The newspapers are seeking an injunction and 2.2 billion ( 15 million) each in damages from Perplexity, they said in a joint statement Tuesday. The suit was filed at the Tokyo District Court. The legal action by the Nikkei, which owns Japan's biggest financial newspaper, and the left-leaning Asahi underscores a widening rift between publishers and AI companies over who controls -- and profits from -- the distribution of news. The media industry argues that AI tools using their work without licenses siphons away readership and ad revenue, threatening already fragile business models. "These actions amount to continuous and large-scale freeloading on journalists' time and effort," Nikkei and Asahi said in the statement.

Japan's Yomiuri Shimbun newspaper, one of the world's biggest by circulation, is suing U.S.-based AI firm Perplexity for allegedly "free-riding" on its content on its search engine. The lawsuit filed Thursday is one of a slew by media companies worldwide against AI firms using their material and is the first by a major Japanese news organization, Yomiuri said. It accuses Perplexity of "free-riding on the results of the activities of news organizations, which have invested a great deal of effort and expense." A spokesman for the paper added that this "could have a negative impact on accurate journalism ... and shake the foundations of democracy." The lawsuit filed in Tokyo seeks damages of 2.2 billion ( 14.7 million), equivalent to 120,000 Yomuiri articles used "without permission" between February and June.

I am a forty-five-year-old journalist who, for many years, didn't read the news. In high school, I knew about events like the O. J. Simpson trial and the Oklahoma City bombing, but not much else. In college, I was friends with geeky economics majors who read The Economist, but I'm pretty sure I never actually turned on CNN or bought a paper at the newsstand. I read novels, and magazines like Wired and Spin. If I went online, it wasn't to check the front page of the Times but to browse record reviews from College Music Journal. Somehow, during this time, I thought of myself as well informed.

Journalism has emerged as an essential domain for understanding the uses, limitations, and impacts of large language models (LLMs) in the workplace. News organizations face divergent financial incentives: LLMs already permeate newswork processes within financially constrained organizations, even as ongoing legal challenges assert that AI companies violate their copyright. At stake are key questions about what LLMs are created to do, and by whom: How might a journalist-led LLM work, and what can participatory design illuminate about the present-day challenges about adapting ``one-size-fits-all'' foundation models to a given context of use? In this paper, we undertake a co-design exploration to understand how a participatory approach to LLMs might address opportunities and challenges around AI in journalism. Our 20 interviews with reporters, data journalists, editors, labor organizers, product leads, and executives highlight macro, meso, and micro tensions that designing for this opportunity space must address. From these desiderata, we describe the result of our co-design work: organizational structures and functionality for a journalist-controlled LLM. In closing, we discuss the limitations of commercial foundation models for workplace use, and the methodological implications of applying participatory methods to LLM co-design.

Recently, an increasing number of news organizations have integrated artificial intelligence (AI) into their workflows, leading to a further influx of AI technologists and data workers into the news industry. This has initiated cross-functional collaborations between these professionals and journalists. While prior research has explored the impact of AI-related roles entering the news industry, there is a lack of studies on how cross-functional collaboration unfolds between AI professionals and journalists. Through interviews with 17 journalists, 6 AI technologists, and 3 AI workers with cross-functional experience from leading news organizations, we investigate the current practices, challenges, and opportunities for cross-functional collaboration around AI in today's news industry. We first study how journalists and AI professionals perceive existing cross-collaboration strategies. We further explore the challenges of cross-functional collaboration and provide recommendations for enhancing future cross-functional collaboration around AI in the news industry.

Polarization, declining trust, and wavering support for democratic norms are pressing threats to U.S. democracy. Exposure to verified and quality news may lower individual susceptibility to these threats and make citizens more resilient to misinformation, populism, and hyperpartisan rhetoric. This project examines how to enhance users' exposure to and engagement with verified and ideologically balanced news in an ecologically valid setting. We rely on a large-scale two-week long field experiment (from 1/19/2023 to 2/3/2023) on 28,457 Twitter users. We created 28 bots utilizing GPT-2 that replied to users tweeting about sports, entertainment, or lifestyle with a contextual reply containing two hardcoded elements: a URL to the topic-relevant section of quality news organization and an encouragement to follow its Twitter account. To further test differential effects by gender of the bots, treated users were randomly assigned to receive responses by bots presented as female or male. We examine whether our over-time intervention enhances the following of news media organization, the sharing and the liking of news content and the tweeting about politics and the liking of political content. We find that the treated users followed more news accounts and the users in the female bot treatment were more likely to like news content than the control. Most of these results, however, were small in magnitude and confined to the already politically interested Twitter users, as indicated by their pre-treatment tweeting about politics. These findings have implications for social media and news organizations, and also offer direction for future work on how Large Language Models and other computational interventions can effectively enhance individual on-platform engagement with quality news and public affairs.

It didn't take long for the downsides of a generative AI-empowered newsroom to make themselves obvious, between CNet's secret chatbot reviews editor last November and Buzzfeed's subsequent mass layoffs of human staff in favor of AI-generated "content" creators. The specter of being replaced by a "good enough AI" looms large in many a journalist's mind these days with as many as a third of the nation's newsrooms expected to shutter by the middle of the decade. But AI doesn't have to necessarily be an existential threat to the field. As six research teams showed at NYU Media Lab's AI & Local News Initiative demo day in late June, the technology may also be the key to foundationally transforming the way local news is gathered and produced. Now in its second year, the initiative is tasked with helping local news organizations to "harness the power of artificial intelligence to drive success." It's backed as part of a larger $3 million grant from the Knight Foundation which is funding four such programs in total in partnership with the Associated Press, Brown Institute's Local News Lab, NYC Media Lab and the Partnership on AI.

An AI-Generated news presenter has been introduced by Kuwait News, an online news organization connected to the Kuwait Times. Fedha, the host, made her debut in a brief 13-second film during which she introduced herself in Arabic. She also solicited feedback from the audience regarding their preferred source of news. The outlet's Twitter account published the video. Additionally, Fedha will reportedly use a typical Kuwaiti accent to provide news updates on the website's social media accounts. A new revolution has begun in the media industry!

The debate over the use of AI technology in journalism is heating up again after the release of the revolutionary ChatGPT Assistant, currently in its research preview phase. If you haven't had a chance to mess around with ChatGPT yet, I highly recommend it -- you know, for science. Personally, I'm intrigued by its ability to generate documentation and planning materials. Things like workshop agendas, project outlines, and discussion overviews. The kind of stuff that, in most cases, nobody really puts a byline on or attributes to any specific individual.

In 2020 The Guardian published an article that had been written by AI. It was about the increasing use of AI in journalism, and how it is changing the landscape of the industry. It discussed how AI is being used to generate news stories, and how it is being used to help reporters with their work. It was so natural that it was hard to believe that it was written by a software called GPT-3 developed by OpenAI, a research company. The Guardian isn't the only news organization using algorithms to write articles.