Newsroom Robots

Francesco Marconi, the co-founder and CEO of AppliedXL, joins Nikita Roy to discuss the opportunities and challenges that Large Language Models present to the news industry, emphasizing the need for collaboration between tech companies and newsrooms. Francesco also covers copyright and data access challenges and proposes long-term business model innovations to support news organizations and the AI sector. He also shares how his company AppliedXL uses AI combined with human expertise to detect events in real-time biotech data and generate specialized reporting for STAT News.

Francesco shares his perspective from years of experience leading AI initiatives at major news organizations. He served as the R&D Chief at The Wall Street Journal, leading a team of data scientists and computational journalists in developing AI-driven newsroom tools. Before that, he managed AI strategy at the Associated Press and co-led their content automation and artificial intelligence efforts. Francesco has been an affiliate researcher at the MIT Media Lab and a Tow Fellow at Columbia University. His work and ideas have been featured in The New York Times, The Wall Street Journal, Financial Times, Politico, Forbes, and the World Economic Forum. His book, "Newsmakers: Artificial Intelligence and the Future of Journalism," was published by Columbia University Press in 2020.

On Tuesday, he testified before the UK Parliament's Communications and Digital Committee as an AI expert on Large Language Models. The committee held evidence sessions exploring the benefits of LLMs to the UK economy, their immediate risks, potential catastrophic impacts, and the broader challenges posed by this technology.

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From fine-tuning large language models, to discussing modular journalism, to developing an AI tool to help track misinformation, there’s a lot to unpack from this week’s conversation with Alessandro Alviani, the product lead for AI at Germany’s Ippen Digital. We build upon the first part of our conversation from last week, where Alessandro shared his editor-centric approach toward building AI products.

A core takeaway from this week's episode is the value of fine-tuning large language models on a newsroom’s content.

Fine-tuning is the process of taking a pre-trained language model that understands general textual patterns and customizing it by training the algorithm on writings from a specific domain – in this case, Ippen Digital's own journalistic content. By fine-tuning models on Ippen Digital's extensive corpus of local German reporting rather than just using out-of-the-box models like GPT-4, they are working on enhancing accuracy for tasks like headline writing, lead paragraph generation, and article summarization.

Their editors and developers work side-by-side to ensure the AI's outputs match the desired quality standards and editorial voice.

Additionally, Alessandro spotlighted their work in building personalized news experiences enhanced by modular journalism or “intelligent content.” Modular journalism involves breaking down articles into discrete, interchangeable components centered on key semantic themes – historical context, opposing views, critical data, etc. These content blocks can then be dynamically mixed and matched by an algorithm to generate personalized news experiences for different reader interests and preferences.

We also discussed how developing AI assistants to break down a human-written news story into modules can enable the creation of customized article versions matching different reader interests or news products.

Such repackaging of information to cater to diverse audiences is one of the potentials of AI in the newsroom. Thoughtful implementation of augmented writing tools could catalyze more engaging, personalized news without compromising editorial integrity.

Of course, prudent precautions are necessary to develop algorithms in the newsroom. While AI has much potential for accelerating and enhancing reporting, we must understand its limitations in fully automating high-caliber journalism. The heart of quality storytelling – weaving together evidence and narratives to reveal truth and empower civil discourse – remains an irreplicable, fundamentally human endeavor.

Ippen Digital’s stance to develop AI solutions that empower rather than replace reporters seems wise. By bonding human creativity and AI productivity with an ethical approach to automation, journalism may structurally shift yet hold fast to its sacred commitments to transparency, accuracy, and public enlightenment.

🎧 Listen to the full conversation available now on Apple, Spotify, Google, and other major podcast platforms.

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In this episode, Jeff Sonderman, the founder and CEO of Delta Flow Solutions, joins Nikita Roy to discuss the transformative potential of generative AI in streamlining business operations across analytics, marketing, product management, and content accessibility. Jeff also shares insights from his experiments with AI, particularly in converting unstructured data from PDFs into hyperlocal news reports.

Jeff is the former Deputy Executive Director of the American Press Institute, where he created the Metrics for News analytics software, revolutionizing audience data for over 200 news enterprises, and invented the Source Matters software to enhance source diversity in newsrooms. He has been a Media Transformation Challenge fellow at the Harvard Kennedy School Executive Education and continues to blend innovation with journalism.

Tune in for an episode to brainstorm diverse use cases, demonstrating how generative AI can be a game-changer on both the business and product side of running a newsroom.

🔔 Introducing the Generative AI for Media Professionals Masterclass.

A live cohort based coursed taught jointly by Jeremy Caplan and Nikita Roy.

Sign up to be the first when course registration goes live.

Jeremy Caplan is the Director of Teaching and Learning at the Craig Newmark School of Graduate Journalism at the City University of New York and the founder of Wondertools.

Nikita Roy is a data scientist, journalist and media entrepreneur. She hosts the Newsroom Robots podcast and has taught AI literacy workshops for the Craig Newmark School of Graduate Journalism at the City University of New York, International Center for Journalists and University of Toronto.

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In this episode, we explore the crucial considerations when developing an AI strategy and the potential risks of generative AI in the newsroom with Charlie Beckett, Director of the JournalismAI project at Polis – the international journalism think tank at the London School of Economics and Political Science(LSE). He is also a professor at LSE’s Department of Media and Communications. He was previously the director of LSE's Truth, Trust, and Technology Commission, which reported on the misinformation crisis in 2018.

Charlie is the author of SuperMedia: Saving Journalism So It Can Save The World (Blackwell, 2008) and WikiLeaks: News In The Networked Era (Polity, 2012).

Before LSE, Charlie was an award-winning journalist at LWT, BBC, and ITN, beginning his career at the South London Press and later a program editor at Channel 4 News.

JournalismAI, a project of Polis supported by the Google News Initiative, is a global initiative committed to helping news organizations use artificial intelligence responsibly.

By fostering innovation and capacity-building, JournalismAI aims to make the potential of AI more accessible and to address inequalities in the global news media related to AI. Through various programs, JournalismAI unites journalists and media professionals to discuss and explore AI, encouraging debates on AI's editorial, ethical, and financial implications on journalism.

Join us as Charlie provides his valuable insights on the significance of AI literacy for journalists, the crucial questions to consider when developing an AI strategy for news organizations, the risks and potential limitations of generative AI, and the influence of AI-powered chatbots on search engine traffic.

Be a part of the conversation on AI in journalism! Send us your questions here.

Here’s a list of helpful resources concerning today’s episode:

1. JournalismAI Case Studies
2. JournalismAI Starter Pack
3. JournalismAI Discovery Course (Applications currently open)
4. JournalismAI Survey Report (2019)
5. Partnership on AI's Database of AI Tools for Local Newsroom

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In this episode, we explore the potential of ChatGPT for local newsrooms with Joe Amditis, author of Beginner's Prompt Handbook: ChatGPT for Local News Publishers. Joe is the Assistant Director of Products and Events at the Center for Cooperative Media at Montclair State University, an Adjunct Professor at the School of Communication and Media, and the producer and host of the WTF Just Happened Today podcast.

Joe, a veteran of the NJ Army National Guard, was deployed to Iraq in 2008 and his unit was activated to help with Hurricane Irene relief efforts in 2011. He earned a BA in political science and criminal justice from Rutgers in 2013 and an MA in engaged journalism from the Newmark Graduate School of Journalism at CUNY in 2016. He was co-founder and director of operations of Muckgers, an award-winning, student-focused investigative news outlet, until 2014.

Joe has also coordinated several collaborative reporting projects, including Democracy Day, a nationwide reporting collaborative involving 300+ newsrooms across the United States.

We explore the exciting world of ChatGPT and its potential to revolutionize local journalism, discussing the transformative power of generative AI, ethical considerations, prompt engineering, and the future of local newsrooms in the age of AI.

Joe can be reached at [email protected] and on Twitter at @jsamditis.

Here’s a list of helpful resources concerning today’s episode:

1. Beginner's Prompt Handbook: ChatGPT for Local News Publishers (Center for Cooperative Media) - Discover Joe's comprehensive guide to using ChatGPT in local newsrooms.
2. Giant List of Useful Tools and Websites (Center for Cooperative Media) - A treasure trove of tools and resources for newsroom operations.
3. Template: ChatGPT Usage and Newsroom Ethics Policy (Center for Cooperative Media) - This template facilitates transparency in newsrooms' ethics policies regarding the use and disclosure of generative AI.
4. Trusting News Newsletter (Trusting News) - Stay informed about building trust in journalism with this insightful newsletter.
5. Journalism AI Starter Pack (LSE) - Get started with AI in journalism with this comprehensive resource from the London School of Economics.

Be a part of the conversation on AI in journalism! Send us your questions here

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