# How Adobe is managing the AI copyright dilemma, with general counsel Dana Rao

- **Show:** Decoder with Nilay Patel
- **Published:** 9 Jan 2024
- **Source:** https://www.podtrac.com/pts/redirect.mp3/pdst.fm/e/pscrb.fm/rss/p/mgln.ai/e/257/traffic.megaphone.fm/VMP7196991987.mp3?updated=1704742055
- **Transcript:** https://podcasts.opennash.com/shows/decoder-with-nilay-patel/how-adobe-is-managing-the-ai-copyright-dilemma-with-general-counsel-dana-rao-6bcd17/
- **Provider:** OpenNash Podcasts (machine-generated)

## In brief

Adobe's general counsel Dana Rao argues that a company can lead in generative AI while sidestepping the copyright fight. Adobe trained its Firefly image model only on licensed and Adobe Stock content, and it backs that choice with legal protection for customers. He pairs this with legal and technical safeguards for creators: a proposed federal anti-impersonation right, and Content Credentials metadata that proves where an image came from.

The episode runs on a tension between caution and speed. Rao says Adobe wants to innovate, yet its values and its lawyers' power to say no shape what it ships. The same logic explains the abandoned $20 billion Figma deal, where regulators' theory of future competition left no workable remedy. Patel keeps pressing on the unsettled parts: fair use, the market harm to creators, and the line between a photo and a fake.

## Key insights

1. **Adobe avoided web scraping to sidestep lawsuits** Firefly was trained on Adobe Stock and other licensed work, so Rao says Adobe would not have to 'rip Firefly out' if courts rule against scraping. The tradeoff was a harder engineering problem, because less data risks a weaker, more biased model.
2. **Regulators' future-competition theory sank the Figma deal** Adobe's discontinued XD tool and the lack of customer overlap did not settle regulators' worry that either company might later enter the other's market. Rao says no remedy could fix a 'might do something' concern, so the companies stopped before an enforcement action.
3. **Typing a prompt probably earns no copyright** Rao argues the AI, not the user, makes the final expressive choices, and US law requires human expression. He says adding your own edits in a tool like Photoshop can make the result copyrightable.
4. **Artists' style has no legal protection today** Copyright does not cover style, so someone can generate work 'in the style of' an artist and sell it cheaply. Adobe drafted a federal anti-impersonation right, modeled on publicity rights and trade dress, and gave it to the Senate Judiciary Committee.
5. **Proving authenticity beats trying to detect deepfakes** Adobe's scientists found deepfake detection only about 60% accurate, which is not consumer grade. So Adobe and partners built Content Credentials, which attach tamper-evident metadata to an image from capture through editing to publication.

## Questions this episode answers

### Why did Adobe's $20 billion Figma acquisition fall apart?

Regulators in the UK and EU argued that Adobe or Figma could one day compete in each other's space. Rao says no remedy could answer a future-competition concern, so Adobe and Figma ended the deal before a formal enforcement action.

### Is Adobe's Firefly AI image generator safe to use commercially?

Rao says Firefly was trained only on Adobe Stock and licensed content, so it avoids the copyright questions facing models trained on web scrapes. Adobe also offers customers indemnification, meaning it will cover their legal costs if they are sued.

### Can I copyright an image I make by typing a prompt into an AI?

Rao says Adobe doesn't think a prompt alone is copyrightable, because the AI makes the final expressive choices and US law requires human expression. He says adding your own edits afterward can make the result copyrightable.

### What are Content Credentials and how do they fight deepfakes?

Content Credentials are like a nutrition label of metadata attached to an image, recording who took it, when and where, and what edits were made. Instead of trying to detect fakes, which Adobe found only about 60% accurate, they let creators prove what is real.

### Can someone legally copy an artist's style with AI?

Rao says copyright law doesn't currently protect style. Adobe drafted a federal anti-impersonation right that would let artists sue people who intentionally imitate their work for commercial gain, and it has been given to the Senate Judiciary Committee.

## Facts

- **Dana Rao** [0:29:47]: "It was only making $15 million of standalone revenue."
- **Dana Rao** [0:05:56]: "last March, we launched our foundation model Adobe Firefly, you know, which is helps uh people do text to image generation."
- **Dana Rao** [0:11:39]: "My whole org is 700, so it's about fifty fifty between legal slash public policy and then security, so security is about 350, and legal is probably about 325"
- **Dana Rao** [0:08:23]: "acrobat is a great example of a place where we dedicated security resources to making sure there's a sandbox essentially around Acrobat."
- **Dana Rao** [0:17:12]: "Because there's a lot, as you know, a lot of pirated Adobe software out there."
- **Dana Rao** [0:20:47]: "we had two amazing founders, um, Chuck Geschke and John Warnock. John just passed away a couple months ago"
- **Nilay Patel** [0:28:34]: "Adobe decides to buy Figma for 20 billion. There is a lengthy review process, both in Europe."
- **Dana Rao** [0:34:23]: "as soon as you go into phase two, which we went into in July, June and July, with both the UK and the European Commission."
- **Dana Rao** [0:34:23]: "And in our case, the decisions were February fifth, February twenty fifth."
- **Dana Rao** [0:38:37]: "Figma's gonna build Photoshop or whatever, they have 800, 800 people, but then they're gonna somehow magically do everything right."
- **Dana Rao** [0:46:23]: "we decided to train Firefly on our own Adobe Stock content and other licensed work from the rights holders to build our model."
- **Dana Rao** [0:47:52]: "we were even more excited about the 2nd version of the model, which we launched at Adobe Max."
- **Nilay Patel** [0:49:10]: "In June, Adobe offered to cover the legal bills of anyone who gets sued for copyright infringement if they use Firefly."
- **Dana Rao** [0:52:11]: "But even in there, they said that you have to obey the EU copyright directive."
- **Dana Rao** [0:53:23]: "it always gets text wrong, generative AI always gets text wrong, cause it has no idea it's words."
- **Dana Rao** [0:54:25]: "The Warhol case clearly showed the Supreme Court is interested in the economic factor as part of the fair use analysis"
- **Dana Rao** [1:00:26]: "we wrote a draft bill, we gave it to the Senate Judiciary Committee. They're reviewing it."
- **Dana Rao** [1:03:12]: "But if someone is actually trying to create harm, like there was a, you know, image of of Zelenskyy saying, you know, lay down your arms, right?"
- **Dana Rao** [1:04:42]: "And the answer came back, it's like, probably like 60% accuracy, so not consumer grade."
- **Dana Rao** [1:06:57]: "Leica is already shipping that camera, it's in the stores. And that means you can take a picture, turn on Content Credentials"
- **Dana Rao** [1:07:52]: "the first time we did this four years ago, there was fifty nine people. This time, there was 180 people."
- **Dana Rao** [1:08:17]: "After just a year, we had the 1.0 version of that technical specification, and we're already up to 1.4 in just four years."
- **Dana Rao** [1:08:48]: "Qualcomm just announced that Snapdragon is going to be C2PA compliant."
- **Dana Rao** [1:12:41]: "we have a site called verify dot org, and on that site, if you bring your content credentialed image, you can just use a slider."
- **Dana Rao** [1:22:34]: "So everybody who creates an AI feature at Adobe has to fill out an AI impact assessment, every engineer"

## Transcript

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**[0:01:24] Nilay Patel:** Hello and welcome to Decoder. I'm Nilay Patel, editor in chief of The Verge, and Decoder is my show about big ideas and other problems. Today I'm talking to Dana Rao, who is general counsel and chief trust officer at Adobe. That's the company that makes Photoshop, Illustrator and other key creative software. Now, if you're a longtime decoder listener, you know that I have always been fascinated with Adobe, which I think the tech press largely undercovers. After all, this is a company that makes some of the most important tools that exist across design, video, photography and more.

**[0:01:54] Nilay Patel:** And Adobe's customers have passionate feelings about both the company and those tools. If you're interested in how creativity happens, you're kind of necessarily interested in what Adobe's up to. I bring all that up because it is fascinating to consider how Dana's job as Adobe's top lawyer is really at the center of the company's future. And that's for two reasons. First, more philosophically, the copyright issues of generative AI are so unknown and unfolding so fast that they will necessarily shape what kind of products Adobe can even make in the future, and what people can make with those products.

**[0:02:28] Nilay Patel:** Second, a little more practically, the company just tried and failed to buy the popular upstart design company Figma. A potentially 20 billion dollar deal that was shut down over antitrust concerns in the European Union. So Dana and I had a lot to talk about. As it happens, we spoke just one day after Adobe and Figma announced the end of the deal. And he really opened up on how the decision to call things off was made, why Adobe wanted to acquire Figma in the first place, and how the deal falling apart really influenced his thinking on industry consolidation in the future.

**[0:03:00] Nilay Patel:** Then we got into the weeds on AI and copyright, a story that I think is going to unfold in unpredictable ways for at least the next year, if not more. Like every company, Adobe is figuring out what the boundaries of copyright law and fair use look like in the age of AI, just like the creatives that rely on its products. But at the same time, it's also making huge investments in and shipping generative AI tools like the Firefly image generator inside of huge mainstream software products like Photoshop and Illustrator.

**[0:03:26] Nilay Patel:** I talked to Dana about how Adobe is walking that tightrope and how he's thinking about the general relationship between AI and copyright as Adobe trains its models and ships the tools to its users. You'll hear Dana frame this in a way that's easy to understand. What data can AI companies train on, and then what are we allowed to do with the output of the AI systems? That's a simple question, but it contains a lot of gray area.

**[0:03:49] Nilay Patel:** For example, what does it mean to copy an artist's style using AI, something that no law on the books really protects? Adobe is pretty invested in that idea, and Dana helped the company draft an anti impersonation bill it presented to Congress. Then, of course, there's the issue of AI being used to deceive people, especially during this current election year. That's an interesting problem for the companies that make AI tools. Should they restrict what their users can do with them?

**[0:04:11] Nilay Patel:** Adobe is at the center of that debate with something it calls the Content Authenticity Initiative. And I am proud to say Decoder is the sort of podcast where a viral deepfake of the Pope dripped out in a puffer jacket is described as a catalyzing event in tech policy. Dana has a lot of ideas on how metadata can help people know what they're looking at is actually real. One note before we begin, like I said, Dana and I spoke one day after Adobe and Figma called off their deal, which means we spoke before the New York Times announced it was suing Microsoft and OpenAI for copyright infringement.

**[0:04:40] Nilay Patel:** But the legal quagmire the AI industry finds itself in is much bigger than just one lawsuit, and the issues are really the same across all of the pending copyright lawsuits. It really feels like the entire AI industry is just one bad copyright outcome away from an existential crisis. And it was really interesting to talk to Dana about all of that. Okay, Dana Rao, Adobe's general counsel and chief trust officer. Here we go. Dana Rao, you're the general counsel and chief trust officer at Adobe.

**[0:05:20] Nilay Patel:** Welcome to Decoder.

**[0:05:21] Dana Rao:** Thank you very much. Excited to be here.

**[0:05:22] Nilay Patel:** There is a lot to talk about with the general counsel of Adobe today. There's all of the AI and copyright conversation that I love having. And then just as we were getting ready to speak this week, Adobe and Figma called off uh the deal to combine companies because of regulatory pressure, particularly from the EU. So I I do want to talk about that, but it's decoder, so we gotta start with the decoder stuff. People know Adobe really well.

**[0:05:49] Nilay Patel:** Almost anybody working i with computers in any way is aware of Adobe. What does the general counsel of Adobe do all day?

**[0:05:56] Dana Rao:** Well, we help the uh company navigate where the world is going, um, which is really it's the coolest job. Because Adobe's right there, as you mentioned, forty year old company, been there at every step of the um digital revolution. Whether it's desktop publishing or web video with Flash, or digital marketing with when we bought Omniture, Acrobat and electronic documents, image editing with Photoshop. Um, it's been amazing. And then, you know, last March, we launched our foundation model Adobe Firefly, you know, which is helps uh people do text to image generation.

**[0:06:30] Dana Rao:** So every step along the way, we're breaking new ground with new innovation, new technology. And on the legal side, that means you're you're thinking about problems that no one has thought about before, because the technology's doing things that no one's ever done before. It's great, so I love that part of my job. I actually have the second title of being a chief trust officer at Adobe. And and uh, we took that on a couple years ago when I took on the cybersecurity organization, so I have the the cybersecurity engineering organization in addition to legal and public policy.

**[0:07:02] Dana Rao:** And then together we think about us as helping Adobe establish that value of trust, um, in a digital world with that relationship with customers. It's a intangible world we live in. And the thing that the currency you have is the trust that people place in you. And that's how you build your products, and it's how you comply with the law. Do you understand the law? can you shape the law? Which is always the fun part of the job.

**[0:07:25] Dana Rao:** And so building all that together into that trust value is one of the reasons we've, uh, we've moved on and called that a a trust organization, which is which is also very cool.

**[0:07:34] Nilay Patel:** Let me ask you a just a very reductive question about that. Cybersecurity, cloud services. That comes along with Adobe really moving into being a a cloud company, right? The Adobe of 1015 years ago sells software that people run locally on PCs and Macs. The Adobe of today sells software that you can access in in real meaningful ways on the on the cloud. At the Code conference, we demoed Photoshop on the web for people for the first time.

**[0:08:01] Nilay Patel:** That's a big change, right? That Adobe now lives in the cloud. Has that meaningfully changed your view of, like, the cybersecurity organization, the trust organization?

**[0:08:10] Dana Rao:** yeah, absolutely. I mean, we had the, as you mentioned, the desktop era. And there was a lot of, as you may remember, issues with Flash, you know, on the security side, right?

**[0:08:21] Nilay Patel:** hey, you brought it up, not me.

**[0:08:23] Dana Rao:** Well, there were. I mean, that's hardly a secret. So all I was saying was, even in the desktop world, or as we were transitioning to the web, security was always paramount and understanding how to minimize security issues. Um, acrobat is a great example of a place where we dedicated security resources to making sure there's a sandbox essentially around Acrobat. So even if someone finds an exploitable vulnerability, there's really nothing they can do with it because of the sandbox.

**[0:08:49] Dana Rao:** So the way we architected Acrobat, and that's really had a dramatic decrease in the amount of um ability uh ability of people to exploit things, so that's been great. But as you say, we moved from that to now a almost an entirely cloud based services model, and we also use a lot more um public, you know, cloud services. So we had to think a lot about the public cloud configuration and how we work with Amazon, how we work with Azure, and and set up those services.

**[0:09:14] Dana Rao:** To ensure that that the data we're, um, providing is the right data and can't be exploited, so that's important. And then on within our own networks, you know, because we have employee data, we have customer data. Spending a lot more time there on endpoint detection and response and other technologies allow us to see what's going on in the network, see if something's happening and then stop it before it spreads. As you know, in the cybersecurity world, you there's no such thing as being immune to an attack.

**[0:09:38] Dana Rao:** Um, all you can do is, you know, do the best you can in terms of reasonable security measures to understand what's going on and stop the spread before it happens.

**[0:09:45] Nilay Patel:** Yeah, do you see those the two parts of your world? They they seem very, very connected to me in a way that they're not connected to other companies. But Adobe has a lot of customers, it puts a lot of data in a lot of places. You need to sign contracts with your customers and your vendors to say here's how the data's gonna be used, and then you need to do the work to actually protect the data.

**[0:10:03] Nilay Patel:** In other places, those those structures are are different and sometimes in tension, right? The things people want to sell, the contracts they want to sign are at the bleeding edge. And then the security organization might say no. In your organization, they're they're obviously together, they're under you. Do you feel that tension? How do you resolve it?

**[0:10:18] Dana Rao:** Yeah, we still have the tension in the sense that, you know, the security engineers have a certain perspective on how to develop and protect our products. And then, as you note, the um sales team and the commercial lawyers are out there in the day to day, trying to make sure we, uh, can sell our products and generate revenue. So there's always that tension. What's nice about it being under me is I'm an escalation point. And, uh, I was an electrical engineer undergrad, so I get to speak the lingo with the engineers, and obviously I'm a lawyer, so I get to speak the lingo with my legal team.

**[0:10:49] Dana Rao:** And I can bring some harmony together. But we have a fantastic chief security officer who's very practical and business minded, and he understands the balance between. You know what we can do and what we need to do in a very positive way, I would say a business focused way. So I feel good about the balance that gets struck even before it comes to me. Adobe's a company with integrity. I would say we have 30,000 people and our salespeople have just as much integrity as the engineers.

**[0:11:17] Dana Rao:** And so they're not typically the ones who are overselling. They have a long term value relationship with our customers and they don't want to sell them something that we can't actually deliver on. So I made a joke about the escalation point. Very rarely does anything actually have to come all the way up to me to to get resolved.

**[0:11:31] Nilay Patel:** we'll, we'll come to that. You're you're foreshadowing the the ultimate decoder question on decisions, but we'll come to that. 30,000 people at Adobe, how big is the legal team?

**[0:11:39] Dana Rao:** My whole org is 700, so it's about fifty fifty between legal slash public policy and then security, so security is about 350, and legal is probably about 325, depending on the day. Yeah,

**[0:11:53] Nilay Patel:** and I would not have expected Adobe in years past to need a giant IP group in its legal department, right? There's obviously you need to protect your software, you need to go get patents, all that stuff happens. But all this is now happening in a world of generative AI, and it feels like having a big IP practice, a copyright practice within your company is gonna become more and more important. Do you see something like that growing inside your division?

**[0:12:17] Dana Rao:** yeah. I think that's a good assessment that historically, intellectual property, it was always important to us in the sense that we wanted to protect our innovations. We've we had a record number of patents filed and issued last year, which is great. But we're never been a company that has tried to sue people on our intellectual property just because we think they're copying us. We've always believed that we're gonna win in the marketplace if we innovate, and that's gonna be the number one way we respond to competition is innovation.

**[0:12:46] Dana Rao:** If somebody is, uh, steals a trade secret or, or, you know, employee leaves their trade secret. It's very nice to have the copyrights, it's very nice to have the patents to stop that person from stealing, you know, our intellectual property. And that's typically how we think about intellectual property is stopping misappropriation as opposed to just out there infringement. It hasn't been something that Adobe's ever had to focus on. In the age of generative AI, it's been funny because, you know, we've had a copyright team, of course.

**[0:13:13] Dana Rao:** Um, it's been small. And, you know, in February, we were really thinking about fundamental copyright questions with, um, generative AI. And I and I suddenly said, You know what, copyright is a sexy legal career. Now.

**[0:13:28] Nilay Patel:** This is great.

**[0:13:30] Dana Rao:** I haven't been able to say that for a while, but it's, uh, yeah, I it lasted two years consider

**[0:13:33] Nilay Patel:** and I quit. I was like, this, no one's ever gonna care about this again. And here we are.

**[0:13:36] Dana Rao:** and here we are. These are they're so sought after, and we have one. Uh, J. Scott Evans is our director of copyright, so we're lucky to have him. Cause you really need somebody who understands technology and copyright, and that's rarer to find in the copyright field than in in other legal fields. Because the copyright typically been, as you know, focused on entertainment and and maybe the the really soft IP areas. So finding someone who can understand how generative AI works and also is an expert in copyright, they're very rare and and, uh, worth their weight in gold at this point.

**[0:14:06] Nilay Patel:** Yeah. So how is that team structured, the the legal team, 350 people? How is it organized?

**[0:14:10] Dana Rao:** Pretty classic, I would say. We have a employment legal team, we have a privacy team, we have a corporate team that does securities and M. A. We have a sales legal team, we have an international legal team, we have an intellectual property and litigation team, so that's combined into one team. They do both the IP and the litigation, and then we have a legal operations team. So we have a we have a pretty clean. I'm sure I'm gonna forget somebody.

**[0:14:34] Dana Rao:** Compliance, we have a chief compliance officer, of course, so important, uh, and lastly,

**[0:14:40] Nilay Patel:** somewhere in the EU, someone's ears perked of up.

**[0:14:43] Dana Rao:** course, she's a shareholder, she's amazing, she's been at Adobe 20 years. I mean, n let me name check her, so it's, I would say, classic, it's very most companies have. Yeah, every company has all of those functions. Sometimes people consolidate them under one person or or two people, but I have those mostly just reporting directly to me. I find that better for me as a style.

**[0:15:03] Nilay Patel:** Legal and cybersecurity, they're the two functions of a company that can say no, that maybe the most often they can say no. You can't do that, that's illegal, you can't do that, that'll create a security risk. You you can't do that. Margaret Vestager will call, call me up and yell at me. Um, how do you manage that? Do you report directly to the CEO? Do you get to sit in all the decisions? Where do you enter the chain in in both of those roles?

**[0:15:24] Dana Rao:** Well, first, I wanna make sure I can show you my mug, which I drink from every day. So it wasn't, it wasn't, uh, can you see this? Is it backwards?

**[0:15:31] Nilay Patel:** very good.

**[0:15:31] Dana Rao:** Yeah, so we have a slogan when I became general counsel. One of the things I wanted to make sure is that my legal team was seen as someone who is there to help the business find answers to problems. And as opposed to being the so called department of no, which is how a lot of people view legal. So we created a slogan it's what it's called, Yes starts here, which is, you know, our slogan in legal.

**[0:15:54] Dana Rao:** And then there's an asterisk and it says, because because we're a legal team, and it says, except when it's a definite no, and that's the balance, right? And so we're here, you know, we, we're here to help the company find ways to deliver great products, deliver value, make money. That's why we're here. We're here on the Adobe team, we're here to make that happen. And so if the way you want to do it isn't the right way under the law, we're not gonna just say you can.

**[0:16:20] Dana Rao:** We're gonna say, here's another way, right? What's another way to do it? And that's our job as in house legal. Find another way to help them achieve that goal. It's the client doesn't understand the law, so they're not gonna be able to brainstorm, but you can and understand that and understand that. However, there are times where you just say no, right? And that is also our job. And we're the only people, you know, in the company who have that sort of final no, as you say, where we can just say, look, that it goes against the spirit of the law, it goes against the letter of the law.

**[0:16:51] Dana Rao:** We can't do this, and that is definitely our job. And and I'm proud to be part of the our legal team because they really embrace that business focus, and I'd say that the business team really enjoys partnering with us, or at least I think they do

**[0:17:03] Nilay Patel:** yeah, all right, you have to give me an example now. What's something that you said no to?

**[0:17:12] Dana Rao:** without any details. Of course, cause I said, I said, I said no to this. But but um, yeah, when we? So I also manage the um anti piracy team, the fraud team that's in there, the engineering team that helps us, um, address piracy and fraud. We talk a lot about the way we can reach out to customers to allow them to know that they may be using pirated software. Because there's a lot, as you know, a lot of pirated Adobe software out there.

**[0:17:40] Dana Rao:** And a lot of people get it, get it on eBay and install it. And and it's unfortunate because that typically is old software. It's not up to date from a security perspective. It's, you know, virus ridden, but people are saying, Oh, it's cheap, I'm I'm installing it. So we want to be able to notify people and say, hey, you may be using a pirated software. You know, why don't you go log in Adobe dot com and get, you know, the Photoshop plan for ten a month?

**[0:18:03] Dana Rao:** And and you'll have the latest, greatest technology, and you won't have any viruses. So we want to be able to do that, but you have to be really thoughtful about the law everywhere in the world. Because that kind of communication direct to the customer in some places can be prohibited because they don't want you communicating that they don't. You don't have that direct relationship. So we had to spend a lot of time. I I think the com the business had the right spirit, right?

**[0:18:26] Dana Rao:** Let's go out there and communicate with people. They may be using pirated software, they may not even know, and they're exposing themselves to these security vulnerabilities, even though they have the right spirit. There are some really clear restrictions about how you can go out and communicate with people who you may not have a direct contractual relationship with. And so we had to say no to some of the ways they wanted to do that. So that is a clean, generic version of the, I'm like, what uh, of

**[0:18:52] Nilay Patel:** were the ways? the Like, how? Like, what like, kind of worms were you installing on people's computers there were no to find Adobe software?

**[0:18:57] Dana Rao:** worms, no worms. Everybody was trying to do the right thing. But to your earlier question, you know if it? I have, uh, Shantanu Ryan's our CEO, and so I always have the ability to talk to him about, you know, hey, we need to go, you know, sit in with the business and help them understand. Maybe the thing they're doing isn't the thing that we should be doing, or maybe there's another way. He's always open to that.

**[0:19:20] Dana Rao:** I would say that my job is very easy because he has the most integrity of almost any business person I've ever worked with. And which is great, cause it radiates out throughout the organization. So they know if things get escalated, Shantanu's always going to be on the side of we're gonna do the right thing. And so very few people even bother to escalate things up to Shantanu because they already know what the answer is going to be.

**[0:19:44] Dana Rao:** And that makes my life a lot easier, it makes my legal team's life a lot easier being able to partner with somebody who who cares so much about integrity.

**[0:19:51] Nilay Patel:** Yeah, let me ask about that in in kind of a broader way. Uh, you were an engineer, you were a lawyer, now you're a tech executive, you oversee the cybersecurity organization, you were at Microsoft, you were at Adobe. The industry has changed a lot, right? And the the classic view of the tech industry, the classic view towards the law has been. We're gonna push the boundaries and we're gonna ask for forgiveness. I'll use one example that we, uh, is very familiar to everyone.

**[0:20:14] Nilay Patel:** Google Books. We're gonna scan all the books, we're gonna get in trouble, and then we're gonna come to some settlement and then everyone's happy because Google Books exists. It worked, the the plan worked. YouTube, uh, picked up on Google and you you t YouTube worked in that exact way. We're gonna push the boundary of copyright law. Now that there's YouTube, everyone's happy and everyone's making money. That is different now. It it feels different, right? Like that move, especially from larger tech companies, maybe not going so well, maybe not as condoned, maybe less exciting, even in a way.

**[0:20:42] Nilay Patel:** Has that changed how you think about these decisions and how you think about evaluating the risks you can take?

**[0:20:47] Dana Rao:** I think that Adobe has a certain set of values as a company that are independent of the moment. And that's one of the benefits of having been around for 40 years and seeing all the changes you talk about. And we have we had two amazing founders, um, Chuck Geschke and John Warnock. John just passed away a couple months ago, but both legends in the valley, but both had this th i opportunity to know both of them, just really strong ethics.

**[0:21:16] Dana Rao:** So when I we think about, like, when we looked at Firefly or generative models and said, how are we gonna train it? You know, we could train it off the web, we could scrape the web and and build that model, or we could try to be more thoughtful about how we train that model. Given the potential copyright issues and the fact that we have creative customers who are concerned about people training on their content without their permission, for us, that's a compelling reason.

**[0:21:41] Dana Rao:** The the connection we have with our creative customers and the connection we have with our enterprise customers. To say, is there another way we can achieve this goal that respects these potential issues and still delivers the value to the customers? But we are an innovative company, and we're not going to be the a company that says, you know, we're gonna in going to ship something that nobody wants but is safe. We know that's the easiest path to irrelevance, and so that's never been a goal by itself.

**[0:22:10] Dana Rao:** Is to to just optimize for safety. We have to also make sure we're delivering product value, and that balance is really important. So the hard part is, can you do both? And that's what's fun about Adobe is we try to do both. We're up for the task of seeing if it's possible to both lead on innovation and do it the right way. And that's that's what's been fun.

**[0:22:34] Nilay Patel:** We're going to take a short break. When we come back, I asked Dana how he makes decisions and how he applied that framework to the Figma acquisition.

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**[0:25:12] Nilay Patel:** We're back and it's time to talk about decision making in Figma with Adobe's Dana Rao. All right, so here's the decoder question. You already foreshadowed it. You, you've been through a lot, the industry's changed, you've got some core values. You have a a very important role to play in the product process and the decision process of the company.

**[0:25:30] Dana Rao:** I'm so excited for this question now.

**[0:25:31] Nilay Patel:** I know this is a lot of hype. This is the whole brand.

**[0:25:34] Dana Rao:** is, it's so much higher.

**[0:25:36] Nilay Patel:** How do you make decisions? What's your framework to make decisions?

**[0:25:38] Dana Rao:** When I have, you know, important decisions that come to me, I have. Uh, someone was asking me the other day how I resist decision fatigue. Um, because what you do at the point where I'm at is you make a lot of decisions every day. Every meeting is basically a decision, right? Because that's that's why you're there, otherwise, people don't know why you're there. And, uh, I find it energizing because what I feel like I'm able to do is is move things along, getting to a result.

**[0:26:03] Dana Rao:** So I like the part of being able to help people understand all the factors and then let's move on. And so I have a a s a system I made up where I call it pre commit, commit, and uh, revisit. It's my decision making framework. The pre commit stage is I'm wide open, like I wanna hear everything from everybody, all the stakeholders, all the points of view. I want all the feedback. Maybe I have a thesis on what I think the right answer is, but I'm just listening and we're just gathering all that information.

**[0:26:36] Dana Rao:** Then we think about it and then we say, okay, after all of that, we're gonna go in this direction. Now, that direction may not make everybody happy, right? And par, and frankly, for sure, will not make everybody happy. Cause I'm picking a side, I'm deciding, and I think this deciding is important. That's the commit stage, though. And what's important about that is we're all in on whatever that was because we heard a lot of things, we thought about a lot of the factors, and we're all in.

**[0:27:04] Dana Rao:** I'm not interested in reopening that decision a month later, two months later, and someone saying, Well, I still think maybe we should go back. And are you sure? I'm like, No, we decided, we're all in, we've committed. Cause you need to move forward, right? You have to just move any direction, any direction is better than no direction. Even if it's the wrong direction, you're gonna learn something that this was the wrong decision. And then you can ba, you can say, you know, in the revisit stage, well, that didn't work out at all.

**[0:27:32] Dana Rao:** Let's go do something else, but the worst thing you can do is nothing. And so for me, the commit stage is really important. And the big company, uh, um, s. You can spend a lot of time in analysis, paralysis. You can just spend a lot of time just sitting there saying, well, well, I need to hear more, I need to hear more. And everyone has a vote, and they have a vote forever, and so that commit stage, really important.

**[0:27:53] Dana Rao:** But as long as you had a good pre commit stage and everyone felt like they had their opportunity to share their view, I find that's that commit stage goes better. And then the revisit stage is really important for me, and I don't do that quickly. So for for me, it's like a year later, two years later. How did it go? Right? Is this still the right decision? Did it work out? I I really believe in postmortems and reevaluating things.

**[0:28:16] Dana Rao:** We have so many priorities as a company, it's really important to let go of the ones that didn't work and not just keep doing them because of inertia. So having an active process where you go back and look at a decision you made and say, did that work out? And and it, and is it still good? Should we double down? should we reinvest? or should we say, forget it, that that's not going anywhere?

**[0:28:34] Nilay Patel:** All right, so obviously I'm gonna put this framework into practice against the news this week, which was 15 months ago. Adobe decides to buy Figma for 20 billion. There is a lengthy review process, both in Europe. There's a lot of rumblings from the United States Department of Justice. I would say, deal review on both sides of the Atlantic, proceeding in different ways, with different success rates, however, that's going. But this week, Adobe and Figma call off the deal.

**[0:29:02] Nilay Patel:** I say, after 15 months of review, we don't think we can go forward. The European Commission is is basically celebrating, saying we preserved competition. Walk me through it. Well, the d. Everyone knows that this review is coming. I had Dylan Field on Decoder right when the deal was announced. I said, this review's coming, he said. We know 15 months later, you obviously revisited and said it's not working out. How did you make that call?

**[0:29:23] Dana Rao:** so it's a actually a great example. I hadn't thought about it within my frameworks explicitly, but it's perfect, actually. We spent a lot of time, as you would imagine, before making the decision to go forward, thinking through the competition issues and what those would be. And understanding to an extent everyone understands the details of this. We had a product called Adobe XD that was a product design tool that we had started five to seven years ago.

**[0:29:47] Dana Rao:** Obviously, we were well aware of that, and Figma was the leader in that space. And and we had tried and failed with our our tool. It was only making $15 million of standalone revenue. We hadn't invested it actually at the executive team level. I didn't even know it was still alive at the time. I like, we don't even talk about it. It was just sort of dead to us, but it was on maintenance mode and we were just serving out some enterprise customers who had already contracted for it.

**[0:30:13] Dana Rao:** So we just left it alone. By the end of it, I think today there's less than five, five or less people working on it just to get rid of bugs and address security issues. So we looked at that and we really pressure tested, you know, is this something that we felt like could stop us? Being like, No, this, this product doesn't exist, it has no share and Figma's the leader and we're out and it's been dead.

**[0:30:35] Dana Rao:** So we felt good about being able to move into the interactive product design space because we had exited the product design space with a failed XD. And we think that's appropriate for businesses to try organically, fail organically, and then say, well, let me look at it inorganically. And we think that's a healthy way for businesses to conduct their business. So that was the pre commit stage, really pressure testing that whole question. And and then obviously we decided to go forward, right, based on those facts.

**[0:31:06] Dana Rao:** Um, the last, you know, whatever it's been since we started, uh, now since September twenty two, so 14 months or so. We've had a lot of interaction with the regulators, and they've been very focused on the newer doctrines of antitrust law that say that future competition is a critical part of the antitrust analysis. So that's the potential that we could go back into product design, even though we had exited it, and then the potential that Figma could go into our space.

**[0:31:39] Dana Rao:** And that's what they were really focused on in in the regulatory process. So that's what we've been talking about for the last 18 months is how do we prove, you know, what's the evidence we can show? And we have a lot of great evidence. I, I would actually argue our evidence got stronger over the over the last year, our economic evidence. So typically, antitrust cases are are defined by economics, and they're defined by customers, right? And in our case, when you look at the economic data, you don't see any overlap between Figma and Adobe's customers, which was powerful.

**[0:32:14] Dana Rao:** We saw positive customer sentiment, really, no competitor or customer complaints about the deal. That used to also be a key fact, so we felt good about the basic facts. But this future competition argument, that was something that they continued to focus on. And it is this is all public, right? Because they published their statement of objections, they published their provisional findings, the s the CMA, the UK authority and the EC, both of them published these findings.

**[0:32:43] Dana Rao:** So I'm not nothing I've said so far is is secret. Um, they're really focused on those two things. And so a as a business, we got together, um, with Figma and just said, looking at the road ahead and the timing and the tenor of the conversations we're having, we're like, this is probably a good time to to stop.

**[0:33:01] Nilay Patel:** and you did that before there was actually an enforcement action, right? You saw an enforcement action coming and you said, Look, we're gonna call this off because we don't want to go through that fight.

**[0:33:12] Dana Rao:** Correct, right?

**[0:33:13] Nilay Patel:** So I just I just want to compare and contrast that to say Microsoft and Activision Blizzard. Microsoft announces a huge deal to buy Activision. There's an enforcement action. They fight vigorously, they come to some agreements and concessions, they they basically fight it through. You decided not to do that. Why? Y, you just thought you were gonna lose? What was the reason to not have the whole fight?

**[0:33:36] Dana Rao:** So we have been fighting, I would like to say that my team of lawyers but you didn't have been get to that official, doing nothing right? We're we're doing but, the, you know, uh, yeah, the way for this audience, I'll the

**[0:33:45] Nilay Patel:** call it a tri. It's not a trial, but you know what I mean, that the official proceeding.

**[0:33:49] Dana Rao:** I don't know how many antitrust geeks you have in your audience, but It's the way that

**[0:33:53] Nilay Patel:** every day it grows. This was it's copyright antitrust. You would not expect it, but every day it's growing.

**[0:33:58] Dana Rao:** the way that works in Europe, um, is quite different than the United States. So the United States, the Department of Justice, who's investigating the case for us, um, they have their own timeline. They bring a case when they want. There's no statutory requirement that they do anything by any time, right? In Europe, it's quite different in Europe. As soon as you go into what they refer to as phase two, so phase one is a investigatory phase, and then phase two is more of a analytical phase.

**[0:34:23] Dana Rao:** So as soon as you go into phase two, which we went into in July, June and July, with both the UK and the European Commission. And they have a schedule that's prescribed by statute by when they're going to come through and have a decision. And in our case, the decisions were February fifth, February twenty fifth. Um, that's when they would be officially deciding. And all along the way, there's set of hearings you would have, and then they would give you findings, and then you would combat the findings, and then they would give you more findings.

**[0:34:51] Dana Rao:** But they're all public, right? They tell you exactly where they're thinking, they tell you what their concerns are. It's I see from that perspective, I appreciate the transparency because you know exactly where their s where they are, and and you and you know what's working, what's not working. In terms of the arguments you're making, and you get to make your arguments. And so we know fairly well what the arguments they are, that that they're making, and we understand what evidence we've been providing.

**[0:35:17] Dana Rao:** And we've seen what has been persuasive and what has not been persuasive. And then we get to sit there and say, well, do we think that it's worth just to continue to fight this? Because we could keep going, we could keep going forever on this. And both of us looked at it and said, it's not worth it. Um, we're both very successful companies. Um, we both have extremely exciting opportunities ahead of us. That's why we wanted to acquire Figma.

**[0:35:44] Dana Rao:** We're very excited about them and their opportunity, but they have a lot of opportunity for themselves. We obviously have um Adobe Express and Adobe Firefly and our digital marketing business and all those other opportunities in front of us. And so you just ask the question, you know, where should we be spending our time, given what we see as a as a fairly consistent position being taken by the regulators on the their version of the facts of the case?

**[0:36:13] Nilay Patel:** yeah, let me just make one more comparison to Microsoft, and then I really just want to talk about copyright law for the rest of the conversation. But Microsoft really wanted Activision. Like at one point, it was almost confounding how badly they wanted this deal to close, even as even as it seemed like, oh, the regulators around the world really wanted it to stop, right? And they had a lawsuit in this country, they had, you know, the UK CMA and the EU do not always get along.

**[0:36:37] Nilay Patel:** I'm told that there was some sort of Brexit situation there. They're fighting this fight on multiple fronts, you know, a proper legal proceeding here. And then they they're making tons of concessions in Europe about game streaming and who can stream games and where the titles will go. Did you come to a point where you thought, okay, these are the concessions we would make, and these are the concessions we won't? Did you ever consider making those concessions?

**[0:36:59] Nilay Patel:** Did you just walk away before that?

**[0:37:02] Dana Rao:** December 18th, um, the CMA published what we refer to as a remedies notice, and that's would be our response to them saying, Hey, here's what we would do from a remedies perspective, and so that's public again. And we said, based on the way they were constructing this future competition theory, like, what would we do and what would they do? We didn't really see any kind of remedy that would address it the way they've constructed the argument.

**[0:37:31] Dana Rao:** There's not a remedy that would make sense to address the issues that they're raising because they're raising future issues, future competition. So the only way to solve a future competition issue that someone might do something is to not do the deal. And that's essentially what they were telling us. So it did not appear in our case that remedies was, uh, an option that they were considering for a way to resolve our situation. And and we saw that, and and then, and we continue to believe that the merits of the case, as for all the things I had said before, we think the facts were are on our side.

**[0:38:08] Dana Rao:** But again, we stared ahead to the next three months. And I think one of the most important things maybe we didn't succeed in talking to the government about, the government's about. But I know, you know, is focus is really important at a company. There's only so many things you can do well. If you try to do everything, you'll fail at everything. And and we say that because in W the argument that the government was making was essentially saying to us and Figma, you guys can do everything.

**[0:38:37] Dana Rao:** So we assume you will do everything, and therefore you're Adobe, you're gonna go do this, and Figma, we believe you can do that. And you know, D, you know, whatever, Figma's gonna build Photoshop or whatever, they have 800, 800 people, but then they're gonna somehow magically do everything right. We have tried to explain to them that the the focus of the company is so important, and and Figma's are very clear about what their focus is. It's Figma design and it's Fig jam, which is their whiteboarding tool.

**[0:39:00] Dana Rao:** And then they wanna build a developer, uh, um, extension that allows, you know, you to generate code out of your product design. So very focused on what their path forward is, and we have our own path, right? Adobe Express and um Adobe Firefly and um, and and dx, this this new product we're calling, uh, Adobe generative studio. That's where we wanna spend our time. And so every moment where we are choosing what we're gonna, we're going to do, we're gonna spend our time on the key priorities we have.

**[0:39:29] Dana Rao:** Like for me today, today, I said to myself, I really wanna make sure people understand AI and copyright, like I think that's hopeful. So I decided to spend an hour with you to talk about AI and copyright.

**[0:39:40] Nilay Patel:** you're, yeah, I can tell you're imposing a hard pivot on this conversation, right now. You're getting the flag from your own lawyer in the corner. Uh, let me just ask one more, cause this is, I think, really important and cuts to the heart of it. Uh, Dylan, uh, field CEO of Figma, gave an interview yesterday, he said. The enforcement climate for antitrust is different now than it was a a year or so ago when you launched the deal.

**[0:40:00] Nilay Patel:** That is true, right? And we've seen, uh, you know, Lina Khan and the FTC in this country really go after some things, not as successfully as the Europeans. We've seen the Europeans go after some things, extract some concessions. Literally, in the last week, Epic won, uh, the antitrust case against Google, Google settled the case against, uh, Google settled its case with the state AGs. There is just a lot more enforcement activity happening around the world in many different ways.

**[0:40:24] Nilay Patel:** Has that changed your perception of how you should do deals, how you should think about deals, how you should evaluate them in that pre commit stage?

**[0:40:32] Dana Rao:** I think that you have to, um, understand that the um regulators are going to be aggressive. They are interested um in tech, that they don't mind bringing a case and losing it. They've posted that publicly. That's not a issue for them. And so when you think about the if you're doing an M A, if you're thinking about the acquisitions you're going to do, you have to be really thoughtful about the likelihood that there will be an enforcement action.

**[0:41:02] Dana Rao:** And also you have to really think through this future competition question that they're using as a new doctrine in antitrust law. It hasn't been the law in the United States, and it's still not the law in the United States. But you have to think about it as you go forward, because you're gonna be in it for, as you saw for us, up to 18 months, maybe longer, right? I mean, I I believe in Microsoft Activision, the FTC's appealing their loss and so that's still going on.

**[0:41:29] Dana Rao:** So you really have to think about your decision. And I would say the government should also be thinking about the consequence of that type of enforcement. Because M. A. s, I think, and I think most of us think, is good for the economy, it's good for innovation, it's good for jobs. You know, Adobe's built itself on organic innovation and inorganic innovation. We've done, you know, we've done both, and we've grown to be successful, and we have 30,000 employees.

**[0:41:55] Dana Rao:** And they're they have salaries and benefits, and they contribute to the world, and we've have technology that lets millions of people build careers off the technology that we provide. And I would say Adobe's been net good to the world and the economy. And we would not be where we are without the ability to do inorganic acquisitions. And so we really make need to make sure as governments that we're having the ability to strike the balance between ensuring competition is preserved and innovation is preserved through antitrust laws and ensuring that companies can continue to innovate both organically and inorganically.

**[0:42:36] Nilay Patel:** I'm gonna give Dana his pivot, but first, another quick break. When we're back, Dana and I get into the weeds on how generative AI is upending copyright law.

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**[0:44:41] Nilay Patel:** We're back with a complex question for Adobe's Dana Rao. What is generative AI doing to copyright law? Antitrust law? Should we protect future competition or not? should we allow more M A or not? should? How much competition should there be in a in a given economy? At least the parameters of those questions are known, right? Like, th there's a body of antitrust law and it waxes and wanes, and maybe some regulators are more aggressive than others, but it it's like a set of known legal principles.

**[0:45:13] Nilay Patel:** Where copyright law is today with generative AI feels like totally novel problems with no settled answers, and almost in a zero sum way, right? If if we allow LLMs to go wild with training data, we will absolutely reduce the market for human generated works. Like, that's just the way it's gonna go. Adobe has Firefly, the foundation model. Your customers are also very loud creatives. We're very opinionated about this stuff. How are you thinking about copyright law in this way?

**[0:45:44] Nilay Patel:** You said earlier, you you realized you had to start thinking about it differently, not just from a protecting IP perspective, but as foundational questions about the law. Where have you arrived?

**[0:45:53] Dana Rao:** now. We think that the law itself will evolve, um, as generative AI evolves, and so we understand that. And there's a lot of litigation going on, as you know, uh, class action lawsuits are being brought against the LLM providers for copyright issues. Saying, you know, you can't train the off the off the web. So we see all of that, and we know the law's going to be different in Europe, and it's gonna be different in Japan, it's gonna be different in China.

**[0:46:23] Dana Rao:** So it's not even going to be one law that you're going to be able to rely on to say, um, I have a, you know, a green light to train my model any way I want to. So, understanding all of that and knowing that our creators themselves have these concerns, we decided to train Firefly on our own Adobe Stock content and other licensed work from the rights holders to build our model. That was a computer science challenge.

**[0:46:50] Dana Rao:** Because for AI to work, you need data, and for AI to work well, you need a lot of data. So the more data you have, the more accurate your AI will be, and the more, um, more it will have. All the different kinds of styles you want, whether it be cinematic or natural, or graphic or illustrative. So you, if you're doing text to image, so you, you need a variety of data in addition, and the more data you have, the less bias your AI will be.

**[0:47:23] Dana Rao:** So the breadth of the data will help reduce the bias. Yeah, but a smaller sample set will naturally have more bias because it's trained and learned from smaller things. So you need data, you need access to data, and that's the tension. So we had we had to go to our AI research team and say, can we build a competitive model without going to the web? That was the challenge. And so we have, you know, decades of image science expertise, plus decades of AI expertise.

**[0:47:52] Dana Rao:** And they worked really hard to understand how to construct the model. Uh, Adobe Firefly that could be competitive with all the people out there who are just, you know, had access to more data than we did, cause they were just training off the web. And we feel really good about where our 1st model was, which we launched in March, but we were even more excited about the 2nd version of the model, which we launched at Adobe Max.

**[0:48:13] Dana Rao:** Um, a month or so ago, and we feel that one is better than our competitors and yet still adheres to those copyright principles. Now, the good news about the choice we made on copyright is that it respects our creative customers who are concerned about this, and enterprise customers. We're very excited to know that they're going to be able to use an image generative model that res that doesn't have IP issues, doesn't have brand issues, isn't trained on unsafe content.

**[0:48:42] Dana Rao:** Because all of that has been either not in the database at all in the beginning because of the way we trained it, or we can use content moderation to address it before it even gets into Firefly. So enterprises have been very interested in using the Adobe Firefly version of text to image generation because of that choice we made. So it's it's kind of cool to be able to do what we think is the right thing and also do the right thing for the bottom line.

**[0:49:10] Nilay Patel:** In June, Adobe offered to cover the legal bills of anyone who gets sued for copyright infringement if they use Firefly. I'm assuming a question of that amount of liability comes to your desk. When you looked at that, do you say, well, look, I know where this was trained, it's fine, you can do it, or is that more? I think the risk is manageable.

**[0:49:28] Dana Rao:** You know, what was cool about this whole process was it's so important to the company. This is why I I talk about a lot about executive focus. We had a weekly meeting with our legal team that I was in from February through probably a month ago, where it was me, the copyright lawyer, the product lawyer, the sales lawyer, the privacy lawyer. All of us met every week because we were just trying to figure out the law was going to be and how to navigate it.

**[0:49:53] Dana Rao:** And what are we going to do about? And we had our AI ethics person there. What are we going to do about training? How are we going to de deal with bias? What are we going to do about indemnification? So all of these issues came up naturally. Because once we realized we were training it this way, then the next question was, well, when we go to enterprises, what are we going to protect? And are we going to stand behind it?

**[0:50:11] Dana Rao:** And the answer for us was, of course, we're going to stand behind it. We know how it was trained, so we're willing to give an indemnification. Um, what's what's good about our indemnification is it's very low risk. You're going to get sued for an IP issue because of how we trained it, so it's good for us, but it's also good for the customers. Because if you get an indemnification from someone who has a model that still has IP issues, you may be able to get someone to indemnify you, and they will, but you're still going to get sued.

**[0:50:41] Dana Rao:** And that's not, that's not fun, right? And so it's still a a competitive advantage, we believe, to have trained it this way. Um, and then being able to offer it to enterprises with the full indemnification that you mentioned. Because not only do they feel good that we're standing behind it, but they also know because of the way we trained it, there's less likely to be a risk.

**[0:50:59] Nilay Patel:** yeah, there's something in here that I I'm s I'm struggling to articulate. Hope, hopefully, you can help me out. You're out in the market, right? You're indemnifying customers, you're selling the products every week. A new Firefly based feature ships in Lightroom or Photoshop. The downstream of the law is happening at the product level. And then I look back and I say, Well, there's just all of this falls apart if one fair use lawsuit goes wrong, like stability loses to Getty.

**[0:51:28] Nilay Patel:** And then everyone has to reevaluate everything they're doing. The copyright office is evaluating whether AI work should be copyrighted at all. You have testified before Congress that you think it should. We're we're all the way at the base level of what should get copyright protection while you are out in market selling AI products. How do you think that resolves?

**[0:51:50] Dana Rao:** yeah, I think it's there. I think there's a couple of things that are are being litigated here that we should unpack. One is, can you? What can you train on? And then can you get an a copyright on the output? So the input and the output are are separate questions. but but And I think both

**[0:52:04] Nilay Patel:** but you understand, like, what, what I'm saying, I can't quite articulate it. That's the whole thing. It's like,

**[0:52:08] Dana Rao:** no, no, I agree.

**[0:52:08] Nilay Patel:** what goes in and what goes out, So exactly so both completely they're funda up in the air.

**[0:52:11] Dana Rao:** fundamental questions. Uh, absolutely. And then when you look at again, as I was mentioning, around the world, you're gonna get different answers, right? You may win in the United States, but you may lose in Europe. And then what does that mean, right? And the EU AI Act not passed, but was was, uh, passed in in the first stage. There's more details to come. But even in there, they said that you have to obey the EU copyright directive.

**[0:52:32] Dana Rao:** And it's not totally clear what that means for AI, but it could easily mean that you're going to have to obey the copyright law and not train off the web in Europe. But it could be easily an interpretation. So my only point is getting getting winning a fair use case in the United States may not even help you somewhere else. So the good news about what we did is so we look at the fair use cases and we say we definitely see the fair use argument on a technical level.

**[0:52:57] Dana Rao:** Like we understand the science of AI, we understand what you're copying, what you're not copying, and understand the transformative use that would happen have to happen. You're not really taking an image and you're not really moving it to the output, you're not. The output of the model is not really a copy of the anything it was trained on. If it is, that was a bug, it's not supposed to be. It's supposed to be creating new work, and it's just learning from a computer science perspective, data about the images, not the images themselves.

**[0:53:23] Dana Rao:** It doesn't even understand what the images are, and you know that because, um, as an example, it always gets text wrong, generative AI always gets text wrong, cause it has no idea it's words. There's no actual cognitive understanding in these generated models, they're not intelligent. So it thinks these w these s words are just symbols. So always, you know, you're always gonna get the misspelling issue. So these things that are coming out are not really the copy.

**[0:53:46] Dana Rao:** So we see the fair use argument, and we definitely think that one to two years from now, or three years from now, if it goes, people appealing things to the Supreme Court. You could see fair use come out and say, Hey, you are allowed to scrape it, that's possible. And wait, then you may look

**[0:53:59] Nilay Patel:** so can I? over Can I just offer you and the the I? I hear the pushback on the fair use argument from other folks all the time. There's four factors, you know, there's amount, there's the purpose of the use, and then the last one is effect on the market for the original works. And in this case, with generative AI, it feels like you're gonna destroy the market for the original works, you're gonna destroy the market for human creators.

**[0:54:20] Nilay Patel:** And no one knows how that argument is gonna go inside the classic fair use analysis.

**[0:54:25] Dana Rao:** I, we totally agree with that as as a danger, and that's why we wanna make sure we have ways to establish rights that are not maybe even copyright rights for creators so they can protect themselves from the economic loss AI can bring. Before I get to that, I think there are four factors. We don't know how it's going to turn out. The Warhol case clearly showed the Supreme Court is interested in the economic factor as part of the fair use analysis, but there is still a th- a threshold question of what got copied and did it get copied?

**[0:54:55] Dana Rao:** You have to have a copy for copyright law. So I can see both sides of this, and I'm just saying you could easily see the fair use cases going the way of the AI models just because of the science. But then you could see kind of a judge looking at this thing, kind of a and saying from a is this the right thing to do perspective, and that's what fair use is. It's an equity-based analysis in saying, Hey, you know, we're gonna try to correct a harm here, and we're gonna expand fair use to cover it.

**[0:55:19] Dana Rao:** It's possible. Go either way. The nice thing about what Adobe did is we said we're sidestepping the whole copyright issue by training on licensed works. And no matter what happens in those class action lawsuits, our model is fine. Like, we don't have any concerns. This is one of the reasons we chose it because we wanted to have the stability in our product. We're not going to have to rip Firefly out because of some court case. And that that is important to us.

**[0:55:41] Dana Rao:** That was a choice we made back in March. Again, harder to do it that way from a science perspective, but our engineers are up to the task, and we feel like they pulled it off beautifully. So that's important. On the second part of your question on the output of AI, is it copyrightable, right? Our position has been, when we stare at this, we don't think a generative AI model, uh, typing in a prompt and having generative AI create the image, we don't think that output is copyrightable by itself.

**[0:56:07] Dana Rao:** Because we think that the, um, last step of expression is being done by the AI, not you. You're typing in your prompt, you're like, you know, pink bear riding a bicycle. The AI is choosing in the first instance, what kind of bear, the shade of pink, all the things that are supposed to be the expression that the artist is supposed to have in order to get a copyright. So we think that just typing in a prompt is probably not going to create a copyrightable expression.

**[0:56:33] Dana Rao:** It is possible, you know, in the future, you can create a very, very detailed prompt, and they may even look at the prompt and say, Is that copyrightable? Because I put so many words in it. And then I, I, you know, controlled the output so much that the thing that came out is almost exactly what I envisioned in my mind. Then and then you I'm not sure can copyright that

**[0:56:50] Nilay Patel:** the the prompt engineering side of it.

**[0:56:52] Dana Rao:** right, right, and maybe the output. I I don't think we're there yet. I'm not even sure that holds up. What I do say is that once you get your output, you can still get a copyright by putting it in to Photoshop and adding your own expression or whatever your tool is, right? But we have one, and, uh, add your own expression, and now it's your work, right? And and that's that, I think, is how you can still take comfort that you can get a copyright in a in a work that is based on generative AI.

**[0:57:19] Dana Rao:** You still have to add something to it on top, and then and most of us will, right? If you're a creative professional, you're never satisfied with what comes out of one of these generative AI, um, models because it's not exactly what you wanted, right? You're always gonna make it whatever your vision is, and it's the f- it's we we refer to. It's the first step in the creative process, and all the other steps are going to be copyrightable.

**[0:57:40] Dana Rao:** So we feel we feel like that piece could get resolved just by, you know, the people using the technology the way they would normally use the technology.

**[0:57:48] Nilay Patel:** yeah. The problem is that generative AI is not limited to use by creative professionals who know how to use Photoshop, right? The it democratizes creation in a massive way, and a lot of people aren't gonna take a second expressive step to make sure that it is co- They're gonna fire off tons and tons of content, believe that it's theirs cause they made it, and then, I don't know, file DMCA requests against whatever platform. Like, that's like the real danger here, right, is the generative AI models can just flood every distribution pipe that exists with garbage, and we have no way of discerning.

**[0:58:22] Nilay Patel:** It is, I know there's stuff Adobe does, like the Content Authenticity Initiative, which I wanna talk about. There's these metadata ideas, but just in the the base step, like, where do the copyrights come in? Where do they go? What is allowed? What is not allowed? Do you have a do you have, like, a position there that at least gives you clarity as you make all these decisions?

**[0:58:40] Dana Rao:** like I said, I think that we do not believe just typing in a prompt is going to create a copyright. It's first of all, right now, the statute requires human expression anyway, and so that's that's going to be a problem for anyone in the United States who wants to to get a copyright on a AI generated work. The one thing I want to come back to that we talked about the economic harm, um, so the place that we see, so so people just generating things off the model, I think they're not copyrightable, and it is what it is.

**[0:59:07] Dana Rao:** I think that the where we worry about for on the creative side is this idea of style, and so we really feel like there's this potential. And we've actually had artists already come to us and and say this is happening, where people will say, I'm gonna create a a a painting in the style of Niele, based on all the work that you've done that I model was trained on. And now I can create something that looks just like something you painted digitally, and I can go sell it.

**[0:59:34] Dana Rao:** People will say, great, either spend 10,000 for something Niele creates, or I can spend it for, uh, can go buy something that looks just like him for a buck for a buck, right? That's the economic harm that we really see as an issue. There's no such thing as style protection in copyright law right now, like, you can't protect that. Y- there's, that's not a concept. So we've, uh, we've introduced in the same set of testimony you referred to earlier, this idea of a federal anti-impersonation right.

**[1:00:01] Dana Rao:** And the idea of that is it would give artists a right to enforce against people who are intentionally impersonating their work for commercial gain with the typical fair use factors. A, uh, um, giving exceptions. But the goal there is to say, hey, if someone is basically passing off themselves as having created your work cause this, it's in the same style, it's an impersonation of you, um, you should have a right, like copyright. You should be able to get statutory damages.

**[1:00:26] Dana Rao:** You should be able to go off, go after those people and and remediate that economic harm. And so that act that s we wrote a draft bill, we gave it to the Senate Judiciary Committee. They're reviewing it. You know, we're talking to people about the the value of style protection. We think again, I think where we sit here at Adobe, is we try to see how, what we think the problems are going to be.

**[1:00:48] Dana Rao:** That's we think that's going to be a problem. We think that people are going to lose, um, some of their economic livelihood because style appropriation, and we think Congress should do something about that, right? They is that should address rooted in copyright it.

**[1:01:01] Nilay Patel:** in your mind, or is that rooted in, like, trademark or another?

**[1:01:04] Dana Rao:** It's not like anything, but it's closest to a, I mean, it's closest to a right of publicity, probably closer, or or trade dress maybe, and then, of course, copyright. So I would say it's it's some version of those three things. But when we sat around again in March and we were thinking about the consequences of generative AI and and text to image, we said we're probably gonna need a new right here, um, to protect people.

**[1:01:30] Dana Rao:** And so that's when we said, let's let's get out after it. It's sort of like the same way you mentioned the content authenticity initiative, same way we thought about this four years ago on when we saw where AI was going in terms of being able to generate deepfakes. We said we're going to need to do something about addressing that problem, and let's get together and figure out a solution for it. And content authenticity, the answer was a technological solution, but for this style issue, we think that's probably a legislative solution.

**[1:01:56] Dana Rao:** And so we we really feel like, as a community, we need to think about the consequences of the technology we're bringing to market and then address them in a proactive way that helps everybody and still ship the world's greatest technology.

**[1:02:09] Nilay Patel:** e- the the shipping, the technology, it seems like everyone understands how to do that, right? It's like, should we? is major, the should we? is the major question in the AI world. Let me ask you Photoshop is like a great playground for hypotheticals when it comes to this. I take a photo of Donald Trump and I say, put him on an elephant using generative AI, and I'm picking elephant cause that's a symbol of the Republican Party.

**[1:02:29] Nilay Patel:** And I say, take a photo of Joe Biden, I say, put him on a donkey, symbol of Democratic Party. And I c- create a composite of these two characters using Photoshop, does Adobe want that to happen? Do you think that's okay? And that's like, obviously, a silly example. You can easily imagine vastly more destructive examples.

**[1:02:47] Dana Rao:** the way we look at all of the generative AI tools, and almost every technological tool, is that you want people to be able to do whatever their vision is, their creativity is. 99% of the users of Photoshop are making art or creative expression, and their marketing materials, advertising campaigns, whatever it is, right? They're just out there expressing themselves, and you want to encourage that, and you want to let people do the things they need to do.

**[1:03:12] Dana Rao:** Um, if someone's out there misusing a tool to create harm, your example may not be harm, maybe parody or satire or something, but not harm. But if someone is actually trying to create harm, like there was a, you know, image of of Zelenskyy saying, you know, lay down your arms, right? Or deep fake of him, right, actually do harm. Then the people, of course, should be who misuse a tool should be held accountable, no question, for causing harm, just like any other bad actor who's misusing something to cause harm.

**[1:03:43] Dana Rao:** So I always think that's important to remember, because most people are using this tool for good. There's somebody out there that says, Ah, I can see the potential of this and I can use it for bad. You should address the person who's misusing it, not address everybody who's using it for good. However, what we th- what we said was the real problem when you asked what Adobe wants is we said. Because people are going to see how the ability to access all these generative AI tools and do amazing things and create realistic but fake images, it's going to be easier, right, for bad actors to create these deepfakes and deceive people.

**[1:04:16] Dana Rao:** And then you've again, looking ahead, you fast forward, well, maybe even to today, but four years ago when we were thinking about this, we said, well, now people can easily be deceived by these fake images, fake video, fake audio. And that could have real serious consequences for their livelihoods if it's just personal to you, or for the world if it's, like, something about the global environment. And so we said, well, what can we do about that?

**[1:04:42] Dana Rao:** Can you detect deepfakes? Is there a way just to say, Hey, I'm gonna create an AI fake detector, and every time you see an image, it's gonna say, this is a deepfake, don't trust it, right? And so we again put our AI image scientists they love me at Adobe, I'm always giving them homework assignments and, uh, said, Hey, can you do this? And the answer came back, it's like, probably like 60% accuracy, so not consumer grade.

**[1:05:04] Dana Rao:** It's always going to be very difficult to to be able to detect something that's a deepfake, and that technology is always evolving. And so we said, all right. So given in a world where you could possibly have things that look real but are not, what can we do to help? And we said, let's make sure people who have something important to say, news or important other stories, that they have a way to prove what's true. Because once everybody realizes that everything can be m faked, uh, these digital images can be manipulated or edited in a way to deceive them, they're not gonna believe anything anymore, right?

**[1:05:42] Dana Rao:** It's the doubt that is more dangerous than the deepfake. And you see that today when, you know, you're looking at, you know, the Israel Hamas thing, and you're like, Did this happen? Did it not happen? Is it a real image? Is it not a real image? Because you know everything can be manipulated, so you don't believe anything you see and hear. And that's very dangerous for a democracy or society because we have to be able to come together, talk about the facts.

**[1:06:05] Dana Rao:** We can fight about the policy, we have to be able to talk about the facts, but for just fighting about whether the facts even happened, we're not, we're not gonna get anywhere. So the technology of the Content Authenticity Initiative, which we we and a few others founded of four years ago, it allows you to s assign metadata to images. It's like a nutrition label, and it gets associated with the images, and it goes with the image wherever the image goes.

**[1:06:28] Dana Rao:** And, uh, a user, and it's the public who gets to decide, can look in an image and can see the provenance and then say, Oh, okay, I believe it. This person went through the bother of proving what happened, so you can capture information like who, you know, who took the picture, when it was taken, where it was taken. We have, um, over two zero members in this initiative right now. We have companies like Sony and Leica, both of whom announced recently they're shipping cameras with this technology called Content Credentials in the camera.

**[1:06:57] Dana Rao:** Leica is already shipping that camera, it's in the stores. And that means you can take a picture, turn on Content Credentials, and when you take that picture, it has that metadata secured to the image right there. Move to Photoshop, which also has Content Credentials, make your edits, tracks the edits that were made, ends up getting published to the Wall Street Journal, who's also a member of of this standard. And then on their website, you can see it, you can see the icon, you can click on it and say, Oh, I know what happened.

**[1:07:22] Dana Rao:** Biden did meet Zelensky, I believe it, cause they proved it. And now we have a way for people to prove it's true in a world where everything can be fake.

**[1:07:30] Nilay Patel:** So you have an amazing quote about the Content Authenticity Initiative, uh, about the image of the the Pope in a puffer jacket. You said the Pope jacket was a catalyzing event. People saw this, they realized the problem is real, they started joining the CAI. It seems like other standards, we love covering standards here at the Verge. They get bogged down. There's politics. How's the CAI going? Is it the Pope really bring everyone together?

**[1:07:52] Dana Rao:** It's going really well. We we, I think we've set a records we, uh, we had a symposium last week at Stanford, where we brought in all the members of the organization and the standard together. And, you know, the first time we did this four years ago, there was fifty nine people. This time, there was 180 people. They're representing all these thousands of organizations. The standard organization that we formed to build this technology is called the C2PA.

**[1:08:17] Dana Rao:** After just a year, we had the 1.0 version of that technical specification, and we're already up to 1.4 in just four years. And that's, you know, describing how to build this provenance technology for, um, images, video and audio, and how you use watermarking. It has all the technical specifications that anyone can go now and implement in their own products and services. And so it's an open standard, it's free to use Adobe doesn't make any money off of any of this technology, by the way.

**[1:08:48] Dana Rao:** We're just helping lead the coalition of people who are coming together. So I don't know of another standards organization that has been more successful. And that's because people are there, and that's what's so exciting at the symposium last week. People are there because they want to make a difference. All these people, they have day jobs, and but they're, they're in it. I mean, there there's arms in there and Qualcomm's in there. Qualcomm just announced that Snapdragon is going to be C2PA compliant.

**[1:09:13] Dana Rao:** So that's an amazing step forward. Uh, we have all the media companies, as I mentioned, you know, the New York Times and Washington Post and AP and Reuters, and and it's international organizations are doing it. Obviously, people like Microsoft and Getty. So so just a breadth of of kinds of companies who are all come together and said, Hey, we want to work together to address the negative implications of the deep fake creation ability of generative AI, because we all want to live in this society and we need it to work.

**[1:09:48] Nilay Patel:** So let me ask a really hard question there. I love the AI denoise feature of Lightroom. I think it's the best. I'm also like the world's leading practitioner of what is a photo hand wringing, because I think the definition of a photo is being stretched by smartphone cameras in really insane ways. To the point where that there's a Huawei phone that now just has a generative AI tool built into it. And after it trains on a bunch of your own photos, you can just generate yourself on the moon, and it the the camera's like, Here's a photo.

**[1:10:17] Nilay Patel:** So the the boundary of what a photo is is getting more and more expansive on the consumer side. Then you have an i an initiative like yours, where you're saying we're gonna authenticate photos at the moment of capture, all the way through the chain, until you're looking at the Wall Street Journal in your web browser. And there's a tag that says, Here's a provenance of this photo. Somewhere in there is a whole bunch of judgment calls, right?

**[1:10:40] Nilay Patel:** We can increase the brightness of this photo, we can change the contrast, we can add a vignette, that's all fun, we can remove dust and scratches. The photo agencies have had rules like this for a million years. Here's the limit of the editing you're allowed to do. Then there's stuff you can do now on smartphones that feels way beyond the limit, but also seems, I don't know, fine, like, if people are gonna make the argument, they're fine.

**[1:11:00] Nilay Patel:** In particular, I'm thinking of best take on the new Pixel phones, where you shoot a whole bunch of frames of a group of people, and then you can, like, make them all look at the camera. Is that a photo in your mind? Does that get a pro? Like, where's the line for you? What is a photo?

**[1:11:15] Dana Rao:** The premise of of the initiative for me is that we want to give people the ability to prove what's true, So, was that right?

**[1:11:22] Nilay Patel:** true? So if I take fifty frames of a group of people and it I assemble a collage of them all looking at the camera, is that true?

**[1:11:31] Dana Rao:** yeah. And so the way I am, I'm, I'm answering that question is this is for somebody who says, I need you to believe this. This thing actually happened, okay? And I'm gonna record everything that happened to this image, all the stuff I did to it. That automatically happened. It's it's it's in the metadata. So my answer to you is not, what is the technology capable of, it's what do you want to do with the technology? And the more you use the technology to blur the lines between real and imaginary, then the less you're going to be able to prove what you did was true.

**[1:12:06] Dana Rao:** So if I was someone saying, I'm taking some very important picture of a volcano exploded in in Iceland, and I want to show you that actually happened. I would probably use less of the artificial intelligence in the initial capture, so I can show people that this happened. The original base image is true, cause I captured it this way, and then I can edit as much as I want to make it easier to see. But people will always be able to understand what the base image was, and they can see what your edits were.

**[1:12:41] Dana Rao:** And one of the cool things that we're doing to show this to consumers, we have a site called verify dot org, and on that site, if you bring your content credentialed image, you can just use a slider. And the slider will just show you the image you're seeing on the Wall Street Journal, and the slider will just move back and forth and you'll see the original image. And then just like that, you can say, Oh, okay, I understand what the base image of reality was.

**[1:13:05] Dana Rao:** If your base image of reality is generative AI, and it'll show that in the metadata, then I'm not gonna believe it. So if your goal was to be believed, my suggestion would be minimize the use of AI in the initial capture in the Huawei phone or whatever it is you're talking about. Because people people will believe you less. And this is all about what we refer to as a it's a kind of like a dial of trust.

**[1:13:26] Dana Rao:** And it's up to the person taking the picture of where you want to put the dial. And you want to be maximum trust. You take it with a Leica camera that has no AI in it and has content credentials, and you put your name on it and the date and location, all that metadata, and that's a high level of trust. Or you can say, I don't really care. This is about my cat that's going to Instagram.

**[1:13:46] Dana Rao:** I'm, you know, or whatever,

**[1:13:48] Nilay Patel:** can I ask you a a really deep and meaningful philosophical question there? That it please. the idea that we will now create two classes of cameras. Leicas are very expensive. The Sony cameras that have this technology in them are for professionals at news agencies, basically. The social revolution of the past decade is smartphone cameras, right? That has democratized all kinds of the social justice movement around the world is built on the back of smartphone cameras. When do those things collide, right?

**[1:14:19] Nilay Patel:** If we create a class of cameras and production chains that we're saying can be trusted in a world of AI, and then there's the thing that is causing the chain, and it's not there yet.

**[1:14:30] Dana Rao:** yeah, we don't see classes, um, we're, we're class-free here at Adobe, and everyone can join this initiative, and I think everyone should join this initiative. It was great to see Qualcomm say, you know, Snapdragon will be C2PA compliant, cause that's a step toward getting it on the smartphones. But we absolutely think all the smartphones should have the ability to add content credentials. There's no reason they can't. So this is just a question of whether or not all the endpoints participate in this standard or some standard like this.

**[1:15:02] Dana Rao:** But I think it's going to be a necessity for everybody if they want to be believed, to have this ability. And there's no reason why this technology can't live everywhere.

**[1:15:10] Nilay Patel:** all right, so come back to my my dumb question. What is a photo? If I take fifty frames and I let an AI point all the faces at me, does that count as the truth? Is that a photo, or is that an AI edited image?

**[1:15:24] Dana Rao:** I would say that my view would be, if it does not accurately capture the reality of the moment, then it is not a photo. Yes,

**[1:15:35] Nilay Patel:** all right, you heard it here. First, I've been so I mean, I I truly struggle with this question. I have old cameras, uh, that, you know, I basically set on the shelf. And now AI denoise and Lightroom has brought them back to life, right? It has enabled me to use them in new ways. And I I'm taking photos of my daughter, and I love using these cameras and my old lenses and all this stuff. And I'm like, is this real?

**[1:15:56] Nilay Patel:** Like? And I don't, I just, I truly do not know the answer. I struggle with it every time, but then the output is so rewarding that I'm using it without a second's hesitation. And I think there's the big questions about election, disinformation and content authenticity and and proving provenance. And then there's this little question of, boy, this technology feels really good to use. And making people apply a moral judgment to how they use technology when it feels that good is an almost impossible task.

**[1:16:24] Nilay Patel:** And

**[1:16:25] Dana Rao:** I don't think there's a moral judgment, though. Again, I'm well, am I lying just I think

**[1:16:28] Nilay Patel:** to people, right? Is, like, kind of I the moral question here at the at I the heart of it,

**[1:16:31] Dana Rao:** see. I think I think everything we're doing, the way your brain works, right? Every image you see, first of all, everything you're seeing happened a second ago, right? It's not even not even present. And all right, now then it's all

**[1:16:42] Nilay Patel:** I have brought you deep into going right, philosophy,

**[1:16:44] Dana Rao:** right, right now. And then everything you're seeing is being interpreted by your own cornea and then your own ability to interpret color. And then it's just what you're looking at. What I'm looking at are totally different shades of blue. And so the whole thing is really kind of fictional, this idea that we're all sharing a common visual reality. So I would, I would not put a lot of stock into that either. Um, so your fifty person composite picture, to me, is certainly a version of reality that I would believe is accurate.

**[1:17:10] Dana Rao:** It's just that there's going to be a slippery slope if generative AI is involved, that you could then easily manipulate it to be something, a pose that didn't actually happen, and then people will be deceived. And I'm saying, if I want to draw a bright line around, I actually need you to believe this happened. I would draw it farthest to the left on before AI gets used. But there's nothing wrong, obviously, with the other parts because it looks beautiful, or and people people are always doing that, and it doesn't change the truth of the image.

**[1:17:41] Dana Rao:** So we're not even saying don't use generative AI, we're encouraging people use generative AI in that picture, but tell people what happened to it, right? Did you remove a background? Did you remove a stranger that was occluding the view of the primary subject? That's all great, as long as people can see what you did, then they can believe you.

**[1:17:59] Nilay Patel:** So one of the things that's really hard there is where you land the enforcement, where you land that mandate. There's some stuff in Photoshop you cannot do right, you cannot counterfeit money in Photoshop. I've tried. I was younger and the the software kept me from doing it. I see You just can't do it. Is is there stuff that you think Photoshop can't do now or should not allow people to do?

**[1:18:21] Dana Rao:** well, there's always the, um, for all people in in the image generation business, there's, you know, the question and their law law enforcement requirements about, um, child sexual abuse material. And you don't want to allow that to be generated, you don't want to allow that to be proliferated on your server, and you have to report it to law enforcement if you detect it. And you should have ways of detecting that kind of material is being created, so that's critical and important to address in all at all times.

**[1:18:50] Dana Rao:** Um, and then, yeah, anything that Photoshop is capable of that is going to break a law, right by the very nature of it, that and that's where the counterfeiting one came from. Is, you know, they engaged with the team and and said, Hey, we want to make sure this can't happen. And so then we complied with the government, and Adobe will always, you know, comply with those kinds of requests. When the government comes to us and says there's something this technology that is unlawful or really harmful to society, then we're gonna take a hard look at it and say, let's see if we can address it.

**[1:19:23] Dana Rao:** On the other hand, we are also on the side of innovation and freedom of expression, and so we're not going to stop everything just to uphold, you know, a particular ideal or point of view.

**[1:19:35] Nilay Patel:** but where you put the enforcement, I think, is the question that I keep coming back to. For example, I had AMD's Lisa Su on stage with me at the Code conference. I said, You can see how open source models running on an Windows laptop completely evade all law enforcement, right? Like, you can just see how you can make a bunch of rules. And then someone has an open source model and they're running it on Linux on an AMD chip, and the last person who can stop them is you, like AMD has to stop them at the chip level.

**[1:20:04] Nilay Patel:** And she said, Yeah, that might be true, you know, the model and the chip have to work together, but we'll, we're, we're open to it, we'll figure it out. For Adobe, as you move more things into the cloud, you have many more opportunities to do basically real-time content moderation. Maybe it's on the prompt, maybe it's in the output, maybe it's what people are storing in their content libraries, or you could push everything back to the desktop where you see less and less of it.

**[1:20:24] Nilay Patel:** Where do you land the enforcement? Where do you think you have to do the checks?

**[1:20:29] Dana Rao:** We have to do the checks wherever the content's being created. And so, and the jury's out where four years from now, where where this will be, will it be on device, will it be in the cloud? And so we have to adapt to wherever that is. Right now, it's on the cloud. And so we understand what prompts you're typing in, and we understand what kind of images are being created, and that's where we have to do the check.

**[1:20:50] Dana Rao:** I mean, if you're uploading your images to our servers, that's where we'll do the check. And so that is still the current world we're living in, and that's that's the our approach.

**[1:21:01] Nilay Patel:** when you see that changing, do you think it happens more and more on device over time as computers get more powerful, or do you think it happens more and more in the cloud as your business pushes more more people to the cloud?

**[1:21:12] Dana Rao:** I think there will be a hybrid. I think that there's definitely a lot of, if you can make this happen, um, on a device, there's a lot of advantages to being on the device. The latency between typing the prompt and calling the image and getting it back, you know, having that on chip would be a better user experience, and that's all we're trying to do here is make sure we can have the best user experience. And so absolutely, I think in the future, if you're able to do it on chip, it would be pretty interesting for us to be there too.

**[1:21:47] Nilay Patel:** last question here, the AI conversation is way ahead of the law, right? There's the AI Act in the EU, which is, again, pretty nascent. It's just in its early stages, but it's passed, at least here in the United States. We have the executive order from the Biden administration, which is basically just a series of prompts themselves for companies to go think about things and some transparency requirements. It's long, but it is not, you know, there there's an election coming up, executive orders come and go.

**[1:22:14] Nilay Patel:** In any case, the industry is way ahead of the law with AI, especially when it comes to copyright law, especially when it comes to safety. What are your internal checks and balances, right? You talked about Adobe's values at the beginning of this conversation. Are you holding all of your decisions against a set of values? Do you think the the market needs the regulation in order to stay in line? Where's the balance for you?

**[1:22:34] Dana Rao:** So when we started our AI ethics program, uh, four years ago, you know, we had set up principles for Adobe to follow, and those are accountability, responsibility and transparency, which spells ART, which is really Well important. done. Thank you. Um, and that's really how we govern all of the technology. So everybody who creates an AI feature at Adobe has to fill out an AI impact assessment, every engineer, and it says, like, what is the impact of th- the feature that you're creating?

**[1:23:03] Dana Rao:** And there's a short form and a long form, and the short form is essentially we're choosing what font the user wants using AI, and we're like, ship it, like, there can be no downside to that. So we want innovation to get out the door as fast as possible. It's low risk. And then if there's something else that we think about as higher risk, m like Firefly or the way we're building the model, then the AI ethics review board itself, which is a diverse group of people who are cross-functional, so not just engineers, but engineers and marketers and communication and and research.

**[1:23:35] Dana Rao:** Um, they'll look at it and say, Hey, on behalf of Adobe, this is sort of how we feel about, uh, the technology should get built and should be shipped. We also have some requirements that every AI feature, uh, that gets shipped has a feedback mechanism built into it so users can give us feedback. Like, cause we know AI will not be perfect, it in because of its black box nature, it will never be perfect. It shouldn't be perfect because we want the black box.

**[1:23:59] Dana Rao:** We want it to do unexpected things, but that means it could do unexpectedly wrong things. And so we need that feedback loop from the community to be able to tell us, Hey, this thing that you're doing now, it's a little off course. Go back and retrain it or or put in some filtering to make sure we don't see that. So having that feedback mechanism as well built into our tools is also really important when we think about building AI.

**[1:24:20] Dana Rao:** So that's the transparency piece as well. So tho- those three principles are how we go about governing our own practical implementation. Again, we've been doing this for a while. Within the government, we know that there are some roles the government should play in understanding this because there are values that societies will have that will be different from country to country. And Adobe wants to comply with the law, and it would be helpful if, when we interact with the government, they have an understanding of, like, this is the percentage of errors you can have in an AI, or this is the percentage of, you know, bias you can have in a in a in a model or and and set out

**[1:25:04] Dana Rao:** those standards. We were meeting with with NIST, um, recently, and we were saying they would be a perfect place to set forward the the standards by which a model should be able to safely operate in the view of the United States government. And says, This is where your model parameters should be. From an output perspective, if we comply with that, then we should be able to self-certify and ship and and feel good about what we're shipping.

**[1:25:30] Dana Rao:** So we do believe there's a role for the government to play in terms of setting out a standard of by which we can attest to.

**[1:25:37] Nilay Patel:** Yeah, well, Dana, I could talk to you for hours and hours about this, I think, as you can tell, but you've given us so much time, I really appreciate it. Tell people what they should be looking for next if they're interested in how AI and copyright law and the regulatory worlds collide. What what's the marker in your mind that people should be looking out for?

**[1:25:56] Dana Rao:** I think I know, in our own tools, when I see in the labs the innovation that's coming, both in video and audio and and 3D and and it's just it's just really going to. A year from now, the way you create will be so much different and so much more interesting than even the way you create today. So I would not be as focused, honestly, on the law. The law is exciting for me personally, but for all the people out there who've ever wanted to create but felt like they couldn't because the tools are too hard or the expertise is too hard.

**[1:26:31] Dana Rao:** It's going to get a lot easier to let your inner child out and express yourself, and that's a cool place to be.

**[1:26:38] Nilay Patel:** that's awesome. Well, Dana, thank you so much for coming on Decoder. We're gonna have to have you back again soon.

**[1:26:42] Dana Rao:** Absolutely, thanks for the time.

**[1:26:47] Nilay Patel:** I'd like to thank Dana Rao for taking time to join Decoder today, and thank you for tuning in. I hope you enjoyed it. We have some news. Starting next month, we'll have two episodes of Decoder every week. On Mondays, we'll be bringing you our exclusive interviews with the biggest names in business, tech and beyond. And on Thursday, we'll be delivering timely analysis, discussions of the top stories of the week, and, of course, even more high-profile interviews with interesting subjects.

**[1:27:09] Nilay Patel:** We're pretty excited about this plan, and we're pretty excited to bring even more voices to Decoder and to you, our audience. If you have feedback or thoughts on what you'd like to see in that Decoder second episode, let us know. You can email us at decoder at the verge dot com. I really do read every email, or you can hit me up directly on Threads. I'm at breckles one two eight zero. We also have a TikTok.

**[1:27:25] Nilay Patel:** Check it out. It's at DecoderPod. It's a lot of fun. If you like Decoder, please share it with your friends and subscribe wherever you get your podcasts. If you really love the show, hit us with that five star review. Decoder is a production of The Verge and part of the Vox Media Podcast Network. Today's episode was produced by Kate Cox and Nick Statt. It was edited by Callie Wright. Decoder music is by Breakmaster cylinder. Our executive producer is Eleanor Donovan.

**[1:27:44] Nilay Patel:** We'll see you next time.