Artificial Intelligence and Synthetic Media in News Broadcasting
By: Tina Gelato
Tags: AI, Predictions, Artificial Intelligence, Trends, Broadcasting

We’re all familiar with news broadcasters like Anderson Cooper or Wolf Blitzer, and their lives outside of CNN. But what if the lives outside of these media hubs did not exist.

The National Broadcasting Company (NBC) was created in 1926, and by 1951 it had coast to coast regular television service. Television programs, like news broadcasting, were prepared well beforehand, and because of the slow travel of information as a result of lack of the internet, not everything was up-to-date as it took place.

The nightly news was always a formal event in suits and ties where families could look forward to not only learning about current events but also to inviting the charismatic anchor into their home for the evening where they would learn a little bit more about his personal life.

By all means, live news broadcasting soared in popularity and found its way to being a prestigious profession. In the United States, Journalists were and still are very respected individuals who go through years of proper schooling in order to deliver information to the people. A relationship was built between journalists and the people, a level of trust in their information, feelings of security and protection, and the feeling that you are tuning in to see your “friend” talk.

Journalists’ main goal is to deliver unbiased information to the people as quickly as possible. Acting as an unofficial fourth branch of the government, the news is a watchdog. However, we have started to see trends of shying away from proper journalism and towards stories that have the most “clicks” in order to curate content.

Content has become an incredibly important resource for media companies to have, it is looked at as currency. The more content the better. However, it is almost physically impossible for human creators to constantly put out new, entertaining, and factually correct content. As a result of this growing media problem, we have increasingly leaned on the convergence of technology and news broadcasting: artificial intelligence (AI).

The 24-hour news cycle is a tough feature to keep up with without a large staff. Information needs to be constantly analyzed, synthesized, and repurposed quickly and in an accessible way for the general population. Because of how disruptive the internet was in relation to breaking news, people demand instant information. No longer are they willing or able to sit through the 6 o’clock news when they could have already had the information at their fingertips.

While viewers do like having a connection with anchors, TV viewing time is decreasing and younger audiences especially are moving towards digital media in order to get their news. This is where artificial intelligence began its slow creep.

When breaking news happens, every news company wants to be the first to report on it with the correct information. We have seen an increase in links to a blank article tweeted by journalists with a statement along the lines of “developing story”. This is because it is physically impossible for a human being to write a full-fledged story within minutes of breaking news. Artificial intelligence is beginning to put out articles in just minutes following a major event.

Journalists have the tendency to be biased even though they claim to be unbiased. The reality is if you are a person who is able to perceive you will have a bias. While not intentional, anyway a journalist chooses to tell a story will be skewed to fit into their own creative narrative. Artificial intelligence does not have the capability of perceiving, therefore it cannot have a bias when reporting.

Not every news broadcaster has the ability to turn niche information into a well-informed story. Artificial intelligence cannot be bored by dull data, it takes in large amounts of data constantly and regurgitates a story out of it.

While artificial intelligence seems like the cure to every issue within news broadcasting, there are many things it lacks that we like in the current climate of journalism. As mentioned before, viewers like feeling a personal relationship with the anchor on their screen. The information feels as if it can be trusted more because it is from a “friend”.

Viewers also learn about the lives of broadcasters, for example, Anderson Cooper’s family is a frequent topic on his show, which makes watching the news a personable experience. Watching a human is not dry, human journalists do not just regurgitate synthesized information, they interweave an intricate story to creatively educate viewers. This is something news broadcast viewers are not ready to give up in exchange for quick accurate information.

Back push from viewers will always be a factor driving AI broadcasters away. Viewers want to avoid the uncanny valley that AI broadcasters can bring on-air, they want to hold on to the emotional aspect. Also, major contracts will keep traditional journalism afloat. Anderson Cooper has at least two years left on his $12 million per year contract signed in 2016. He, like many other anchors, is a personality that people are not ready to give up.

As mentioned before, artificial intelligence is slowly creeping into traditional news broadcasting and disrupting what we know. As time progresses we will only see a further convergence of journalism and AI in order to create content.

The direction of news broadcasting is already heading the way of artificial intelligence, and it is just a matter of time before we have the full technology for AI to fully integrate with the broadcasting system. AI is already seen within journalism, it is just not as prominent in some places as it is in others.

Starting with a basic amount of AI in news broadcasting, many media companies have adopted their own versions of the technology. Watson is a program used by The Weather Company to perform on-air captioning and it is now training to pull out key concepts of videos in order to make a condensed version of the most important information. In the United Kingdom, Channel 4 uses “Contextual Moments” in order to analyze scenes and to discard moments that score low in importance. This is a basic level of AI that pulls out information, recognizes its importance, and reworks it for a more optimal story.

Getting more complex, The Los Angeles Times was able to publish a report about an earthquake a mere three minutes after the earthquake took place because of their software robot Quakebot. No human could ever do this. Many media organizations have their own version of Quakebot. The BBC has Juicer, the Washington Post has Heliograf, and Bloomberg has Cyborg; Cyborg is credited with creating “nearly a third of the content” published by Bloomberg. The U.S. has taken a much slower turn towards reliance on AI than other countries, like, for example, China has.

China has already rolled out a few AI news anchors who regularly appear in their line up of presenters. The first AI anchor was in 2018 named Qiu Hao, and the most recent is Xin Xiaomeng; Xin is based on a real-life anchor by the name of Zhao Wanwei. These AI anchors are developed by Xinhua, the Chinese state news agency, and the search engine Sogou; they are able to “imitate human voices, facial expressions, lip movements, and mannerisms using only text inputs”. China hasn’t kept these innovations to itself, Xinhua worked with ITAR-TASS, a Russian news agency, to create a Russian-speaking AI anchor. China created this technology and is now beginning to expand it past just its own people.

There is definitely quite the difference between Watson who live-captions on-air production and Xin Xiaomng who analyzes data, graphs, tables, and spreadsheets to pull out the main ideas in order to form a narrative and then present that narrative on live television. China has fully embraced artificial intelligence as news broadcasters, and are looking to improve the technology. The U.S. on the other hand has not accepted it with the same open arms.

This is the trend of artificial intelligence existing in news broadcasting, China has just utilized the innovation earlier than most. A valid prediction is that this technology will become widespread in the world and everyone will eventually have to adapt to AI anchors on live television.

One of the Six SuperTrends is Technological Process, and the “T” in “DEGEST” is Technology. Artificial intelligence in journalism is a prime example of these trends. Over time technology improves, it is a basic fact. It is only probable that as technology improves we tend to incorporate it more into our lives until there is no separation. As artificial intelligence improves we will see more synthetic media produced. More articles will be written by software robots within minutes of an event, and then presented by an avatar.

We sometimes tend to look at technological growth as stagnant when there are only small updates in between innovations, but the technological trend looks at technology in chunks of time. From year-to-year AI might not seem like it is a huge disruption to traditional broadcasting, but twenty years ago the thought never even crossed journalists’ minds. This shows how a slow transition is needed in order for the innovation to be accepted.

According to the Gartner chart, the U.S. lies somewhere between Level 2 and Level 3 of artificial intelligence in the broadcast industry. This means we have moved on from the Active stage, which is using AI in an experimental way, towards the Operational stage, which is beginning to practically apply the innovation in order to create content. This chart shows how AI is taking off but it is not necessarily running the broadcast industry just yet. That is when we get to Level 5, where it is impossible to separate AI and news broadcasting. The progression towards AI in journalism is already underway, and it is just a matter of embracing what is to come.

As mentioned before, content is currency. Meaning, AI can create rapid, accurate content which will draw in money for media companies. Another of the trends is Economy. News companies are able to lower their costs of production without having to pay for anchors and curators and can pump-out articles in a way a human never could.

Artificial intelligence will continue its journey towards integrating with the traditional news broadcasting industry until that Level 5 is reached and it mimics what China has already been doing and then surpasses it.

As evident, journalism industries are already adopting artificial intelligence it just needs time to work out all of the wrinkles.

New players will enter the field as the innovation proceeds. News companies will no longer have to invest in creating their own AI infrastructure as they will be able to outsource. Companies like AWS create free services based in the cloud with an upgrade available for companies who want to use their AI technology; the services include text to speech, speech to text, image and facial recognition, language processing, and other technologies. As a result of artificial intelligence convergence with journalism, technology companies will be created just to outsource the program.

The companies who have created technology like Xinhua and Soguo, or the news companies like the Washington Post’s Heliograf, will not remain as the front runners or providers for the innovations. We will see many businesses that focus solely on AI come to fruition in order to license their software to journalists. Outsourcing will be a large part of AI in broadcasting because it will become a commonplace technology but it is not the easiest to create on its own. A reason for this being that artificial intelligence runs on data, and for smaller companies, it is very difficult to collect big data in an effective way. Creating a business that solely focuses on collecting this data gives the resources to smaller journalists, making the trend more accessible, therefore, more widespread. Which as we see with AWS, is already happening.

This again goes into the idea that content is currency. The data collected for AI to analyze is the foundation for the content to be produced and as a result, make money for the company. The convergence of the two is very important for both industries to thrive.

It is probable for ethical and other problems to arise as this trend fully takes off. Ethically we ask who owns AI curated content. The argument is that considering a robot (nonhuman) wrote this article (or another form of expression) this piece should not have copyright privileges and should be deemed fair use. The opposing side is that someone has to gather the data, create the AI, and present the data to the AI, but who does this belong to; the machine, the software, the company behind it, the man who collected the data? There are so many options of who could possibly own the content created and considering we hold being a human to be a standard for copyright it is possible these articles could be considered fair use. New companies will not like not having control over their own stories and the data behind them.

Humans also hold creativity to a high standard, and as a uniquely human thing. However, we are not far off from AI picking sides and creating their own opinions in order to write “articles with flair, imagination, [and] in-depth analysis”. This will throw a curveball in the idea that AI curated content cannot be copyright because if AI is having original thoughts instead of just regurgitating data in a condensed form then this should be able to be copyrighted.

This then leads to the idea of a loss of jobs. No matter how amazing technology progresses the first worry is always who and how many people will lose their job. Artificial intelligence has the ability and will take over jobs. AI can pump out accurate articles rapidly in a way humans cannot, it also lowers production prices because software does not have the same salary price point as a human news broadcaster. This is all dangerous to the traditional journalist and is a reason there will be barriers for AI in journalism thriving. Humans want to keep in control and they want to remain employed even if the robots do their job better than them, this is specifically true in the U.S. There this culture centered around working hard, and AI poses a threat. Instead of focusing on converging the innovation with what already exists, there will be a push back against it.

Another barrier would be a lack of connection between anchors and the audience. As mentioned earlier, people like to trust the source they are getting information from. They also like to learn about the personal lives of broadcasters, and this cannot happen with AI anchors. Viewers will pushback against having fully synthetic people on screen in the U.S. because there is no relationship between the broadcaster and the audience.

There are many scenarios of what can play out decades down the line, but I am only highlighting three possible generic scenarios that can be seen for the future of artificial intelligence in news broadcasting. It is impossible for AI to be fully ignored and unused as it has already been integrated too much for the rejection to be possible, because of this the scenario is not entertained.

The first scenario is that artificial intelligence will continue to slowly creep in but only to a certain extent. Journalists will stop bothering themselves with minute and boring work and leave this up to AI instead of taking the job on themselves or having an intern do it. AI will not be invasive to the U.S. broadcasting industry and we will very rarely see synthetic people on television and only give air time to humans. There will still be the old issues of biases in writing, inaccurate information published, and articles taking a long time to be published. AI will work more as an aid to small things within the broadcasting industry and its full potential will not be used within the U.S. because of constant pushback from the workers and viewers. The innovation in this scenario remains pretty much stagnant.

The second scenario is that artificial intelligence will fully take over the broadcasting industry and will put journalists out of jobs. New jobs will be created to assist AI in data collection but the software is the one curating the content. All anchors will be synthetic, and all articles published are reproduced from data collection services. No journalists are human and the emotional connection between the viewer and the anchor no longer exists. The issues of misinformation, biases, and timely articles have been fixed because AI fully running the industry, but it lacks chemistry and depth. This is an extreme view of what AI could do to the broadcasting industry but it definitely is a reality that could happen.

The final scenario is the one I believe to be most probable. Artificial intelligence will continue on its path of converging with broadcasting until the two are synonymous. AI will work alongside journalists to put out quick, reliable, and unbiased information. AI will have a huge part in quickly putting out articles in order to avoid the issue of blank links while the story is still developing. Journalists will take a step back from always being the ones to publish factual articles and will watch over AI’s curation. News broadcasters will still have a spot on television alongside synthetic anchors. They will seamlessly interchange spots, which will maintain the emotional relationship with the audience. Fully integrating AI into journalism will reduce a lot of the issues that exist today, because artificial intelligence can only write factually. This will almost eliminate biases within journalism, and continue to act as a watchdog for the government. A huge emotional side of journalism will be reduced because there is not a person reporting these huge issues. Audiences can get the facts and go. There will however be big data conglomerates that license out their artificial intelligence to news companies and are only concerned with turning a profit. Because AI runs on data collection, there will be a lot of stored data. News broadcasters will work in tandem with artificial intelligence in order to curate the best possible content and information for the general population. In summation, AI will converge with journalism like any other trend and become a commonplace practice.

Artificial intelligence has a large spot waiting for it in the future. We have already seen the trend in action both within the United States and globally in ways that are almost sci-fi like. It is impossible to stop the disruption AI will bring to the broadcasting industry, as we have already seen the small effects of it so far. The journalism industry as we know it to be has been stagnant for so long and needs its next big innovation, and artificial intelligence will be the trend to do so.