Local Media Association hosted “AI Discovery Day” on March 12 in New York, in partnership with the Craig Newmark Graduate School of Journalism at CUNY, to drive AI innovation and collaboration in local news.
The goal of the event was to convene and connect local news leaders with AI product innovators and thought leaders in order to better understand the ways artificial intelligence will disrupt news discovery and consumption, and to empower local newsrooms to accelerate their adoption of ethical AI to better serve audiences.
The day included a morning ‘Shark Tank’ session where leading AI product innovators presented their AI tools and the benefits for news organizations; and, an afternoon of ‘speed dating’ where newsrooms picked the best-fit AI innovators for one-on-one deeper dive conversations. In between, a lunch panel of four local news organizations shared ways they were integrating AI in their operations. The day began and ended with keynotes from AI thought leaders who identified the key disruptions the technology is likely to cause to the information ecosystem and the opportunities it creates for local newsrooms.
Nikita Roy, founder of Newsroom Robots, identified three key disruptions to existing assumptions about news. Gina Chua, executive director of the Tow-Knight Center focused on the intersection of news and AI, and described four significant opportunities AI creates for news organizations.
“What are the best uses of AI in the newsroom?” Roy asked, and answered that question by pointing out that, in the early days of AI, too much emphasis has been on using it for “newsroom efficiency.”
“The best use of AI is not just to make things slightly better,” said Roy. “Don’t just optimize yesterday’s workflow!” While Roy agreed that using AI to create efficiencies was necessary, she also warned “efficiency is not enough.” She noted that newsrooms risked “slightly improving” workflows that were actually outdated, and outcomes would be better if these workflows were reimagined altogether.
Roy posed the larger question behind these workflow optimization debates: “What are the assumptions of the old legacy news model that are no longer true? What assumptions is AI breaking right now?”
Roy detailed three key assumptions about news that AI is disrupting, and how newsrooms could respond to these changes.
Assumption #1: How discovery of news works
The old model, upon which legacy news business models were built, is that audiences come to news websites, newspapers and radio and TV station channels to get the news. The information supply chain was “B2C”, with the news organization serving the news directly to the customer.
Artificial intelligence breaks this model, said Roy, by “intermediating” news. “The AI is now deciding how people get information and which sources are used,” said Roy, creating a “B2AI2C” structure where AI is ‘in between’ news publishers and news consumers, shifting the dynamic from a search economy to an AI answers economy.
Assumption #2: News site visits are human
The traditional digital revenue model, whether for news websites or email newsletters, was based on traffic metrics like page views, visitors and open rates. Those visitors were, of course, humans.
Roy warned that we are already seeing a disruption to this assumption —where increasingly, the visits to news websites and newsletters alike are by bots that are crawling those sites and mining the information to use it as a source for AI answers. For example, Roy noted that a news site’s newsletter open rate could go to 100% in a world where bots become the primary subscriber. These shifts will render traditional metrics like page views and open rates meaningless, requiring news outlets to find new and more relevant success metrics.
Assumption #3: The format is the product
Traditional news outlets have viewed their primary format — a newscast, a home page, a printed paper — as their core product. Roy noted that AI will dramatically disrupt this relationship by disaggregating the ‘data points’ of news, and then recombining those scraped data points in all kinds of different formats, personalized to individual user’s needs and preferences.
AI will be able to reformat and personalize answers, with a news outlet “reduced to simply a citation,” said Roy. “Publication is no longer the end point of journalism.”
Given these three dramatic disruptions by AI, which change the traditional model of news publication, distribution and consumption, where does that leave a local news leader?
Both Nikita Roy and Gina Chua, executive director of the Tow Center at CUNY, saw real opportunities for news leaders to reimagine the ‘value proposition’ of news in the era of AI.
“Artificial intelligence changes news into a living document, an opportunity for dialogue with the audience,” noted Roy. She described how she uses AI herself as a personalized news assistant that assembles a daily briefing for her of stories relevant specifically to her interest.
She encouraged news leaders to think of publication as the starting point, rather than the end point — to think of news as a conversation with the audience, for example, enabling audiences to use AI to ask questions about an outlet’s news reporting.
For Gina Chua, the disruptions to news by AI are both urgent, and an opportunity. The urgency is around the need to shift our focus from “about us” and our business problems as news operators to “about the audience,” recognizing and better serving their information needs and wants.
Chua posed the question: “What new kinds of news products could we create, thanks to AI?” Chua identified four broad areas of opportunity for news leaders to lean in and adopt responsible AI uses.
AI for efficiency
Chua noted there are many AI use cases that have already been identified that can immediately save newsrooms time, freeing up reporters to do more and better reporting. A few examples include transcription of interviews to save time for reporters, using AI to generate and optimize headlines and more. There are countless opportunities to streamline existing news workflows with AI.
AI for scaling
Artificial intelligence creates opportunities to better serve distinctive audiences, provide customized formats and broaden content reach. Translation is one example of an opportunity to immediately scale with AI to extend the reach of our content to new audiences. Another example is to take content created in a news organization’s primary format – for example a TV news script or radio script – and use AI to convert and reformat that story content for the web, or vice versa.
Conceptual AI applications
Chua, like Roy, noted that there is an entire category of opportunity beyond “efficiency” for newsrooms to think about, by starting with the question: ‘What was formerly a constraint that is now possible?” For example, highly personalized news formats were not feasible under traditional workflows and business model constraints. Artificial intelligence now makes new kinds of hyper-personalized forms of news possible.
Public-facing AI applications
Chua sees a new kind of value proposition possible for news outlets who build and embrace tools that help their audience navigate the information ecosystem, from querying and interrogating the news to engaging in ways that make news a two-way conversation.
“We will be able to serve people in a much more personalized way” if we lean in to these opportunities created by AI, said Chua, who also warned: “and, if we don’t keep up with the changes, we’ll be left behind.”
Roy agreed on both the overarching threats and opportunities presented by AI. “How does traditional media compete,” asked Roy, “where your journalism is seen but your brand is not?”
For Roy, the answer to how the value proposition of local news changes in an AI-answers world is trust and connection: “How can we build trusted direct relation with our readers?” For Roy, “belonging and connection” become part of the new value proposition for local news, where truth, trust and accountability are valued most.
Learn more: Meet AI innovators building solutions for local news
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