The Media Copilot

Business Insider's CEO on the Legal Challenges Reshaping the Media Industry

This week, I’m thrilled to welcome Jakob Waisto the podcast. Jakob is the CEO and Editor-in-Chief of Business Insider Germany, a key player within Axel Springer’s media empire. Axel Springer was one of the first major media companies to embrace generative AI, striking a groundbreaking deal with OpenAI in late 2023, which integrated their publications, including Jakob’s, with ChatGPT.

I was eager to dive into Jakob’s insights on how a major media company leverages AI in its newsroom. We explored the flexibility he has in applying AI to editorial workflows, the ways his team of journalists perceive and adapt to these tools, and—most critically—how Business Insider Germany’s audience reacts to the integration of AI into the content they consume.

Our conversation also touched on the legal battles shaping the media landscape, including the recent lawsuit between News Corp and Perplexity. Jakob shared a thought-provoking perspective on what AI engines truly do with content, offering a fresh way to think about how machines "read" compared to humans. And don’t miss the surprising connection Jakob draws between men’s fashion in Tokyo and the future of quality journalism.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2024

This week I'm thrilled to welcome Liam Andrew to the podcast. Liam's been working with machine learning and AI for a lot longer than most of us. He worked on the product team at the Texas Tribune for more than eight years before making the jump earlier this year to the American Journalism Project, where he serves as Technology Lead for its Product & AI Studio, which obviously has a huge focus on how newsrooms can leverage AI. Liam constantly talks to local newsrooms all over the country, so he has a front-row seat into what their challenges are, how AI can help, and how it's actually being used day to day.

I loved getting into the weeds with Liam. He and I talked about AI newsroom issues big and small — like whether or not ChatGPT is any good at headlines, but also the ethics of using generative images. We tackle some heavy issues in the state of media today, and I hope you'll listen to the end, where he gives some excellent advice for newsrooms who may be closer to the beginning of their AI journey than the end. 

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2024

If you follow AI at all, you’ve probably heard of Google NotebookLM. The Gemini-powered feature got a huge popularity boost recently when it introduced the ability to create a totally synthetic podcast around any material you gave it. The idea of a “podcast this” button on any article, video, or set of PowerPoints is a powerful one, and it underscores the transformative power of AI and large language models (LLMs).

That transformative power has actually been around much longer than NotebookLM’s audio overviews. On this week’s Media Copilot podcast, I talk to Daniel Rascon, co-founder of AnyTopic. His AI startup is entirely about creating audio experiences about, well, any topic. Essentially you tell the app what you're interested in — anything from medieval architecture or how to get better sleep — and it'll go out and find the most relevant content about that topic, creating a mini audiobook for you to listen to whenever you want.

These aren’t word-for-word readings of text articles like The Washington Post and The New York Times are doing. I'd actually call the broader idea a “content polymorph” — essentially an AI agent designed to search for, interpret, and reformat information around whatever the user specifies. Right now it's centered around audio experiences, but there's no reason the same idea couldn't be applied to all kinds of formats, potentially giving everyone their own personal media reformatter in the future.

Daniel and I explored what that future might look like, and how AnyTopic might be the first step in getting there. It was an illuminating conversation, and be sure to listen to the end where we don't shy away from why such a flexible, customizable future might be scary to a lot of people.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2024

When should we use AI and when shouldn't we?

That's a question that comes up often when I consult with media companies and PR firms on integrating AI into their editorial teams. You have to balance a number of factors — chief among them goals, ethics, and cost. You also need to consider the long-term picture and what it looks like when AI begins to take on tasks that were previously human-driven.

It's a tough thing to get right for an individual or a company, let alone all of society. What would help is a framework for how people can approach AI, a guide to where it can make the most difference, with careful weighing of the benefits and the risks of using such a powerful technology.

Journalist Jeremy Kahn has just what you're looking for. His book, Mastering AI, explores many facets of how AI is changing our world, from healthcare to the military to, yes, the media. Jeremy has covered AI extensively, most recently serving as the AI Editor at Fortune. He's also the latest guest on The Media Copilot podcast.

Jeremy and I had a wide-ranging conversation about AI, exploring some big-picture factors that I don't often get to sink my teeth into. We talked about copyright, bias, journalist copilots, and what the future of media looks like in a world where chatbots summarize everything. He also has a really good sense of what disciplined use of AI looks like, something I think journalists can really benefit from. 

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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This week on The Media Copilot podcast, I'm thrilled to talk to Joanna Stern, Senior Personal Technology Columnist at the Wall Street Journal. Joanna and I used to see each other quite often at various tech events when I was the Tech Editor at Mashable. She's known for her clever tech videos and deep reporting on how the titans of Silicon Valley are altering our lives in big and small ways.

Lately, though, she's making a name for herself by being an AI innovator. Normally this time of year she'd have a big review of the latest iPhones, but instead she gave the world Joannabot: an AI-powered chatbot created the Journal tech team and Joanna herself, designed to give readers all the advice they could ever want about buying the iPhone 16 and iPhone 16 Pro — in Joanna’s unique voice (or a close approximation).

As soon as I saw Joannabot, I knew I wanted to talk to Joanna about it. Not just because it's a wildly interesting AI experiment from a major publisher, but also because I've been dying to get Joanna's thoughts on the big picture of AI: how far it's come, what is on the horizon, and how it's changed the way she does her job.

Mission: accomplished. It was a really fun conversation, and I hope you listen till the end, where I squeeze out of her what she really thinks of Apple Intelligence Apple's upcoming feature upgrade that will add AI to the iPhone experience — and how that will change what we think of as "consumer AI."

NOTE: This podcast was recorded prior to Meta Connect, where Meta unveiled itsOrion AI-powered smart glasses.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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Remember that AI song based on the voices of Drake and the Weeknd that made the rounds last fall? It was a polarizing moment for AI — underscoring its power but also its peril, since neither artist had a say in the creation of that song.

Enter Hooky. The fresh AI startup is trying to solve this problem, one that isn’t unique to music. It’s actually one of the biggest issues in generative AI, undergirding the lawsuits against OpenAI, Stable Diffusion and all the rest: How do you ensure content creators can both control and profit from the use of their work when it's gobbled up by AI?

In Hooky’s case, it enables artists to license their voice to service, allowing the app’s customers to create original songs with that voice, and even distribute them to streaming platforms like Spotify. The artist approves every single AI song, and how much revenue they get entirely up to them.

The idea makes a ton of sense, but Hooky is also performing for a tough crowd: artists have a lot of AI skepticism, the regulatory landscape is really unclear, and there are plenty of competing AI apps that don't have any licensing or safeguards.

In the latest episode of The Media Copilot podcast, I talk to Jordan Young, CEO of Hooky. Jordan is a longtime music artist and producer who's worked with the likes of Jay-Z, the Chainsmokers, and Coldplay. We explore how the music industry might be best equipped to deal with the copyright-and-compensation problem, and we also tackle a key question: whether or not anyone really wants to listen to AI music in the first place.

And, yes, Taylor Swift does come up.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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I always feel good when I see fellow journalists going out on their own to build something new, and that's exactly what Nick Toso and Catalina Villegas are doing with Rolli. Toso is the former Washington Bureau Chief at CNN, and Villegas has worked as a producer and anchor for TV news. And with Rolli, they're creating a set of tools for journalists to help them work faster while producing better work — exactly what every newsroom in asking them to do. "Do more with less" is a tired phrase, but that's because it's everywhere now. It's the rule, not the exception.

How to do more with less doesn't get talked about nearly as much, but Rolli has a lot to say about that. You need an expert for your story — fast? Rolli can help. You need to know if a viral story is true or not, and where it originated? Rolli can help. And you don't actually have any money to pay for this service? Rolli can still help.

I went deep on Rolli with Nick and Catalina in this discussion, but beyond the features of service, I also put the focus on the forces in media that are putting services like Rolli in demand, including — what else? — AI.

It was a really fun conversation, and I hope you listen to the whole thing, since I don't shy away from asking them some tough questions about trust and bias that curated services are often accused of. Hey, I'm a journalist, too.

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© AnyWho Media 2024

When it comes to the right and wrong of using AI in creative work, it's safe to say we're still figuring it out. That goes double for music, where AI has cultivated more than its share of lawsuits and suspicion from artists.

From the audience perspective, AI is arguably changing things even more. Recommendation algorithms have the power to influence our tastes, but they also can put us in bubbles. At the same time, AI-cloned voices paired with auto-generated lyrics could end up changing our expectations of what's good entirely — we may not care whether it's Drake or fake.

For some thoughtful opinions on all this, I looked to authorities in both entertainment and AI. At the recent Ai4 conference in Las Vegas, I sat down with none other than comedian and actor Cedric the Entertainer as well as Alex Elias, CEO of AI recommendation engine Qloo. Our conversation got into the potential benefits and drawbacks of AI in music and show business.

Despite concerns about what AI could mean for artists' legacies (Tupac does come up), both Cedric and Alex expressed cautious optimism about the future of AI in music. Ultimately I came away convinced that it comes down to finding the right balance — harnessing AI's potential while preserving the human element.

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© AnyWho Media 2024

For companies building new things and trying to tell their story, there's a lot of talk about "going direct" lately. This is shorthand for a new(-ish) type of PR, where the founder and sometimes other key people simply use social platforms, newsletters and all the other tools of media themselves — eschewing the traditional route of telling their stories through journalists.

The idea has gained traction in the last few years (I moderated a whole discussion about it at Consensus 2024), and whether or not you think it's a smart PR strategy, there's a lesson here for the media itself: bypassing intermediaries is an essential part of audience "ownership" — one of the biggest concerns in a world where AI chatbots now answer user questions without connecting those users to the source that originated the information.

To better understand how publishers and the media can re-assert ownership of their own audiences, I talked to Mike Donoghue for The Media Copilot podcast. Mike is the CEO of Subtext, which transforms text messaging into a broadcast channel — reaching audiences through one of the core apps of the modern smartphone. Publishers use Subtext to create conversations with readers, celebrities use it to connect with fans, and all those interactions can be two-way. All they need to do is hit reply.

In a lot of ways, texting seems like the new email, and potentially a way for publishers to create a new surface to reach audiences that they control, shielded from Google, AI, and everything else. I talked to Mike about how Subtext came to be, why texting and SMS might be the last frontier for owning the audience relationship, and the role Subtext can play in a media ecosystem where AI is rapidly becoming the new platform to worry about — and perhaps to master.

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© AnyWho Media 2024

Perplexity is here to answer your questions.

Answering questions requires good information, though, and providing answers is easier if the people with the information actually want to give it to you. That’s a super-simple way of describing why Perplexity — the “answer engine” AI startup that pairs generative summaries with search — this week launched the Perplexity Publishers’ Program. By sharing advertising revenue with partners, Perplexity hopes to create better incentives for them to allow access to their content.

To unpack the new program and what it means to the media business, I spoke to Dmitry Shevelenko, the Chief Business Officer of Perplexity. If you're a cynic, you might think the move is purely defensive — that Perplexity is doing this so it doesn’t get sued. My takeaway, though, after talking to Shevelenko, is that Perplexity recognizes it needs good facts and good journalism to help fuel its so-called "answer engine, and that it wants to find a way to keep those coming.

But yes, he and I do talk about those notorious accusations about plagiarism from Forbes and Wired, what's the right way to attribute original reporting in an AI summary, and yes — that OTHER AI search engine that was just announced by a competitor you might know called OpenAI.

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© AnyWho Media 2024

AI companies hoovered up the entire internet before anyone questioned: Is that OK? This is the question that has led to a multitude of lawsuits (including, famously, The New York Times suing OpenAI), many deals between AI companies and various publishers, and an emerging consensus that content creators should be compensated for their data.

That's all well and good in theory, but what about the "how?" That's what my guests this week, Olivia Joslin and Toshit Panigrahi, are here to talk about. Joslin and Panigrahi are the co-founders of TollBit, which is one of a handful of companies tackling a very hard problem in media today, and that's how to get people to pay for content. Well, not people — machines. The web scraping that AI companies do used to be fairly benign. It helps power things like Google search and has traditionally been used as a research tool. But now the big AI guys are just taking that information and summarizing it, without doing that much of the linking anymore. And that's kind of a problem.

Publishers are very motivated now to find ways to be compensated when someone scrapes their content, and that's exactly what TollBit is trying to create: a marketplace where publishers and those who want their data can make a simple exchange: money for information. Of course things aren't always that simple, and I got into the complexities, the politics, and the realities of trying to get someone to pay for something that they've up until now been getting for free.

It was a really illuminating conversation, and I hope you listen all the way to the end where we zero on what a healthy media future looks like. As ever, if you enjoyed this conversation, it would be great if you could follow the show on Substack, Apple Podcasts, Spotify, or any other podcast app, really. Also, I’d appreciate it if you’d leave a rating or review — it really does help the show. And if you’re on YouTube, please like the video and subscribe to the channel. Much obliged.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2024

When you think about AI disrupting Hollywood, you typically think about CGI characters and creation tools like Sora and Pika that turn text prompts into impressively realistic visuals in seconds. But while technologies that create the things that meet our eyes understandably grab most of the headlines, there’s a quieter disruption happening at the very beginning of the moviemaking process.

Dilip Rajan is the co-founder of Jumpcut, whose tagline is, “Automate grunt work so you can get back to storytelling.” It does that with a product called ScriptSense, which inserts AI into the tedious slog of script coverage — the act of reading and evaluating screenplays. If a script isn’t from a known writer, a studio doesn’t have a lot to go on, so they often outsource it to a network of contractors, which obviously takes time and depends a lot on the tastes of those contractors. Powered by large language models (LLMs), ScriptSense can read way more scripts than any human could, analyze them to a common standard, and then summarize what they're about and if they're any good.

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Of course, there's a little more to it than that, but you can see why any movie studio would be interested in a machine that can read screenplays at scale, especially when there are tens of thousands of scripts floating around Hollywood at any given time — a number that will surely increase now that ChatGPT is joining the writers room.

I chatted with Dilip about where Jumpcut came from, how writers and agents should think about the disruption AI represents, and why Jumpcut's script processor might be just the tool Hollywood needs to get out of its current creativity rut. I thought it was fascinating conversation, especially when we went deep on how ScriptSense works — it's not just "Chat with PDF" on steroids.

If you want to check out Lucihub, please email us a ⁠team@mediacopilot.ai⁠ with Lucihub in the subject and we'd be happy to send you a discount code.

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© AnyWho Media 2024

When it comes to AI changing video, generative tools like Sora and Dream Machine have stolen a lot of the spotlight. with their ability to "imagine" video clips from text prompts. As cool as they are, most of them aren't available yet, and there's a big question of whether they actually save you any time.

But while these magic clip generators create a lot of excitement, there's a quiet disruption taking place downstream. Because in the real world, when you undertake a video project (whether it's editorial or marketing), there’s a universal rule: You want it done well, you want it done fast, and you want it done cheap. And you can only have two of those things.

Could AI put us on a path to getting all three? That's what I wanted to find out from Amer Tadayon. Amer is the CEO of Lucihub, a service that can create videos that would have taken days or weeks, and turn them around in hours — sometimes minutes. You still need to give it raw footage (it's not a purely generative tool like Sora), but it uses AI so that Lucihub’s human editors can cut videos incredibly quickly, and for a lot less than you'd pay an agency. For creative teams struggling for manpower and resources, it feels like a game-changer.

I talked with Amer about how Lucihub is disrupting the conventional wisdom around video, as well as what that means for the big picture. Could AI make video great again?

If you want to check out Lucihub, please email us a team@mediacopilot.ai with Lucihub in the subject and we'd be happy to send you a discount code.

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© AnyWho Media 2024

Quick question: How do you know it’s really me in this podcast video? After all, with AI services like Synthesia and ElevenLabs ready to clone my likeness and voice in mere minutes, it’s more than a possibility these days.

Besides obvious artifacts you might see in an AI-generated video, there’s the concept of content provenance, which in practice means a set of technical standards that imagery must adhere to so it can include metadata — nonvisible information that reveals whether an image was created by AI or not — and what modifications there were before it hit your eyeballs.

The thing is, for content provenance to work, you need everyone in the chain — from camera to website — to pay attention to it. So it turns out infrastructure plays a big role, and that’s what I wanted to to talk to Livepeer CEO Doug Petkanics about on The Media Copilot podcast.

Livepeer is a decentralized video platfom, which has an ace up its sleeve with respect to content provenance: the blockchain. By using the same tech that powers cryptocurrencies, Livepeer aims to create a cost-effective, scalable, and reliable way to both process video and label it properly. Its new AI subnet means the network now supports AI-generated content, including tools like OpenAI's video generator, Sora.

Doug and I explored the critical issue of content authenticity in the age of AI. As deepfakes and AI-generated media become more prevalent, this is obviously a growing challenge. Doug explained how Livepeer's blockchain tech can help maintain a healthy media ecosystem by providing verifiable “attestations” of content creation and modification, helping ensure that audiences can trust the what they’re looking at.

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© AnyWho Media 2024

Journalists are naturally skeptical people. They look critically at new things, especially when the incentives around them are complex, and that's certainly the case with AI. Given the early missteps of some sites publishing AI content and the existential threat the technology poses to distribution, it's only natural that a stigma around using AI has emerged among many reporters.

That stigma is something Josh Brandau is wearing down, one newsroom at a time. Josh is the co-founder of Nota, a content platform for augmenting newsrooms with AI tools. I spoke to Josh for The Media Copilot podcast about the company and how it's grown since its launch in the summer of 2022 — well before ChatGPT and generative AI exploded into the mainstream.

Josh and I discussed how Nota is helping newsrooms, especially small to midsize ones, giving them easy ways to leverage AI to create content more efficiently across multiple formats. But we also talked about how transformative AI is going to be, both for how journalists do their work and the industry as a whole. With everything happening with Google’s AI Search and ChatGPT’s new ability to really talk to you, that discussion is definitely more urgent than ever.

If you enjoy this conversation, I’d encourage you to follow the show on Substack, Apple Podcasts, Spotify, or any other podcast app, really. Also, we’d appreciate it if you’d leave a rating or review — it really does help the show. And if you’re on YouTube, please like the video and subscribe to the channel.

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© AnyWho Media 2024

In the latest episode of The Media Copilot podcast, I had the pleasure of talking with Jon Gillham, founder of Originality.ai, about the nuanced world of AI-generated content and its detection. Jon's company started from a simple need in his content marketing business: ensuring that content was authentically created by humans, not AI. As AI sophistication has grown, so has the necessity for robust detection tools.

The field of AI detection is more complicated than you might think. Jon points out that while not all AI content is spam, almost all spam is now AI-generated. That leads us to an unpacking of Google’s dilemma — that targeting AI-generated content in search results might result a better experience for customers but its position as a major LLM developer inherently conflicts with that goal. Nonetheless, AI detection tools are essential for publishers trying to navigate the new digital landscape without compromising their search rankings or credibility.

We also talk about the importance of transparency and authorship as AI becomes more ingrained in digital content creation. Projecting forward, you can begin to see a “hybrid” future where AI aids content creation under stringent guidelines to ensure quality and authenticity, and that’s OK!

I’m really happy with how the conversation goes deep on the complexities and realities of having AI “out in the wild” in our information ecosystem, and how the interplay between AI technologies and content creators has evolved — and will continue to evolve.

If you enjoy this conversation, I’d encourage you to follow the show on Substack, Apple Podcasts, Spotify, or any other podcast app, really. Also, we’d appreciate it if you’d leave a rating or review — it really does help the show. And if you’re on YouTube, please like the video and subscribe to the channel.

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© AnyWho Media 2024

If past is prologue, the story of how AI changes media won't have a happy ending for those in the news business. Tech platforms profoundly altered the media landscape over the last 20 years, forever redefining how news is created, distributed, and monetized, and most media brands that tethered their strategy to tech platforms now find themselves diminished and, in some cases, demolished. Will history repeat itself with AI?

To guide me toward an answer, I turned to Ricky Sutton. Ricky is one of the most interesting personalities in media today, and we spoke on The Media Copilot podcast. He’s had a wildly diverse career, cutting his teeth as a reporter before moving on to very important roles at both media companies and tech companies. That experience has enabled him to spot trends long before they were obvious to the rest of us. Ricky's also founded Oovoo, a video platform for media companies that’s powered by — what else — AI.

Last year he stepped down from the day-to-day at Oovoo to focus on AI through his own Substack called Future Media, where he regularly shares his thoughts on how AI is changing how we consume information, and how those in the media can get ahead of those trends so we’re not always at the mercy of Big Tech.

If you enjoy this conversation, I’d encourage you to follow the show on Substack, Apple Podcasts, Spotify, or any other podcast app, really. Also, we’d appreciate it if you’d leave a rating or review — it really does help the show. And if you’re on YouTube, please like the video and subscribe to the channel.

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© AnyWho Media 2024

This week on The Media Copilot podcast I’m thrilled to talk to Alex Fink. Alex is the founder and CEO of Otherweb, a news aggregator that uses AI to give readers a healthier news diet than your average social media feed. Instead of optimizing for outrage or clickbait, Otherweb favors “kale over cake” — an analogy we come back to a few times in the conversation. Alex has an interesting career. After working for a long time in computer vision, he decided the world had enough cameras and decided to focus instead on the decisions technology could help with rather than the tech itself. Otherweb isn’t his first rodeo — he’s been a founder twice before and a very astute observer of the media business. He’s full of great observations about the arguably corrupted incentives of ad-based media, which helps to guide Otherweb and the way it ranks and serves up content. You can check out Otherweb here: https://otherweb.com/

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© AnyWho Media 2024

Yes, we know generative AI is bad for writing articles whole-cloth. But what IS it good for when you want to apply AI in a newsroom?

In this week's episode of The Media Copilot podcast, host Pete Pachal explores that question Joe Amditis, Associate Director of Operations at the Center for Cooperative Media. As part of his role, Joe researches how journalists can apply generative AI, both at the individual and organization levels, and has written guides on publicly available tools, including the how to create custom GPTs for reporting use cases.

Joe's advice to those new to using AI for journalism? Experiment. Journalists need to use AI to understand its capabilities and limitations, and should focus on low-stakes tasks initially. Once they're comfortable, some of the most useful applications he's found are:

Documentation and transcription

Brainstorming ideas on why people should care about a story

Filtering through data and documents to surface potential leads

Generating stock images and graphics to accompany articles

The key takeaway: Use AI tools pragmatically to gain efficiency in workflows, but do not lose sight of the human element and relationships at the core of journalism. As long as journalists don't lose sight of creating quality, valuable content for their communities, they'll be able to find ways AI can help move faster toward that goal.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2024

What's it like to come face-to-face with your own deepfake? Anne-Marie Tomchak knows, and the encounter is captured vividly in her documentary Game Changer: AI and You, which aired recently on Ireland's public broadcaster.

It's a powerful moment, and one I would argue every journalist covering AI should experience: the unnerving feeling of seeing your own image and voice co-opted to say or do anything that the programmer desires. It's one thing to hear about a celebrity like Taylor Swift being deepfaked; it's quite another to have it done to you personally. And with the technology becoming so accessible, that becomes a greater possibility every day.

On this week's episode of The Media Copilot podcast, Anne-Marie shared the insights she gained by working on the documentary (her second on the subject of AI), zeroing in on AI's growing influence in journalism. We discussed how AI is reshaping the media landscape, from newsroom operations to content creation, and the ethical and legal conundrums emerging from AI-generated content. As the founder of BBC's social media investigative unit, Anne-Marie talks about how this technological shift is different from digital media shakeups of the past.

If you enjoy the podcast, please subscribe on your favorite platform, check out our channel on YouTube, and leave a review or a star rating. It really does help the show, and it'll ensure we keep bringing you great conversations like this one.

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© AnyWho Media 2024

Doing journalism with AI? What even is that?

Up until recently, the answer to that question was a small part of the profession, mostly restricted to big publications with deep pockets and a sophisticated data strategy (think: The Washington Post or the AP). But after ChatGPT said hello to the world a year and a half ago, however, "AI-powered news" was suddenly a blank canvas.

After the world saw the disastrous results of using the content produced by generative AI without a robust process surrounding the creating, vetting, and publishing of that content, the media world went back to the drawing board: What is this "magical" new technology good for, and what does a newsroom need to do to use it safely and ethically?

David Caswell spends most of his days thinking about exactly that. David has been working with machine learning and AI in media for well over a decade, leading product teams at the BBC, Tribune Publishing, and Yahoo. He's now a consultant and researcher focused on AI in newsrooms, and he wrote arguably the definitive guide on the subject last fall in his article "AI and News: What's Next?"

This week David joins The Media Copilot podcast to talk about everything that's happened since his article dropped, and how his thinking about AI's role in our media ecosystem has changed. We also explore what he hopes to see come out of The New York Times lawsuit against OpenAI, how reporters should be leveraging generative tools, and why journalists are naturally good prompt engineers.

If you enjoy the podcast, please subscribe on your favorite platform and leave a review or a star rating. It really does help the show, and it'll ensure we keep bringing you great conversations like this one.

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© AnyWho Media 2024

What happens when you teach your AI to churn out believable fictional characters? AImmersive co-founders Max Salamonowicz and Casey McBeath have built a tool for writers and creatives who want to create realistic video game and fiction characters.

The tool they've created isn't just a simple character generator. It's an advanced AI system designed to produce believable, complex characters with unique personalities, backstories, and traits.

Salamonowicz and McBeath spoke to John Biggs for The Media Copilot podcast. Their insights offer a glimpse into the merging of technology and creativity, and how generative AI is poised to redefine the landscape of narrative arts.

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© AnyWho Media 2024

Copyright is one of the biggest issues in AI. Eric Wengrowski, the CEO of Steg.AI explains how digital watermarking can help.

It's fair to say the subject of copyright comes up a lot when you're talking about AI. Whether you're talking about a large language model (LLM) like the ones that power ChatGPT, or diffusion models that serve text-to-image creators like Midjourney, these generative systems suck up massive amounts of training data from the open web.

This has concerned many content creators and publishers, including The New York Times, which brought its concerns to the courts in late December. While the world waits for the law to catch up to the AI industry, the question remains: can authors, photographers, videographers and anyone else in the business of creating content do anything to ensure they stay connected and in control of the things they create?

There might be. What all these issues are circling is the concept of content provenance: ensuring the copyright holder of any piece of content is embedded within the content itself. One way to do that through digital watermarking — essentially creating an "Invisible QR code" that travels with the document, image, or video, even if it's copied and stripped of metadata.

Steg.AI is a company that specializes in digital watermarking, and The Media Copilot spoke with its CEO, Eric Wengrowski in our latest podcast. We fully explored the role of watermarking in a world where all kinds of web crawlers are constantly hoovering up data, why it's important to label synthetic content, and the incredibly important question of: can you still detect the watermark of a piece of training data in model output?

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© AnyWho Media 2024

"Just imagine the whole society just crumbling over AI."

People in Iceland don't have to imagine it. That quote from Siggi Arnason, CEO of OverTune, is describing the fallout from a viral video that his company's AI-powered technology helped create. The video was a comedy sketch that featured a recreation of a popular deceased Icelandic comedian, Hermann Gunnarsson. After it aired, over 90% of the country ended up seeing it, and in response, the country's parliament is fast-tracking legislation around deepfakes and the use of AI.

Another effect of the controversy is that OverTune has gone viral. Arnason spoke to John Biggs on The Media Copilot podcast about the skit and the resulting firestorm. Arnason, a former musician and self-described "lover of cats," is unique in that he never wanted to be an AI influencer. But when his team built Iceland’s first deepfaked political comedy sketch, he knocked over a can of cod. Now his country is wrestling with the concepts of ownership, creativity, and the future of AI. 

Join us in New York on February 1! We are planning our first meetup in Manhattan and we’d love to meet you! Sign up to our⁠Meetup Group⁠here and we’ll send you the details shortly.

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© AnyWho Media 2024

When The New York Times filed its landmark lawsuit, accusing OpenAI of violating copyright by training its large language models (LLMs) on its journalism, some savvy observers had been expecting such a move for months.

One of those people is Louise Story. Louise is a former Times staffer, spending several years as an investigative journalist before getting involved in strategy and building new formats for the paper (such as live video). She also led content and product strategy for The Wall Street Journal — including its approach to AI — so few people have a better perspective on how newsrooms regard technology platforms. She now offers that perspective as an independent consultant, helping guide media companies on digital strategy and how they can adapt to an AI-mediated future.

I spoke to Louise for The Media Copilot podcast. We of course talk about the lawsuit and dissect the stakes for the players involved and the media. I was also excited to get her perspective on the infamous Sports Illustrated debacle and how incidents like it have added to the stigma of generative content. Of course, I couldn’t let her leaving without getting her to share some practical advice on how newsrooms can take their first steps into the world of GenAI.

Join us in New York on February 1! We are planning our first meetup in Manhattan and we’d love to meet you! Sign up to ourMeetup Grouphere and we’ll send you the details shortly.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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When ChatGPT showed how easy it was to write an "original" academic paper that could get a passing grade, the need for some kind of AI detector was suddenly starkly clear. The market quickly responded, and GPTZero, created by 23-year-old Edward Tian, was an overnight sensation last spring. College professors now routinely check papers for AI authorship.

In the media world, the need for such a tool was perhaps less urgent, since editors tend to have a tighter grip on how copy is produced, and few writers would risk their reputations trying to pass off synthetic articles as their own. That is, until the boondoggle with Sports Illustrated, where articles supplied by a third party appeared to have been written by AI (note: the company that supplied the articles claims they were human-written).

The incident got widespread attention, and it underscored the need for AI detection in media, especially when you publish content at scale, from multiple sources. Even if your in-house editorial team is strictly human-driven, freelancers and syndication partners may not have gotten the memo.

So do managing editors need to add "copy and paste article into AI detector" to the long list of editors' duties? They can, but another solution may be to build it into existing processes and tools, which is exactly why Copyleaks exists. The company began as a plagiarism detector and now markets itself as an AI detection company. It claims to be able to do detect synthetic text across models, in multiple languages, and in detail (i.e. showing which parts of a document are AI generated, as opposed to a simple Yes/No result).

Lee Gaul is the enterprise sales director at Copyleaks, and he's this week's guest on The Media Copilot podcast. Our conversation goes beyond simple AI detection and explores the big-picture issues driving the demand for the service as well as the increased need for human judgment when machines enter the picture.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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Newsrooms can only get so far with pasting prompts into ChatGPT. Once you want to get more serious with generative AI, a media business should think seriously about running, fine-tuning, and perhaps even building their own large language model (LLM).

There are a number of approaches to this, and it's easy enough to download a commercial or open-source model to run on your private cloud, or even your MacBook. But what are the factors to consider when rolling your own AI operation, and how expensive can it get?

In this week's conversation, John Biggs talks with Viktor Shpak, lead developer for VisibleMagic, about what it takes to run your own LLM in the privacy of your own office. He also explores the future of AI-generated content and code, pointing out that the rising AI tide will — theoretically — lift all boats. We're grateful we had the chance to probe the mind of an extremely plugged-in developer.

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In the year since ChatGPT arrived on the scene, journalism has grappled with the ethics of generative AI. From robot-written articles to the proliferation of “fake” images, the problems the media needs to think through have been bubbling in the background for a long time, but they've been exacerbated by the scale that generative AI makes possible.

One person who's spent a lot of time thinking about all the perils and promise that AI brings to journalism is Charlie Beckett. A professor in the Department of Media and Communications at the London School of Economics (LSE), Beckett is the founding director of Polis, the school’s international journalism think tank. He’s currently leading Polis’s Journalism and AI project, which hosts the JournalismAI Festival, starting on December 6.

The festival promises to unite dozens of journalists who are innovating and using generative AI in  newsrooms all over the world. It'll take on topics like detecting bias in content, the role AI can play in covering elections, and how small and local newsrooms can leverage the tech to punch above their weight.

In talking to Beckett, I was struck by the tone of optimism that emerged in our conversation. Even though we tackled thorny topics like the ethics of generative images in war and the recent generative-content brouhaha involving Sports Illustrated, it's clear his focus is on how this manifestly transformative technology can help the truth that journalists seek shine through.

I hope you enjoy the discussion as much as I did. You can register for free for the JournalismAI Festival here.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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Music: ⁠⁠⁠⁠⁠⁠Favorite⁠⁠⁠⁠⁠⁠ by Alexander Nakarada, licensed under Creative Commons BY Attribution 4.0 License

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The past few days have turned the entire industry of generative AI upside-down. Before the weekend, OpenAI was sitting comfortably in pole position, riding high from a series of recent announcements designed to keep it there. Most of the world saw ChatGPT as the default starting place for anyone taking their first steps into AI, and the company’s models as setting the standard, with competitors fighting for scraps of mind share.

Now we're in a completely different world. Ever since its board fired CEO Sam Altman in a surprise move Friday afternoon, the situation at OpenAI — and the marketplace for generative AI tools — has been in flux. There have been so many developments since Friday that it's been difficult to keep up (here’s a good summary), but the current state of affairs is a standoff between OpenAI's employees and the board. The staff wants Altman reinstated and the board to resign, or they're all going to follow Altman to Microsoft (far and away OpenAI's biggest investor), which offered him a job as CEO of a new AI subsidiary. Microsoft has said it would indeed hire the defecting staffers.

On this week's Media Copilot podcast, John Biggs and I are joined by Peter Bittner from The Upgrade to discuss these possible scenarios for OpenAI and what they mean to customers… and competitors. Whatever happens, one thing has been made very clear: the field of generative AI will not be the same after this.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2023

In this week’s conversation, I talk to Brennan Woodruff of GoCharlie about how AI services based on content generation can contend with a ChatGPT-dominated world. Plus John Biggs and I break down the week’s news: YouTube’s guidelines for synthetic content, a new study rating the big models on hallucinations, and an inflection point on the thorny issue of fair use.

John Biggs and I offer a crash course on using AI for marketing and media. Learn more about the 3-hour session here.

When you’re running a startup, you’re already in a race. When you’re running an AI startup, you’re essentially in the New York City marathon. It’s already a slog, and you’re wall-to-wall with thousands of competitors of all stripes. Whether or not you succeed depends on the kind of race you’re running: Do you want to win the whole thing, beat your personal best, or be top in your category?

GoCharlie appears to be aiming for the third option. The AI startup is one of many that specializes in creating marketing copy, images, and other material, but it differentiates itself by applying its own large language model (LLM) trained specifically for that use case. That would seem to give the young company an advantage, but now that OpenAI had made it easy for anyone to create task-specific GPTs with assistants — and is creating a platform to sell them — can GoCharlie get past this “extinction-level event” for AI startups?

I spoke with co-founder Brennan Woodruff about GoCharlie, what it brings to the table to marketers and media people, and how AI entrepreneurs can stay in the race even when running alongside a ChatGPT that’s wearing rocket boots.

In this week’s AI news that’s most relevant to media…

What even is fair use anyway?Ed Newton-Rex, the VP of Audio at Stability AI — the creator of the Stable Diffusion image generator — very publicly resigned from the company, arguing strongly against the perspective, common among tech companies, that training AI models on copyrighted material constitutes fair use.

Let’s put “Hail Hydra” at the end of every deepfake:YouTube kinda-sorta took a stand on deepfakes, introducing new requirements for creators to label “synthetic” content made to look realistic, but allowing a parody/satire exception. It’s a important step, though still leaves a lot up to YouTube’s human moderators. Also: anyone making bank off of songs made from cloned voices of various artists is on notice now that those artists can force synthetic songs to be taken down. Progress? Probably. But other platforms (a certain single-letter network comes to mind) will likely have different standards.

Wait, people use Notion? This week Notion launched Q&A, an AI-powered feature that can scan all the material you’ve put on the service to inform answers to specific queries — essentially letting you have a conversation with your work. This is the dream of Google Bard’s feature that connects with all your Gmail and Google Docs, but Notion’s thingie probably has a better chance of giving useful answers since it probably won’t have every grocery list you’ve made since 2006 in there.

The Hallucination Olympics: Rankings for which generative AI model hallucinates the most are out, and boy, Google’s Gemini upgrade can’t come fast enough — Google Palm, which powers Bard, was dead last. Perhaps not surprisingly, OpenAI’s models lead the pack, though some smart folks were able to get Llama 2 into the same category. Hallucinations will never go away entirely, but we’re optimistic that the robots will continue to get better at, you know, facts. Now if we could just to the same with bias…

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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There are thousands of generative AI tools for content, and some actually work well. Generative tools can create SEO headlines, social copy, document analysis, and lots more for reporters and editors, all ready to enhance your productivity.

However, there are roadblocks to incorporating these tools in day-to-day work. Beyond the basic concerns about quality and hallucinations, often the workflow itself is the issue: Incorporating a new tool typically means another login, another browser window open, and a new app to get familiar with. Then, if you’re constantly copying and pasting from the tool to your CMS and back again, the gains in efficiency start to drop. In other words, GenAI has the best chance of being effective when it’s integrated into existing workflows.

That’s the magic of YESEO, a tool developed by Ryan Restivo in partnership with the Reynolds Journalism Institute (RJI) at the University of Missouri. While there are any number of tools that will serve up SEO headlines for news stories, YESEO was created specifically for Slack, the collaboration platform found in almost every newsroom.

I spoke to Ryan about developing YESEO — which he began before the general release of ChatGPT — how newsrooms can develop a pragmatic approach to generative AI tools, and what a reporter’s workflow looks like in a future world where GenAI tools are as common as spellcheckers.

The Media Copilot is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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© AnyWho Media 2023

At a time when most newsrooms across the world are considering, studying and, in some cases, experimenting with generative AI, at least one publication has enthusiastically embraced the technology, building it into workflows and publishing "synthetic" content on the regular.

BusinessDesk in New Zealand uses ChatGPT and other AI models to augment what it’s serving up to subscribers, using the tech’s generative capabilities to both monitor news events and create content around them almost instantly. After launching AI-powered articles and summaries in the spring, BusinessDesk is going further, using it to summarize lengthy reports and assist in news gathering.

Matt Martel, general manager of BusinessDesk parent NZME, spoke to The Media Copilot about why the BusinessDesk newsroom jumped into the realm of generative AI so quickly, how it avoids the pitfalls of the tech without slowing things down, and the ways the company’s organizational structure made it so friendly to integrating GenAI into real-world workflows.

You can hear the full version of this PREMIUM episode of The Media Copilot by⁠becoming a paid subscriber⁠.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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It's still early days for generative AI, but the change it will inevitably impose on the news media is massive. If that sounds sounds scary to you, you should talk to someone. We'd recommend Brian Morrissey, author of The Rebooting newsletter and host of The Rebooting Show podcast, both of which get into the weeds of the media business. In this wide-ranging conversation, Brian and Pete Pachal attack the big questions around GenAI and media: What happens when AI becomes the dominant force in search and SEO traffic to news sites dries up? What does the publisher-audience relationship look like in an AI-mediated world? And how can media companies get ahead of the coming GenAI wave — and maybe even ride it? The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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Perhaps the people best positioned to thrive in tomorrow’s media ecosystem are today’s journalism students. Learning how generative AI can assist in their work while also learning the fundamentals of the trade means the next generation of reporters will have machines assisting their work from the start. Helping guide this vanguard of robot-enhanced journalists is Thomas Seymat. Thomas is the Editorial Projects and Development Manager for Euronews, and he also teaches at the Journalist Training Center in France, one of the oldest journalism schools in Europe. This fall he’s leading a class on the use of GenAI in reporting, coaching them on how ChatGPT, Midjourney and other tools can make them stronger, more efficient reporters while also establishing where the guardrails are on their use. Our conversation was illuminating — and somewhat reassuring — about the future of journalism and the next generation. Thomas revealed how his students are already using these tools, their thoughts on the ethics of AI, and some “road to Damascus” moments in their journey. On the news brief, John Biggs and I discuss why labeling content as “AI assisted” is practically useless, whether or not Apple’s new AI-ready Macs mean anything, and that the White House executive order on AI might actually be pretty good? That’s up first. Information on the AI class John and I are teaching is here. More to come on that soon.

This week's top AI stories for media:

The White House executive order on AI

Labeling won't solve AI's problems (Axios)

IAC warns regulators generative AI could wreck the web (Axios)

Apple mentions AI, finally (CNN)

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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The Media Copilot is a weekly discussion about generative AI and how it's changing media, journalism, and the news. After a news briefing where journalists Pete Pachal and John Biggs discuss the most recent AI headlines relevant to the media, we present a conversation with a new person every week — innovators, media executives, and fascinating people with compelling perspectives on AI. For this week's conversation, we welcome Jeremy Caplan, author of the newsletter Wonder Tools and Director of Teaching and Learning at the Craig Newmark Graduate School of Journalism at CUNY. We spoke to Jeremy about not just the tools journalists can use to begin using generative AI in their day-to-day, but also the mentality needed to get the most out of this unprecedented moment in media. If you watch the video version of the podcast, you may notice Jeremy’s video was slightly out of sync with his audio. We tried to fix this in post and failed, but rest assured Jeremy talks just like a normal human when he has a better internet connection. Here are the stories from the news briefing: Nightshade "Poisons" AI models by altering metadata on images (Ars Technica) Twelve Labs shows off AI that can "watch" and interpret videos (The Neuron) An AI designed to clean up Wikipedia citations (Nature) Anthropic is crowd-sourcing an "AI constitution" (Axios)

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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The ethics of generative AI are more complicated than they might seem. Take generative images, like the ones created by DALL-E and Midjourney. Even when legal issues like the licensing of training imagery are addressed (as Adobe Firefly seems to), does that mean it's OK to create an image in the style of a well-known illustrator without their knowledge or approval? And does the prolific use of GenAI images cheapen the entire practice of photo illustration?

That was one of many topics I talked about this week with Harry McCracken, Global Technology Editor for Fast Company, and a key member of the publication's internal team exploring generative AI. Harry has been covering tech since the dawn of the internet and has had a front-row seat every innovation in tech since then. Over the past several months he's plunged deep into AI, and the topic features regularly in his newsletter, Plugged In, such as this recent piece on the dawn of "self-aware" software.

Harry is also the first guest in what will become a regular feature on The Media Copilot: Friday Conversations, where I chat with journalists, media executives, and interesting people doing interesting things with generative AI and the news. This first conversation is free for everybody, but I plan to make these conversations exclusive to paid subscribers starting next week. If you don’t want to miss any, it might be a good idea to take advantage of that subscribe button below 👇

I hope you find the conversation as stimulating as I did. Look for more insights from fascinating people working at the intersection of media and GenAI in the coming weeks.

The Media Copilot is a podcast and newsletter that explores how generative AI is changing media, journalism, and the news.

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Music: ⁠Favorite⁠ by Alexander Nakarada, licensed under Creative Commons BY Attribution 4.0 License

© AnyWho Media 2023