Artificial intelligence and the future of broadcast industry

Content and artificial intelligence is so intricately married today, that it is difficult to even try and think about them separately. For a long time, our predecessors tried to hold on to the age-old practices, but the next journey is about keeping abreast of changes, rather than trying to stall.

The picture of a journalist with a typewriter will always stay embedded in our heads. The newsroom culture is vastly different at present with greater exposure to global media, whereby a journalist needs to be multi-skilled and aware of current developments within the industry.

In fact, the more up-to-date the journalist, the more impact his news has and, therefore, the more relevant his work.

It has now become paramount to embrace these changes, as frequent as they may be, because like news and information, the world is transforming at an equally frantic pace.

What is artificial intelligence?
The crux of AI is to lessen human intervention by developing computer systems that can perform tasks. The program mimics human cognitive functions like learning and problem-solving.

Whether it be answering direct questions or smarter systems that map users’ habits, artificial intelligence has far reaching effects because of its evolving nature.

At present, AI is being integrated into not only in our professions, but in our everyday lives as well. Take for instance, our commonplace interactions with Siri or Alexa, scheduling our calendar or even Google maps. There are more complex systems that were originally coded by humans, but its algorithms change as it learns and updates.

How is AI integrated in newsrooms across the world?
The use of artificial intelligence in newsrooms across the world have been adopted in diverse ways–whether it is in natural language processing or collating data–in order to gather, generate, process, and distribute content.

The New York Times used machine learning to take its archive of recipes and create the NYT Cooking app, and hopes to use automation to digitally archive its photo collection.

Dataminr is used widely to track tweets as well as geomap it as a form of news generation. In China, news app Toutiao has 120 million users with individual engagement.

Newsfeeds are updated based on the reader’s preferences, time spent on an article, and location.

In the UK, a service called James is being developed by The Times and Sunday Times, which will help learn about individual preferences and automatically personalize each edition in terms of format, time, and frequency.

The Swiss newspaper Neue Zürcher Zeitung (NZZ) is developing AI algorithms that are not optimized for clicks but to uphold journalistic standards.

AI helps journalists pre-empt the answers to questions
You may be the biggest icon in the industry but you will have to continue to turn your attention to the story that is being told from places that may be difficult to access. So, when I hear things like machines will take over writing, I know for a fact it is not possible.

One of the biggest challenges of journalists on the field is contextualizing the stories, so teams sitting on the backend in a newsroom even though may have more access to resources will sometimes miss the big story because they were not seeing what the reporter was seeing on the ground.

But artificial intelligence helps solve that gap. It helps both the newsroom managers and reporters on the ground. AI takes a story, its context and takes references to other articles and analyzes what is missing in the story. Millions who search for the story or anything related to it leave a trace on the web, indicating what people are seeking.

Video and artificial intelligence
Storytelling through video has become an integral part of our discipline. Although textual stories still manage to hold their own, giving us perspective that a 1-minute video cannot, yet in this fast-paced world where everyone is crunched for time, videos are the need of the hour.

They are informative and attractive, presenting facts that would have otherwise been dubbed boring. In a nutshell, videos have a greater impact on the human mind than a mere text piece.

Almost all news media houses have realized and accepted the shift of audience toward video for news consumption. But there is a whole lot of process behind making videos, including skill-based expertise.

The nuances of a language and the twists and turns of story that a human being is able to provide, a machine will not be able to do that ever. Similarly handling video is even more complex. The subtle juxtaposition of images, sound mixing and structure of the video will always be a complex process determined by the aesthetics of the human mind.

But there are also multiple repetitive tasks that need to be outsourced to machines. The machines can do it faster and better and deliver it back for review. The review helps the machine learn what it needs to fix and over a period of time the machine learns not to make the same mistakes again.

Let us say that a text story has been written and a video around that story has already arrived in your system. The artificial intelligence platform is capable of delivering a script based on your text story, along with images that will go with the script of your story.

It is also able to identify interview clips aligned with the text quotes you may have included in your text story. The task of getting them all in line is now done and this is where the human comes in to review the work of the algorithm.

The review process of the AI now is resting on a learn mode, learning how the humans make changes on the system. After enough usage of the system, the machine begins to get better at its task.

It also learns how to handle audio levels like when the natural sound needs to be higher and when it needs to be lower. It also puts on name supers, location bugs, and information crawlers on the story. If each of these tasks had to be done manually it would take a video editor much longer.

Conclusion
Artificial intelligence and machine learning together have the ability to make the job of journalists easier and empowering. At the moment, in order to compete on multiple mediums, one is getting burnt out, struggling to stay relevant within a small space and span of time. But artificial intelligence should be able to bring a cohesiveness and ease of doing a comprehensive story without going crazy on a manual treadmill.

The purpose of AI is to understand your mechanical actions over a period of time and become better at implementing those actions. What technology brings to journalists is empowerment with less dependence on sound recordists, editor, assistant, producer, and others.

AI empowers you to stitch your story together faster with least technical knowledge. It is important to understand that the aim of the technical people is to build advanced technologies to empower non-technical people. For using hi-tech or AI, you do not need to have a technical degree.

As we all restructure our lives to integrate AI, such questions and dilemmas are bound to arise, and it may take a while to solve it. But one must realize that AI is here for good, and we must look forward, use safeguards, and embrace the changing tides.