Robert Levitan (Ethical Tech Project): Unlimited Intelligence, But Where's the Wisdom?

0:08Kevin Werbach: Hi, I'm Kevin Werbach, Professor of Legal Studies and Business Ethics at the Wharton School of the University of Pennsylvania. For decades, I've studied emerging technologies from broadband to blockchain. Today, AI is promising to transform our world. But AI needs accountability, mechanisms to ensure it's developed and deployed in responsible, safe, and trustworthy ways. On this podcast, I speak with the experts leading the charge for accountable AI.

0:40Kevin Werbach: Robert Levitan was an executive at some of the first successful internet companies during the dot-com boom, and then has had a long, successful career as a serial tech entrepreneur. He's now chairman of the Ethical Tech Project, where in full disclosure, I'm an advisor. We talk about his sense of the parallels between the early internet and the AI world of today, why it's critical for companies to do something to get started on AI governance, why that's ultimately in their interest to be ethical and focus on accountable uses of AI, and why, despite it all, despite all of the risks and despite the likelihood that we will see large, significant AI harms in the near future, he's still an optimist.

1:26Robert, really delighted to have you on the podcast. So happy to be here.

1:31Kevin Werbach: You and I have known each other for a long time, going back to when you were the CEO of a dot-com startup called Flues and my wife became your general counsel. and you've done a lot since then, other startups, other work in interesting areas. What got you interested in AI governance? Well, for those of us who were around in the 1990s, and actually my first internet company was iVillage, and we know each other back then from 1995. It was such a great spirit in the early days of the internet. We were all optimistic, and we thought we were changing the world for the better. and we just wanted to connect the world and share information.

2:12And we really thought we knew something, right? We knew a secret. Well, we learned a lot of lessons, didn't we? And over the last 30 some odd years, what we learned is there are always unintended consequences. New technologies always have unintended consequences. And what we thought we were doing, building online communities, turned out a little different than we expected. So I found myself about a year ago going down the AI rabbit hole, but not down the AI rabbit hole of, I've got to start another company. I've got to raise venture capital. I've got to do this much more. Wait a second. This moment in some ways feels like the early days of the internet.

2:51And in other ways, it's very different. And what lessons did we learn? So I started writing on LinkedIn about lessons learned and how we should be approaching this moment, which is obviously really important. And the next thing I know, I got a phone call from the Ethical Tech Project and they asked me if I wanted to get involved. So that's how I arrived at this place. And I'm so excited. I can't think of anything more important than being on the road to accountable AI or teaching ethical tech, responsible AI, whatever you want to call it right now. And people like you and I to be sharing whatever insights we have.

3:31Kevin Werbach: Absolutely. What are some of the parallels that you see to that experience back 20 or 30 years ago? Well, you know, I do think that when I talk about unintended consequences, of course, you know, one of the great moments that we thought happened in the early days of the O-Net was like section 230. You know, I was running online community or involved with online community IVILs. We thought 230 was the answer because, you know, we couldn't monitor everything and we had some rules, but this, well, it turns out this is a prime example of something well-intended, probably meant to be revisited, never revisited, now interpreted in a way that people today think, well, that means you can say whatever you want on the internet and it doesn't matter.

4:16That wasn't the intent of Section 230. You know that. I know that. And yet I hear people say that. So the big lesson is that, one, there are always going to be unintended consequences. is two, you need to think a little more carefully now. Instead of move fast and break things, I think we all know the internet, you can move fast and break things. It was just a browser. Nothing bad was going to happen. Now we've got the internet on top of mobile, on top of AI. And if you think fast and break things, you're going to really break things and it's going to have a really bad effect. So we need to think a little more before we deploy technology.

4:58And every company has a responsibility to be thinking about what they're building, what could go wrong, and how to create whatever guardrails can keep you accountable. And the other thing I'll say, trust has always been important. Trust is more important now than ever. So why should a company do this? Well, number one, we're not going to have a lot of government regulation around responsible, accountable, ethical use of technology. But if you lose trust, it's going to really hurt your business. And with AI, you're likely to lose trust. So every company should think about how to put in guardrails, think about what could go wrong, and come up with their own version of a responsible or accountable AI plan because it's a competitive advantage.

5:50And we've seen that in the marketplace already.

5:54Kevin Werbach: So as you described, you joined as now the chairman of Ethical Tech Project. Let's get some context in or tell us about what that is and how it's evolved from where it started. Sure. So the Ethical Tech Project was actually started about six years ago by two tech entrepreneurs, Tom Chavez, Vivek Vaidya. and Tom and Vivek actually started two companies, one called Wrapped and one called Crux. And these were actually data marketing companies. One was sold to Microsoft and one was sold to Salesforce. And Vivek actually went on to be the head of the Salesforce marketing cloud business, the engineering head of that.

6:37They know data. And about six years ago, So they were on the leading edge of data privacy. Yes, it's really important. And if you're going to have an ethical company and you're going to be in marketing, you better make sure you've got the right data engineering and data privacy policies. So they were way ahead of this. So they funded the start of the Ethical Tech Project because they believed in the importance of trusted data. Well, guess what? What's at the core of AI? Data. Bad data, bad AI. so it's a logical thing that ethical tech project is about trusted data and then other deployments of that including ai so that's the history of the company um we like to call ourselves a think and do tank yeah why yeah you like that right i mean you and i are doers we're not just thinkers um you're probably more of a thinker and i'm more of a doer.

7:38I'm not sure you're an academic, but you know. We're all these both, yes. But think and do. Why? There are a lot of people thinking about AI policy. There's a lot of people thinking about all kinds of AI stuff, but just talking about it isn't enough. You know, we believe that we can think about these things, but then we have to teach them to people actually building AI. So what the Ethical Tech Project does primarily is we try to work with people who are deploying AI and help them figure out how they can deploy AI. I was going to say help them think about, help them do, but we're not technical.

8:16We don't go in and do the tech for them. And we're not just teaching them to think. We're saying, okay, here's a real-life scenario. What do you do? You've got an option here of using the data in this way, or you can use the data that way. What do you do? What are the choices? What are the implications? What's the trade-off financially, ethically? So we teach this to two different distinct groups of people. One is engineers, product managers, business leaders who are in their early to mid-career stage. And we teach what we call the Ethical Tech Project Fellowship. so here we'll take uh 20 people out of about two to 300 applicants and we'll spend 10 weeks with them every thursday night for two hours for 10 weeks and we've had three cohorts of this group and i'm talking about executives from google deep mind bank of america roku amazon google other products, you know, Roke, whatever.

9:18It's Spotify. I mean, we've had some really great young people who have self-identified. They've applied and said, I care about ethics. And it is amazing to see. I mean, they're deep inside some of these companies and they are thinking about ethics. So we're trying to help them translate that because we believe that's where change happens. The other thing we do is we work directly with companies. And this, I think, is really important. We get it. It's competitive out there. I'm an innovator. I'm an entrepreneur. I know what it's like. I know it's like to raise venture capital. I know it's like to be on the flywheel, and every six months you better make progress.

9:55But how do you, in that environment, think about being accountable with your AI deployment? And the answer is, well, you can work with us. We'll help you think about it. We'll be your partner. We'll bring best practices to you. We'll bring experts to you. will help educate your team and will even help you develop an AI governance plan. So to me, this is kind of our golden moment as the Ethical Tech Project to go into a company and say, okay, you need a governance plan and you need not something off the shelf. It has to be tailored just to you. How are you going to do that? Well, you're going to think about what are your core principles?

10:34What's your mission statement? How do we translate those into core principles of an AI governance plan, and then how do we build that plan, and then how do we implement it? So we will help companies do that. Now, we're not the monitoring tools. We're not any of the technology behind tracking your AI deployments, but we are a great thought partner to help companies do that in a way that is very specific to them and aligned with their core values. And we think that's the first step for every company having an accountable AI program.

11:08Kevin Werbach: What is your sense at this point about how much companies are at that stage where they get it, they realize this is an issue, they need to do something about the need to invest, but they don't know how? So I think every company is thinking about this. And when you read recently about, you know, OpenAI and Anthropic and everybody's got models that are breaking out, every company knows what can happen. but they they're almost paralyzed by how fast everything's changing and i don't know and should we invest any time and money and what should we do and frankly they think i literally had a conversation yesterday with somebody who said well you know i said look you need to have this because you've got legal and regulatory risk and they said well i think we're pretty good on the regulatory risk.

11:58We understand all the policies and our AI is internal. I think we're okay. What do you mean legal and regulatory risk? I said, well, guess what's going to happen? Your AI is not always going to behave the way you think it is. And somebody is going to be affected. Now, it may be one of your employees. It may be one of your customers. It may be a business partner. And guess what's going to happen in lack of clear legal rules, they're going to sue you. And whose fault is it? You built AI on top of some other model. Well, guess what? They're going to sue your company and they're going to sue the model and they're going to go to court and this is going to get resolved in litigation.

12:43So don't wait for the dust to settle. Be proactive. Go out, build an AI governance plan to mitigate that risk one that if something does happen that's not aligned you should be observing and aware and able to fix it two you should be able to go to court and say no no we we did all these things and you know and they thought like well you know we're just using it internally whatever but no the reality is yes every company is aware of this but they're not moving enough And maybe they just don't know, you know, like, so they spend$200 ,000 and have some consultant come in and build them an AI governance plan and take nine months.

13:27Kevin Werbach: Now, my answer is hell no. Whatever the question is that you're going to spend a bunch of money on the consultant, the answer is probably no. Is no. And you and I both know this is going to evolve really quickly. So what you want to do is go out with kind of core principles that are, you know, are true, but be able to adapt. But put something in place. Don't freeze. And we're here to help companies do that and do it very reasonably because we're on a mission. We're nonprofit. We don't have to answer any shareholders. Yeah. No, I want to go back to where you started with the comparison to the early days of the Internet and the dot-com era.

14:04Kevin Werbach: Because you are out there talking to companies and seeing what engages them in this area. You know, the big difference for me from back then is, you know, you take everything and it's just so much faster and there's like two or three more zeros behind everything. Wow, this is so much at stake. So certainly, you know, we have the experience of what happened with the Internet and social media and digital platforms. You're absolutely right. Back then in the 90s, we were all so optimistic and naive about the potential of the technology, which is real. all the good really happened, but also there was the bad.

14:41Kevin Werbach: Nowadays, I think no one comes into tech not being aware of all of those problems that have come up. So it's always on people's mind, but we're in this environment where companies are being told you got to do AI transformation yesterday. So in that kind of situation, again, given how much is at stake, how do you make the convincing case to people to step back and do that kind of governance exercise you're talking about well i mean one of the things i i try to impress upon people and you're so right and guilty as charged we were so nice i mean that's you know something we learned that yes the stakes are so big now that you have to move fast you have to compete but you also can't afford to make a mistake and of course i use examples of people that i think are positioning themselves as ethical companies.

15:35And, you know, and of course the two biggest ones, you know, let's look at Apple and data privacy. Like they got a lot of benefit from that and they leverage it well in the marketplace, get some premium pricing. And the other, of course, anthropic and the way they position themselves. And so what I say to companies is, well, what do you want to be? You know, you want to be in your industry and be trusted and be the partner who commands maybe some premium pricing or do you want to just you know throw a lot of spaghetti against the wall you can't afford to do it but yes there is less naivete for sure but as you know and i know the compliance departments or the risk departments or the ai governance departments in these companies is not yet stacked not yet fully staffed and they don't have budgets and they don't have resources but one of the things i tell them to is don't create everything in-house one of the things i see which i think we get a little pushback on is wait a second okay these people are gonna come in and they're gonna help you think about a governor's plan based on the company core principles and ethics and then they may tell you that we will there are companies that can build tools to monitor your AI department.

16:58And in fact, one of the companies, of course, is somebody I met on your show, Andrew Burt and Luminos. And I recommend them. I say, you should go talk. But then some of them have internal departments. No, no, we got it. You know, we're building it ourselves. And I think that's a big mistake. I think that's a big mistake because as you and I both know and we learned the early days of the internet, I mean, all of us built everything. And now it's all, you know, we plug and play the best. And I think people have to do that here. The compliance people need to think that, yes, the tech people want to build everything themselves, but they shouldn't build their own tools.

17:37So there are definitely a lot of challenges. Some companies don't make it a strategic priority. And I feel sorry for them because I do think the litigation is, you know, it's already starting and it's going to happen more. my my my line to them is look it took 30 years for you know the internet to get litigated to multi-billion dollar what's it going to take for ai two years multi-billion dollar settlement well

18:01Kevin Werbach: we've already had that the anthropic barch settlement is one in that billion dollars well there you go so it's all going to happen faster including the litigation but you're right getting people to move you know you're out there preaching it and getting people to move on this stuff. Now, I have one theory and I'm an eternal optimist, but this may sound a little pessimistic. Yes, people are pinging me. I should turn that off. But I recently wrote an essay about the triangle shirtwaist fact. Yeah, I was going to ask you about it. So go ahead. Sure. So, you know, it's on LinkedIn and I'm a student of history.

18:36I also studied public policy in high school. But then I went and I was a tech entrepreneur. And then one day I'm in New York and I'm walking past this building. And it's where in 1911, there was a fire and it was a sweatshop making shirts and clothing. And the people were locked in. There was no fire escape. They were locked in because owners wanted them to work and not to steal things. And, you know, 146 people died quickly. Many of them burned to death. Some of them jumping from the ninth floor of a building. It was that that triggered workplace safety regulations, that all of a sudden you had to have fire escapes.

19:17You couldn't lock doors. You had to have certain spacing. You couldn't have fabrics lying on the floor that were flammable. You had to have sprinklers. In fact, it was that that also inspired a woman who became the Secretary of Labor for FDR, Frances Perkins, who then triggered the whole New Deal. I mean, the whole New Deal workplace, 40-hour work weeks, no child labor, social security, unemployment insurance. And I wrote an essay saying we're going to have an AI moment. That's like the Triangle Shirtwaist factory. And I really don't want this to happen. But I think everybody, as you say, does not have the naivete.

20:01We know this is going to happen. And this is going to be a moment. There are already things that have happened that are not good, that are really, really bad. And, you know, anytime you hear about a teenager and suicide, you're like, oh, this is terrible. But something's going to happen and it's going to be some bank's going to get hacked or some, you know, deepfake video is going to incite riots or some health care institution is going to misdiagnose thousands of patients. and something bad is going to happen where a lot of people get really badly hurt and i think then what we're going to have and you're starting to see it but i think then the people are going to say to elected officials we have to do something we have to have some guardrails yes we need to compete on a global stage but we can't put lives at risk here and you know what happens if 10 000 some people in a bank account get in their bank, get their savings all wiped out.

20:59I mean, it's really serious. So I wrote that essay. I hope it's not true, but I kind of believe that's probably what it's going to take to wake people up.

21:09Kevin Werbach: Yeah. But if that's the case, let's say I'm a company that's deploying AI, why shouldn't my response be, obviously, I don't want that disaster to happen, but it's going to happen and then regulation is going to come in. It's going apply to everyone and then I'll have to do it then why should I be investing my time now ahead of that well I'm gonna give you two reasons you know uh you know one is I think the businesses between now and then that don't proactively explain to their employees their customers and their business partners, how they're using AI are going to see their market share decrease.

21:56So number one, I really, really believe, you know, let's just take employees. They're nervous. They're going to lose their job. If I were running a company, I'd say, okay, look, what we're going to do is AI gives us unlimited intelligence. It doesn't give us wisdom. You all have wisdom. You've been in this business. What we're going to do is we're going to grow this company. What we're planning to do is grow the company with the number of people we have, but be a lot more productive.

22:23Kevin Werbach: That's the goal. And these are the core principles of the company and we're applying it to our AI and da da da. So we're going to make you partners fully informed. So we're going to be transparent with our employees as best you can. Doesn't guarantee we're not going to eliminate jobs. We might have attrition. We may not rehire people who leave, but this is, you know, be clear. Then there's business partners and customers, both of them. They're a little different, but both of them want to hear that you, if they do business with you, your business, that your business has an AI governance plan, you have tools, you're monitoring, that them doing business with you will not create risk for them.

23:02They will not be in the press, you know, being associated with something really bad happening as best you can. There are no guarantees, but we're doing this. And by the way, our business is distinguished from all these brand new AI startups that are just grabbing data and doing this and doing that and that because we're established and we're layering AI on top. And I say this, obviously there's some very reputable AI startups from scratch, but you can imagine there's all these incumbents that are fighting off all the innovators and the innovators say, we can do it less. We're moving faster. We can do it cheaper.

23:39We're doing it better. We're all AI. Yeah, but where's the wisdom? You know, now, am I being naive here?

23:44Kevin Werbach: A little. But number one is, I do think it's a competitive disadvantage. And then number two, and my title of the article about, is don't be the, and my subtitle, don't be the factory owner. Okay. So my subtitle to that piece about the Triangle Shirtwaist Factory Fire was, so if you own a company or you run a company and it happens on your watch and something really bad happens, it's a bad feeling. You could be personally liable. interestingly enough in this fire there the people who owned the factory were not found guilty um because they couldn't prove that they locked the doors and how the doors were locked they were found guilty in a civil not a criminal case and they had to pay a very small fee 75 dollars per person killed to the families but i can assure you in today's world if your ai goes rogue and something bad happens you're not going to pay 75 dollars per person you're going to pay a lot of money in and if they don't get you on the corporate liability they may get you on the civil so why do you want all that right i mean do the right thing that's a nice thing to say but business-wise this makes sense yeah is it most important for a company just to have something in terms of an ai governance framework how important is it to really get it right it's so important to just have something start somewhere because it's going to change the technologies are going to change your policies might change it's important to get something in place and then recognize you need to evolve over time in fact that's one of our lessons from the early days of the internet that whatever you build is going to evolve and you have to be that nimble and if you have something including an ai governance committee and i know that we're committee but you can build these in ways that they're not burdensome.

25:42But if you're monitoring what's happening and you're making adjustments and clearly you have to have the right guardrails for the right severity. So, you know, one of the keys is you don't build an AI governance plan and slow down innovation everywhere. It's like, oh, well, that's low risk and that moves faster. That's really high risk. We better be really careful with that. But yes, it's just important to get something in place, know that it's going to change. I would say don't overspend and don't spend too much time on the early part of AI governance. Get something in place. Understand it's going to evolve over time.

26:15And build some expertise in-house by starting somewhere or work with people like us who will help you get up to speed and then learn as you go and adjust as needed.

26:27Kevin Werbach: And let me ask you just about some more of the things that you've talked about or that the Ethical Tech Project is doing. You mentioned the fellowships. What attracts these early career people to want to go and spend the time doing this? Well, I think these are people who are so smart and so aware that they're playing with real fire. And they're idealistic. and to say I'm going to commit 20 hours over a 10-week period after work on Thursday nights in New York City where we did the last cohort, that's a big commitment. And I'm blown away by them, really. I mean, ironically, there are times I say, what am I doing teaching them?

27:11I mean, I understand, I have experience, and thankfully, they appreciate my perspective. But really, I'm in there with somebody from Google DeepMind, and we're talking about AI and ethics. And to hear this person talk about the level of awareness internally about ethics is much higher than you think, but you don't hear it. In fact, one little secret, which I think reflects well on Google and her, we were talking about, as a case study, we did a class, we go through the Facebook algorithm. And over 10 years, 10 different tweaks to the Facebook algorithm, what was the initial intention, what was the effect, and what was the compounded effect?

27:55So obviously switching from chronological to engagement, which post gets put at the top, had an effect. And then switching from text and photos to videos has an effect, et cetera, et cetera.

28:10And then we talked about also the awareness. I defended entrepreneurs. I think they just thought it would be a better experience, but at a certain point you have awareness that, wait a sec, we thought that tweak would be good, that tweak would be good for the experience, but now we're seeing the compounded effect and we're seeing there's some negative effects. At that point is when the company becomes liable. So we're having these conversations. And I kid you not, the person from Google said, oh, yeah, we're fully aware of this. We're being asked to think about the compound effect. And I thought that was great.

28:47Like it's having, so the court is having the fact that that trial was going on is before the settlement of a couple of days ago. People inside of Google are thinking about it right down to the, you know, people working directly on the product. So that's a good sign. Can they do anything about it? Not really. It's above them, but it starts to permeate. I don't know. After all that, I forgot what your direct question was.

29:15Kevin Werbach: I was just asking about the. But it's great. You got into a lot more of what's going on. Yeah. So, I mean, the second part I want to ask you is, okay, so you have these cohorts that go through this program. They get this knowledge and insight. What do they do with it? Well, interestingly enough, several of them are consultants now working for consulting companies or companies that have products to help people govern AI. so that's really interesting that they're thinking ethics and going into companies and so they're spreading that um some of them are product leaders who are i'll tell you our session on privacy engineering data privacy had a real impact on people who went back and said hey what are we doing here are we giving people real control over their data are we making it easy for people to manage their own data because we need to be a little more proactive there you know so i think that's what they're doing um some of them will go start companies actually in the space like some of them are starting companies trying to leverage ai and connectivity to try to create businesses that have kind of ethical outcomes as their um you know whether it's in whatever climate change or equal opportunity for hiring or education.

30:46Like there are people who are out there trying to figure out how do I use the technology? But we hope it just infects people. Like, you know, because, and you said it, because there's less naivete, because this is really the first big technology wave that you and I have seen that people aren't excited about. They're equally excited and afraid. Yeah. Okay, we were so excited about the internet, I was so excited about mobile phones. Heck, we were excited about satellite TV, whatever it is, right? Nobody was thinking, like, people lining up to get their first iPhone. Remember that? It was on the news.

31:22Hey, I got my iPhone. I'm so excited. I can look at this phone. And now, technology, people are equally excited and afraid. Because of all that, I think if we can help channel some of the knowledge, some of the fear into, okay, what can we do about it? How do we think about it? how do we channel this fear instead of just saying no,

31:44Kevin Werbach: no to data centers, no to this, I don't trust them, is what if we can demand from companies and certainly from frontier model companies, but from businesses that use AI that they explain to us how they're using AI, you know, why we should trust the data behind their AI. What if we work at places and we say we want to know these things? That maybe we can build a culture that technology is something that you don't just you know throw the spaghetti against the wall you think and and how do you think well you think a little bit about what what's our company mission where our core value is what what's the effects and how do you build guardrails that are simple yet not cumbersome and that's hard i know it's hard but if that's all we did is help people think great and everybody knows the difference when they see like grok nudifying images but open ai or anthropic or google gemini won't allow you to do that you know that i i sat in a restaurant having brunch and i listened to a conversation of some parents with some grant their their parents telling about their kids that they took their kid's image and they tried to put ai images on them and that grok would do it and the others all said sorry we will not take an image of your like you know 10 year old girl and and put in different outfits, it's against our rules.

33:08And I heard them say, oh, well, you can understand, that's reasonable, right? And so people know. That's ethical right there versus not, right? And putting something behind a paywall doesn't make something legal or ethical, just FYI. Yes, absolutely.

33:26Kevin Werbach: Well, so I think we conclude that you're still an optimist, as I am too. You know, you and I, I have my moments, Kevin. I mean, you know, I'm sure you do too, where, you know, I'm scared and excited about the potential, but I do believe that in general, with just a little human involvement, AI can deliver more benefits than harms. And by the way, we have examples. And I'll just quickly, I like to think about industries. And what I would say is you and I probably have, I don't know, you and I have this conversation, a gut instinct about some industries where AI will have more benefits than harm.

34:05And one of them is healthcare. Why? Because healthcare has two things I say every industry and every company should have. They have an ethical framework and they have some guardrails. the ethical framework of course is the hippocratic oath that people in this industry take an oath not to harm and to help people and that's part of their pledge number two they have guardrails they have the fda they have hipaa regulations on data so these two things actually make me feel more confident bad things might happen in health care but probably less than in other industries right social social media of course a lot of bad things but i would argue that the financial industry probably has a lot of regulations that will help it in the long run hopefully be safe um but yes i am still an optimist i do this obviously there's volunteer work because i believe that maybe some of it will seep in and become part of the culture i know you do the same you teach students every day and we just hope it has some some effect right because uh we are so privileged to be living at this moment in history and for us to lend, even though we were naive and made some mistakes, to at least lend our perspective and experience and stories, if it can have some positive effect, well, I feel pretty good about that.

35:30I like to be doing that.

35:34Kevin Werbach: Robert, it's been delightful to speak with you. Thanks a lot. Thank you. My pleasure. This has been the Road to Accountable AI. If you like what you're hearing, please give us a good review and check out my sub stack for more insights on AI accountability. Thank you for listening.

35:52Kevin Werbach: If you want to go deeper on AI governance, trust, and responsibility with me and other distinguished faculty of the World's Top Business School, sign up for the next cohort of Wharton's Strategies for Accountable AI Online Executive Education Program, featuring live interaction with faculty, expert interviews, and custom-designed asynchronous content. Join fellow business leaders to learn valuable skills you can put to work in your organization. Visit execed.warden.upenn.edu slash ACAI for full details. I hope to see you there.

36:37Thank you.