Abstract
Artificial Intelligence (AI) is all around us—whether it’s in the form of automation algorithms, autocorrect on our cell phones, digital assistants, or chatbots—and it continues to grow. Recent reports suggested that the AI market could grow to as much as $42.4 billion by the end of 2023 (Carmiel, 2023).
Journalism has been utilizing forms of artificial intelligence for some time now—that’s not a surprise. What is interesting is the increased role that these tools are playing in the industry. AI transcription tools are routine in most newsrooms. Journalists and editors are using AI to fact check and cross-examine information sources. It can also be used for content verification, social network analysis, and generating personalized news digests. Associated press uses AI to produce data-driven sports stories and templated game recaps. Newswire organizations like Dow Jones, Bloomberg, and Reuters have experimented with automation to streamline their coverage of the stock market and earning reports (Fischer, 2023). A recent survey of media executives (publishers, editors, and those holding senior positions within their organizations) found that nearly a fourth (23%) said they use AI regularly for recommendations, with 5% saying it’s “a big part of what we do” (Newman, 2023).
But the question does need to be asked—how much is too much? As media organizations continue to rely more on AI technology, there will enviably be ethical and moral ramifications. Journalist and digital strategist Nic Newman suggested that AI will
help media companies do more with less, as well as open up opportunities in the creation and distribution of smarter content. But it will also bring new dilemmas about how these powerful technologies can be used in an ethical and transparent way. (Newman, 2023)
Some organizations have already had to face those dilemmas. In January 2023, CNET announced it was pausing all publication of stories generated by artificial intelligence “for now” after the accuracy of some of the AI content was brought into question. This led to an internal review of the articles, where editors discovered that a “small number” of articles required major corrections, while “several” had minor issues (incomplete company names, transposed numbers, etc.) (Guglielmo, 2023). In an article addressing the controversy, CNET editor-in-chief Connie Guglielo said they were committed to fixing the problems and committed to exploring and testing how AI can be used to help their teams create “unbiased advice and fact-based reporting that we’re known for”:
There’s still a lot more that media companies, publishers and content creators need to discover, learn and understand about automated storytelling tools, and we’ll be at the front of this work. We’re committed to improving the AI engine with feedback and input from our editorial teams so that we—and our readers—can trust the work it contributes to, she said.
CNET is not the first news organization to face ethical and moral dilemmas related to AI and it will not be the last. Independent journalist Peter Sterne posed a few questions that he believes will need to be answered by journalists as we navigate the use of AI:
As these tools enter newsrooms, they will spark new questions about journalistic ethics: Is it wrong to train a generative AI model on thousands of artists’ images without their consent? Is it misleading to publish an image of something that does not actually exist or an event that never actually occurred? If a reporter uses a large language model to write an article, should that be considered plagiarism or even fabulism? (Sterne, 2022).
As scholars, we have an opportunity to be at the forefront of the research exploring journalism’s use of AI—where it’s being used, why it’s being used, and the ramifications of its use, legally, ethically, and morally. This important research and its findings will be pivotal in informing and directing current journalists as they continue to implement these tools into their work, while also educating the future journalists coming in behind them. I am looking forward to seeing what we can learn from studying these recent trends.
In This Issue
We have some interesting research for you in this latest issue. First, Juan Liu studies the effects that news frames have on the attitudes related to Syrian refugee admissions and anti-immigrant sentiment. Through a single-factor, between-subjects experiential design involving more than 600 participants, Liu found that framing Syrian refugees did bring about changes in attitudes toward admitting Syrian refugees, depending on the type of frame used. In addition, participants who were exposed to a victim frame story had stronger anti-immigrant sentiment than those who read a threat frame story. “This study provides significant implications for enacting refugee policies and suggest that political elites who advocate for refuge admissions face a stronger challenge to garner public support for their agenda,” Liu suggested.
Hans Schmidt explores the intersection between the COVID-19 pandemic and the “increasing politicization and polarization in America’s news media.” He did this through a content analysis of newspaper articles from various periods during the 20th and 21st centuries. Specifically, this analysis measured the extent to which politicalized and polarized content was included in COVID-19 reporting and compared the extent of this coverage with other pandemic reporting. Schmidt found that political topics, actions, and actors have often been the focus of COVID-19 coverage, and this political content has grown more substantial over time. “Simultaneously addressing politics and science in news reports can cause confusion, encourage partisan views about medical authority or advice and contribute to the overall politicization of health care in general,” Schmidt said.
Jessica Fargen Walsh and Mildred Perreault examine the coverage by 22 Nebraska newspapers, and a wire service covered nitrate contamination in the state’s groundwater over the course of 4 years. Through a thematic narrative analysis of more than 150 news articles, the researchers found that the coverage “lacked depth” and focused more on routine general news, meetings, and government activities, rather than exploring the “economic, agricultural and public health considerations.” “The stories in local newspaper do matter. What publishers are putting on newspaper pages can impact policy decisions and opinions . . . For communities to see these issues and be impactful, the coverage needs to run deeper,” they argued.
Frank M. Russell, Miguel Hernandez, and Korryn Sanchez study Twitter use in large local news markets through a case study of 20 U.S. news organizations. They found that nonprofit newsrooms and one regional newspaper used replies to engage in exchanges with their audiences, while broadcasters used retweets, hashtags, and mentions for branding purposes. There were also differences in the attention the organizations gave to topics valued by audiences. Local newspapers with resource constraints overemphasized sports coverage, even though those posts were less likely to be liked or retweeted than posts about weather and crime. “The results indicate that newsrooms should use hashtags, retweets, and other Twitter affordances, but cannot rely solely on interactive functions for audience engagement,” the authors concluded.
Finally, Elina Erzikova and Wilson Lowrey discuss the adaptions made by Russian regional journalists during the COVID-19 pandemic. Through in-depth interviews, they found that a worsened economic situation increased journalists’ dependence on state subsidies. This dependency, combined with COVID-19 limitations “further aggravated” news production and prevented the journalists from being able to provide adequate coverage of the pandemic. “This article underscores the importance of studying local journalism worldwide as local journalists across media systems face some similar challenges, such as resource scarcity, diminishing staffs, and distrust from local audiences,” the authors said.