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Can Al Completely Replace Journalists and News Anchors’ Jobs?


The future of journalism can potentially go massive changes if the progression of artificial intelligence (AI) goes as predicted and takes center stage. Journalists and News Anchors have a lot to worry about as their careers can come to a sad and technological ending but to what extent is this claim real and how fast can AI replace these jobs?

Professor Charlie Beckett, head of the Polis/LSE Journalism AI research project has advised caution and would discourage journalists from using new tools without human supervision: 

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“AI is not about the total automation of content production from start to finish: it is about augmentation to give professionals and creatives the tools to work faster, freeing them up to spend more time on what humans do best. Human journalism is also full of flaws and we mitigate the risks through editing. The same applies to AI. Make sure you understand the tools you are using and the risks. Don’t expect too much of the tech.”

There are numerous pros of AI-powered journalism, as it is free of bias and personal preference and promises to deliver faster, more accurate, and more in-depth coverage. With machine learning algorithms at their disposal, journalists can analyze vast amounts of data and information, uncovering patterns and insights that would otherwise remain hidden. 

The result will be a new era of investigative journalism, one where reporters can delve deeper into complex stories and bring to light important issues that would otherwise go unnoticed.

However, the cons of AI also bring with it a darker side. The growing reliance on algorithms and automation threatens to undermine the credibility and trustworthiness of journalism. The rise of AI in journalism also raises concerns about job security and the potential for AI to perpetuate existing biases in the data it uses to generate news. 

With machines taking over the tedious and time-consuming tasks of journalism, many worry that human reporters will become obsolete, replaced by cold, impartial algorithms. And as AI continues to evolve, it is becoming increasingly difficult to distinguish between news generated by humans and by machines, putting the very foundations of journalism at risk.

Slavica Ceperkovic, a visiting professor of interactive media at New York University Abu Dhabi, has a front-row seat to how media is changing. Her students – who are learning to build new worlds in augmented and virtual reality – are adapting fast to this changing technological landscape, using online AI tools such as Notion and Discord to organize their work and what they are learning, she told The National.

And they don’t discriminate regarding the medium their information comes in – through short-form video, as seen with the meteoric rise of TikTok, which is having a moment of popularity.

Despite the expert predictions and guesses, the future of journalism is uncertain, but one thing is clear: AI will play a critical role in shaping its evolution. Whether it will be a force for good or a harbinger of doom remains to be seen. But as the field continues to evolve, journalists and news organizations must be vigilant, embracing new technologies while preserving the core principles of truth, accuracy, and impartiality that have always defined the profession.

The use of AI to support and produce pieces of journalism is something outlets have been experimenting with for some time. Francesco Marconi categorizes AI innovation in the past decade into three waves: automation, augmentation, and generation. 

“During the first phase the focus was on automating data-driven news stories, such as financial reports, sports results, and economic indicators, using natural language generation techniques,” he says. 

There are many examples of news publishers automating some content, including global agencies like Reuters, AFP, and AP, and smaller outlets. 

According to Marconi, the second wave arrived when “the emphasis shifted to augmenting reporting through machine learning and natural language processing to analyze large datasets and uncover trends.” 

An example of this can be found at the Argentinian newspaper La Nación, which began using AI to support its data team in 2019, and then went on to set up an AI lab in collaboration with data analysts and developers.

The third and current wave is generative AI. It’s powered by large language models capable of generating narrative text at scale. This new development offers applications to journalism that goes beyond simple automated reports and data analysis. Now, we could ask a chatbot to write a longer, balanced article on a subject or an opinion piece from a particular standpoint. We could even ask it to do so in the style of a well-known writer or publication.