This Week in Startups - How AI startups can navigate the legal landscape with Adam Shevell | Wilson Sonsini Startup Legal Basics

Episode Date: August 3, 2023

Today’s show: Wilson Sonsini partner Adam Shevell joins Jason to discuss gaining access to datasets (1:10), fair use in copyright cases (6:29), and more! * Time stamps: (00:00) Wilson Sonsini partner Adam Shevell joins Jason (1:10) Gaining access to datasets, avoiding copyright infringement, and why IP is protected (6:29) The concept of fair use and when it applies (11:26) What new founders should pay attention to (14:59) The Github case (17:42) Proper strategy for getting permission (22:56) How startups get crushed with legal bills (23:32) The Andy Warhol supreme court case * Check out Wilson Sonsini: ⁠https://www.wsgr.com * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason’s suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Hey, everybody, welcome back to one of my favorite series to do here at this week in startups. We call it our startup legal basic series. We do it with what's considered the top firm, one of the top firms in technology and startups in capital allocation, Wilson Sincini. Now, Wilson Sincinn's got a lot of talents. I got a deep bench. I work with them. They're my attorneys. And we had a very niche discussion we wanted to have for this year's startup basics around

AI. And so when I was talking to Becky DeGraa, who usually does this series with me, and you could see the archive at This Weekend Startups.com slash basics. She said, you know, I got an expert for this topic. Can I bring in, go deep on the bench? And Adam Chavelle is a partner at Wilson-Susini.

He works on IP. What's IP? That's intellectual property. And AI is coming up big time. You've heard me talk about this, both on the All In Podcast and this weekend startups, of, hey, what should be framework B, if I'm training an AI model on somebody else's data set.

This is an emerging topic. Welcome to the program, Adam Chavelle. Thanks for having me. It's really great to be here. All right. So I got a lot of startups. They're looking at data and they're saying, I got a great idea. Look, there's all this Disney IP in the world.

Can I take all the Marvel scripts and comic books I find and then make a new. new character out of them, hey, I would like to do something in recipes. Can I go to Condi Nast's website or some recipe database or some famous chef, Mark Schroesman's incredible recipes from Marksuff Madsen in New York? Can I go take his lasagna and use it to iterate on lasagna recipes? What's the answer here? And I know it's a moving target. I'd be all of Mark Bittemins's recipes. But yeah, no, it's a great question, right? You know, getting data, access to data is like the lifeblood of anyone who's building a model, right? You need that huge pool of data to make it execute really effectively and do that magic that we see when we go on to the tools that we have access to, right?

And there are different places you can get them, right? Like universities have databases that they've compiled over the years. The challenge with those is typically they're non-commercial. So if you want to make a product that you're going to sell eventually, you can't really use those, right? against other rules. Open source software, right, GitHub repositories. There's tons of data there.

It's available. And then obviously, the internet itself, massive treasure trope of data. But the challenge is, if you go out there and scrape data, there are a bunch of legal risks you're taking, right? And so you really should go in with your eyes open

so you understand, hey, here are the risks they're running. There might be ways we can mitigate these risks, but it's not a risk-free opportunity, right? The biggest one is copyright infringement. So you mentioned Disney, Marvel. Obviously, they have fabulous IP assets that they've built over decades. They won't take it lightly if you go in there and grab their stuff.

You know they don't. Like, you know, they are aggressive and rightfully so, because they have a really valuable asset to protect. Right. So go ahead. Yeah, I mean, and they have spent billions of dollars acquiring some of those. Marvel, Star Wars, and Pixar were multi-billion dollar acquisitions that then had multiple billions of dollars put into them. And my understanding is these are all protected IP.

There is a concept. And Disney has actually, just to pick them specifically, they have worked really hard with IP law here in the United States to protect those characters. And I think some of them, like the original Mickey Mouse's, there's this concept in IP law of like 75 years since the creator or something, and I'm not up on that exactly right now. But if you're taking data off the internet, by definition, it's under 30 years old. So it's going to be protected unless somebody explicitly didn't protect it. Am I generally correct in my framing here?

Absolutely. So for the purposes of what we find on the internet, almost all of it is copyright protected. Now, there are artists, let's think of like Vincent Van Gogh or Mozart, who lived a long time ago. their copyright protection is gone, and so their work is in the public domain. But stuff like Disney, like, that's still copyright protected. And copyright law gives the owner some exclusive rights, right? No one else can reproduce that IP, that work of authorship. No one else can prepare derivative works of that authorship, distribute them publicly before them.

So basically, it gives them a monopoly over using that art and that work of authorship, right? So if you're scraping, let's just use Disney's art or data as an example. If you are scraping their site and pulling their art down, you know, you're reproducing, right, which is a violation of copyright in order to train your model, right? And actually, there's a lawsuit currently, Getty is suing Stability AI. And the argument there is when Stability AI scraped Getty's website, they reproduce without authorization and they violated Getty's copyright. That's the argument they're making.

It remains to be seen how that goes. Yeah. The fact is when, and the example is given in that suit and that claim literally showed the watermark from Getty. So it did. It did. This was, I would say, not a very thoughtful execution on the part of stable diffusion. And the best practice always in law, because I'm a content producer for many years as a journalist, is when in doubt, get permission. Now, there is a concept of fair use.

That's right. I have had long, I have a long history with this, just as a content creator again. If people want to understand fair use, they need to understand this is a multi-part test here in the United States. Again, you can correct me where I'm wrong, but I try to explain this to my founders. This is a multi-part test that is subject to the interpretation of the courts. it very rarely gets to a decision because people tend to have a lawsuit or legal letters or a debate over

do they feel that you're being fair in your interpretation of fair use? So let's give a little primer to people listening of the multiple part tests of fair use and where it's obviously applicable or where people maybe are selectively interpreting fair use incorrectly. Sure.

So the biggest challenge with fair use is that you don't know what fair use is until a court tells you what it is. Each time is different, right? There's no, there are, there's a test, and then we can go through the tests and tell you what different parts are. But ultimately, if the case of stable diffusion is or is not fair use, is going to be cited by one judge, maybe it gets appealed, but essentially the court's going to decide. And if there's another case that Getty sues, let's say a different company in a different case, that would be a different test.

And we'd reapply the same legal test to the different facts, right? So it's factually dependent. The four main factors for fair use that the court's way are the purpose and character of the use, right? This one gets a lot of attention, right? Is the new use new in some way? Are you adding a new transformative nature to that work of art? or work of authorship, right? The second is the nature of the copyrighted work.

A technical manual for your dishwasher gets less protection than, let's say, a novel by Dickens, right? So the artistic merit of the actual work weighs in. The amount of and substantiality of the portion you've copied is also important. If you took a small snippet as opposed to the entire work, that will weigh differently. Is that fair? Are you taking a very small piece? Or are you just kind of taking the whole? whole thing and copying the work and doing something with it.

Lastly, yeah, it was very interesting because, you know, I am obsessed with fair use as a contact creator. I remember there was like a famous documentary and it was at Sundance and they were talking about, you know, the rating system and they came out. I remember talking to some attorneys. It would come to be the name of the film, but it's not important. They wanted to use certain scenes to explain this point. And they, upfront, because usually when you do apply for distribution for a film, they want to see that every single clip has been

cleared. They said, nope, this is a documentary, it is fair use, we're using it and I'm jumping the gun here a little bit, for educational purposes, etc. We're using a tiny portion of these original films, and we will not get permission in advance, and they did not get stopped because, again, with fair use,

you have to have somebody on the other side, as you very clearly said, a judge has to decide, it's open for interpretation. The Other person has to feel it's worth going to bat to protect their IP. And if a documentary film wants to use five seconds or ten seconds to make a point that's educational, and it's obviously, you know, in context, you know, the other copyright holder might not even feel this is an existential threat to them in any way and they don't take action. So yeah. Well, actually, that's a great story.

That's a pragmatic part of it. So go ahead. Yeah. Yeah, no, it leads into the fourth factor, which is the effect on the copyrighted works market, right? If you're taking the original work, making a different version of it and selling into the same market, you know, that first owner is going to lose market share, right? You're a competitor. So if you're competing with the original owner, that's also going to weigh against fair use.

If you're taking it and putting it to a completely different use and it's transformational, then that's more likely going to be determined as fair use. But again, each time is fact specific, right? Yeah. And what's interesting is, you know, you talked about the parties really having the desire and resources to go all the way and fight the fight for fair use. You know, a really high profile case was the Oracle v. Google case, right, with the Java APIs.

And Oracle sued Google in 2011, okay, or 2010. And it took almost 11 years to get to the Supreme Court ruling where the Supreme Court ruled that Google's use of the APIs in this instance, didn't say all use of copying API, you know, command lines are fair use. but in the assistance, it was fair use. It took 11 years. And you had two companies with some of the biggest resources, biggest pockets on the whole world to fight the cell.

I think we know who won that case. We know who won. Your attorneys won that case. The attorneys did fine, I'm sure. However, the, you know, but if you think about 11 years, okay, from start to finish, how does that match up with the pace and rate of change in generative AI? It's so mismatched.

How can the court systems be relevant with the rate of change that's happening in the AI industry? It's going to be really interesting to see because a lot of these questions, like when I advise my startups that my clients, like, hey, can we do this? The answer is always like, I don't know yet. We're going to find out. Here are the factors that are going to it. Yeah, see, this is the frustrating part for, I think, a lot of young individuals, starting companies who haven't had to deal with this issue. and an attorney cannot tell you,

here's the bright line, and here's where you're good, and then here's where you stepped over the line. And what you have to then take into account is the totality of the situation. And a framing I use, and I'm curious, what you think of this is, it relates to that fourth part of the test,

which is, hey, is this going to affect the original copyright holder's ability essentially to monetize and to exploit their creation? in the future. Now, if you look at what stable diffusion did, this will be my opinion. I don't speak for you, or Wilson-Sinini, but my opinion is, it's obviously going to affect it because Gettie could create their own stable diffusion, which is, by the way, based on an open source project, they could create

their own product that builds off of that. And the IP holders of those original photos, if they are in a revenue sharing deal, would be able to monetize that. So, of course, they're infringing on it, but a more simple step to take is, how fair does the person on the other side of your innovation feel about it? And when you look at Google, their use of content with snippets, you know, they're only using a snippet of your website's information. That felt fair to people, and there was traffic being sent to you. Therefore, you very rarely saw anybody saber-rattle a threat to sue Google for putting a little snippet because there was a blue link directly to your website. and it essentially was like a little amuse bouge that, you know, first 500 characters. And by the way, you could opt out of it too. You can do robots. t-hc, which Facebook did, which Craigslist does.

So let's talk about the fair in fair use and how founders that you work with, you could kind of walk them through how to think about this and avoid problems in the future. Yeah, sure. So, you know, as you allude to, the test is technical and almost no one ever finds out if it actually is or is not fair use, right? You make a pragmatic decision balancing all the risks. And what you mentioned, how impactful is this going to be on the company or the individuals that we are reusing their original material?

Are they going to be impacted negatively? Are they going to dislike that we're in the market doing what we're doing? Or actually, they might like that we're channel for them in the case of Google and the snippets, right? So that's a real sniff test as far as, are we going to come down? the line and in a couple of years have people throwing claims at us or not, right? And the more competitive your use is with the original data owners market and the more competitive you are with them.

I mean, it's just common sense. You're running a higher risk of running into issues. And the other thing is it's important to have a coherent strategy whatever you do, right? Like there are lots of different ways to get there, but being able to articulate what the risks are, how you balance them and why this balance and approach is right for your company is not like good for the company, but when you get into term sheet land and you have a venture firm coming to invest in your company, they're going to want to hear this strategy, right? They're not dumb. They have lawyers who are looking at this very intently. And so being able

articulate why you're taking this balanced approach to this risk is going to be really important for your company's success if you're looking for venture investment. What are the major cases right now. I know there's a GitHub. Open source folks are suing GitHub for their co-pilot. Explain that one maybe Grouchrofts. This is really interesting, right? Because it has to do with open source software. And for those who know open source software, it basically, it's software that the owner has made available to the public to use, right? So on its face, you think, okay, well, here's some source

code, so-and-so wrote it, and they've released it to the public, right? So, So the arguments in this case, where you have some software developers suing GitHub, I think OpenAI, Microsoft is in there too because Microsoft now owns GitHub. They're arguing that even though the open source software is made

available and anyone could grab it, download it, fork it, develop it, whatever they want, there are still licensed terms that apply. And even the most permissive license terms have some requirements that weren't being followed by co-pilots and the developers.

And the argument is, they allege that There is both a duty to notify future users that part of the software was copyright so-and-so, whoever wrote it, right? And so by ingesting all the software and then producing new software that could match, you know, word for word, line for line, the old software, they weren't providing that copyright attribution notice that they're required to. So there's a breach of contract, right? You had a license with me. I gave you a license to use my code. And one of the few requirements was just tell people when you distribute it. Attribution.

Yeah. It's giving credit. It's a core tenet of open source. If you want to use this, you just got to, and I think they even say in their license, link back and give credit. And there's creative commons and open source, and there's a very granular thing. This would be de minimis for Microsoft to actually put links. In fact, I was so vocal about this with Open AI.

that I noticed with OpenAI's web crawler with Bing, they now will, from time to time, put a citation in. And I was using Bard the other day. They now have images and thumbnails in there. And they give credit to Yelp. And they linked to Yelp. Interesting. Again, back to the fair in fair use.

It's nonsense that these AI models cannot point to where they got the information from. If properly constructed, you could say some of this information came from here, some of it came from there. It's kind of nonsense to say you can't give a link. And so I think this one will be solved

with the links and credit being given to folks and also permission. Let's talk about permission. The gold standard is to get written permission from people in advance of doing stuff. Nobody in technology likes to do that. They like to beg for forgiveness. So what is a proper strategy for folks?

Is it to beg for forgiveness? Is it to, you know, ask for permission, to not kick the hornet's nest, as it were, and just put out a little experiment without monetization and see how the market responds to it? What's the pragmatist approach to this? Yeah, sure. So, you know, it really depends on the data source. Like, there are certain data sources that are known to be challenging. Like, for instance, Craigslist, you cannot take Craigslist's data. They will fight you tooth and nail.

it's a matter of philosophy and principle for them. And so in that case, ask permission or don't do it. Because they will hunt you down if you take it without permission and they will get you as best they can. So understand whose data you're using. Craigslist does not stop. They've been very clear from the beginning. Yes.

And then you also, you're seeing a shift in the market from, you know, companies with huge pools of very valuable data. Like look what happened with Reddit, right? Yes. They went from a free model to a pay-to-use model. From their perspective, that makes a lot of sense because, hey, our data is now so much more valuable with the huge rush to make these models that we're a for-profit company, we need to make some money, and here's an asset we could leverage, right?

So you also have to know, like, how is the market moving, right? And so there, they want to give permission. They want you to pay for it, right, rather than coming and taking it without their understand. And so going back to your initial question, though, you know, as long as what you're doing is sort of measured in steps. The challenge is if you do a test and maybe you don't ask permission and maybe you take some data, you run the model, you see how it works. You're like, hey, this is great.

Let's keep doing it. If you get to a point down the road where someone sends a cease and desist letter, you don't want to be at a point with your product development where you can't put the genie back in the lantern, right? You want to be able to stage how you're using the data in a way so that if you do run into a claim down the road, you can kind of, I'll say hide your tracks a little bit if you can, right? And sort of be able to take away maybe the data that they're complaining about from your product without completely ruining how it works, right? And so just thinking

about contingencies, really, you know, I wouldn't necessarily go out and ask permission each and every time, even though that would be the legally correct thing. I think pragmatically for startups who are resource strapped and have to be a little bit scrappy, sometimes you need to take a little more risk. And all I say is just take that risk very calculatedly. Be thoughtful. You know, this is, I think, great advice. I can give really granular examples here. People want to do all kinds of things with the things with the archive of this week in startups

and all in. And one of those things a couple of years ago was, hey, I want to make clips on TikTok. And we had a couple people who wanted to do clip shows. And I said, yeah, I tell you what, and they contacted me, is it okay? I said, yeah, if you're a fan of the show and you want to do a couple of clips,

you know, go for it. Just always link back to the original episode. and just say that, you know, you're not the copyright holder, the copyright holder is whoever. And, you know, let's check back in a year or two and see where it's at. Now, some of these things have become big, but, and they're not monetizing. So I'm like, okay, fine. And then in some cases, if they want to monetize, I might be like, well, what is it making? Just keep me informed. If you're making $10,000 a year or less and you're putting hundreds of hours into this, I guess I'm okay with it. You know, it's promoting the show. But then I had this one group that

was taking the entire episodes and then using AI to put them into sections, clipping them, and then putting ads around them. And I said, no, Bueno,

this is not fair. And they were doing it with Tim Ferriss and some other folks, and I just told Tim and other folks, like, hey, do you know this is happening? And they were like, this is BS.

And I said the person, listen, if you want to not put ads on it, and you're using the original MP3 file, I'm okay with it. and you give credit, and you link back to the original show in the interface. And their interface was always like, this week and startups, next episode,

where this week and start up, you know, and no links back to us, or they would make a tiny little link. And this is where I think, you know, if you wanted to do an experiment, okay, do it. But think about the person who put the effort into that content and how you could be fair with them, linkbacks, credit, using the original MP3 file. It's a very subtle point here, but we get the data on that person listed. to it. If you rip the file and put it on your server, I don't know how many views you're getting.

My advertisers don't know. I can't cookie the person if they're, I have cookies turned on. So I like your strategy here. You can take a little risk. You can do a little experiment. I think turning off monetization on these things is also critical and framing them as an experiment and taking feedback in good faith. Super important. Yeah. All right, listen, this is incredible. get a good lawyer if you're doing this because it's going to lead to a lot of discussions. Man, I just sent you a link in the chat. Craigslist has gotten judgments against people.

I was reading this headline here. Craigslist garners $60 million judgment against rad pad in scraping dispute. I think just be careful if you're doing this kind of stuff that this could be the end of your startup. Pragmatically, you raise a half million dollars or a million dollars. You're coming out of TechStars or Y Combinator

or launch accelerator, and you get hit with one of these, that's it. Game over for your firm. You have seen this happen. Startups get crushed with the legal bill freezes future funding. So this could be existential,

be the end of the line for your startup. Yeah, absolutely. Adam, I was super fascinated by this one. I could talk to you all day. It's supposed to be like a short segment, but I got to bring it up. Andy Warhol lost in the Supreme Court is tomato cans or whatever it was

that were based on photos. I can't remember which. one it was that they actually took to the mat. Yeah, it was not transformed. It was a, yeah, it was a photograph of prints, right? And in the 80s, Andy Warhol had made a painting, a silk screen or some

form of reproduction based on this photograph, right? And what happened was his estate sold, that, licensed that photo to a magazine as part of an article about prints. And the regional photographer suit, right?

And what was interesting here is the court really focused on the fourth factor, which is the impact on the market, right? They basically said, this licensing of the Warhol for use by journal, like in a photo journal in a magazine, is directly competitive with the intent and use of the original photograph, right? She took a photo for a magazine. And so, right, direct competition, right? And it really took away the focus from the first.

factor, which is whether this use is transformative or not. And so if I read between the lines, I think this makes it a harder climb for companies who are scraping and training models on internet data to reuse fair use. Because the real crux of that argument is this is transformative, right? There might be an image or data or there might be a conversation. What we're doing is like changing all of that into this really complex computer system, this model and then creating a predictable outcome later. That's like the original author had none of that in mind.

And, you know, so historically the Supreme Court and courts have really focused on transformative use as one of the prevailing and strongest factors, whereas, you know, this competitive, you know, is the market competitive or not? This factor is kind of, they've risen its importance. And I think that cuts against the developers of, of, generative AI models. Yeah, you got to be really thoughtful about this. If you're taking Tarantino scripts and then you write a Tarantino-like movie,

and, you know, that's all clever and good, except Tarantino still making movies. I think he's going to do one more. So you literally, it's not the intent. Now, if you're inspired by somebody and, you know, Quentin Tarantino was literally inspired by a lot of the exploitation films of the 70s. and he is doing an homage to them in Jackie Brown in Kill Bill in Glorious Bastards. These are literal

homages, but it's so transformative that for you to know that this reference is from the killing and this reference is from this 70s film with Pam Greer that you would have never even heard of and it's such a minor inspiration of this one piece of dialogue or that piece of dialogue. There's no, like, it's not interfering

with the person who made that film in the 70s. And in fact, that person who made that film in the 70s, when people do figure out that it had some inspiration to Jackie Brown, would go seek it out and it would make more money. So you're, but the Andy Warhol one is like, it became a cult thing.

It became a cult thing. But the Andrew Warhol one is like, should I buy the photograph? Or should I buy this colorized version that Andy Warhol did and transformed? You're like it's in either or. Yeah. It's so easy. I also note that the Supreme Court was really only focused on the licensing

of the image, the licensing of the work, not on when he made the original work, the derivative work from the photograph. So what does that mean? So they haven't ruled, they haven't said that it wasn't fair use when Warhol made the work of art as a derivative work off of this photograph.

They just said using it, licensing it versus licensing it is not fair use. So he could make the painting, he could put it on his wall, perhaps even sell the painting one time. Sell it at auction. Sell it at auction one time. No problem. But licensing it to,

because if you did make the painting and sell it at auction one time, did that really screw up the original photographers? You might be able to make an argument if they were making prints, maybe of prints, Prince of Prince. Maybe.

But anyway, rest in peace, Prince. And by the way, just speaking of Prince, I know you're a music lover like me, he does a guitar solo at the Rock and Roll Hall of Fame of While My Guitar Gently Weeps

Oh Yeah And if you haven't seen Prince do This solo Because you know And we'll leave this in the episode He does Just type in While My Guitar Gently Weeps

And you watch this With Tom Petty Steve Winwood And Jeff Lynn Somebody had said like I don't know if it was Rolling Stone Or something Somebody had said Prince was like overrated as a guitar player.

And he was like, oh, yeah? I'll see at the Rock and Roll Hall of Fame. And he gives Mark Knopfler, you know, level performance of a, of a guitar solo that breaks the internet. This video is so good. I'm not going to play it here because I don't have fair use. I don't want to take away from the copyright of the Rock and Roll Hall of Fame. But this video has got a hundred and twenty three million views.

It should have a billion. All right. Listen, if people want to get in touch with you, they got this issue. You got an email. You got a way for them to get in touch with you, Adam? Yeah, sure. It's A. Cheveld at WSGR.com. A-S-H-E-V-I-V-N-V-V-E-L-L at WSGR.com.

Perfect. Thanks for doing this. I appreciate you sharing all the wisdom and giving really pragmatic advice to the startup community. And if you want more information on this, this week in Startups.com slash basics for more information in our basic series. We do it every year.

Thanks so much for my friends at Wilson-Sincini for supporting this and doing it with me. on the most important topics for founders, and we'll see you next time on this week in startups. Bye-bye.