Title: AI and the Global Supply Chain

Title: AI and the Global Supply Chain

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Good. Evening and, welcome to, this brand new semester, here at the Robert H Smith School of Business at, the University of Maryland College Park, I'm. Rebecca Belanger I'm the executive, director of the Center for Global Business here at Maryland Smith and I, am very pleased to welcome you all to our first, event of our annual distinguished, Speakers and international, business series and this. Evening we'll be looking at artificial intelligence, and the supply chain I'd. Like to give a very special welcome, not only to our panelists, but. Also to you the students who are here with us in the audience and. Those. Of you who are joining us via livestream, thanks, everyone for being here this, evening I'd. Also like to give a thank you to Marina August ITA's and Santiago, Luna, for putting together this. Evenings, event. Excusing. Before. We get started I'd like to say a few things about the center itself, we. Are the hub of global learning here, at the Smith School and indeed, global. Activity, our mission. Is threefold, first. To, bring the Smith School to the world and the world to the Smith School second. To provide opportunities. For students. Faculty staff alumni, the business, community, to gain, global mindset and international. Business skills and third. To serve as a resource in, the state of Maryland, for businesses. Seeking to be successful, in the global marketplace and we. Achieve this mission through student, programming students. Are any of you interested in studying abroad a. Couple. Of you international, business treks. Passport. To global mindset program, all of that runs out of the center we, also have faculty development, programs, we, work with businesses, on capacity, building and training programs. And we, are the place where school internationalization. And, partnership. Building happens. We. Also are part of a thought leadership and research community, and this, event here our distinguished, speakers series is part of our and really, our signature, thought leadership, event, we. Bring together policy. Makers academics. Thought-leaders. Industry. Representatives. To, explore and discuss hot topics, if you will in international. Business really. To complement, what we're doing what we're teaching and, what we're learning in, the classroom, here, at the, school the. Series is sponsored hosted. By the Center for Global Business and funded, in part by title, six grant known, as Sipe that, comes to us through the. US Department of Education, we. Hope that you will join us not just at this evenings event but all of the events that we have throughout the year including next. Month's highlight, which focuses. On North, American, trade and the u.s. MCA and then, in November we'll be doing our annual panel, on global competencies. For the 21st, century workplace. At. This, event and all of the other events, we encourage. Audience participation. Our, panelists. Are prepared for the toughest, questions, that you have so. If you're here with us in the audience in, College Park we're, going to ask you to recognize the two mics here, when. It's time to ask questions I ask you to stand at, one of the mics introduce, yourself, and address the question, to the panelists, if you. Are joining. Us via livestream for, the first time you too can ask questions, by tweeting us at at Smith, global, business. Bi Z or, by sending an email to Santiago, Luna at s Luna, @rh, Smith um, de D, u so please, everyone be ready to ask questions, and now. Finally the main event I would. Like to turn the evening over to, our moderator Sarah, acharya, one of our very own faculty, members in DOI, t please. Join me in welcoming our panel. Thank. You Rebecca, I just, want to echo what Rebecca, just said and really extend. A warm welcome to our distinguished, guests of, course students. Faculty. The extended. Maryland. Family I know it's, it's a Thursday, evening and you've chosen. To be here so thank you thank you very much.

Before, We start I also want to express my gratitude, to, Professor to kiss Leah Prasad who asked me to moderate. This certainly, looking forward to it so. What I want to do first is I'll just quickly introduce. Our. Distinguished. Guests just, the name and their current titles and then, we'll have them, introduce themselves. Tell. Us a little bit more about who they are what they do but also their. Journey. If you will so, to, my immediate left. You made el Jannetty. Who serves, as chief. Procurement officer at, Troas. After. Him, John. Miller who serves as vice president, of. ITIC. That's, information technology. Industry Council and, then. Two, to my far left and, to get to Gandhi who is partner, at, 80. Kearney focusing, on the digital, supply chain so. Again welcome. And, you. Made from, from. Your if. If. You could introduce yourself and. Thank. You Suresh. Imaginative. Chief. Procurement officer for a company called truenox. Truenox, is a titanium, mining. And manufacturing company. We operate in six different, continents around the globe so. In the continent we don't operate in is Antarctica. So but we plan, to find a mine there and operate. The. Before. That you, know I, worked, for GE for about ten years also in supply chain and operations and, I work for Chrysler before, that they're, very very happy to be part of this and and looking forward to the event. And. And, you're also a fellow. Terrapin, I am I am so it's a. Appreciate. So I actually. Used. To I was part of the Executive, MBA program. Cohort. 13 and this. Used to be our dining hall and the classroom was just down down the hall there so I'm very familiar with campus, and in this place. Before. That I did a master's at Syracuse University in. Manufacturing, engineering and and I'm a mechanical, engineer, on the ground. Thank. You and, thank you to. The Smith School and, students. For, joining. Us here this evening my. Name is John Miller I am vice president, and senior counsel, vice. President policy and senior counsel at ITI the information, technology industry Council we. Are based, in Washington, DC as, well as Brussels, and. We are a trade association representing. Major. Large. Technology, multinational. Companies. Companies. Doing it really from across the tech sector hardware, software. Internet. Companies. Other. Tech. Enabled companies, and. Services. And, cybersecurity and a host of other types, of companies I, lead. Our trusts data and technology, policy practice, so, dealing. With issues ranging, from cyber, security, and supply, chain to. Privacy and data protection to, artificial intelligence and, other data. Innovation. And. Policy. Issues, I. Also, do quite, a bit of work with the the, public-private partnership. Mechanisms. In Washington DC including. Chairing, the IT sector Coordinating, Council which is comprised of over 100. IT. Organizations. And co-chairing, the. ICT. Supply chain risk management task force along with the. Communications. Sector and, Department Homeland Security in terms of my journey prior, to iti I, worked for nearly a decade for. Intel Corporation, one. Of the iti, members, and. Prior. To that was a lawyer, in private practice. In. New York working on business. Litigation, primarily. An intellectual, property litigation, true. What they say you can do many, things besides be a lawyer with a law degree. Sukey, Sukey do, Gandhi I'm a partner, with a t Carney a leader, product. Area of a global digital supply, chain, started. My career at a small retailer, in Bentonville. Arkansas. Some, of you guys know it and. It. Truly learned where supply chain meant but I didn't understand, at that point and. Along. The way have picked up some technical, skills that kind of brings it all together, now, and it's, it's, a wonderful place to be and.

In A wonderful area that is growing rapidly. And, just, this thing around the title right the. Global. And AI and supply. Chain it's because you know there's a lack of global, intelligence so, we have to use artificial, intelligence. To make up and make, the supply chain work better that's. A joke. Great. Thanks. So what. I want to do is before I jump right into the questions you know some of you are probably wondering a, I. Global. Supply chain what, is what is this all about and so what. I thought we would do is hear, from the from. Our distinguished, guests our panelists, about, what what they view a I and the global, supply chain is so that we know that what we're going to be discussing. So without. Any particular. Order if anyone wants. To. Define. If you will what, we mean by AI. In the global, supply chain. Sure. I mean I think in terms, of well. I'll. Take them separately anyway at least start with AI you, know I think AI gets gets thrown around a lot in, policy. Discussions in, the media and elsewhere and. You. Know a lot of times there there isn't necessarily definitional. Clarity as to what we're actually talking about you, know, I don't think we're quite to, the you. Know terminate, or rise of the machines species. Of AI, that. You, see in the movies it's, actually, I think, it's really instructive to break, it down into its component, parts. To. Me and. In. Frankly, a lot of the work that I'm, doing these. Days. Data, is at the center of everything and, and and, I think that's certainly true in the case of artificial intelligence, you know a lot of the focus is often on the, algorithms, and the software and they don't want to minimize the importance, of, algorithms, and software to AI but if you don't have, large. Diverse. And. Valid, datasets to train those algorithms, with and data to, process. Your. Your algorithms, aren't going to are going to do much for you whether it's an a supply, chain application. Or anything, else, you, know there's also some differences between. You. Know I think probably. Fairly, stated, you, know the types. Of AI that, we see, in. Use today are really probably more fairly. Characterized, as as. Narrow, AI focused. On specific tasks rather than you. Know, a you. Know some type of a. Broader. A I and, also there's a lot of machine, learning. Today. Which. I think is really important. To distinguish too so I don't know if others have anything, to to, add in. Definitely. All, these components, when. You speak a ice people immediately think a robot or a computer in reality. Is all about data is, all. About the, algorithm. That depth that. Define. The data and handle.

The Data together but also the computing, power that would allow you to respond, and and, and, give you that intelligence. That you need almost instantaneously. And that that has been progressing, exponentially. Over the past decade or so. Maybe. One way to also think about is that the. Dean corrected. Me she said the supply chains have been around, for a long period of time they've, always been there but, they've been fairly, simple, and the. End. Consumers. Of the supply chain have. Had. Very predictable, behavior because, we were primarily. Supply. Constraint, now. As demand, exploded. And the. Complexity. Of the product exploded, it has become increasingly difficult to. Manage that and. As. We truly made our supply chains global, initially. It was fairly straightforward to, control it and manage it and now, it's impossible. To control it using. Just human, intelligence and that's, where artificial. Intelligence. Comes into, play so you, know on the one side you've had supply chains and products getting more and more complex become, difficult to manage and then, technology, is progressed far enough to, come, together with, the AI and that's where. The, intersection. Brings, out a wonderful. And a powerful mechanism, to bring more, ideas, more products, more services, more complexity. But, it managed it in a very simple way one, last thing I'd like to say is, there's. All the conversation, about singularity. And things of that nature, human. Intelligence is still very valuable, even. In supply chain so, please, go to school learn about supply chain and you'll have a wonderful job. Great. Thanks, I, just. Want to build, on what each of you touched. Upon and. You know, specifically. To you you know when it comes to this. Discussion. Around AI we. Tend. To think about. The. Infinite, compute power that we seem to have. The. Proliferation. Of data the. Advances. That we've made in. Algorithms. For example. But. How. Has that really, come, together in, in, the space that we know which is the space of supply, chain and logistics what, do you see in, your organization. And what do you see across, the industry. Thank you serious. How, many maybe I can inconsistent. How many our supply chain major is here. Okay. That's, good so, not. Not most of the room so, maybe maybe it's important, to actually. Define. What supply, chain is What's, in scope. You, know it's it's really the entire. Value. In any business an entire value, chain from, from, procuring. The. The materials, and the services, to. In. Bringing, that material, and services, into warehousing, warehousing. Then in a traditional, manufacturing, than manufacturing, as. Well as a. Distribution, and, their custom customer service that so the entire, everything. Could be referred to society, if some, company could could, call just, the, the early part supply. Chain some some some businesses, could call the, entire the entire value chain to chain the supply chain so so. Wherever we go it. Is really what what facilitates. The the product, the services from. From the point that that the, the sale has happened, to, actually bring, it to the consumer whatever, that is it's. Called supply chain so III hope everybody has that same definition but. But to build on to build on on the point that you, raised a, I.

Defined. The way we defined it actually. Can touch every, single component of this and deliver value so, in recent years and I'll talk about you know the industry I mean and and other other industries. Productivity. And cost is probably one of the major drivers, of adaptation. And implementation. Just. The just the the the. Amount of data and the, computer. You know the power, of computing, if. You take just the warehousing, activity. For example and, the efficiency, and the productivity, is there larger. Companies now have very minimal human error, within, their warehousing from. Receiving to stalking to. To to, to to issuing and distribution, but. But also you, know one one of the recent. Breakthroughs, technology. Like the one you see at the airports you know scanning, the products and all that stuff, inspection. You know that. That. Was usually. A bottleneck, on area of cost because of you know defects, and all that stuff when, it gets the consumer, now, with it with the power of AI you. Know and and on how fast you process, this you can detect these, the the, the, products, very, very quickly when they come in when they leave so. That, cost is completely, gone, when you only adapt something like this another. Area of supply chain is is demand. And. And and the business, planning. Major. Companies, or and, businesses. Can get an instantaneous. Feedback, about, the, how how they are their demand for their product, is they, can with the AI, even. Even some sophisticated, businesses, can automate. This adjust. Their their their business plan, and their manufacturing, processes, and. Their schedule in this schedule and then, even stop ordering of raw material, or increase orange raw materials, to, to, deliver the product to, the. Customer so so, most, of these, are just two, areas of many you. Know another areas customer service a lot of us deal. With that on a day to day basis, you know when, you call or when. You go to to, a customer. Service website, and you're, dealing with the chat bot or automated.

Service You know there's a lot of intelligence that built in into that you, know they're. Slowly but, surely you, have less and less human, interaction, and customer. Service is very. Fully, automated, these things. John. And so. Can if you wanted to add anything to that in. Terms of what you see out there. Yeah. Sure I am you. Know being, the. Policy. Guy on the panel and I see, it just, a little bit higher level sometimes, but I think you, know again breaking it down. Minoan. And viewing it through the lens of innovation. You. Know we're, as, well as data we're talking about technological. Innovations. You know in the fields of transportation. And communication. For sure in the supply chain context. And. Really it, you know just to slightly. Rese restate. What my fellow panelists, said you know you, know companies, are now able to operate, on six. Or seven, continents, for whoever's doing business in Antarctica. But, and maintain constant, virtual. Communication. With, not only their employees, but their warehouses. Their, suppliers. Their, production, facilities, and. You. Know further if you look at some of the other innovations, that would. Seem, to me anyway to be particularly relevant in the you know in the supply chain context. I think one example would be GPS. Technology, for instance and, just you know using. Software. To manage, fleets, or or, various. Other, you. Know parts of the supply chain you, know whether we're talking about the fact factories. Or. You, know you using, just. Other types, of tracking. Technology, with respect to to you know to inventory management, and things like that. The. Role of data in supply chain is about making better decisions, that's. The simple truth and. Why do these decisions, require artificial, intelligence, or anything of that sort if. You go to an average store your book store here you probably have 10,000, items you. Go to a slightly larger store, 50,000. You, go to a larger. Grocery. Store with the other goods you have somewhere between hundred fifty thousand items you. Go to your favorite, online places. There. Are millions, of items and there's no limitation, to that so how do I decide, what. Do I store what, do i buy where. Do I keep it so I can deliver it to you next day or within, the next few hours all. Of these are what I would call decision, domains, and they're based on data now, as the complexity, and the size of the data increases the, set of tools, use to, make these decisions get, more and more advanced, but that's you know data is the you know all kinds of stuff people say data the oil, data. Is like dirt but, you don't go from you know brown, to green that's money without. A lot of processing in between and better decision, but it's all about making, better decisions and.

That's, What data is wonderful, for and that's, where all the technology, and the conversations. Around you know the plan makes or something will come into play. Excellent. Thank you what. They're. There a few, follow-ups, that I certainly want to do but coming. A little bit closer to what we want to talk about. So. How. How, is AI then, enabling. Things like. Cross-border. Trade how. Is it helping, bring, together potentially. Intricate, possibly. Intelligent, supply. Chains making it more reliable. If you will so, if you could shed. Some light on that you. Know. Any. Of you. Well. I mean from, the. From. The global trade standpoint. You. Know there. Really is no. There. Really is no modern no. Trade in the modern society. Without. The, ability to you know to move data and to move data digitally. You. Know so. If. We, consider that that, really you, know what artificial, intelligence, is is going to be able to do whether it's in the supply chain context. Or in any, other context, is allow, us to. Move data more efficiently. And. And and potentially, quickly. It's, going to be very important, and you. Know arguably is going to help increase, global. Trade I think you, know we might get into some. Potential. Policy. Measures. That are out there that actually stand. To potentially. Kind. Of put the brakes on some, of our ability, to move data and. In the global, context. And, I. Guess I'll hold those come and since well then but that's. Just the way that I would start the answer to that question yeah I'll, use actually a specific. Example. In our own experience we're, exploring, upgrading, ERP, the. System. Into into the cloud and to into the new. Universe. One. Of the advantages, on from a global trade perspective, is you know one. Traditional. Companies got their own servers, their own data they. Manage it they're protected, and they operate their business accordingly, but when you go to - to the cloud and you have also access, to two common, data, such as such as regulations. Or customs, or, data, like this and that gets implemented. Across, different. Businesses, ERP, you're able to respond and run. Re. Optimize, your your, your business and and, make decisions according. To that, you know it, would have made sense to to, serve customer. A from, from you or your facility, in in, Europe now with with the change of this regulation now you, may want to do it from you know from from, China. Or from India, or from the Middle East or wherever, your, other so so you're able to react, respond, and if, you if you automate the, the, decision-making in, your behalf you're able to keep. Your business at the optimal level and you and you see some of that happening it is it is happening those solutions are out, there and and that's, the power of actually, the car the commonality. Of the data rather than the traditionally. You know ERP, system sitting on the business and protected. By the city the business is the balance of between having, your own data but having access to the war to the rest of the world at the same time. - did, you want to add anything to that no, I think. I. Wanted. It to you, know. Follow up and tap into your expertise, around policy. Right so when. We think about AI and. Supply. Chain a lot of that conjures. Up images of what companies, are doing but what, are what are government's, doing in terms of policy, in terms of these, proposals, to. Facilitate. Leverage. The power what. Are the opportunities and. Of course are there any risk. Thank. You. Well. We were just chatting a little bit before the the, the, panel began about how you, know AI and, and supply chain are or, two of the hotter policy.

Issues Right now particularly, technology. Policy, issues and. You. Know on the positive, side. Governments. Are I, think, recognizing. The power of, artificial. Intelligence in, particular as a real differentiator. And a force multiplier. You, know that's going to be important for their. Societies, and their economies, and you've got you. Know a host of proposals. You know including, here. In the US the there was a recent, you. Know White. House AI. Strategy. That. Was put forward including an executive, order as well, and. You've got you. Know the, Department. Of Commerce and, the, National Institute, of Standards and Technology. Actually. Putting out some you, know a strategy, for international. Standards development and artificial intelligence you. You you've got R&D. Money being, being, pledged. Not. Only in the US but in. Europe. And in China and. Really governments are really focused, on trying to. To. Really, get a competitive advantage over, each other which is potentially, good from a business standpoint. But. You know particularly if these are not unfunded, mandates, but but we actually see you, know dollars going, into research. You, know but by the same token there. There are some sub concerns from a policy standpoint with the technology. With. With AI technology. It can range from it everything, from. You. Know privacy. Related, concerns. Particularly, when we start talking about decisions. Being made and data being transferred with, with potentially. Removing, the human element, whether. They. Were going to be, you. Know whether we're gonna be able to adequately protect that data and particularly personal. Information. You, know beyond regulating. Personal, information, you've also got a variety of policy proposals. Including. In Europe, there's, something called the e privacy, regulation. Which, is seeking to regulate non personal, data and there was actually just a proposal. Coming. Out of India within the past week or so to do, the. Same thing, and. It. Particularly, raises, issues in, the content, context, such as supply, chain because you're talking about metadata. And, data that, that's just usually kind of back-end. Data that doesn't necessarily implicate. The fundamental, human, rights such as privacy, or. Anything. Else and it's and if you're going. To have policy, proposals, that aren't necessarily, tailored.

To. To that. You. Know you could you could potentially undermine, the ability to move that data across, borders, and then on the supply chain front you, know there again there are some very. Valid. Concerns. Regarding. Potential, national security implications of. Supply, chain right, now and there, are a lot of discussions going on in the context, of the, 5g, network build-out, for instance, about. Trustworthy. Communications. Networking equipment and non, trustworthy, communications, equipment and. There's a whole host of policy. Proposals, that. Again, have the ability, to potentially. Undermine. The ability to transfer, data or, technology. And arranging, you know everything from supply, chain regulation, and legislation. To. Export, controls, to, investment. Restrictions, etc, and. Again. At. The end of the day we want to make sure that these policy, proposals. Are carefully, tailored to addressing the risks whether they're national security risks and privacy. Risks without undermining that, they you know the great potential, of using these technologies, to do things do. All the things that the government's want to do in, the first place including. In the supply chain context. Maybe. A slightly. Different, view. Which. Is governments. Cannot control data, unless. You. Are they're. Definitely trying yeah they're trying that's right unless you're part of the Hermit Kingdom or something like that. They. Try right you got to turn off the internet to, turn off data and. If it's the troika, of the government, and businesses. And individuals, that really. Can bring a. Difference. Right they make a huge, difference, so let's take the example of GDP, I it, started out because young, kid in Austria, didn't, like the fact that data, was being published at least that started, the spark that. Led to quite. A comprehensive. Legislation. That comes into play so you as individual, consumers do. Have a lot of power in this data discussion, and. You're speaking up right um talk, about Greta who, has kind of changed or how we think about global warming the, same way this this hat this is one of these days you're gonna explore in a way which, is gonna cause people to really think about it the, business.

Is Care about it because you, will not buy their product. There's. Plenty. Of examples, in the beauty. Space in, the fashion, space where somebody's, picture was used improperly that leads to a backlash, that, dramatically. Changes, consumer, behavior so when, we think about data it is the three sides coming together government. Is important, but, you know the consumer, and the companies coming together that's. Where the power lives and then, the last thing is there will be two sets of companies um one, that, will openly, tell you that we won't use your data and it will live on your device and. Almost. Promise you and then there's others who won't. Say a thing and US consumers, will make a choice and that. Data in the supply chain. Is absolute. Gold, because. Tells, me what, I should make what. Do you like what, you don't like when. Should it arrive at your door and what's the price you're willing to pay for it so. We. Should not underestimate the. Power of the individual, in making. This dramatically. Different especially in the supply chain world. Absolutely. Agree with that I could just comment just a comment briefly. You. Know certainly. Companies, are. Partnering. With governments, and trying, to work with governments and in particular to lend their technical expertise, to, governments and I think governments, many many government policymakers to their credit recognize. That they don't necessarily you. Know have the, same. Capacity for hiring engineers as. Companies. And and I think are increasingly, working together and and and you know your points. Well well, taken about the power of of even one consumer. In the case of think, you're referring to max schrems and, you, know in fact. Something. Called the the, the, safe, harbor agreement between, the, US and the EU was. Actually. Invalidated. Because. Of Max. Ramsey's, lawsuit, and, you. Know it gave rise to something ultimately, called the privacy, shield agreement, but the bottom line is there there was actually a period of several, months where the, ability of companies to transfer. Data, from Europe to the United States the. United States was what. Was in jeopardy and, in many ways. And. Again that's why you know data is really, so important, here and I think for consumers, and. For companies and for governments, that's why really trying, to figure out how to build trust in this global, digital ecosystem. And economy is. Really so important. When. It comes to to. Policy. I. It, is, I think, that predicament would, be is. In. A making. It an enablement, as opposed to a tenderness. To. Hinder the the progress of supply. Chain and globalization. The. Phenomenon, has been happening of course in, recent. Years. There. Are societies. That are trying to regulate and over regulate and. There are societies, that don't want to regulate and, I think that clash. You, know between you know Europe the US. And the likes and and then maybe you. Know China and the parties their different view how. That happens would would have a significant. Impact on, own. Progress and and. How the global trade will actually happen between, those countries. It could be potentially, disruptive. In that sense I absolutely. Absolutely and, you know you you could start dividing, the world into different, segments. In particular. It's in, the, global context, it's not just domestic, privacy, laws that we're talking about but, restrictions. On transferring, data across borders, which is really the key I think in in so many ways, and. There are no borders in data so it's a this is a predicament really right, I wanna, there, are many topics that we could because certainly talk about, security. Being one of them but I did want to touch, upon something that I'm sure is important, to all of us when when it comes to AI we talked about the, great compute power we, talk about algorithms I could talk about data but, at the end of the day it's human. Being that kind of impacts us right. I, was. Told that babies, born after 2016. Will not need a driver's license when they grow up how about that right. So so, key I wanted to tap into you, know your expertise you've you've talked. About this movie how how. Are how. Does AI especially. As it applies to the supply chain impacting, Huss humans, so then what are the positives, one of the negatives what are the apprehensions, and what. Are the opportunities, so. One, of the most interesting, or maybe a little bit misunderstood. Thing about AI is, you, know it's written by human.

Beings And it's, affected, to by data so. All your, biases, are. In your code whether. You. Like it you know it or not, and, unfortunately. You cannot look at code and say, what the outcome, will be it. Depends, on the data set going in so there's plenty of examples of. The. Ability, of an, algorithm to recognize. One. Type of human being versus, another because, the data set did not have, that building and that. Inherent. Bias is, incredibly. Scary. Because. You can only detect, it after. He does process, something and come up with an outcome so. As we think, about in the supply, chain and that's why we refer, Mele believe that until AI reaches, a point where we can be confident, of its. Analysis. And outcome human. Beings, have, to have their, hand on the rudder so. That, biases. That were built in the code or some, biases, in the training set of the data do. Not affect. People, so, that's kind, of one, big challenge. To think. Through and. One. Of the things there's been a lot of conversations. Is that, should there be a. AI. Council, that that regulates, that it's very hard to do but, there are I don't, know the work here that happening, at Maryland but there's a couple of other, universities, on the, in. Boston, that are really, focused, on them we tend to work with them to understand, that how do you identify the, bias so that's one big thing the second thing is it is becoming, a board level issue for, companies because. Now your, decisions, are being, moved from the hands of people to, algorithms. And if, an algorithm. Mistreats. A customer, is. The. Board responsible. The. Simple answer today, is, yes, and. Then. Do. You want to be on the board of a company that does that so and so then there's going to be some, kind of regular around, that and then, the last thing, is on. The. This whole debate of who owns the data and. At. The end of the day it could you know there's again companies, would say consumer. Owns the data and then you say points, the. Algorithm. That was with that so, one classic, book that's out there it's called weapons, of mass destruction. Which. Is wonderful, in illustrating, what, this can do to. You. Know, how data and AI can, combine and the, last thing I'd say is ten years ago Mark Anderson wrote a great piece called software, is software, is eating the water now. Software. Eating the world is on, to compound to is built on two things one is data and the second is AI. When. Those two come together. And. About. A week ago Elon. Had this musket this thingy going on in China where he said humans, are the actual, original bootloader. For the technical guys in the room. For. For, AI engines, which is a fascinating comment. Then we, are just some. Small piece of software to get a, technology. Started, which. Is an, interesting way to look at it that's. What. I. Think. What one thing that's worth mentioning from a you. Know human, perspective, particularly. With respect to AI is, that. You. Know there is still not necessarily. Widespread. Understanding. Of AI. And, the result I mean and there was significant. Fear about you, know is AI coming. And taking, my job and displacing. Jobs so there's a lot of focus right now from a policy perspective on. Workforce. Development. You. Know workforce. Training and and, rescaling of employees, for you know this new world, even though hey I may displace, some. Jobs it's going to create other new jobs and it's going to create a greater.

Need For high higher. Educated, you know high more, highly skilled workers, due to. Work in at capacity. So. You. Know that's just something that's just something that and, really, one of the best ways to do that and again whether it's, telling. A kind of a good, news story about how, it's being used to, help it in the supply chain context, nor in many other applications, you, know helping to demystify the technology. And explain, it and to explain positive, use cases of, how we can use, AI. Or other technologies, to help. Enable, global business, is something that I know that our, members are very focused. On I. Mean. Technology. Has been advancing, for for, decades and centuries. And and if you look at with your rewind 50 years ago and, look at what, jobs human. People. Used. To do it to what job they're doing today and and and their different technology, is taking over you. Know people have you had the same rhetoric when we automated, the the assembly, lines on on you. Know in the. Auto. Industry. But. It's the same you started your question, driver's. License what said 2026. So. Babies. Born after 2016 it's 2016, so, so it's this. Is coming you know I mean, we the, drones, and driverless trucks and cars, that's coming so so those jobs will will, do you, know deliveries, but even, even the mail person, you know, those. Will, be displaced. So but but then skills need to go elsewhere, you, know AI, means artificial, intelligence, and intelligence, is actually built by human that will continue to be to, be, built. But, by, human at least in our, lifetime. And and the skill set and and the development, needs to go there thank. You I could, I could go on asking, my list of questions but I do want to open it up to the, students. And the, members of the audience if you could grab, one of the two mics, first, of all of course introduce, yourself and then, ask. Your question please thank. You. And. Then. I know we, might have some, online. As well that Santiago's, monitoring. So. Recently. Master's. Degree graduated, from MIT. My. Biggest question is we, all, tell. Them updated this entire time but, do you foresee, a future in. Which data is captured, as. A non-cash, asset, one, adoption. So. That's. The realm of accountants. But. Here's. A interesting. Statistic, which. Is the. Value of data in, in, companies, is somewhere. Between 80, to 200 billion, dollars so. One, of the conversations. We tend to have is and. It's been utilized. For extremely. Minimal, payoff, extremely. Small payoffs. So. The question we tend to start with if. You had 80 billion worth of assets in your firm and they. Were not being used what. Would you do, so, that's a wonderful question to ask you see you on a board and you get a dramatically. Interesting. Response so, you are correct that accountants. Are working through on how to capture that but, the inherent, value will, never be truly. Understood. And calculated. Just looking, at the base value of data because, there's the base value as the implied one there's the, third level calculations. That come out of that which are so dramatic on you, know John use the example of GPS, right GPS. Was. A free, technology. Invented. By the government, to track let's. Just say something. And it sits in the open space but it was there. For the right reason that, technology, alone actually we ran some numbers is. Probably, worth. Three. And a half trillion and I. Know I'm wrong. Why. Because, that has structurally. Changed, how all of us are behaving. So. Tracking. Data is hard right but. It is you your question is very valid and an incredibly, powerful one, to think through as people look at companies. In. Short that needs to be addressed very good question right the. Question will there be a balance sheet in the future. Hi. My name is Krishna, Parikh and I am senior, international, business, so. My, question, is that we are currently discussing on, digital, divide and island ization and you, talked about how, data is shared. And I cannot be controlled by government, but. Since. There is like a forecast, going on on digital, divide and like separating. Economies, and separating. Virtually. In totally. How. Will you then.

Incorporate. All, your. AI or information. Sharing in different. Countries, how will you. How. Will you work your supply chain in those different countries like if your, product. Does not get to customer, then it's like meaningless. After. Crossing, the water so, that's my question thank you. Well. I mean I think I. Mean. It's it it's. Try. To think of the best way to answer that you, know I mean I think that you, mentioned, that the digital divide, I, mean. Something. That I. Mean. You, want to say I don't think I said that governments can't control data my one of my fellow petal this much might. Have but. I you know I will. Say this about it you. Know governments. Are. Your. Question raises that the following, point governments. Are looking at ways are. Actually looking at their even their own very. Large in many instances, caches, of data and trying to figure out how to unlock the value of that data you. You, know for. Instance public, datasets here, in the u.s. at various different agencies, I mean they agencies, are sitting on huge. Troves of data that, you. Know in many ways they'd like to make available for, commercial. Use or you know to to bring more value. You, know economically, and, also to bring more value you. Know. In terms of socio-economic. Benefits, for. Their citizens and there's a lot of you. Know different. Challenges. That that still, need to be figured, out in terms of you. Know in particular combining. Those datasets with other pre-existing, datasets. You've got issues involving standards. Etc. I mean there there is obviously a commercial, element, to, to data I mean so the the larger question of who owns data, I don't think is is is necessarily, always, easily. Answered. You, know it's somewhat relevant to the question previously. About the value of data from an accounting standpoint some. They're not going to offer any accounting. Massiah. Know. That I have any for. Sure but you know just the concept. Of data, as a market, path set is being looked at by policy. Makers in Europe. And elsewhere you, know in the in the context, of competition. And. You. Know I I don't. Think it's it's, I mean it's it's not the case that all data is shared by everyone, but, really figuring out how to. Maximize. The value of the data that's out there and in some instances companies. Are working together to pool that data for, instance one. Example that just pops to mind is in the cybersecurity context. You, know cooling, data together so, that you all get, you know it's kind of one plus one equals, more than two and that in, that, regard because you. Know you're you're sharing, the data you know there are also things that, you. Know are sometimes, you, know creating test beds or, data. Sandboxes, even, to to, really try to figure out you know different ways to use, data you know these are all ideas. With merit and, you, know I think they're all being, focused. On right now to, figure out how to. Again. Unlock the most value of the data for the most people I think I. Want. To build on that question because. In. The day, and age of trade. Wars and we're kind of thinking you, know the are we going to have them. The. US. Bloc and the European bloc and maybe the Asian bloc one. Of the things I think we forget, is that. There's a generational. Change that's happening as well a. Good. Number of folks in this audience are of, a generation, where they feel comfortable sharing information, and, that. Then perhaps gives us some optimism, that while we're, in this who owns the data let me let me protect, mine and, we have you. Know all these rules do, you see, hope that, perhaps. We'll have more efficient, supply chains because, a more, sharing, generation, is, will. Move, up the ranks. The. Simple answer is yes right the, more data you have you can make better decisions back to the same thing and. More. Intelligence. We've built into it yeah, these supply chains are gonna get, significantly. More efficient, at some point you do reach the point of diminishing utility. So. If I get to a statistically. Significant. Sample and. I can use that word here without any, without. Any fear, of people not understanding, but I think, that's where it starts to kind of reach, a point where diminishing, utility right if I know about a million people in a segment a million, ten thousand ain't, gonna change my insight.

But. That's the thing that's where you start to can, really, work through the data to understand, at what point you know it's valuable versus not and what, should be shared versus, not so it's a it's we. Are learning let's just say that I think we are learning. Understanding. And playing with this. Incredibly. Large, amount of datasets that we have. First. Of all thank I want, to thank all the Fuhrer I have so many questions that I'm trying to pick which one I should ask you but maybe I'll go, with this one that, for those, people in the audience who, are thinking of careers, that you. Know in supply chain. What. Do they need, to learn about AI, before. Getting. There one thing I'm taking away from you is that you need to understand, data, issues, and the, strategic, importance, of data for companies or where that's going to come from but, could, you sort of elaborate, on that more, on on, what, they need to know as managers. And. I don't know that there many computer scientists here what they need to know as managers, about. In. Choosing. Making career choices in. The generation, today everybody. Is a computer, scientist, there. Is nobody in here, who cannot, be trained on how to use large quantities, of data and. And you, know whether you look at so the simple language is out there Python, and things of that nature they're, very simple so everybody. Here is prepared, for it and here's an interesting carrot, a, phenomenal. AI supply. Chain person, can. Easily, take home, 1.2. Million bucks. So. There's a little bit of value when you're doing that it. Is harder, to understand. How. The supply, chain works that's. The harder, part and how do I tie the. Data I have with. The flow as you know you talked about the flow of the information, and the flow of the chain and and how do you make decisions so those are kind of things that matter more. So. This, was about eight years ago I a CFO, of a very large wonderful global company, said hey my, people don't know how to use this data in supply chain that's, wonderful, and what do people do every day well they, make decisions about where to send their kids into college, what, mortgage, to take how to travel for place a to place B, how. To find the best ticket, right flight ticket and what do they do they go through said. Okay if they can make those decisions outside why. Do they come here and do, you perform a frontal. Lobotomy that. Stopped, them from making decisions right so I think that's. How we gotta think about it that you understand, supply, sin as a business, you understand, what data is needed to make decisions, and then. You deal, with kind of the larger context, of the massive, size of data and what tools do I use but, um we, tend to call it mindset, skill set and tool set you bring those three thing together and it becomes fairly straightforward.

The, Speed of change and. We think it's fast now it's gonna be exponentially. Faster, and and, you know for, the future supply, chain professionals. You, just get a stay up to the technology, and and. And be able to adapt it and and, because. It's it's gonna be part of doing doing doing business, so that's that's, maybe advice. Yeah. And just to build, on that a little, bit. You. Know. Reference. That you know the the 5g, network build-out is, coming and you. Know, that's. Another one of those terms that gets thrown around a lot and maybe people don't know exactly what what you, know 5g, fifth-generation wireless. Networks, are really. All about and what they're going to enable and. Again. In terms of data. You, know 5g, is something. Along, the lines of, you, know potentially. 200. Times. We're. Talking about 200, more. 200. Times more, you. Know a multiple, of data flowing through those networks you know we're talking about 20. Times. You. Know faster, throughput, speeds etc. You, know so I. Mean. If it's true we in some ways we haven't, seen anything yet in terms of you, know how this, this the, that that network, networking. You know speed and capacity itself is going to just further enable the even quicker development, of AI again, across, a whole range of applications. And. It is going to change, things so again, I don't know what kind of classes. They have in the business schools, these days regarding, data but I think. Understanding. Data or studying, that I think is going to be really key to AI and a, bunch, of other things in the future. Good. I see not. Enough. I'll. See we're have any classes on day two when I was in school. Before. Before, we go to you I just wanted to ask you yes. I have a question from one of our remote participants, thank you for sending it can. You talk more about potential, workforce displacement. Because of AI do. You foresee, the government, needing to create incentivize. Retraining. Programs, like, those that are meant to retrain, those displaced, because of global trade I. Mean. Governments. Are studying. This issue right now, you. Know I actually, I, think. It was just last week the, White. House held an artificial, intelligence. In. Government, summit to you know to talk. About these issues and and and that was one of the the. The. Opening. Discussions. Was was talking about the the various different plans that are underway at. The government now you, know around. Retraining. And and and rese killing workers and it's in it again the the business community has a very large part to play in, that in. That. Conversation. As well you. Know several, companies. Have have, you know essentially stood, up and pledged, to, you. Know create I forget, that what the number is but you know a number, of different jobs to to, try to you. Know balance things out so to speak but. Yeah I mean it's, probably much, too early to say with any certainty what type. Of or, what numbers there might be in terms of displacement, but I think that working together I, think governments, and industry are hopeful that you. Know we, can counteract that by creating new jobs. There's. Gonna be a natural need, and the businesses, will be forced to to actually. You know the new developments, and training too because because, they're gonna need those skill sets that don't don't exist so so, it's gonna be a combination to follow the end and their business need. Good. Evening gentlemen thank, you for coming I'm, think, I sent from. American. Graduate from American University, my. Question, is first. Off let's talk about ai ai is very, easy. To understand in, technologically. Advanced, countries like America but, back. In the scope it says global supply chain.

For. Countries like this we have a high demand for coffee right what, about not, so. Technologically. Advanced, countries like Uganda they, have a very, good supply of they, have good demand over coffee beans but, how will you implement this. Type of AI into, such not, technology. Events countries, and how will you account the, labour force that's relying on these businesses, and how, will you account the law that. Is in different countries, since it's a global supply chain. And. Then, replicate that, you know it's it's. You'll. See that because there's there is a need societies. Will well, adapt some would be much slower than than, others but to. A certain extent everybody, is in the AI world just by using a simple, device like like the iPhone, yeah. I want to chime. In with what Amanda said so I think that, while the, digital divide will, exist. I'm. Also optimistic for. Those. Of you in the room I have gone through this. Phone to. This phone to. That phone and, the. Last time I was in my home country, of Nepal. I noticed, that the orange. Vendor was using a smart phone she. Bypassed, all of, those things that I went through so. Technology. Is advancing, and yes. Will there be a time when there, will be the haves and the have-nots I think the answer is yes but, I'm optimistic that, we can get there that that if anything, technology. Is going to be the equalizer. Thank. You yeah. And actually just add one other thing to that yeah. I mean there if you look at just statistics. Such as you. Know you. Know per capita, Internet penetration I, mean it it's, you, know ninety percent you, know upwards of ninety percent in places like like Europe and I think, probably the, United States that at this point and. And below fifty percent and, you know on the African continent and elsewhere. And, that's it's, one of the reasons why you know kind of prioritizing. You know the kind of broadband. You. Know digital. Infrastructure. Build out in in those countries is such a priority, and a way to actually. You, know shrink, the divide. You, know government's in, again. The. United States for example. And. End companies, are very focused, on that and how to to, actually you. Know, again. Bridge that gap and so I do think that over, time that that the Bible should shrink. We. Can take one, last question yes please uh hi I'm hopping, and I'm a freshman, here in the business school um, so, my question is like how, will. The. Introduction, of AI into the global supply chain how will that affect barriers of entry for certain companies will it cause, the, barriers of entry to be higher for. Like companies I want to enter the global market but, can't you know maybe can't afford them or don't have access to this technology or, will it make, it lower and make it easier for people to enter the. Global market.

Yeah. Definitely. Will be a differentiator. And and and will increase the bar of Erica entry so so if you're if. You're a new entrant, in the supply chain world, and you're not up to where it needs to be to you, know from a technology, and a I adopt. Asian you probably want to be able to get off the launching pad so. Yes it is gonna be a differentiator, it is already at the frontier. Anything. Else you want to add. I. Know. I think Curtis. It sure I'm looking. At the marina cheese have given, me the, the. Hand. Wave that were that. Were that we. Have our time is up I want. To ask, all of us to give. A very you, know warm round of. We. Do have gifts, for our distinguished. Guests so read through me if I can ask you to come. Here and, hand. Handle, the gifts and I'm assuming that you'll be around for a bit to interact with our students. As well so this is for you Matt and. I'm. Sure this is for John. Thank. You thank. You thank you very much. You.

2019-09-29 20:37

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