as editing, approval processes, publishing to third party APIs on web and social media.

We need to do more with less and create efficiencies in workflows allowing organisations to improve productivity by reducing the training and cost of too many apps per team member.

We teamed up with Mr MXF to make a video that explores this concept:

Change Management: It’s Not All About The Technology

Defining the solution as being a technology is unhelpful, there’s better things to focus on like, what are the real frictions in our newsrooms?

Using these older legacy technologies creates friction in a workflow, it’s fighting the last war, not the current one. What we are not changing, we’re not improving.

However, people always matter and relationships always matter.

One thing people don’t like is change. If we want to reduce workflow friction then we must also manage the changes that come hand in glove.

This can be achieved by creating a partnership between the people and the technology, enabling the people to focus on the higher value, more meaningful actions and behaviours.

The tech should play to it’s strengths… lightning fast processing, doing repetitive tasks without growing bored and analysis at scale that’s impossible for humans to accomplish.

In Summary

So when we are looking to invest in new technologies this year we need to bear in mind more than just the technology per say. We have to consider the morals, the people, the change management and the cost.

More often than not we underestimate the amount of investment required. We haven’t thought about how much it costs to maintain and support these solutions, because we’ve used a more complicated technology rather than a simpler one.

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We’ve applied the wrong set of skills to solve the problem because we are using the new technologies in the same way we used to use the old technologies.

We cannot release the powerful full potential of these new technologies in this way, that’s what we need to focus on.

At end of year, if you’re disappointed with the results you’re achieving despite all the technology you’ve invested in and the great people you’ve hired, could it be that you’ve been looking in the wrong place for answers?