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Artificial Intelligence in Newsrooms

Updated: Oct 28

How AI can create new jobs in journalism.


 

So, here is something I wrote a few months back. I have a backlog of stuff that I thought would be fun to share on here in case anyone stumbles onto this, for some reason. So here it is, the thing about how machine learning will change reporting. Future Guy, out.

 

Journalism has always been beholden to technological innovation. The printing press made newspaper production more efficient, and news thus became easier to distribute to literate audiences in the 16th century. Contemporary journalism and the relationships between reporters and audiences have been significantly impacted by the internet and social media platforms. Likewise, wire services like the Associated Press, Reuters, and Agence France-Presse have begun employing artificial intelligence (AI) technology to gather and deliver news from weather and sports to breaking news and investigative reports. Microsoft’s MSN announced the replacement of all its journalists with AI algorithms and Google’s DSI fund has invested millions of dollars into hundreds of AI projects. AI can serve as a tool for journalists to gather or analyze data more efficiently. News templates allow algorithms to curate articles for fans of niche sports or generate hyperlocal news stories. Machine learning can hasten translation or transcription, detect social media trends, and even help determine the newsworthiness of online posts (Stray).


There are just as many potential machine intelligence applications as there are ethical questions on how this new technology will impact news creators and consumers. Journalists and their audiences alike must be privy to deceptive deep-fakes — hyper-realistic yet counterfeit AI renderings of anyone from politicians to celebrities — and social media algorithms that filter news on their feed. Machine learning systems can generate biased results that reflect the intentions and assumptions of their developers. The journalism industry was critically underprepared for the disruptive effects of social media, so AI applications in journalism must be scrutinized and used transparently while also considering implicit lurking biases.


Artificial intelligence is still in its infancy and much of its potential is yet to be explored, especially when it comes to journalism. Machine learning can save time and money for data-intensive reporting because it allows human journalists to redirect their attention and resources to other tasks, thus making newsgathering a more efficient process. Furthermore, machines can conduct cognitive tasks — such as pattern recognition — on large volumes of data better than humans, despite their ineffectiveness in determining the newsworthiness of such patterns. Intelligent computers won’t replace human journalists, but the latter can serve as a tool that supplements reporting and even bring light to stories that would otherwise have gone unnoticed.


Journalism has an unhealthy relationship with social media tech companies because news organizations and reporters rely on products that are guided by values that contradict their own. Companies like Twitter and Facebook build algorithms that optimize for traffic and revenue rather than prioritizing important information and improving the accessibility of news for the betterment of society. The rift in values between the companies that develop and control technologies and the newsrooms that adopt them can only be addressed if journalists also become developers of the technologies reporters use.


The way news is consumed has changed due to the advent of social media algorithms and the dependence of newsrooms on those platforms to disseminate their work. As mentioned earlier, the goals and values of social media can differ or even conflict with the goals of newsrooms, which is to keep consumers informed with the most timely and accurate information. While tech giants have employed AI fact-checkers to keep misinformation from spreading online, journalists have little influence or insight on how these algorithms work. Part of the AI strategy of newsrooms should be to understand the AI systems they already use and inject them with journalistic values. But ultimately, innovation lies in developing explicitly journalistic AI applications.


Newsrooms can’t avoid the increasing adoption of AI, so the logical next step is to brace for impact. Since the dawn of the internet, newsrooms have increasingly incorporated individuals with backgrounds in scientific disciplines to strengthen reporting and make news more accessible, aesthetically pleasing, and interactive. The demand for AI applications in journalism will only increase, so newsrooms must proactively adapt to the trend by fostering collaborations between journalists and AI developers. Building technological competence allows journalists to adequately understand AI and their role in news reporting while enabling them to relay that understanding to consumers, but they must also go further and become AI developers themselves. Newsrooms have an incentive to develop machine intelligence in the service of journalism, but this is contingent on incentivizing leading developers to leave technology giants in favor of joining newsrooms’ mission to make AI work for journalism.


The development of AI technologies for journalistic applications may threaten the business of smaller newsrooms. The journalism industry is resource-scarce, and the few organizations that are an exception to that are far outnumbered by struggling and dwindling newsrooms. There exists a conflict between short-term financial gains and the investments needed for newsrooms to fully capitalize on the opportunities of AI. AI tools must be intentionally developed with accessibility in mind rather than as a luxury exclusive to journalists employed by elite institutions. If AI are adopted by only the companies that can afford to develop them an imbalance will be created in favor of big newsrooms and at the expense of smaller organizations; If only the profitable newsrooms can harness AI, the entire industry becomes less competitive since smaller newsrooms will require much more resources to maintain the same quality of journalism.


Technological innovation is in flux and newsrooms must be proactive in taking advantage of emerging machine intelligence applications while also implementing safeguards for ethical issues that may occur. If large, resourced newsrooms begin developing journalistic AI applications, ensuring that smaller newsrooms also have access to these tools is their responsibility. Unlike tech corporations that cloud AI in mystery, the news industry must make a concerted effort to prevent a capability imbalance between newsrooms with access to AI and the AI have-nots. In the same vein, transparency in how these AI are developed and their role in the newsgathering process is essential for maintaining the audience’s trust. Most people don’t understand how AI works and what it does, so journalists must take it upon themselves to make sure they are transparent regarding the role of AI in news reporting and how they can impact the final product. Newsrooms must open an honest conversation with their audiences about how AI can help or hurt journalism because this is the only way to build trust and understanding. If that conversation doesn’t start soon, then future journalistic AI applications will be met with skepticism.


To conclude, the incorporation of the computer science and programming disciplines into newsrooms is imperative to develop AI that serves the goal of delivering audiences with accurate information in a timely fashion. Journalists must build collaborations with AI developers because such relationships will help newsrooms capitalize on this technology and will allow reporters to build a comprehensive understanding of AI so that they can convey how those applications work and why they make journalism better. The entire news industry must adapt to the challenges introduced by AI, but that doesn’t mean that newsrooms can’t leverage the technology for journalistic purposes. Journalists with adequate AI literacy can ensure that their existing machine learning tools meet their newsroom’s ethical standards and develop new tools that meet intrinsically journalistic goals and values.


 

Works Cited


Beckett, Charlie. “New Powers, New Responsibilities. A Global Survey of Journalism

and Artificial Intelligence.” Polis, London School of Economics and Political Science, 18 Nov. 2019, blogs.lse.ac.uk/polis/2019/11/18/new-powers-new-responsibilities/. Accessed 6 Oct. 2021.


Dierickx, Laurence. “Artificial Intelligence and Journalism: A Race with Machines.” Equal

Times, 6 Apr. 2021, www.equaltimes.org/artificial-intelligence-and?lang=en#.YVSj4S9h01I. Accessed 6 Oct. 2021.


Keefe, John, et al. “The Present and Potential of AI in Journalism.”

KnightFoundation.org, Knight Foundation, 12 May 2021, knightfoundation.org/articles/the-present-and-potential-of-ai-in-journalism/. Accessed 4 Oct. 2021.


McCarthy, Isobel, and Marcela Kunova. “How Artificial Intelligence Can Help Solve

Journalism’s Problems | Media News.” Www.journalism.co.uk, 26 May 2021, www.journalism.co.uk/news/how-artificial-intelligence-can-help-solve-journalism-s-problems-/s2/a825693/. Accessed 4 Oct. 2021.

Stray, Jonathan. “Beyond the Hype: Using AI Effectively in Investigative Journalism –


Global Investigative Journalism Network.” Global Investigative Journalism Network, 9 Sept. 2019, gijn.org/2019/09/09/beyond-the-hype-using-ai-effectively-in-investigative-journalism/. Accessed 9 Oct. 2021.


White, Patrick. “How Artificial Intelligence Can Save Journalism.” The Conversation, 5

May 2020, theconversation.com/how-artificial-intelligence-can-save-journalism-137544. Accessed 6 Oct. 2021.


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