Musso Media, Author at The Media Copilot

Building the newsroom AI playbook with journalists in the loop

The Copilot — Thu, 05 Mar 2026 13:15:00 +0000

AI in journalism is often discussed in extremes, either as a revolution that will transform reporting or a threat to the profession.

In this episode of The Media Copilot podcast, Pete Pachal speaks with Gina Chua, Executive Editor at Large at Semafor, where she leads AI strategy, and Executive Director of the Tow Center for Digital Journalism at CUNY. The conversation focuses less on theory and more on how AI tools are being used in everyday newsroom workflows.

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At Semafor, some of the systems Chua describes are simple tools designed to reduce time spent on routine tasks. These include internal tools for copy editing and proofreading, and a workflow that reads a story draft and suggests datasets that could help illustrate it. The reporter can then decide whether to explore those datasets or build a chart using existing newsroom tools.

Another example involves helping reporters find related coverage more quickly. A tool reads a draft story and searches across publications for related reporting, sometimes across languages. It then returns summaries of potential articles so editors can decide which ones are worth reviewing.

Semafor also works with large volumes of interview transcripts from events and panel discussions. Chua explains how those transcripts are integrated into Slack so reporters can search them directly. Journalists can ask whether a speaker mentioned a particular topic, locate the section of the transcript where it appears, and review it themselves. The next step the team is experimenting with involves automated alerts that notify reporters when certain topics appear in interviews across the archive.

Elevating the human element

Throughout the conversation, Chua emphasizes that these tools are meant to assist newsroom work rather than replace editorial judgment. When discussing publishing standards, she says the key principle is that anything published must be reviewed by a human editor who takes responsibility for it.

She also offers a practical way to think about large language models. They are designed to handle language, not verify facts. When used with a defined body of text, such as a transcript or speech, they can be helpful for tasks like summarizing, comparing passages, or identifying themes. Problems are more likely to appear when they are asked to generate information outside of that context.

The discussion also turns to how audiences are already encountering AI in everyday information environments. Chua points to research showing a small but growing number of younger users say they get news from chatbots. She argues that the shift may be larger than the statistics suggest, since AI summaries are now embedded in search results and other tools people use to find information.

For news organizations, that raises broader questions about how people will access information in the future. If AI systems increasingly sit between audiences and publishers, journalism will need to think carefully about how reporting reaches readers and how trust is maintained.

Why this matters

AI tools are already influencing how newsrooms work and how audiences discover information. Understanding the practical uses and limitations of these systems is becoming part of the daily reality of journalism.

What we cover

How Semafor is experimenting with AI tools inside the newsroom
Using transcripts and Slack to search interviews and discussions
Why language models are useful for handling text but not verifying facts
The role of human review in newsroom publishing decisions
How AI interfaces are changing the way audiences find news

Key takeaways

AI tools in newsrooms are often used for efficiency rather than automation
Large language models work best when applied to known text sources
Human oversight remains central to publishing decisions
AI driven discovery tools may increasingly shape how audiences access journalism

About the 👤 Guest: Gina Chua

LinkedIn 👉 https://www.linkedin.com/in/ginachua

X (Twitter) 👉 https://x.com/GinaSKChua

Instagram 👉 https://www.instagram.com/gina_chua_nyc

Personal Website / Writing 👉 https://ginachua.me

Author Page (Semafor) 👉 https://www.semafor.com/author/gina-chua

📰 Semafor Official Website: https://www.semafor.com

About the show: To explore more conversations like this and see what’s new, visit the freshly updated Media Copilot website at mediacopilot.ai. You’ll find new episodes, expanded resources, and tools designed for journalists, communicators, and media leaders navigating the fast-changing world of AI. It’s the home base for everything Media Copilot and it’s just getting started.

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube? Tap the Like button and Subscribe to the YouTube channel.

For more AI tools and resources built for media professionals, visit MediaCopilot.ai.

Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

The post Building the newsroom AI playbook with journalists in the loop appeared first on The Media Copilot.

She’s building an AI that replaces your news feed, your analyst, and maybe your morning routine

The Copilot — Thu, 26 Feb 2026 13:25:42 +0000

What if the future of news is not a website, an app, or even a search box, but a personal intelligence agent that quietly understands what matters to you and delivers it as signal, filtering the noise?

Key Takeaways

Gnomi is building a real-time AI agent designed to replace the news feed.
It filters global news into actionable understanding tailored to each user.
Reframes news from browsing to delegation — a direct challenge to publishers.

In this episode of The Media Copilot, Pete Pachal speaks with Eva Cicinyte, co-founder and CEO of Gnomi, an AI powered real time news agent designed to synthesize global information into actionable understanding.

Eva’s path to building Gnomi began in political data analytics, where she witnessed firsthand how information can shape decisions at the highest levels and how easily it can also distort them. That experience led her to a mission that sounds ambitious and deeply human at the same time: make high quality understanding accessible to everyone, not just institutions with research teams.

Gnomi aims to function less like a news app and more like a Bloomberg Terminal for everyday intelligence. It pulls from licensed data sources, social platforms, video, audio, and global publications across languages to deliver personalized insights in real time. The platform’s newest push into finance highlights this vision, offering live earnings call analysis, KPI extraction, and predictive context before headlines even hit.

This podcast explores whether AI can actually improve how we consume information without becoming just another engagement machine.

Why this matters

We are entering a phase where AI is rapidly becoming the front door to information. People are increasingly asking chatbots instead of searching, skimming summaries instead of reading articles, and expecting answers tailored to their interests rather than curated for the masses.

But personalization has a dark side. Systems optimized for attention can amplify outrage, misinformation, and echo chambers.

Eva argues for a different model. One that optimizes for understanding instead of engagement.

If platforms like Gnomi succeed, the future of news may look less like scrolling through feeds and more like consulting a trusted analyst who never sleeps. That shift could reshape journalism, finance, policymaking, and everyday decision-making.

It also raises urgent questions about trust, bias, monetization, and whether AI will help close the knowledge gap between elites and everyone else or widen it further.

What we cover

• Why Gnomi calls itself an “intelligence layer” instead of a news aggregator
• How real time agents differ from traditional feeds and chat based AI tools
• The challenge of measuring “understanding” instead of clicks
• Personalization without manipulation and why engagement driven AI worries Eva
• How multilingual analysis reveals narratives that single country coverage misses
• Using social data, video, and audio to capture local and emerging signals
• Finance Mode and the race to interpret markets before headlines move prices
• Why Eva believes AI agents will replace search for many information tasks
• The economics of AI and why only a tiny fraction of users currently pay for it
• Advertising, subscriptions, and the struggle to monetize intelligence tools responsibly

Key takeaways

The next battle in media is not content creation but context creation.
As information volume explodes, the ability to synthesize meaning becomes more valuable than producing more articles.

Real time insight may matter more than breaking news.
In markets and policymaking, the first signal often appears long before headlines catch up.

Personalization can either empower users or trap them.
Design choices determine whether AI broadens perspective or narrows it.

Global understanding requires crossing cultural as well as language barriers.
Translation alone is not enough. Narrative context matters.

AI could democratize institutional level research, but only if built with the right incentives.
Systems optimized for truth look very different from those optimized for engagement.

If you care about the future of journalism, markets, or simply how you will stay informed in an AI first world, this conversation offers a glimpse into what may replace the news feed entirely.

About the 👤 Guest

LinkedIn

👉 https://www.linkedin.com/in/eva-cicinyte-1447161b2

Instagram (Personal)

👉 https://www.instagram.com/evapariscicinyte

Official Website

👉 https://www.gnomi.com

LinkedIn (Company Page)

👉 https://www.linkedin.com/company/gnomi

Instagram (Company)
👉 https://www.instagram.com/gnomi.app

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube? Tap the Like button and Subscribe to the YouTube channel.

For more AI tools and resources built for media professionals, visit MediaCopilot.ai.

Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

The post She’s building an AI that replaces your news feed, your analyst, and maybe your morning routine appeared first on The Media Copilot.

Fake news at machine speed: inside AI’s impact on media trust

Musso Media — Thu, 19 Feb 2026 13:25:26 +0000

AI is already embedded in how people discover and consume news, from search to chat interfaces to automated summaries. So the question is no longer whether journalism will be shaped by AI. It’s how newsrooms maintain trust while experimenting responsibly.

Key Takeaways

Poynter’s Mahadevan: AI is now embedded in how people discover news.
Public-facing AI ethics policies are essential for newsroom credibility.
Verification and clear sourcing are the new differentiators in an AI-saturated web.

In this episode of The Media Copilot podcast, Pete Pachal sits down with Alex Mahadevan, Director of MediaWise and a faculty member at Poynter, to unpack what media literacy looks like now that anyone can generate convincing content at scale. Alex shares how his background in data and local journalism shaped his approach to tools, why public-facing AI ethics policies matter, and what it will take for news organizations to bring audiences along for the next phase of the information ecosystem.

Why this matters

Trust is the core product. AI can either widen the trust gap with errors and low-quality content, or help rebuild credibility through transparency, better products, and clearer communication about how journalism is made. This conversation gets practical about what responsible AI use looks like, where disclosures help and where they can unintentionally slow innovation, and why the newsroom AI divide is becoming a real competitive advantage for organizations that adapt.

What we cover

• Alex’s journey into journalism and the global mission of MediaWise

• How AI is reshaping misinformation, trust, and newsroom transparency

• Practical uses of chatbots, coding agents, and AI workflows

• The widening divide between AI enthusiasts and skeptics in newsrooms

• Ethics, job concerns, and gray areas around AI-assisted writing

• What the future of news may look like beyond traditional articles

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About the 👤 guest

🔗Alex Mahadevan

🔗Poynter / MediaWise

🔗MediaWise

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube? Tap the Like button and Subscribe to the YouTube channel.

For more AI tools and resources built for media professionals, visit MediaCopilot.ai.

The post Fake news at machine speed: inside AI’s impact on media trust appeared first on The Media Copilot.