The Future of AI and Business Education – Wharton Global Forum São Paulo

It is now my privilege to welcome Eric Bradlow, Vice Dean of AI and Analytics at Wharton, KP Chow Professor, and Chair of the Marketing Department. Eric graduated from Wharton in 1988 with a distinguished career. His groundbreaking research spans various academic disciplines, focusing on tech enabled data and its application to business challenges. He's a renowned scholar and an award-winning educator, and he is now leading Wharton's brand new AI and analytics initiative as The School works to become the world's leader in AI. Welcome, Eric. Thank you, Debbie. I stand here humbled in a lot of ways. As Debbie mentioned, I'm just one of you. I'm a Wharton alum, and a proud Wharton alum. I'm also the son of a Penn alum, I'm the parent of two Penn alums; and soon my youngest son, Ben, is joining the class of Wharton 28. So, I'm as red and blue as anybody here. Thank you. A month ago, my life changed, and all of your lives changed in a way you may not appreciate. Thanks to the strategic vision of our Dean - and I say our Dean - Erika James, Wharton committed itself to be the number one business school and leader, thought leader, in artificial intelligence and data science. I have to admit I've been through six deans in my 28 years as a faculty member. I've been waiting for such a phone call patiently, patiently, patiently. And it took the leadership of Erika James to recognize that for Wharton to be number one - and we're number one, everybody knows we're number one - but for Wharton to sustain itself at number one we have to be the leader at artificial intelligence and data science and its application to business problems. Then, of course, she asked me to be Vice Dean, and that's when I started sweating a little bit as anybody would. So, what I want to talk to you now is let's imagine what our Wharton School could be like if we were the leader in artificial intelligence and data science. So that's the journey in the next eight or 9 minutes I want to take you through. So first, let's imagine students learn by doing. So, for example, many of you may have other institutions you deal with. I went to one in Cambridge, Massachusetts for my PhD. When they do data science, they talk about data science. When Wharton does data science, we ingest data from companies, work on real business problems in real data, our students learn data science by doing. So, when Alberto, Roberto, etc. want to hire students, they know they've actually done data science, not just talked about data science. So, we're the Ôlearning by doingÕ school. The second thing is all of these colleagues in front of you - Lynn Wu gave a presentation yesterday Ð imagine a world where Wharton had tons of scholars in every department doing work in artificial intelligence and data science so that we could have hundreds and hundreds of courses. Wouldn't that be wonderful? Be great. Imagine that. That would be great. Imagine a world where I could act as a venture capitalist and invest in the next big idea of The School. So, for example, - oh, there we are - for example, we just started a health care analytics lab at the school. Something I've been talking about with many alums. We're going to solve, Wharton is going to help solve, the world's health care crisis through predictive analytics. We're not going to treat you when you're sick. We're going to prevent you from getting ill. And data science is going to play a big role in that. We're working in tons of areas now: neuroscience, ethics, etc.. Also, imagine a world where Wharton partnered, my colleague Lori Rosenkopft, I don't know if she's in the room at the moment, but one of the things we're also doing is we're partnering with Venture Lab in entrepreneurship to incentivize students to start the next big company in artificial intelligence and data science. So, we're actually giving monetary prizes to the best startup company. That sounds pretty exciting. And the other thing I would say is we're also doing what I call Ôhashtag analytics for goodÕ. We're also partnering with nonprofits and other organizations to bring data science to bear to make the world a better place. Now, when I say imagine all of that, I've spent five minutes already of my time, four minutes of my time and I've just been lying to you for the last four minutes. All a lie. Everything I presented to you so far, we're already doing. Now I want to spend the last six minutes tell you about what we will be doing over the next two to three years. But imagine, we have great faculty already. We already have students doing experiential learning. We're already ingesting data from companies. We're already having students like Rafael, who's going to be coming soon, working on real data and real business problems. We're already working with nonprofits to make the world a better place through data science. Now, let me tell you what amazing things we're going to be doing over the next two to three years. When all of you come back to the forum in two years and I'm standing up on this stage, you have a scorecard, ÔBradlow said we're going to do this, this, this and thisÕ. Well, let's see how many we can get accomplished together in the next two to three years. So first, let me tell you about the future. So first, there are four major areas that our Dean, Erika James, has asked me to focus on. The first is AI for students, which I'll talk about in just a second. The second is AI for researchers. How do we make the faculty better through artificial intelligence? The third is how do we partner with industry in an even more sincere way? And last but not least, how do we make the world a better place through artificial intelligence? So let me start first with AI for students. So, we just announced that all Wharton students, MBA, PhD. and faculty - we're working on the undergrads is a little bit of legal stuff in the United States about that. Will be receiving chat GPT licenses. So many other - thank you for the applause there. Many other business schools are running away from technology. We run towards technology. People you hire have to know how to use AI and large language models to make better decisions. We're also establishing what we're calling an Ôeducation innovation fundÕ. Any faculty member who wants to improve her or his class in data science or artificial intelligence will receive support from the school. And last but not least, this is something that we haven't even announced yet, as a matter of fact it's new. The LatAm group here is the first people ever to hear this. We're announcing the creation in 2025 of an artificial intelligence major at The Wharton School. So, you can come to The Wharton School - my home department is marketing Ð you can major in marketing and artificial intelligence; finance and artificial intelligence; entrepreneurship and artificial intelligence; that will become possible starting in 2025. We're starting a research fund. So, matter of fact, Alberto was talking about at our board meeting. We're going to be hiring post-docs, PhD. students, RAÕs, to help us work in the area of research in artificial intelligence. Imagine a PhD. student who has a PhD. in astrophysics that wants to work in business but has never been to a business school but knows a lot of math and a lot of computing. We're now going to be able to bring them to The Wharton School to bring an interdisciplinary focus to the school. So, this is what we're going to do to help enhance faculty research. The next one, we already do this. Let me - I'm going to tell you a 15 second story. When I - in 2007 - I started the first ever center on data science in any business school in the world. People told me I was nuts. That's what the engineering school does. I say, Ôyou wait and seeÕ. It's what the business school does. The reason I did so wasn't because I was being nice to the school, or any Dean asked me to do so. The reason I did it is that the best research was being done in industry, the best data sets were in industry, and the best business problems are in industry. The lifeblood of what we do at Wharton around artificial intelligence and data science is because of our partnerships with companies. Without companies, without real business problems, real data, we have no WAI Ð AI, there is no A.I and analytics initiative at Wharton without deep partnerships with companies. And last but not least, maybe one of my favorite parts is what we're calling ÔAI in societyÕ. So, I'm going to say two things. One is we're going to teach teachers - very much - actually Roberto's words were very inspiring to me yesterday about how you change the world through education. We're going to teach teachers how to teach artificial intelligence and data science. I can only teach so many people, even my faculty can only teach so many people. So, we're going to partner with organizations that help teach artificial intelligence and data science to the world. We're also going to create an open-source platform so people that want to create educational products can do so. And my colleague Ethan Malek will be joining us virtually in just a second to talk to you about that. So let me wrap up and say the following. Matter of fact, Debbie said how you can give to the Brazil Ð by the way, I think I'm going to give to that fund, by the way. I will give to that fund. Because I'm going to tell you - and the fact that the student Ð matter of fact - go to that QR code and I'm going to give. The fact that that student is also an M&T student is absolutely remarkable, is an absolutely remarkable achievement. And again, part of our mission is to democratize education. Anybody can learn artificial intelligence and data. So, it doesn't matter who you are, where you are from the world, everybody can learn it. So how can you help? A few things: datasets, come and see me, if your business has an interesting dataset problem, we're interested. Of course, I have to talk about philanthropy. I don't mind saying the number; over the last 15 years, I guess I call it - I've invested - you could use the word ÔspentÕ - but I've spent 50 to $60 million building our brand, our brand around artificial intelligence and data science. All of that has been paid for through philanthropy and corporate partnerships. Third, every one of you can be a mentor to future business leaders. Our students love one-on-one mentoring from alumni. There's ways for you to be engaged, I'll use Roberto's words, with your time. And last but not least, when Eric Bradlow shares something on social media, reshare it. When the Wharton AI and Analytics Initiative share something on social media, you share it. That's how we're all going to build the Wharton brand together. So let me wrap up. This is our mission. We're going to be the academic thought leader for research and education on AI and analytics and its impact on business and society. So very bold but aggressive mission statement. And let me just wrap up by saying the following. I'm extremely proud, for 40 years now Alberto, 40 years, I've been E Bradlow at Wharton dot UPenn dot EDU. If you say ÔI'd love to help Wharton out, but I couldn't reach EricÕ, you're lying. You're absolutely lying. And secondly, follow us at AI dash analytics, our new website is up. Again, we should all take this as an opportunity. 28 years, six deans, it took one visionary Dean, Erika James, to start us on this path. So, I look forward to talking to you more about AI and data science. And thank you.