Generative AI in news and media
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Generative AI in news and media

Whether we like it or not, the presence of Generative AI in news and media is palpable. Therefore, understanding what it is and its effects is in our best interest.

By
Customer Success Team
December 23, 2024

There are few technologies that have had as big of an impact on news and media as Generative AI. The internet has shifted the focus from TV to computers. Social media has kept us glued to our phones and made it vital to keep the newsreels short and sweet. But, both of these, along with many other factors, will substantially change in the coming years. To better understand this we will take a closer look at Generative AI in news and media and outline what the future of journalism is likely to be like.


What precisely is Generative AI


To fully appreciate this revolutionary technology, let's first outline what it is. Generative AI is a developing technology powered by advanced natural language processing and machine learning. By getting the necessary prompts, Generative AI can, as the name suggests, generate whatever content is necessary. Written, audio, visual... All traditional types of media content can be made through Generative AI. The more advanced the AI is, the harder it will be to differentiate the content it creates from the man-made content. Especially if the person using the AI knows how to use prompts. While this makes a lot of things easier and more approachable, it also poses considerable risks.

open artical on a laptop
Having AI write out an article is the easiest, but also the laziest and most dangerous option a journalist can choose.

Before long, generative AI will be a must-have tool for any aspiring journalist. Regardless of who your audience is, and how you wish to engage with them, the power of AI will simply be too big to overlook. This powerful assistant can be of great use, especially if it is relatively low cost. But, it can also put the entirety of publishing in jeopardy, especially if we overuse it.


Pros of Generative AI in news and media


If we put on our pink glasses and look at Generative AI in news and media we'll see that there is plenty to be positive about. Firstly, by using Generative AI, the everyday job of the journalist will be far easier. A well-trained AI can automate routine tasks like summarizing news, drafting reports, and generating headlines. Secondly, AI tools can sieve through massive data sets to identify trends and generate insights. This makes the research part of being a journalist far easier. Why go through tons of data when an AI can act as an ideal intern? It will always have the answer and never get confused.


Augmented creativity


Ok, so we have automated tasks that AI will take care of. Is that all it is good for? Of course not. It wouldn't be much of a Generative AI if it could only sum up what it reads. Another, quite notable aspect in which AI will aid journalists is in content generation. Even now journalists rely on AI to generate ideas, make content visualizations, or put what was written into drafts. This frees up the time for in-depth reporting and more devoted storytelling.


Cost-effectiveness


Having a tool that can create visual representations of your content is a godsend. Especially for smaller, local news, where budgets are often constrained. Large news companies usually have professional artists on staff to create whatever visualization they need to better cover important topics. It is important to note that these professionals have a limited time span to create the necessary visual elements. And that most of that time is spent going back and forth with the journalists to understand what the visual ought to be. So, it is understandable even larger news companies choose to visually represent only the most necessary news.

Well, with Generative AI this is no longer an issue. Both the artist and the journalists can rely on AI tools to give a visual representation of what they have in mind. This ability drastically reduced the miscommunication that is often present. Once the artist knows what they ought to make, the rest of the work is fairly easy. Not to mention far less stressful.

A woman using an AI robot to draw and image, showing the use of Generative AI in news and media.
Having AI draw up what you have in mind can save a lot of time.

Personalized content

AI enables personalization, delivering tailored news feeds based on user preferences, behavior, and location. This, in a sense, ensures that every reader gets the news that they find interesting. Just think of TikTok, for example. All of us who use TikTok have different content reels. Mind you, none of it was by our choice. It is simply that TikTok has a top-notch algorithm that recognizes what we find interesting based on certain metrics.

A large group of people.
All of us have different content needs.

The time we spend watching something, what we share, what we come back to, what we search for, the language we use... All these are important points that personalization algorithm uses to create a unique content feed for us. This is why online search and shopping is so different from what it was just a couple of years ago. Now, imagine all of that but only for a news company. Instead of getting cute videos or recipe recommendations, you get important news and discussions about them.


Scalability


Every aspiring news company wishes to become a globally recognized brand. Well, what Generative AI has brought us is the ease of scalability. Namely, if a company wishes to engage a different target demographic (say a different country or a different region) they no longer have to spend that much time localizing their content. AI can do it for them. A Generative AI system can quite easily evaluate local trends, optimize your content, and even translate it (if necessary). As such, what was once months if not years, or tiring work, now is only a few prompts away.


Data-Driven Reporting


The final positive aspect of Generative AI in news and media is that it allows for a new type of journalism. So far we've only covered how AI can mimic something that journalists did, and even be better at it. But, there are certain jobs that can be only handled by large-scale, data analytics systems. Since AI can analyze complex datasets and present them in accessible formats it can easily enable journalists to uncover stories buried in data. We have to keep in mind that the modern age is not one of hidden information, but the overabundance of it.

Filtering through endless amounts of new data quickly enough to produce timely news would be impossible for a human being. A large enough team could, theoretically, do it. However, such a team would never be financially viable, even for a large-scale company. Meanwhile, Generative AI can do what it does best and go through vast amounts of data in a fraction of the time that a team of well-trained professionals would need. As such it allows journalists to provide in-depth, time-sensitive analytics the nature of which was essentially impossible until now.


Cons of Generative AI in news and media


If what we've written so far was the only truth about Generative AI there would hardly be a concern for the future of journalism. Unfortunately, there are certain cons that some of you have likely thought of even while reading the pros. So, let's now take off our pink glasses and see what those are.


Risk of misinformation


Generative AI works based on prompts. The better the prompt, the better the content it will output. But, what if the prompt contains false premises? What if we ask AI to twist something we know isn't true? Will it stop us? Well, unfortunately, no. Again, AI works based on prompts. There have been plenty of examples where AI can generate some funny, provoking, or even quite disturbing content, just as long as the user plays around with prompts enough. As such, unchecked AI-generated content can amplify false narratives or create convincing but inaccurate stories. A lazy frivolous journalist can easily make use of this and flood the news with poor content.


Ethical concerns


If I copy something from you that is called plagiarism. But, what if I ask AI to do it? Even worse, what if I ask AI to change your content just slightly enough so that I can claim it's original? How will you prove that this is plagiarism? Or, even if you do, is it me who plagiarized you, or the AI? Issues such as these arise when AI tools are used for content creation. Namely, what stops a lazy journalist from simply copying something that their colleague has written? Strict laws and high industry standards are somewhat of a safeguard against such journalism. But, unfortunately, modern laws are hardly strict (not to mention the industry standard in journalism).

The problem of AI is especially difficult when it comes to law as it is a non-human entity that can seemingly do things on its own accord. Never before have we had such an entity, which is why it is difficult to put it in a legal framework. Furthermore, it will take years before different countries reach a consensus on what AI is and what it should be allowed to do. And before that happens we will see a lot of misuse.


Bias amplification


Having TikTok only recommend the videos you would interested in seems pretty harmless. But, is it really so when it comes to news? After all, we all have our own biases, especially when it comes to politics and current events. If we only get the news we like, we will only increase our biases. And even if we try to manually search for different content, we are still likely to get the same issue with AI-powered search engines, like SearchGPT or Microsoft Copilot.

Open ChatGPT screen
It can be surprisingly difficult to explain to AI what is bias and what isn't.

This bias amplification can further be seen when AI itself becomes biased. While this might seem improbable, it has already happened. Namely, in order to keep the AI unbiased we actively have to filter the information it receives and ensure that it interprets it in the right way. Not all new companies are diligent enough to go through this, which can produce some biased Generative AI. The news readers would get from companies using this AI would be questionable at best, as it would take a lot of work to outline why and when the AI model became biased.


Job displacement


AI will automate many of the jobs in journalism and media jobs, particularly those involving routine tasks. While this may seem like an awesome thing for the people owning the news companies, it does spell trouble for the workers. Namely, every job that AI automates is a job lost for the average Joe. Many journalists start their careers at low-end, routine jobs and slowly build their skills and knowledge for the more creative parts. If we take away these mundane jobs, where will the upcoming journalists make their living? The same goes for visual artists and data researchers. While at the moment AI makes their job easier, what will happen if it developed so much that it can completely substitute them?


Loss of trust


At the end of the day, people like to read what other people have to say. After all, if we wanted to know what AI has to say, we would simply ask AI. This innate trust in human knowledge means that an overreliance on AI can erode public trust. If the audiences suspect a lack of human oversight or authenticity they will decide that the news is simply not worthwhile. If enough news companies make this mistake of overusing AI, the total trust in the news and media can be substantially eroded.


Final thoughts


So, on the one hand, we have the unlimited potential of AI to sieve through data and produce well-informed stories for journalists. Those journalists can then use AI to better work with artists and create visuals that will be both informative and engaging. On the other hand, AI can cause tremendous job loss and reduce the role of journalism as a whole. If left unchecked, the news and media landscape will become either too biased or too saturated with untrue content. So, what will the future be like?

A woman working
Like all powerful tools, Generative AI can be a good servant or a poor master.

Well, as of writing this article, it is hard to tell. The journalists will, over time, likely adopt a hybrid model, combining AI tools with publishing expertise. AI will handle routine reporting, leaving investigative and creative work to journalists. Seeing that this leaves a lot of room for innovation, we are likely to see things like AR/VR content, enabling interactive and immersive news experiences.

The one thing we have to worry about is laziness and shortsightedness. Not only from journalists but from all of us. If Generative AI is going to be a useful tool, it has to be well-controlled and set up to first protect human rights. If we misuse AI, we are likely to create a scenario where no news is trustworthy and everyone simply believes what they want to believe. All in all, we have to be careful with AI development and approach with a degree and respect that it, at least so far, is hard to find.

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