Ashley Taylor, Ghillaine Reid, David Stauss, and Matt Berns take a practical look at how states are actually regulating artificial intelligence in 2025–26.
In this episode of Regulatory Oversight, host Ashley Taylor continues the multipart series on artificial intelligence with colleagues Ghillaine Reid, David Stauss, and Matt Berns for a practical look at how states are actually regulating AI in 2025–26. Framed through a consumer protection lens, the discussion moves beyond theoretical federal proposals to real bills and regulations moving through state legislatures today.
David surveys the national landscape, noting that nearly all state legislatures are active and that roughly 500 AI-related bills have been introduced, with major themes around pricing rules, consumer-facing interactive AI, health-related AI, provenance requirements, and the Colorado AI Act. Matt then focuses on the rapid growth of algorithmic pricing laws — 2025 statutes in Connecticut, New York, and California restricting the use of competitors' data and requiring disclosure of personalized or "surveillance" pricing, as well as 2026 proposals in states like Maryland, New Jersey, and California that increasingly target personalized pricing in groceries and other essential sectors. Ghillaine turns to transparency in synthetic content, contrasting New York's broad but stalled GenAI warning bill with its more precise "synthetic performers" law and tying those developments to California's AI Transparency Act (SB 942), which requires watermarking and detection tools for large generative AI platforms.
The conversation rounds out with an overview of new state rules on chatbots and "companion AI," particularly in California, New York, and other states, describing requirements to clearly disclose when users — especially minors — are interacting with AI, protocols for handling suicidal ideation, and growing concerns over mental health use cases and broad private rights of action.
Regulatory Oversight Podcast — AI State Regulatory Frontiers: Inside the New Wave of State AI Laws
Host: Ashley Taylor
Guests: Ghillaine Reid, David Stauss, and Matt Berns
Aired: 5/5/26
Ashley Taylor:
Welcome to another episode of Regulatory Oversight, a podcast dedicated to delivering expert analysis on the latest developments shaping the regulatory landscape. I'm one of your hosts, Ashley Taylor, the co-leader of our firm's nationally recognized State Attorneys General practice and a member of our Regulatory Investigation Strategy and Enforcement, or RISE, practice group. This podcast highlights insights from members of our practice group as well as guest commentary from industry leaders, regulatory specialists, and current and former government officials. Our team is committed to bringing you valuable perspectives, in-depth analysis, and practical advice from some of the foremost authorities in the field today. Before we begin, I encourage all of our listeners to visit and subscribe to our blog at regulatoryoversight.com to stay current on the latest in regulatory news. Today we are continuing our multi-part series on artificial intelligence. My colleagues Ghillaine Reid, David Stauss, and Matt Berns will examine how states are actually regulating artificial intelligence in 2025 and why state action is accelerating as federal efforts have slowed. They'll cover three main areas: algorithmic pricing, new disclosure and warning requirements for AI-generated content and synthetic performers, and early efforts to regulate chatbots and companion AI.
Ghillaine is a partner in our RISE practice group and co-leader of the Securities and Investigations group based in New York. She brings deep experience from both government service and private practice, regularly representing corporations and individuals in investigations by the SEC, DOJ, FINRA, and other regulators. She has successfully defended high-profile SEC enforcement matters and previously served as a branch chief and staff attorney in the SEC's New York regional office. Dave is a partner in our Privacy and Cyber practice group, advising clients across the full spectrum of state, federal, and international privacy, AI, and information laws, including comprehensive state privacy regimes, children's and social media laws, data broker and biometrics laws, AI frameworks like the Colorado AI Act, and the GDPR. He is a leading voice on state privacy and AI regulation, tracking state-level developments. Matt is also a member of our RISE practice group based in Philadelphia. He brings an insider's perspective from senior leadership roles in the New Jersey Attorney General's office and Governor's office and as a trial attorney at the United States Department of Justice. As chief counsel to the New Jersey Attorney General, he oversaw key divisions and major civil enforcement matters in areas such as consumer protection, data privacy, and cybersecurity, and he also served as deputy chief counsel to the governor. Ghillaine, Dave, and Matt, thank you for joining me today to break down some state-level AI developments.
Ghillaine Reid:
Thank you for that introduction, Ashley, and thank you also to you, David Stauss and Matt Berns, for joining me today. We are zeroing in today on what states are actually doing with respect to AI in 2025, and not theoretical proposals, not what might happen in Congress, but rather real bills and regulations moving through state houses right now, viewed through a consumer protection lens. We are going to organize our conversation around three specific buckets. One, the safer AI topics that states have found they can actually pass. Those concern pricing rules, disclosures and warnings on AI-generated content, the regulation of chatbots, and the regulation of companion AI. The second bucket is a small group of bellwether states to watch, signaling where AI policy is likely heading next. And finally, issues companies should pay attention to this year, helping them avoid surprises from fast-moving state rules. Overall, federal AI regulation has largely stalled on the harder, more contested issues. States have found a lane, and state activity now moves faster than most companies realize. Dave, to set the stage for 2025, how would you describe the big picture on AI legislation right now?
David Stauss:
Yeah, thanks so much. And thanks so much for having me to start with. Happy to sort of paint the larger picture. So we've been tracking privacy bills in my practice for seven years now. We added AI bills about three years ago. This year has been a bit of a unique year in two regards. The first one is we have 46 of the 50 legislatures open, state legislatures open this year. Texas, Nevada, Montana, North Dakota, they meet only every other year, so this is their off year. Around 20 legislatures have closed to date, so big ones like Utah, Virginia, Washington, and Maryland have already gone dark for the year, and they've been early movers on some bills and we can kind of talk about those as well. And at least as we're recording this right now, some big states are still yet to come. So Connecticut, early May; Colorado, mid-May; New York is June; California is at the end of August. So we're sort of in a good position right now to really say the halfway point almost, and what's going to happen with the legislature. Overall, we've tracked about 500 bills that have been filed that we've categorized as AI.
What I'll say is we narrowed the scope of bills that we tracked this year as opposed to last year. Last year we were tracking bills like CSAM and election interference bills, deepfake ones. We really narrowed that scope down to what companies I think really need to be thinking about. So that'd be like you mentioned before, chatbot bills and consumer-facing interactive AI bills, high-risk AI bills, those types of ones, provenance... The list kind of goes on. We're seeing them filed in both red states and blue states. There's really no rhyme or reason. It's not something that's on a state level, at least, it's a bipartisan issue. We have seen the Trump executive order that was issued in December, I think, really tamp down on the high-risk AI bills. So we really have not seen many of those bills at all be introduced. Those would be like bills like the Colorado AI Act, which we'll talk about in a second. So if there's been any impact from the Trump executive order, I think states have in fact stayed away from that. And it's kind of interesting too, because by now we are a month past the time in which the Trump executive order was supposed to actually have produced a list of state AI bills that were onerous and would be challenged by the federal government.
That is yet to come. But I think sort of it's almost like it's already been baked in because state lawmakers have not pursued those bills. We've seen at a high level, I know we're gonna dig in on a few issues, the most bills we've seen are pricing bills. I know Matt's gonna talk about that in a second, so I won't steal his thunder there. But the most bills that we've seen passed by category has been chatbot, consumer-facing interactive AI. And I think you and I are gonna talk about those a little bit later too, which is one of the reasons why we pulled those two out as our specific categories. We've also seen a lot of health-related AI bills. So how does your medical provider use AI in the practice? Can an AI chatbot really give you mental health advice? The answer is no, to preview that one. We've seen a couple states, Tennessee and Maine, pass laws in that regard. And then we've seen provenance bills. Washington and Utah introduced and passed provenance bills. So those are basically companies being able to say how their AI is trained and what's in it.
And Arizona, of all the random states, is actually close to passing a bill. We'll see if that one gets across the finish line. Two things I'll say before we jump to other topics. We track all these on a weekly basis. Right now we push them out on the privacy blog. And I know that there's also the Regulatory Oversight blog, which also pushes out individual articles on specific laws. But we do the weekly updates on privacy and AI bills. So if you're interested in tracking that on a regular basis, that's the troutmanprivacy.com webpage. And then the last thing I'll say as we sit here right now, the Colorado AI Act is certainly a hot topic for many, many companies. There has been a repeal and replace bill that has been worked on by the governor's committee. They're currently undergoing a process whereby they are trying to turn the committee's recommendations into an actual bill and get it introduced, hammer out some final details. And so probably by the time you're listening to this, we'll know the answer to that question about what happened in Colorado. But at least right now, we are still in anticipation. So those of you listening to this in the future, you are in a better spot than we are today. But we'll know that by May 13th, which is when the legislature closes. Okay, so that's my very short but long overview of what's happening with all state AI bills.
Ghillaine Reid:
That's awesome. Thank you so much, Dave. You briefly touched on pricing bills, and Matt, that's something that you've been following very, very closely as well. Can you talk with us about the main trends that you're seeing on pricing?
Matt Berns:
Thank you, Ghillaine. I would love to talk about the legislation that we are seeing on AI and pricing. Before I do that, I do want to thank Dave and his team for all of their work tracking legislative activity on AI around the country. Without those weekly updates, I do not know how I would stay on top of all of the bills that are out there, let alone talk about them on this podcast. So just on pricing, there are more than 50 bills addressing algorithmic pricing that were introduced by state lawmakers last year in 2025, and we've already seen close to that number in 2026. I'll talk about those at a high level, including the laws that were enacted last year and the trends that we're seeing this year. Algorithmic pricing bills are advancing now in red and blue states, although the momentum is greater in the Democratic states, and each bill is unique. I'm not going to talk about the details of all of them. I'll gloss over some distinctions that could be important for individual companies that are exploring their compliance considerations, but I'll highlight some other differences that do stand out. So in 2025, most of the new laws that were enacted focused on prohibiting companies and landlords from algorithmically setting prices using their competitors' data.
Connecticut and New York enacted laws specific to the rental housing market, while California enacted a law that applies more broadly. It's important here to note that the concerns underlying these laws relate to competition and antitrust rather than privacy or consumer protection more broadly. And this is an area where we've also seen some regulation by enforcement. State AGs or other regulators brought enforcement actions relying on generally applicable antitrust laws even without the benefit of laws specifically addressing algorithmic pricing using competitors' data. These new laws could bolster those efforts even as they provide more clarity for industry. The other notable algorithmic pricing law from 2025 is New York's disclosure statute. This law requires companies that algorithmically set prices based on a consumer's personal data to disclose that fact. The New York law addresses what is sometimes called personalized or surveillance pricing. That is distinct from other kinds of dynamic pricing because it relies on data about a specific consumer to set a price for that consumer instead of adjusting prices based on more general market-related data like real-time demand. For example, personalized pricing may involve setting a price for an individual consumer based on their browser history, their family size, their prior purchases, or most frequently, a variety of these data points.
Matt Berns:
Turning to 2026, we are seeing state governors and legislators really focus on personalized or surveillance pricing as part of their broader efforts to address issues relating to affordability. A number of states are advancing disclosure bills like New York's from last year, but importantly, they are not stopping at disclosure. There are legislators who want to generally prohibit personalized pricing, at least in certain industries, or to prohibit consideration of certain types of personal data. For example, some proposed laws would prohibit pricing methods that rely on personal data from minors. Others would prohibit the use of demographic data relating to legally protected classifications like race. For proposals that would prohibit personalized pricing more broadly, some, like a bill that is advancing in California, would apply to all retailers. But the bills that have gained the most traction so far focus on specific industries rather than across-the-board prohibitions. And most of those bills focus on the grocery industry in particular. In Maryland, the legislature, as of our recording today, has sent the governor a bill that would prohibit personalized pricing by food retailers and third-party delivery services. And in New Jersey, we saw a bill that broadly prohibited personalized pricing be replaced with one that targets groceries after the original bill faced industry opposition.
One common feature of these bills is that they attempt to carve out loyalty programs and other personalized discounts because the goal here is to prevent personalized price increases rather than personalized price decreases. A key difference from state to state is whether the law creates a private right of action or limits enforcement to the state attorney general, which of course is going to affect the risks of non-compliance. Another difference I want to note here is that some of the grocery-related bills, like Maryland's, focus on grocery stores, while others, like New Jersey's, focus on food and household products regardless of whether they are sold by grocery stores or through other channels. The bills that focus on particular products rather than particular merchants present compliance concerns for a lot more companies than the food retailers and delivery services that are targeted in the Maryland bill. So overall, we are paying close attention to the details of these bills as we monitor their progress through legislatures around the country and as we help clients understand the potential impact on their business operations and how to come into compliance.
Ghillaine Reid:
Fantastic. Thank you, Matt. The pricing landscape really shows how focused states have become on day-to-day consumer experiences. And staying with the focus on the consumer lens, I want to shift to another big theme that's being presented in these bills, and that relates to GenAI warnings and synthetic performers. The New York GenAI warning bill, I want to touch on what it is specifically and why it's being stalled and held up in the legislature. So to start, the New York legislature passed A3111 in March of 2026, and that requires any operator of a GenAI system to post a conspicuous notice that outputs may be inaccurate from GenAI. And the bill is now sitting with Governor Hochul, but please do not expect her to call it. The bill has been widely criticized as unworkably broad, and the pattern in Albany has been to let bills like this sit rather than veto them outright. This "dumpster fire" characterization that you hear from practitioners gets at the core of the real problem. The bill is 30 lines long, applies to any GenAI system, and doesn't give any guidance on what "conspicuous" really means. Practically speaking, it would require a warning on every customer service chatbot, every AI writing tool, every product recommendation engine, every email autocomplete. If it touches a generative model, it needs a warning. And that's where it collapses, actually, as a consumer protection policy. When everything carries a warning, nobody really reads the warnings. So you've created this liability theater, if you will, and not actual consumer protection. So why does the path forward probably require a narrower bill? This doesn't die. It sits, and the legislature comes back to it in a revised form. What a workable version looks like: a targeted trigger tied to a specific harm. Warnings where AI-generated content could be mistaken for factual, human-generated content in a high-stakes context, not a blanket requirement on any system that might use or trigger a generative model. New York has already proven it can write targeted AI disclosure laws, though, and the synthetic performers bill is actually real proof of this concept. So let's talk about that. The synthetic performers law was signed by Governor Hochul in December of 2025, becomes effective on June 9th of 2026. This one is already law, and companies need to be moving on that compliance right now. And the trigger is actually quite precise. You use an AI-generated figure that actually appears to be a real human in an advertisement, and so you disclose it.
The harm is concrete, and it's defined: consumers being deceived about whether the person endorsing a product is actually real. Penalties are as follows: $1,000 for a first violation, $5,000 for each subsequent one. And each advertisement, significantly, is a separate violation. The carve-outs for the synthetic performers bill are pretty well drawn. Audio-only ads are out. Language translation is also out. Ads for movies and TV shows, those are out as well. So what do we have left? What's left is exactly what the bill is targeting: fake human spokespeople, synthetic influencers, and AI-generated endorsers in commercial advertising. The contrast between these two bills tells the whole story. If you put them side by side, you have a masterclass in exactly how to and how not to write AI disclosure legislation. The synthetic performers law has a clear trigger, a defined subject, a specific harm, and a workable enforcement mechanism. The GenAI warning bill has none of these things. And that contrast is exactly why one is already law and the other is sitting on the governor's desk, presumably going nowhere. So let's talk about how California is connected to all of this and why that matters. So New York isn't alone. The state of California has an AI Transparency Act that requires large AI platforms to provide content detection tools and watermarking. It's a different mechanism, but it is very much the same goal: to give consumers the ability to know what's real and what's not. California's AI Transparency Act, known as SB 942, was signed into law on September 19th, 2024, added to California's Business and Professions Code as a consumer protection measure by the state.
It only applies if your company builds a generative AI system that creates audio, video, or image content, and it makes that system publicly accessible in the state of California and has over 1 million monthly users or visitors. Miss any one of these criteria, which are quite specific, and the law does not apply. Together, New York and California are effectively setting the national standard, really, for synthetic content disclosure and advertising. And other states are watching and modeling off of both of them because here you have two of the nation's most prominent states enacting legislation in the space. The pattern that works across both states starts with the clearest, most concrete harm: fake people in ads, undetectable AI-generated media, and build the targeted disclosure requirement around the specific harm and tie the enforcement to existing consumer protection laws. That is the model. It's the model that the GenAI warning bill hasn't followed yet in New York, and that is the reason why the synthetic performers law is the more important development to watch right now. Now, these developments show how focused states have actually become on transparency around synthetic content and AI-generated media. But the disclosure is not the only theme. More and more bills are targeting how people actually interact with AI every day, especially through chatbots and, quote, unquote, companion AI. So, Dave, let me turn it over to you to walk through exactly what we're seeing on that front.
David Stauss:
Yeah, thanks so much. And I really liked how you juxtaposed in the last discussion about how it's California and New York who are sort of pushing these issues to the forefront. And that's what we see as well with the companion chatbot laws as well. It's California and New York that passed those laws last year. Admittedly, this time last year, I didn't know what a companion chatbot was. I knew what a chatbot was, but I didn't know what a companion chatbot was, but I know what a companion chatbot is now, and maybe our listeners would benefit from that. And basically, it's AI acting as your boyfriend, your girlfriend, your best friend, those types of things. And remarkably, I was at a conference over the fall and they had some keynote speakers come in and they had just gone to a high school to talk about AI. There were some podcasters who had gone in and given a speech, and they asked the audience of high school kids, "How many of you have an AI friend?" And they said a third of the audience raised their hand saying that they had an AI friend. Now, second data point. So I'm in Denver, right? And I watch the morning news almost every morning religiously when I work out. And they ran a piece on companion chatbots, right? And they finished, and the morning show people started talking about the use of companion chatbots. And they said in the piece that something like 25% of the United States uses companion chatbots. It's higher for, I think, men than it is for women, but I've got those numbers probably backwards.
And then one of the morning show people said that she uses a companion chatbot for mental health purposes, right? And so these are really issues that are eye-opening, right? I think they're things that I just had missed. I've got young kids, and I've asked them, "Hey, do you have an AI friend?" And they swear that they don't, but oh, my goodness, right? These have just come out of nowhere, right? And so I always tell people on state lawmaking, state lawmakers are just like you and I, right? They see issues in the wild, and their constituents talk about those, and they bubble those issues up. And that's why we see these bills getting run. You can see what Matt's talking about with pricing, like having your personal data be used to price something, that has an ick factor at the end of the day, right? Or you were talking about the New York bills and California around disclosures, like, yeah, we should be able to tell whether this image I'm looking at is real or if it's AI. Those are just some basic issues, especially when you talk about things like elections and those types of things, right? Companion chatbots is another one of those areas. And so California and New York lawmakers last year said, "Hey, we got to start creating some structure around this." And one of the things we need to do is we need to understand how kids are interacting with this, and we need to be able to tell kids, the chatbot providers need to be able to tell kids, "I'm not real" on a regular basis. And we have seen the horrible stories. They're awful.
Where kids have committed suicide, and there's a chat feature that has said things like "come home" or encouraged suicidal ideation and those types of things. And so when you understand that sort of use case and the harm that's being addressed, it's really kind of easy to understand these bills, right? And so what these bills want to do is, for the most part, they want to do two things. They want to say if it's a minor, anybody under 18 interacting with a chat feature, you got to tell that kid that you're not real. And you got to tell them not just at the beginning, but you got to keep on telling them along the way. Every three hours, Connecticut's going towards one hour in its bill. Again, there's an issue of am I just clicking a button and it goes away, but what can you do? And then if a kid starts saying things like suicidal ideation, you've got to have a protocol in place, and that protocol has to stop it, right? To say, "You need to contact services," those types of things. So does it resolve the issue? It's really hard to say. It helps a lot, I think, at the end of the day, especially as parents thinking, "This is interacting with GenAI, I don't know how it's going to interact with my child." So those are like the threshold issues. And then when you get to like the adult issues, what we've been talking about is things like mental health capacity, right? Like, should a chatbot really be providing you with mental health advice? Right. And lawmakers have looked at that and been like, I don't think that that should be the case. We see these bills that are passing in the mental health capacity saying, like, that's just not a use case we feel comfortable with. Republican and Democrat states passing those. And then just like the broader aspect of how do we regulate just consumer interactive AI with individuals? And those are things like, listen, if it's not open and obvious to a reasonable person that they're interacting with AI, you've got to tell them. Right. And the use case there is really like, if you're calling customer service and you're interacting with something that sounds like a person, but it's not a person, then you've got to tell somebody. So like, there was a commercial that was on TV during football season, and it was like a woman, she was like, "Are you a bot? I don't know. Are you a bot?" Right. And like, that was the use case, right? It was like, "I don't know, maybe I'm a bot. Maybe you're a bot." Right. And so those types of things are what lawmakers looked at.
Now, what I'll say is that's conceptualizing what it is. When you look at the specific laws, we get into concerns. So what are the concerns we get into? One is there's private rights of action associated with those, right? So California and Oregon have private rights of action with statutory damages, right? So that's a big deal. Washington, which passed its law this year, also has a private right of action, but there's no statutory damages, right. And then the definitions of like what types of chat features fit into these boxes is becoming concerning as well, and whether lawmakers have adequately threaded the needle as to what actually fits into a companion chatbot and what doesn't. So let me give you the example out of Oregon. So there you got to satisfy three criteria. One is you retain information between sessions, right? So like, if I leave the chat feature, I come back to the chat feature, does it remember me? A lot of customer service chat features do that as a matter of course, right? Number two, it asks unprompted or unsolicited questions that suggest or concern emotional topics. Well, a lot of chat features will be acting like that. They will be asking you questions like, "Is that enough? Does that satisfy you?" And "emotional topics" isn't defined. And it could be things like financial services or education or all those types of things are, quote, "emotional topics." And the last one is sustaining an ongoing dialogue concerning matters that are personal to the user. I don't know, like, I like to think that everything I do on the internet is personal to me.
Anyway, so you look at these types of things and you think, oh, my goodness, do we have this quite right? There is an exception there if it's used solely for customer service purposes. But the word "solely," I think, is doing a lot of lifting there. And if it's doing these other things, this interactive in between sessions, is it really solely? Right. And so what we've been saying to clients is, hey, this hasn't quite gotten spun up yet, but we're worried about troll litigation, right? Where all of a sudden, you have these statutory damages, and do we need to do stuff to make sure at the end of the day that we're not unintentionally triggering these laws that are clearly, clearly directed at solving a specific harm, but because lawmaking is really tough, does it end up triggering liability for companies? And all of a sudden we've just got a bunch of ambulance-chasing litigation in these states type stuff. So interesting issues. Again, we've got a long way to go with the legislative session. We've seen other states pass interactive AI bills, and I've been calling them interactive AI bills as like the larger category. So we've got, like, Nebraska and Idaho have gotten bills across the finish lines, but no PRAs. And there's a bill waiting on the governor's desk in Georgia. And there's other states. We'll probably see, I don't know, maybe three or four states, if I had to guess, also pass these bills this year as well. So lots of interesting things that dovetails really well with your conversation on California and New York. They are the ones that really jumped in last year. And I'd say too, like, New York doesn't close until June. California doesn't close until the end of August. So we could be looking at a much different landscape by the end of the summer.
Ghillaine Reid:
That's right.
David Stauss:
And we should come back again and talk about exactly what the heck has happened out there. Because until those two big states go, and New York's got something like 60 bills under consideration, I think California's got around 20 right now under consideration. So we could have a much different state legislative outlook come the end of summer.
Ghillaine Reid:
Yeah, for sure, for sure. Thank you so much, Dave. And for you and Matt, as we wrap up, what are some key takeaways that you'd like to highlight for our listeners in terms of state-level legislation on the use of GenAI? What are some things that are super top of mind for you that you think are critical for our clients, our contacts, our listeners to know about?
David Stauss:
So what I would say is this: create a responsible AI program at the end of the day, right? One of the hard things to do is when you look at 500 bills and, listen, I spend my nights and weekends trying to track legislation, read it, figure out what passes. It's a fool's errand in some regards, right? Look at your use cases, look at your use cases in which, hey, I'm having AI interact with individuals, I'm having AI decide who gets loans and who doesn't get loans, I'm having AI decide mental health issues, and then create a risk matrix around those. This is what we do with our clients. We create risk matrices around those issues that you have, right? And we create responsible AI principles around there. And yes, it is definitely, unequivocally, incorporates the legal construct, but it incorporates things like transparency and not having bias and all these types of responsible AI, because that way you have explainability and notice and rights. Because if you're just chasing after a 50-state solution to AI laws, you're just going to be consistently redoing everything, right, as opposed to taking a deliberate approach.
And we are thinking about this all as use cases. We started initially with what is the use case in which you are doing? What are the risks associated with that? Hallucination, bias, those types of things. What are the mitigations we can get through contractually with our third-party vendors, such as like they're not going to train on my data, they're going to help me provide notices? And then what are the mitigations I need to put in place with my company, right, like notices to employees or consumers, those types of things? And if we build that structure and we build that structure for clients and they can walk through those doors, that's going to hopefully accommodate 95% of the problem. And when we get these random bills like the New York GenAI one like you were talking about, which is like, oh man, do we really need to put a notice on every single GenAI that says, you know…. That we can at least take those and say, like, we understand where this would apply and we understand what we could do. So again, I think it's one of those things where hopefully the front-end work, so you're not so reactive in the back end, can really be a huge leverage. Matt, I invite you to jump in.
Matt Berns:
Thanks, Dave. Since you talked about compliance, I'll just talk about engagement in the policy process on the front end. The issues that companies are dealing with from a compliance perspective are often technical, and the policymakers are not going to have the insight that the companies themselves have into what their legislation is going to mean from a compliance perspective. Policymakers might be operating at the level that Dave talked about, where surveillance pricing or personalized pricing has an ick factor to it or it seems creepy, and they have a gut reaction that makes them want to do something about it. But companies should be actively engaging in that process if they think that legislation might advance that could significantly affect their operations in a way that would be detrimental to the company. And they should be working with their trade associations and others to build coalitions to make sure that their perspective is heard and that legislators actually know what effects their bills are going to have in the real world.
Ghillaine Reid:
I have to say this was really an enjoyable and very informative podcast on a cutting-edge issue. Dave and Matt, thank you so much for the time you've spent today. I think that is all we have for today. Really appreciate you both. And Ashley, thank you for having us on the podcast. It's been great.
Ashley Taylor:
Thank you all for joining me today. It's been a really thoughtful and practical conversation about where state AI regulation is headed and what it means in the real world. I appreciate you all sharing your insights. I want to encourage our listeners to tune in next time as we continue our conversation focusing on how AI is actually being regulated today and what practical steps companies should be taking now to manage AI-related legal and operational developments. And thank you to our listeners. I encourage you to tune in next time as we continue our multi-part series on the developing regulatory landscape of artificial intelligence. Remember to subscribe to this podcast via Apple Podcasts, Google Play, Stitcher, or whatever platform you use, and we look forward to having you join us next time.
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