SAS Innovate 2024 | Reggie Townsend | SAS & Miriam Vogel | EqualAI

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Reggie Townsend

Director, SAS Data Ethics Practice

SAS

Miriam Vogel

President/CEO

EqualAI

National AI Advisory Committee seeks to head off disruption as use of AI expands

Members of the National AI Advisory Committee are tasked with advising the president of the United States on competitiveness, the state of science and workforce issues surrounding artificial intelligence. When 27 members were appointed to the committee in 2022, artificial intelligence had not yet become the economic and cultural juggernaut that it is today.The attention of the world is now focused on AI and its potential to reshape everyday life, and Committee members understand the broader mission of the group in providing guidance for what has become a topic of great interest and influence

play_circle_outline Explanation of how the committee seeks input from the public

play_circle_outline The Crucial Role of Clear Rules and Oversight in Building Trust for Responsible AI and Effective Regulation

play_circle_outline Discussion on the role of data and GPUs in AI performance

play_circle_outline Urgent Need: Collective Action, Guardrails, and the Ethical Education to Embrace AI in a World of Anxiety

play_circle_outline Being a responsible AI actor and establishing best practices

play_circle_outline Understanding the Need for Fairness and Transparency: Model Cards for Evaluating AI's Health and Impact

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Reggie Townsend | SAS & Miriam Vogel | EqualAI

Reggie Townsend

Director, SAS Data Ethics Practice SAS

Miriam Vogel

President/CEO EqualAI

search

>> Welcome back everyone. theCUBE live coverage here at Las Vegas for Innovate 2024, SAS's event where everyone comes together to talk about policy, technology, customer-user behavior, new experiences. I'm John Furrier, host of theCUBE with Dave Vellante. We have Reggie Townsend, CUBE alumni, back, VP at SAS for data ethics practice. And Miriam Vogel, President and CEO of EqualAI, doing some amazing work. Miriam, you are also on the National AI Advisory Committee and you worked for Obama administration. You're also CEO and attorney. Reggie, you're doing great work. We know your pedigree, you've been on multiple times. Policy side of this game is really interesting. AI is booming. It's the hottest trend, innovate AI everywhere. There's a lot of trust, responsibility that's really mandated in. You guys have that in your pillar as a core guiding principle. Miriam, I want to go to you first. Talk about the agency that you guys are involved in, just so people know what's out there that's being developed so people can understand the groups that are working around understanding AI at a national level.

Miriam Vogel

>> Absolutely. Well, I'm very fortunate I get to work with Reggie in both of my hats and both very squarely fall in ensuring that trust is earned and developed for AI systems. The National AI Advisory Committee is a congressionally mandated committee that came out of the NDAA that required several things, including that NIST created an AI framework, which we now enjoy as a really important tool to help level set on how to establish responsible AI, what the best practices are, as well as numerous other developments. Our committee was established to provide recommendations to the president and the White House on AI policy with a host of experts and specifically mandated that we have AI experts from academia, civil society and industry, which we do.

>> Reggie, what are you involved in? Which groups are you involved in? Your groups?

Reggie Townsend

>> Yeah, so I actually chair the education and awareness work group, but I also sit on the workforce work group, so on education and awareness, we're very interested in things like AI literacy and making sure that the country, everybody in it, has an opportunity to not only understand AI, but has an opportunity really to enjoy some of the fruits of AI. And that's where the workforce piece comes in, right? Look, we recognize that any technology is a company generally with some level of disruption, and we want to make sure that that disruption does not occur at a rate that the country can't sustain. So, workforce is really all about understanding how we make sure that that doesn't become a reality.

>> I really wanted to get that up front before we get into the conversation because there's a great innovation opportunity for everyone with AI. At the same time people are concerned. So, is there a way people can get involved with some of these groups? Is it open to the public? How is it structured? Give a quick... I don't want to burn too many minutes here, but I want people to understand if they want to get involved, if there's an opportunity that they should know about it.

Reggie Townsend

>> Yeah. So, we'll maybe tag team this one. So, all of us who sit on the committee were nominated to be a part of the committee, and there was a whole vetting process, so we're special government employees. As a consequence, I don't know if everybody wants to go and work for the government or not. But in that sense, as Miriam said earlier, our task really is to advise the president and the White House, the AI initiative Office specifically and OSTP, on matters associated with AI. Part of what we've done as a function of that committee, however, is in fact broaden the access as much as we can so you can find out when we're meeting, and a lot of times we have briefings. And we make that available, all online. People can stream right in. In fact, if you're in DC, a lot of times people can just come because we know this has to be an everybody all in moment and so-

>> They can consume the content. They can consume the content and maybe-

Reggie Townsend

>> And participate to creating that content, because we're looking to hear from people so that we can incorporate some of those thoughts into our recommendations.

Miriam Vogel

>> Yeah, exactly. As Reggie said, there's both the standard mechanism, so it's a federal advisory committee. It's governed under FACA, which is an affectionate term in DC to describe these committees that come with a lot of regulatory requirements. One is all of our meetings are live-streamed and open to the public, so people can send in comments in advance, they can come in person and ask a question. We leave time at each public session for that. And we issue reports and provide an opportunity for feedback. We have an email. All this information is listed on AI.gov/NAIAC, N-A-I-A-C. But a part of what we did adding to our mandate is, as Reggie said, it's so important to us that we hear from more voices, leading experts and new experts, new voices, those we don't hear from enough. We want to make sure that they're incorporated in our advice, in our education and opening up the tent. And so, we have had many panel sessions. We had one just yesterday. They're all online, they're livestreamed and recorded, so people can enjoy those as well.

>> Great transparency. Thank you

>> for sharing.You're very thoughtful individuals and thinkers. It's not like you're trying to control the world of AI, but there are people, big tech in particular, very concerned about regulation. Maybe that's a way to say, "Hey, let us self-regulate," which is probably not the answer. What does history tell us about the impact of regulation? And knowing what you know, how do you think with this world of AI, we should be thinking about regulation in AI? To be flexible, to make sure the innovation is there, but at same time create safety?

Miriam Vogel

>> I think if done right, regulation helps build trust. It helps support innovation. So, first of all, building trust. If people aren't going to use it, it didn't happen. We need to make sure that these are systems that people want to use so that it can be the democratizing force that we want it to be, so that it can up-skill and broaden education and create these healthcare outcomes that are just so exciting. But we have to make sure if we hear a healthcare outcome, if we hear that we've learned that dermatological screening can be 93% effective when used with AI. We've learned that from recent studies that costs can go down 50% and upgrades in healthcare offerings can go up 40% if we're using it right. But we have to make sure, is that true for all Americans? Is that true for all of our citizens? Have we tested to make sure that it's not just who's been tested in a clinical trial because that's often going to be predominantly men and predominantly Caucasians. Do we know that if a doctor is giving an indication to a patient that they're not giving a false negative because that person has not been part of the representative population that's been tested and trained for with that AI system. So, building trust, making sure that there are safeguards in place can help build trust-

Reggie Townsend

>> Accessibility, to your

Miriam Vogel

>> point.And that brings up another whole point of who can use it? Can the AI hear all of us? Can it see all of us? We've had several federal agencies come out and share the laws they have on the books currently are actually applicable to AI in addition to the additional regulations that we'll need. When you say accessibility, the EEOC was one of the first out to say, "If you are using AI in how you're working with people in your employment systems, you are regulated by us and our civil rights laws." And they had a first joint historic statement with the Department of Justice saying, "You better make sure that everyone can equally hear what you're producing on AI, see and other forms of inclusivity, because you've got the Americans with Disability Act otherwise that you could be violating."So,

Reggie Townsend

>> that transparency is key.

>> That's hugely important. I want to make sure to jump on the idea of regulation because I think people tend to have a visceral reaction sometimes. And with all the conversation, it's going to slow down innovation. Stop. We have rules, we have laws, they exist today. And Miriam always says, "It's not like with AI, we're lawless here." There are a lot of laws that exist today that are already regulating AI, so we're really clear. I think what people are really afraid of is whether or not they will have permission to just run roughshod and do whatever the heck they want to do. No, is the answer to that.

>> Yeah, absolutely.

>> And nor should they, and nor have they ever able to. I think there's a little bit of disingenuous sentiment that creeps into that conversation. I think all of us mature adults realize that there are potential negative consequences that we have to mitigate. And all the, quote, unquote, "regulation conversation" is about is trying to mitigate those harms so that we don't harm actual people like you and I. That's it at the end of the day.

>> But the visceral reaction is, "Oh, the government can't keep up with the AI case." It's easy to say that, but at the same time, the example you gave in healthcare, I want regulation. Where it gets kind of interesting, and I'd love your thoughts on this. If the government says to Apple, you can't game the app store, good for them. They should do that. But on the other hand, if there are certain regulations that large companies can actually afford to follow, but a small company might not have the resources... You understand, I'm sure you've heard this all the time. That's a tricky balance for regulators. I don't necessarily have the answer. I'm sort of looking for answers and I think we evolve it as we go.

>> Yeah.

Miriam Vogel

>> I think part of it is demystifying. When we're talking about regulation, it's such a big word and it's such an unfriendly word, but if you think about where has it been helpful? Where has it helped in trust or spur innovation? Think about in airlines, people generally feel safe because they know it is regulated. There are rules. If you're driving, there are lanes on our roads, and for the most part, people stay within their lane. They know to stop at a stop sign, and not every street has the same speed requirements, but we know that there is a speed requirement. And so, I think that's a really good model. Not every state, not every action, not every level of activity needs the same level of oversight, but if we're talking about areas that could be really dangerous, if we're talking about areas that are high impact in hiring, healthcare, et cetera, I think that's an area where we want to make sure there are clear rules.

>> It's interesting you both have that perspective, and I think that I love that standards view because look at roads, you got to get the infrastructure done right, the foundation. And if you over-build, over-rotate, whatever word you want to use, on things that are hypotheticals that might happen, you got to get the basics right. Rules of engagement, how do we do that? So, I think that's good. And I wanted to get in on this because I think there's other things we can look at. For instance, the FCC, broadband, AI fits into that. The domain name system started in America and then became global phenomenon. So, AI's got this global piece, so now we have global AI, geopolitical overlay to that. Really interesting kind of dynamics. I've never seen this before. How would you compare this challenge or opportunity with policy in the US now, notwithstanding the innovation opportunities, just to make it work? How would you scope the challenge? Like hella hard, or doable, attainable?

Reggie Townsend

>> I think those things where you bite the elephant a bit at a time, right? First of all, start with the definition of AI. And I know we've had several of them here in the US and there's been agreement between both sides of the Atlantic, at least now on a clear definition. So, you got to start there. I think we can debate the implementation possibility of the EU AI Act, but I think they did a good job in terms of at least approaching this from thinking about risk, to say, "We recognize we don't want to capture all things AI. That's not the point. But if you are going to execute AI in a certain domain that might have a certain impact, we should know about it." Right? I think that's a reasonable approach to this for now. Now, the reality is right and wrong is always going to be a function of time. What might work now may not work five years from now. And so, the ability to look at that from a longitudinal view will be really important. So, we're monitoring the AI over time. But I cannot overemphasize this idea of use case, and we talk about that a lot at SAS, right? It's like AGI is not all of AI, LLMs are not all of AI. We do a lot of AI that has very specific use cases in pharma, financial services, law enforcement and what have you, and it's really important that we get those bits right, especially because they represent a level of risk that would be unacceptable if we got it wrong. If you want to go out and figure out your travel plans, okay, great. You can have some variability on that. I'm okay with that. But not in some of these highly impactful areas that, by the way, are already regulated. So, we got to make sure we get it right.

>> Well, I mean EqualAI, that's in the name. Love the name, by the way, of the company. My big issue, kind along Dave's line, is that the entrepreneurial opportunity in this country is what we've been founded on, and there's been talk, which I've certainly said this on theCUBE and other events, the rich get richer with the cloud and AI, except, to Dave's point, scale is about size. And so, I joke about the GPUs for America, campaign meaning you get public service GPUs, tongue in cheek. But really that's scarce resource power. So, as the infrastructure gets richer and gets bigger, it's going to be harder for equality for me to compete or do something entrepreneurial or provide a service potentially. I bring it up only as a hypothetical, but that's a scenario that could play out. And again, things like broadband in rural areas was an area where that was mandated. That was a policy decision I thought was one of my favorite things Bill Clinton ever did. Farm Bill. And that was great, but it kind of didn't happen. It's good it passes but . What's your guys' view on the ability to move the needle faster to get it done right so that we can have the opportunities and symbiotically live with the big players? Is that a factor or am I overthinking this?

Reggie Townsend

>> No, it needs to be all hands on deck. I think the stakes are high enough that I feel comfortable that people are going to rise to the challenge. We will not have a sufficient workforce. We will not have a strong enough economy if we do not have more people ready to participate in our AI economy. And that doesn't mean that everyone needs to be a computer scientist, but it means you need some more AI literacy, like what Reggie was referencing earlier. I think the good news is when you're talking about the international front, I mean it's such an important point. AI doesn't have boundaries, so how are we going to operate in a false narrative where we are looking at certain domains to understand what the rules are? The good news is both for that and in thinking through innovation general, we've had some significant steps forward. So, we've seen some activity in Congress. We've seen a lot of work where they're trying to educate themselves with the insight forum, that was a bipartisan bicameral effort as well over the fall. We've seen the president's AI EO, executive order that was released in October that I believe was the longest in history with 150 action items assigned to over 50 federal agencies and quasi-federal agencies.

>> I

Reggie Townsend

>> don't know that they like to admit that it was the longest.Keep people busy while the change is going on. Keep your day job, Reggie.

>> There are deadlines coming up in the next week, 120 day deadlines where action plans are required. So, I think they have at the Department of State, USAID, they have significant taskings there. But also we should note that it's been building on actions that have been underway. So, it's not lost on anybody in the federal government that there needs to be collaboration in order for the rules to be meaningful. So, the there's Trade Technology Council, there's several established entities, the OECD in which we participate, as well as other government bodies and organizations through which we've been participating to make sure that there's alignment and clarity.

Miriam Vogel

>> So, I know we're talking US, but we got to keep in mind, this is a global conversation. Right? Now, here in the US, one of the recommendations that we actually offered on NAIAC was that the White House support the idea of the National AI Research Resource. And what that is expressly designed to do is to provide access to those small businesses, to those entrepreneurs because we recognize that there is a bit of an arms race to gain access to platforms. So, that's one. Two, I think we have to also question the premise, and I think they're doing this in a lot of other nations, questioning the premise of whether more is necessary to be more performative. And there are actually studies to show that-

Reggie Townsend

>> More AI or wait, what do you mean?More

>> data, more GPUs in order to reach levels of performance that are necessary. So, what's your goal? Is your goal to build the next largest foundational model with billions of rows and parameters? Okay, that's one thing. But if your goal is to simply use AI to advance the needs of your business and you're not in that business, then that's something completely different. And so, I think we got to kind of cut at this a couple of different ways. And when you look at what's going on in a lot of different nations, they're cutting at it, I'm sorry, from the latter way because they recognize that they're not getting in the foundation model business.

Miriam Vogel

>> There are a lot of wealthy nations and a lot of wealthy companies trying to get to AGI and they're trying to throw as many GPUs and as much data as possible. Are you suggesting that there should be, and maybe there already is, a conversation from government in terms of regulating that or at least having some degree of transparency around that? I wonder if

Reggie Townsend

>> we can -So, I wasn't making that statement just now. We can have that conversation though. I think in terms of purpose, let's have a broader social conversation and not just leave it up to a handful of tech bros as to whether or not we ought to create something that is cognitively superior. I think that's worth the conversation.

>> Open and transparent has to be there because we are living in an era where the title of this is Navigating Ethical Horizons. That is a huge three-letter words, three words. Ethical is a big part of this. Ethics.

Reggie Townsend

>> Of course.

>> But that is happening.

Reggie Townsend

>> It's happening.

>> And there doesn't seem to be any kind of guardrails on that.

>> Right. So, again, this is a collective action issue. We can't just leave it up to a handful of tech companies and we can't just leave it up to a handful of governmental leaders either. This is why this idea of literacy is so important to me. We've got to make sure that people are empowered with information so that they can figure out for themselves, if they are okay with the direction that we're headed with things like AGI. Now, AI is much bigger than just AGI. Let's just say that out loud. And it's okay for them to question some of those aspects as well. But first you got to educate people on what it is so that they can have a better sense for whether or not they're willing to accept how it impacts their lives. And last bit, when you look at studies globally as to whether people are okay with AI, generally speaking, what you're starting to see is a rise in AI anxiety more than a willingness to accept AI. And that's problematic for folks like us at SAS. We're providing this product, we want to make sure that people eventually embrace it. We think we're doing it for the right reasons. But if they're just freaking out because they hear AI, that's problematic for us and everybody else.

Reggie Townsend

>> It's a huge problem. We've been hardcore reporting this because we've seen evidence, real evidence and examples of people and companies that have changed their outcome of their situation by having access to AI and knowledge to level up. There's a huge leveling up opportunity. Anyone could get to a point quickly. You don't need to have a many, many years of computer sciences, but I think you mentioned computer science, you can be smart and instantly smarter. So, I think access to AI is going to be the critical thing and it can't be one company.

>> I think it's a really important point that you're making. I love this conversation. You can talk about products and stuff, but AI makes you smarter. Who doesn't want to be smarter? At the same time, I worry that if some rogue nation gets AI before we do, I think we're the good guys. Not everybody would agree with that. But that scares me. But I'm an AI optimist like John because it makes me smarter.

Reggie Townsend

>> Well, this is where we debate all the time. This is not the Manhattan Project as Vinod Khosla thinks it is. He said that publicly.

>> I mean, how do you know?

>> Well, because open source is already global and it's already happening. So, for this to be a Manhattan Project, we have to have a national cloud, one. A national AI cluster, that would be national security based. Probably do. But AI is already open source globally, so we have to change the paradigm of open source. So, that would be a policy question, how do you enable the growth of open source software?

>> But it's how you apply that open source software, right?

>> I'd want to see a

>> -I don't know, what you guys think.I

>> don't see .This

>> is the debate of our time.

>> Absolutely. Yeah.

Reggie Townsend

>> And I think it's important for us all to take a breath and take a beat and say there are just some things that we don't know.

>> Unknown.

Reggie Townsend

>> Now, it's okay to hypothesize about some stuff, but to me it's much more impactful to say we've got something that makes us smarter, that we can apply today to people who could use this capability. So, if we could take, I don't know, 25% of our energy and redirect it to people who are without today. So I was a couple of weeks ago in London talking to the folks at the Commonwealth. Oh, the Commonwealth has like 33 small states, but they've got like two and a half billion people. So, the 33 small states are just kind of the smallest of all of the nations that they cover. These are nations that don't have the infrastructure to support a big data center full of GPUs and all of this sort stuff. These are also the nations that are the less developed on the globe. And so, who are we to be talking about all of this turning into different species when we are leaving people behind today? Today. So, if we could figure out ways to help them embrace this technology to grow economies today, to me that seems like a better use of our time than exploring the possibilities of destroying us all.

>> Reggie, that is great vision. Your passion's awesome. Appreciate you for that. And thank you both for coming on theCUBE here.

>> Good to have you.

>> We're going to wrap here, but would love to follow up. Miriam, we'll give you the last word. Love your company. Give a plug for what you guys are doing. Give a quick highlights of where you're at, what you're working on, and what you're hoping to accomplish.

Miriam Vogel

>> Absolutely. At EqualAI for five and a half years, we've been trying to get people to focus on what it means to be a responsible AI actor. The hard thing is it's not clearly defined in national standards or international standards like we were just talking about. So, in the meantime, we work with companies who want to lead in this space and help them align on what is the best practice, what does one do to make sure that they're being responsible and thoughtful and build that trust with their consumers. We also work with policy makers to help them establish what are the right guardrails, exactly as you said, so that they can make sure they're spurring innovation and not inhibiting it.

>> Awesome. And Reggie, a quick plug for you. I know. Quick plug.For what SAS is working on, the ingredients, the nutrition label you have. You call it the nutrition label for AI. What is that about?

Reggie Townsend

>> So, these are model cards where we're able to evaluate the health of a model, any AI model for SAS and Python today. It's the equivalent of a nutrition label that we get on our food, but this time for AI. So, get a chance to see levels of fairness and transparency, if a model is drifting over time. So, we should all be able to evaluate the impact.

>> So, we're going to call OpenAI the supersized model, and we going to have to go on a low calorie, smaller model.

Reggie Townsend

>> The sodium-free. Yeah.The

>> smaller models actually turn out to be pretty agile.

Reggie Townsend

>> Great. SAS and Python and R is coming. Yes?

>> R is coming. Yes, sir.

>> Miriam and Reggie, thanks for coming on

>> theCUBE.Thanks, you guys.I appreciate it.Okay,

>> we leave it there. I'm John Furrier, David Vellante. You're watching theCUBE. We'll be right back after this short break.

Reggie Townsend | SAS & Miriam Vogel | EqualAI

search

>> Welcome back everyone. theCUBE live coverage here at Las Vegas for Innovate 2024, SAS's event where everyone comes together to talk about policy, technology, customer-user behavior, new experiences. I'm John Furrier, host of theCUBE with Dave Vellante. We have Reggie Townsend, CUBE alumni, back, VP at SAS for data ethics practice. And Miriam Vogel, President and CEO of EqualAI, doing some amazing work. Miriam, you are also on the National AI Advisory Committee and you worked for Obama administration. You're also CEO and attorney. Reggie, you're doing great work. We know your pedigree, you've been on multiple times. Policy side of this game is really interesting. AI is booming. It's the hottest trend, innovate AI everywhere. There's a lot of trust, responsibility that's really mandated in. You guys have that in your pillar as a core guiding principle. Miriam, I want to go to you first. Talk about the agency that you guys are involved in, just so people know what's out there that's being developed so people can understand the groups that are working around understanding AI at a national level.

Miriam Vogel

>> Absolutely. Well, I'm very fortunate I get to work with Reggie in both of my hats and both very squarely fall in ensuring that trust is earned and developed for AI systems. The National AI Advisory Committee is a congressionally mandated committee that came out of the NDAA that required several things, including that NIST created an AI framework, which we now enjoy as a really important tool to help level set on how to establish responsible AI, what the best practices are, as well as numerous other developments. Our committee was established to provide recommendations to the president and the White House on AI policy with a host of experts and specifically mandated that we have AI experts from academia, civil society and industry, which we do.

>> Reggie, what are you involved in? Which groups are you involved in? Your groups?

Reggie Townsend

>> Yeah, so I actually chair the education and awareness work group, but I also sit on the workforce work group, so on education and awareness, we're very interested in things like AI literacy and making sure that the country, everybody in it, has an opportunity to not only understand AI, but has an opportunity really to enjoy some of the fruits of AI. And that's where the workforce piece comes in, right? Look, we recognize that any technology is a company generally with some level of disruption, and we want to make sure that that disruption does not occur at a rate that the country can't sustain. So, workforce is really all about understanding how we make sure that that doesn't become a reality.

>> I really wanted to get that up front before we get into the conversation because there's a great innovation opportunity for everyone with AI. At the same time people are concerned. So, is there a way people can get involved with some of these groups? Is it open to the public? How is it structured? Give a quick... I don't want to burn too many minutes here, but I want people to understand if they want to get involved, if there's an opportunity that they should know about it.

Reggie Townsend

>> Yeah. So, we'll maybe tag team this one. So, all of us who sit on the committee were nominated to be a part of the committee, and there was a whole vetting process, so we're special government employees. As a consequence, I don't know if everybody wants to go and work for the government or not. But in that sense, as Miriam said earlier, our task really is to advise the president and the White House, the AI initiative Office specifically and OSTP, on matters associated with AI. Part of what we've done as a function of that committee, however, is in fact broaden the access as much as we can so you can find out when we're meeting, and a lot of times we have briefings. And we make that available, all online. People can stream right in. In fact, if you're in DC, a lot of times people can just come because we know this has to be an everybody all in moment and so-

>> They can consume the content. They can consume the content and maybe-

Reggie Townsend

>> And participate to creating that content, because we're looking to hear from people so that we can incorporate some of those thoughts into our recommendations.

Miriam Vogel

>> Yeah, exactly. As Reggie said, there's both the standard mechanism, so it's a federal advisory committee. It's governed under FACA, which is an affectionate term in DC to describe these committees that come with a lot of regulatory requirements. One is all of our meetings are live-streamed and open to the public, so people can send in comments in advance, they can come in person and ask a question. We leave time at each public session for that. And we issue reports and provide an opportunity for feedback. We have an email. All this information is listed on AI.gov/NAIAC, N-A-I-A-C. But a part of what we did adding to our mandate is, as Reggie said, it's so important to us that we hear from more voices, leading experts and new experts, new voices, those we don't hear from enough. We want to make sure that they're incorporated in our advice, in our education and opening up the tent. And so, we have had many panel sessions. We had one just yesterday. They're all online, they're livestreamed and recorded, so people can enjoy those as well.

>> Great transparency. Thank you

>> for sharing.You're very thoughtful individuals and thinkers. It's not like you're trying to control the world of AI, but there are people, big tech in particular, very concerned about regulation. Maybe that's a way to say, "Hey, let us self-regulate," which is probably not the answer. What does history tell us about the impact of regulation? And knowing what you know, how do you think with this world of AI, we should be thinking about regulation in AI? To be flexible, to make sure the innovation is there, but at same time create safety?

Miriam Vogel

>> I think if done right, regulation helps build trust. It helps support innovation. So, first of all, building trust. If people aren't going to use it, it didn't happen. We need to make sure that these are systems that people want to use so that it can be the democratizing force that we want it to be, so that it can up-skill and broaden education and create these healthcare outcomes that are just so exciting. But we have to make sure if we hear a healthcare outcome, if we hear that we've learned that dermatological screening can be 93% effective when used with AI. We've learned that from recent studies that costs can go down 50% and upgrades in healthcare offerings can go up 40% if we're using it right. But we have to make sure, is that true for all Americans? Is that true for all of our citizens? Have we tested to make sure that it's not just who's been tested in a clinical trial because that's often going to be predominantly men and predominantly Caucasians. Do we know that if a doctor is giving an indication to a patient that they're not giving a false negative because that person has not been part of the representative population that's been tested and trained for with that AI system. So, building trust, making sure that there are safeguards in place can help build trust-

Reggie Townsend

>> Accessibility, to your

Miriam Vogel

>> point.And that brings up another whole point of who can use it? Can the AI hear all of us? Can it see all of us? We've had several federal agencies come out and share the laws they have on the books currently are actually applicable to AI in addition to the additional regulations that we'll need. When you say accessibility, the EEOC was one of the first out to say, "If you are using AI in how you're working with people in your employment systems, you are regulated by us and our civil rights laws." And they had a first joint historic statement with the Department of Justice saying, "You better make sure that everyone can equally hear what you're producing on AI, see and other forms of inclusivity, because you've got the Americans with Disability Act otherwise that you could be violating."So,

Reggie Townsend

>> that transparency is key.

>> That's hugely important. I want to make sure to jump on the idea of regulation because I think people tend to have a visceral reaction sometimes. And with all the conversation, it's going to slow down innovation. Stop. We have rules, we have laws, they exist today. And Miriam always says, "It's not like with AI, we're lawless here." There are a lot of laws that exist today that are already regulating AI, so we're really clear. I think what people are really afraid of is whether or not they will have permission to just run roughshod and do whatever the heck they want to do. No, is the answer to that.

>> Yeah, absolutely.

>> And nor should they, and nor have they ever able to. I think there's a little bit of disingenuous sentiment that creeps into that conversation. I think all of us mature adults realize that there are potential negative consequences that we have to mitigate. And all the, quote, unquote, "regulation conversation" is about is trying to mitigate those harms so that we don't harm actual people like you and I. That's it at the end of the day.

>> But the visceral reaction is, "Oh, the government can't keep up with the AI case." It's easy to say that, but at the same time, the example you gave in healthcare, I want regulation. Where it gets kind of interesting, and I'd love your thoughts on this. If the government says to Apple, you can't game the app store, good for them. They should do that. But on the other hand, if there are certain regulations that large companies can actually afford to follow, but a small company might not have the resources... You understand, I'm sure you've heard this all the time. That's a tricky balance for regulators. I don't necessarily have the answer. I'm sort of looking for answers and I think we evolve it as we go.

>> Yeah.

Miriam Vogel

>> I think part of it is demystifying. When we're talking about regulation, it's such a big word and it's such an unfriendly word, but if you think about where has it been helpful? Where has it helped in trust or spur innovation? Think about in airlines, people generally feel safe because they know it is regulated. There are rules. If you're driving, there are lanes on our roads, and for the most part, people stay within their lane. They know to stop at a stop sign, and not every street has the same speed requirements, but we know that there is a speed requirement. And so, I think that's a really good model. Not every state, not every action, not every level of activity needs the same level of oversight, but if we're talking about areas that could be really dangerous, if we're talking about areas that are high impact in hiring, healthcare, et cetera, I think that's an area where we want to make sure there are clear rules.

>> It's interesting you both have that perspective, and I think that I love that standards view because look at roads, you got to get the infrastructure done right, the foundation. And if you over-build, over-rotate, whatever word you want to use, on things that are hypotheticals that might happen, you got to get the basics right. Rules of engagement, how do we do that? So, I think that's good. And I wanted to get in on this because I think there's other things we can look at. For instance, the FCC, broadband, AI fits into that. The domain name system started in America and then became global phenomenon. So, AI's got this global piece, so now we have global AI, geopolitical overlay to that. Really interesting kind of dynamics. I've never seen this before. How would you compare this challenge or opportunity with policy in the US now, notwithstanding the innovation opportunities, just to make it work? How would you scope the challenge? Like hella hard, or doable, attainable?

Reggie Townsend

>> I think those things where you bite the elephant a bit at a time, right? First of all, start with the definition of AI. And I know we've had several of them here in the US and there's been agreement between both sides of the Atlantic, at least now on a clear definition. So, you got to start there. I think we can debate the implementation possibility of the EU AI Act, but I think they did a good job in terms of at least approaching this from thinking about risk, to say, "We recognize we don't want to capture all things AI. That's not the point. But if you are going to execute AI in a certain domain that might have a certain impact, we should know about it." Right? I think that's a reasonable approach to this for now. Now, the reality is right and wrong is always going to be a function of time. What might work now may not work five years from now. And so, the ability to look at that from a longitudinal view will be really important. So, we're monitoring the AI over time. But I cannot overemphasize this idea of use case, and we talk about that a lot at SAS, right? It's like AGI is not all of AI, LLMs are not all of AI. We do a lot of AI that has very specific use cases in pharma, financial services, law enforcement and what have you, and it's really important that we get those bits right, especially because they represent a level of risk that would be unacceptable if we got it wrong. If you want to go out and figure out your travel plans, okay, great. You can have some variability on that. I'm okay with that. But not in some of these highly impactful areas that, by the way, are already regulated. So, we got to make sure we get it right.

>> Well, I mean EqualAI, that's in the name. Love the name, by the way, of the company. My big issue, kind along Dave's line, is that the entrepreneurial opportunity in this country is what we've been founded on, and there's been talk, which I've certainly said this on theCUBE and other events, the rich get richer with the cloud and AI, except, to Dave's point, scale is about size. And so, I joke about the GPUs for America, campaign meaning you get public service GPUs, tongue in cheek. But really that's scarce resource power. So, as the infrastructure gets richer and gets bigger, it's going to be harder for equality for me to compete or do something entrepreneurial or provide a service potentially. I bring it up only as a hypothetical, but that's a scenario that could play out. And again, things like broadband in rural areas was an area where that was mandated. That was a policy decision I thought was one of my favorite things Bill Clinton ever did. Farm Bill. And that was great, but it kind of didn't happen. It's good it passes but . What's your guys' view on the ability to move the needle faster to get it done right so that we can have the opportunities and symbiotically live with the big players? Is that a factor or am I overthinking this?

Reggie Townsend

>> No, it needs to be all hands on deck. I think the stakes are high enough that I feel comfortable that people are going to rise to the challenge. We will not have a sufficient workforce. We will not have a strong enough economy if we do not have more people ready to participate in our AI economy. And that doesn't mean that everyone needs to be a computer scientist, but it means you need some more AI literacy, like what Reggie was referencing earlier. I think the good news is when you're talking about the international front, I mean it's such an important point. AI doesn't have boundaries, so how are we going to operate in a false narrative where we are looking at certain domains to understand what the rules are? The good news is both for that and in thinking through innovation general, we've had some significant steps forward. So, we've seen some activity in Congress. We've seen a lot of work where they're trying to educate themselves with the insight forum, that was a bipartisan bicameral effort as well over the fall. We've seen the president's AI EO, executive order that was released in October that I believe was the longest in history with 150 action items assigned to over 50 federal agencies and quasi-federal agencies.

>> I

Reggie Townsend

>> don't know that they like to admit that it was the longest.Keep people busy while the change is going on. Keep your day job, Reggie.

>> There are deadlines coming up in the next week, 120 day deadlines where action plans are required. So, I think they have at the Department of State, USAID, they have significant taskings there. But also we should note that it's been building on actions that have been underway. So, it's not lost on anybody in the federal government that there needs to be collaboration in order for the rules to be meaningful. So, the there's Trade Technology Council, there's several established entities, the OECD in which we participate, as well as other government bodies and organizations through which we've been participating to make sure that there's alignment and clarity.

Miriam Vogel

>> So, I know we're talking US, but we got to keep in mind, this is a global conversation. Right? Now, here in the US, one of the recommendations that we actually offered on NAIAC was that the White House support the idea of the National AI Research Resource. And what that is expressly designed to do is to provide access to those small businesses, to those entrepreneurs because we recognize that there is a bit of an arms race to gain access to platforms. So, that's one. Two, I think we have to also question the premise, and I think they're doing this in a lot of other nations, questioning the premise of whether more is necessary to be more performative. And there are actually studies to show that-

Reggie Townsend

>> More AI or wait, what do you mean?More

>> data, more GPUs in order to reach levels of performance that are necessary. So, what's your goal? Is your goal to build the next largest foundational model with billions of rows and parameters? Okay, that's one thing. But if your goal is to simply use AI to advance the needs of your business and you're not in that business, then that's something completely different. And so, I think we got to kind of cut at this a couple of different ways. And when you look at what's going on in a lot of different nations, they're cutting at it, I'm sorry, from the latter way because they recognize that they're not getting in the foundation model business.

Miriam Vogel

>> There are a lot of wealthy nations and a lot of wealthy companies trying to get to AGI and they're trying to throw as many GPUs and as much data as possible. Are you suggesting that there should be, and maybe there already is, a conversation from government in terms of regulating that or at least having some degree of transparency around that? I wonder if

Reggie Townsend

>> we can -So, I wasn't making that statement just now. We can have that conversation though. I think in terms of purpose, let's have a broader social conversation and not just leave it up to a handful of tech bros as to whether or not we ought to create something that is cognitively superior. I think that's worth the conversation.

>> Open and transparent has to be there because we are living in an era where the title of this is Navigating Ethical Horizons. That is a huge three-letter words, three words. Ethical is a big part of this. Ethics.

Reggie Townsend

>> Of course.

>> But that is happening.

Reggie Townsend

>> It's happening.

>> And there doesn't seem to be any kind of guardrails on that.

>> Right. So, again, this is a collective action issue. We can't just leave it up to a handful of tech companies and we can't just leave it up to a handful of governmental leaders either. This is why this idea of literacy is so important to me. We've got to make sure that people are empowered with information so that they can figure out for themselves, if they are okay with the direction that we're headed with things like AGI. Now, AI is much bigger than just AGI. Let's just say that out loud. And it's okay for them to question some of those aspects as well. But first you got to educate people on what it is so that they can have a better sense for whether or not they're willing to accept how it impacts their lives. And last bit, when you look at studies globally as to whether people are okay with AI, generally speaking, what you're starting to see is a rise in AI anxiety more than a willingness to accept AI. And that's problematic for folks like us at SAS. We're providing this product, we want to make sure that people eventually embrace it. We think we're doing it for the right reasons. But if they're just freaking out because they hear AI, that's problematic for us and everybody else.

Reggie Townsend

>> It's a huge problem. We've been hardcore reporting this because we've seen evidence, real evidence and examples of people and companies that have changed their outcome of their situation by having access to AI and knowledge to level up. There's a huge leveling up opportunity. Anyone could get to a point quickly. You don't need to have a many, many years of computer sciences, but I think you mentioned computer science, you can be smart and instantly smarter. So, I think access to AI is going to be the critical thing and it can't be one company.

>> I think it's a really important point that you're making. I love this conversation. You can talk about products and stuff, but AI makes you smarter. Who doesn't want to be smarter? At the same time, I worry that if some rogue nation gets AI before we do, I think we're the good guys. Not everybody would agree with that. But that scares me. But I'm an AI optimist like John because it makes me smarter.

Reggie Townsend

>> Well, this is where we debate all the time. This is not the Manhattan Project as Vinod Khosla thinks it is. He said that publicly.

>> I mean, how do you know?

>> Well, because open source is already global and it's already happening. So, for this to be a Manhattan Project, we have to have a national cloud, one. A national AI cluster, that would be national security based. Probably do. But AI is already open source globally, so we have to change the paradigm of open source. So, that would be a policy question, how do you enable the growth of open source software?

>> But it's how you apply that open source software, right?

>> I'd want to see a

>> -I don't know, what you guys think.I

>> don't see .This

>> is the debate of our time.

>> Absolutely. Yeah.

Reggie Townsend

>> And I think it's important for us all to take a breath and take a beat and say there are just some things that we don't know.

>> Unknown.

Reggie Townsend

>> Now, it's okay to hypothesize about some stuff, but to me it's much more impactful to say we've got something that makes us smarter, that we can apply today to people who could use this capability. So, if we could take, I don't know, 25% of our energy and redirect it to people who are without today. So I was a couple of weeks ago in London talking to the folks at the Commonwealth. Oh, the Commonwealth has like 33 small states, but they've got like two and a half billion people. So, the 33 small states are just kind of the smallest of all of the nations that they cover. These are nations that don't have the infrastructure to support a big data center full of GPUs and all of this sort stuff. These are also the nations that are the less developed on the globe. And so, who are we to be talking about all of this turning into different species when we are leaving people behind today? Today. So, if we could figure out ways to help them embrace this technology to grow economies today, to me that seems like a better use of our time than exploring the possibilities of destroying us all.

>> Reggie, that is great vision. Your passion's awesome. Appreciate you for that. And thank you both for coming on theCUBE here.

>> Good to have you.

>> We're going to wrap here, but would love to follow up. Miriam, we'll give you the last word. Love your company. Give a plug for what you guys are doing. Give a quick highlights of where you're at, what you're working on, and what you're hoping to accomplish.

Miriam Vogel

>> Absolutely. At EqualAI for five and a half years, we've been trying to get people to focus on what it means to be a responsible AI actor. The hard thing is it's not clearly defined in national standards or international standards like we were just talking about. So, in the meantime, we work with companies who want to lead in this space and help them align on what is the best practice, what does one do to make sure that they're being responsible and thoughtful and build that trust with their consumers. We also work with policy makers to help them establish what are the right guardrails, exactly as you said, so that they can make sure they're spurring innovation and not inhibiting it.

>> Awesome. And Reggie, a quick plug for you. I know. Quick plug.For what SAS is working on, the ingredients, the nutrition label you have. You call it the nutrition label for AI. What is that about?

Reggie Townsend

>> So, these are model cards where we're able to evaluate the health of a model, any AI model for SAS and Python today. It's the equivalent of a nutrition label that we get on our food, but this time for AI. So, get a chance to see levels of fairness and transparency, if a model is drifting over time. So, we should all be able to evaluate the impact.

>> So, we're going to call OpenAI the supersized model, and we going to have to go on a low calorie, smaller model.

Reggie Townsend

>> The sodium-free. Yeah.The

>> smaller models actually turn out to be pretty agile.

Reggie Townsend

>> Great. SAS and Python and R is coming. Yes?

>> R is coming. Yes, sir.

>> Miriam and Reggie, thanks for coming on

>> theCUBE.Thanks, you guys.I appreciate it.Okay,

>> we leave it there. I'm John Furrier, David Vellante. You're watching theCUBE. We'll be right back after this short break.