AI Writing

AI Writing Tools and Journalism: What Does the Future Look Like?

There’s no doubt that with the breakneck pace of digital technology adoption, AI is quickly making its presence known in a variety of sectors. From actor and screenwriter strikes to artists filing lawsuits and everything in between, journalism is no exception to the industries that have changed in a major way because of AI. 

Sherice Jacob

There’s no doubt that with the breakneck pace of digital technology adoption, AI is quickly making its presence known in a variety of sectors. From actor and screenwriter strikes to artists filing lawsuits and everything in between, journalism is no exception to the industries that have changed in a major way because of AI. 

But what does the future look like? In this article, we’ll take a closer look at how AI writing tools are impacting the journalistic process and whether or not the technology and the field can have a symbiotic and beneficial lasting relationship. 

Understanding AI Writing Tools

Before we dive right into the implications of AI in journalism, it’s important to understand the AI writing tools behind the profession. In short, AI writing tools are software programs or algorithms that digest vast amounts of data and leverage natural language processing and machine learning techniques to create written content that mimics human writing patterns. Common examples of AI writing tools include ChatGPT, Google Bard and many others.

How are AI Writing Tools Used in Journalism?

In order to look toward the future with confidence and predict how AI writing and detection tools might be used, we first need to understand how these tools are currently used in the journalism landscape. 

Automated News Reports - Many news organizations, including the Associated Press, use AI writing tools in order to create short, easily digestible reports, especially when it comes to financial news and sports scores. These tools can process significant amounts of data and transform them into readable reports in seconds, drastically shortcutting the process

Preliminary Research -  Journalists often use AI to help them sift through a variety of data, concentrating on finding patterns or extracting relevant information. This cuts down considerably on the time needed to do preliminary research and helps in investigative journalism pieces. 

Content Personalization - AI allows news platforms to deliver more personalized content that aligns with the preferences of the demographic they’re targeting, ensuring higher engagement and retention rates. 

Predictive Analysis - AI tools can predict trending stories, helping journalists prioritize what they cover to ensure a steady stream of viewers/readers.

Pros and Cons of AI in Journalism

As you might imagine, the aforementioned methods of using AI in journalism and the rapid speed of development have led to a number of exciting opportunities as well as deep concerns. 

Greater Efficiency and Ability to Create Content at Scale

Because AI writing tools can gobble up content and pull out information in seconds, they can churn out news reports within moments of an event taking place, particularly when drawing upon specific data sources. 

For example, they can be fed financial quarterly reports and create comprehensive summaries within moments of the release of those reports. The same can apply to global events like election results or sports scores, making it easier for news organizations to stay at the cutting edge of breaking news. 

Lower Costs

AI in journalism brings with it profound financial implications. Traditionally, newsrooms require reporters, editors and other staff. With AI-driven reporters, however, vast amounts of content can be produced with little human intervention which leads to considerable cost savings in terms of salaries and benefits. 

However, the flip-side is the initial investment needed in sophisticated AI tools which can handle this workload with precision and accuracy along with the necessary infrastructure, so it’s truly a tradeoff.

Job Concerns

With lower costs and the ability to create content at scale comes one of the greatest concerns with using journalism in AI: job displacement. The fear is real, especially as AI becomes more and more proficient at producing standard news reports. For those journalists who focus on data-intensive reports on things like finance or technology, the spectre of job loss can feel especially close. However, the evolving landscape also opens up job opportunities for sports journalists to leverage Al-driven tools in enhancing their covergage and analysis.

Lack of Depth and Nuance

Although AI is good at analyzing data and reporting on facts, it lacks a decidedly human touch. It doesn’t understand nuances, emotions and the deeper implications of what a story can mean. A human journalist, on the other hand, can “read a crowd” and understand the emotion behind an interview.

They understand cultural contexts in connection to global events. No matter how sophisticated AI becomes, it’s still lacking this intuitive understanding, and for the moment, this isn’t something that can simply be programmed in. 

Ethical Considerations

Last, but certainly not least, are the ethical questions regarding AI. If an AI tool misinterprets that data that leads it to an erroneous conclusion, who is responsible, the AI or the news organization? Beyond this example, how can readers be sure that the AI that’s making these decisions or recognizing these patterns isn’t being fed biased or skewed information designed to make a specific point? Who decides what’s acceptable to train such an AI on?

What the Future Holds

What might the future look like when we take the points above into consideration? What might AI be like a year, five years or even a decade down the road? 

Collaborative Cooperation - The future of AI in journalism doesn’t have to be journalists vs. AI. It can be journalists working together with AI to focus on using the skill set of both to take journalistic endeavors to the next level. Journalists could use AI to do the data crunching as they focus their own efforts on the human side of interviews, analyses and storytelling. 

Higher Accuracy - As machine learning improves and algorithms evolve, you can expect AI writing tools to become even more accurate and detailed in their responses. As they continue to learn from the content they’re fed (and the content they create) these tools can quickly help define narratives in the newsroom with a much higher degree of confidence in their accuracy. 

Ethical Grounding - In order to protect the livelihoods of journalists, editors and other professionals in the field, it’s likely that some sort of ethical guidelines will be developed and refined in order to maintain trust in the organization’s reporting. These guidelines could include standards on the transparency of using AI, who is accountable for mistakes, and overall best practices and standard operating procedures when using AI writing tools. 

Ongoing Training - You can expect journalists to become more than just reporters and writers in an AI-powered future. You’ll be expected to know how to not only use AI writing tools, but also check AI facts, analyze the data and leverage the technology in new and interesting ways. 

All of these developments paint a picture of the future where journalists are as much about uncovering and reporting the truth as they are about using technology and related skills for a new type of reporting, where breaking news on-demand is the norm and the latest data is already compiled, verified and on the air minutes after it becomes available.

Sherice Jacob

Plagiarism Expert Sherice Jacob brings over 20 years of experience to digital marketing as a copywriter and content creator. With a finger on the pulse of AI and its developments, she works extensively with Originality.AI to help businesses and publishers get the best returns from their Content.

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