What Is the Business with Ai? Preparing Future Decision Makers and Leaders

Technology and Innovation, Vol. 21, pp. 1-14, 2020 ISSN 1949-8241 • E-ISSN 1949-825X Printed in the USA. All rights reserved. http://dx.doi.org/10.21300/21.4.2020.4 Copyright © 2020 National Academy of Inventors. www.technologyandinnovation.org

WHAT IS THE BUSINESS WITH AI? PREPARING FUTURE DECISION MAKERS AND LEADERS

Helena S. Wisniewski

College of Business and Public Policy, University of Alaska Anchorage, Anchorage, Alaska, USA

With companies now recognizing how artificial intelligence (AI), digitalization, the internet of things (IoT), and data science affect value creation and the maintenance of a competitive advantage, their demand for talented individuals with both management skills and a strong understanding of technology will grow dramatically. There is a need to prepare and train our current and future decision makers and leaders to have an understanding of AI and data science, the significant impact these technologies are having on business, how to develop AI strategies, and the impact all of this will have on their employees’ roles. This paper discusses how business schools can fulfill this need by incorporating AI into their business curricula, not only as stand-alone courses but also integrated into traditional business sequences, and establishing interdisciplinary efforts and collaborative industry partnerships. This article describes how the College of Business and Public Policy (CBPP) at the University of Alaska Anchorage is implementing multiple approaches to meet these needs and prepare future leaders and decision makers. These approaches include a detailed description of CBPP’s first AI course and related student successes, the integration of AI into additional business courses such as entrepreneurship and GSCM, and the creation of an AI and Data Science Lab in partnership with the College of Engineering and an investment firm.

Key words: Artificial intelligence; Business intelligence; Business analytics; Machine learning; Neural networks; Artificial neural networks; Deep neural network; Data science; Fourth Industrial Revolution

INTRODUCTION Online (2), the global AI market will have grown to Motivation for Studying AI in Business Schools $118.6 billion by 2025, and Figure 1 illustrates how Artificial intelligence (AI) is reshaping and rev- business executives and leaders perceive AI and its olutionizing business. The speed of technological benefits. advances has no historical precedent. Gartner pre- Thus, the demand for talented individuals with dicts that by 2022, just two years from now, one in management skills and knowledge of advanced five workers engaged in non-routine tasks will rely AI applications will grow exponentially. Business on AI to do their jobs (1). According to Finances schools that develop an AI-ready workforce will have

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Accepted: September 1, 2020. Address correspondence to Dr. Helena S. Wisniewski, FNAI, College of Business and Public Policy Rasmuson Hall, Suite 302C, 3211 Providence Dr., Anchorage, Alaska 99508, USA. Tel: +1-201-675-4093. Email: [email protected]

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Figure 1. This figure illustrates how business executives perceive AI and its benefits. a competitive advantage. With change coming at THE ENABLERS OF AI breakneck speed, business schools must make dra- Technology Maturity and Convergence matic changes to prepare our future decision makers AI has become enhanced by technology matu- and leaders. rity and convergence with other technologies. These In this paper, I discuss how business schools can include advances in computing and chip design and meet these needs by incorporating AI and data sci- in algorithms such as neural networks, which have ence into their curricula, not only as stand-alone evolved into deep learning, as well as the convergence courses but also integrated into traditional course with other technologies such as robotics, augmented sequences, and establishing interdisciplinary efforts. reality, virtual reality, 5G, and the internet of things I start with a discussion of the enablers of AI, tech- (IoT). McKinsey Global Institute predicts that IoT nology maturity and convergence, which includes will have a total economic impact of up to $11 tril- basic definitions, a brief historical overview, and a lion by 2025 (3). Currently less than 0.1% of all the discussion of the influence of the Fourth Industrial devices that could be connected to the internet are. Revolution. In the next section, I address adapting the Consider, then, the tremendous potential IoT brings business school curriculum to prepare future leaders. for business and society. In addition, the introduction The last section presents how the College of Business of the quantum computer presents another enabling and Public Policy (CBPP) at the University of Alaska force. Together, these hold enormous promise to Anchorage (UAA) is pursuing multiple approaches to change the future for business. fulfill these needs. The conclusion poses some ques- The proliferation of data—big data—is also trans- tions for further discussion. forming the way organizations operate and increasing the demand to convert data into actionable decisions and predictions. Predictive analytics is the use of data, statistical algorithms, and machine learning (ML) WHAT IS THE BUSINESS WITH AI? 3 techniques to identify the likelihood of future out- customer-centric company” by providing fast, con- comes. It goes beyond knowing what has happened venient, and reliable delivery speed with customer to providing a best assessment of what will happen satisfaction. Amazon uses predictive analytics for in the future. In fact, we are at the start of a new era targeted marketing to increase customer satisfaction in decision-making with the integration of AI and and build company loyalty. In its fulfillment cen- business intelligence (BI). This integration surfaces ters and warehouses, Amazon uses robots and AI to significant insights that would otherwise remain hid- streamline processes for faster delivery. Its patented den and provides predictive capabilities, solutions, anticipatory shipping model uses big data and data and actionable decisions in real time. analytics to predict the products in demand, when A good example of a real-time environment that purchases will occur, and where the products will benefits from AI is the stock exchange. Some hedge go, thus increasing its sales and profit margins while funds use AI to decipher as many as 300 million data decreasing its delivery time and overall expenses. AI points on the New York Stock Exchange in the first has helped Amazon achieve a trillion-dollar market hour of daily trading alone. Computers make 60% cap (7). of all market trades—sometimes as high as 90%. Powerful computers match buy and sell orders in Some Basic Definitions and a Brief Background the blink of an eye without human intervention and of AI are able to crunch countless data points in minutes. AI is the field of study dedicated to simulat- However, AI can spot trading inefficiencies or market ing intelligent human behavior in machines. It has differentials on a very small scale and execute trades developed a set of computer-driven tools intended to according to investor instructions. It can detect his- mimic human abilities. AI enables machines to learn torical and replicating patterns for smart trading and from experience, adjust to new inputs, and perform evaluate thousands of stocks in moments (4). human-like tasks. ML is a specific subset of AI based NASDAQ is using AI to detect irregular, poten- on artificial neural networks (ANN). It discovers and tially fraudulent activity. Combined with ML and recognizes useful patterns between different items of high-speed processing power, AI is identifying com- data using sophisticated mathematical algorithms. plex trading patterns across all markets in real time. When this paper references AI, it will include ML. NASDAQ has found that AI can capture informa- In the 1980s, there was a big shift among AI research- tion that statistical models have not (5). ers from a “rule-based” approach to one based on In transportation, autonomous cars are an exam- statistics—probabilistic methods of machine trans- ple of technology convergence. They use AI—neural lation. This reflected a broader shift to ML. ANNs networks, sensors, LIDAR, and computer vision in provide a complex form of ML modeled after the particular. In 2019, dozens of such vehicles logged human brain and how its neurons process signals. In millions of miles. BMW, Mercedes, and Toyota as our brains, each neuron receives signals, processes well as Apple, Google, Uber, and Tesla are compet- them, and sends them to other neurons. The human ing for this emerging market. Many date the pivotal brain consists of billions of neurons interconnected breakthrough for autonomous vehicles to 2004 when to each other. ANNs view problems in terms of lay- the Defense Advanced Projects Agency (DARPA) ers of inputs and outputs, and layers in between that created a driverless car competition—the DARPA assign weights to variables that associate inputs with Grand Challenge—to turbocharge development (6). outputs. In ANN, the nodes are the neurons, and the In 2021, an autonomous car race will be held, and the synapses are the weights. To train the neural network, organizers attribute their inspiration to the DARPA the weights are adjusted (8,9). Grand Challenge. A deep neural network (DNN) is an ANN with Amazon shows how AI can benefit a corporation. multiple layers between the input and output layers. AI, combined with BI, robotics, and IoT, has helped More than three layers (including input and out- Amazon evolve into a giant among online retail stores put) qualifies as DNN. In deep-learning networks, and to achieve its CEO’s vision to be “Earth’s most each layer of nodes trains on a distinct set of features 4 WISNIEWSKI based on the previous layer’s output. The further you Language Translation,” causing the shift from a “rule- advance into the neural net, the more complex the based” approach to one based on statistics. However, features your nodes can recognize since they aggre- it was not until the 2000s that many of the landmark gate and recombine features from the previous layer. goals were achieved (11), partially due to the conver- Each mathematical manipulation as such is consid- gence of technologies. The last few years have seen ered a layer, and complex DNNs have many layers, techniques that were science fiction transform into hence the name “deep” networks (9). Neural networks science fact. are an example of a technology that has matured over time. Many AI examples that you hear about The Fourth Industrial Revolution today—from computers that play chess and Jeopardy The Fourth Industrial Revolution is causing cor- or debate with humans, to self-driving cars, to object porations to redefine how they will do business and recognition, including facial recognition methods— reshaping the definition of work. Klaus Schwab, rely heavily on DNNs. founder and executive chairman of the World AI is not new. In 1951, Marvin Minsky and Dean Economic Forum in Geneva, nicely summarized Edmonds developed the first ANN called SNARC, the Fourth revolution: or the Stochastic Neural Analog Reinforcement Computer. It was not made of microchips and tran- The First Industrial Revolution used water sistors but of vacuum tubes, motors, and clutches. and steam power to mechanize production. In 1950, Alan Turing published a paper including The Second used electric power to create mass the major philosophical benchmark “The Turing production. The Third used electronics and Test,” which is still used today to evaluate machine information technology to automate produc- intelligence. Whether this has yet been achieved is tion. Now a Fourth Industrial Revolution is still debated. In 1956, John McCarthy coined the building on the Third, the digital revolution phrase “artificial intelligence” at a conference held that has been occurring since the middle of the at Dartmouth College, and in 1959, Arthur Samuel last century. It is characterized by a fusion of coined the term “machine learning.” In 1961, the technologies that is blurring the lines between first industrial robot, Unimate, started working on the physical, digital, and biological spheres. (12) an assembly line in a General Motors plant in New Jersey (10). The early to middle 1970s experienced an Technologies like AI, nanotechnology, quantum AI winter, largely due to lack of the required compu- computing, synthetic biology, and robotics will all tational power. Computers could execute commands, drastically supersede any digital progress made in the but they could not store enough information or pro- past 60 years and create realities that we previously cess it fast enough. In addition, funding was an issue. thought to be unthinkable. Such profound realities The late 1970s brought change and the 1980s a resur- will disrupt and change the business model of every gence of AI research enabled by an expansion of industry. When compared with previous industrial funds, computational power, and innovative algo- revolutions, the Fourth is evolving at an exponential rithmic tools (11). An example of increased funding pace. According to McKinsey, up to 375 million work- was DARPA’s Strategic Computing Program, which ers worldwide may need to change their occupational gave DARPA an extraordinary level of funding for categories by 2030. However, millions of jobs will be research in AI and innovative computers and enabled created (13). The World Economic Forum predicts it to significantly advance these fields. John Hopfield that 1.6 million jobs will be displaced in the U.S., but and David Rumelhart popularized “deep learning” 2.6 million will be created, a gain of one million jobs. techniques, which allowed computers to learn using Digital talent platforms could contribute $2.7 tril- experience. Edward Feigenbaum introduced expert lion to global GDP by 2025. These platforms would systems, which mimicked decision-making processes increase employment by 72 million full-time-equiva- of a human expert. Members of the IBM Watson lent positions by connecting talent with opportunity Research Center published “A Statistical Approach to in the digital age (13,14). WHAT IS THE BUSINESS WITH AI? 5

AI Coupled with the Fourth Industrial Revolution that the Fourth Industrial Revolution will reshape The Fourth Industrial Revolution and AI are society, and future leaders will need to be intimately driving a new model of work (14). AI-centric orga- familiar with technologies such as AI, robotics, and nizations exhibit a new operating architecture, advanced analytics. He argues that we need to expose redefining how they create, capture, share, and deliver students to applications through more action-based value. High demand for skills in AI and data science learning models—to move from “classroom to lab.” will continue to grow drastically during the next Businesses are recognizing that their role in society decades. To meet this demand and transformation, it involves not only paying attention to shareholders is vital that AI and business applications be integrated but to stakeholders as well and that they need to be into various curricula beyond engineering and com- a part of crucial solutions that affect society. Schools puter science and that an AI business curriculum be need to support lifelong learning and need to “be rel- created for those who are not planning to pursue a evant over the course of a working life”(15). career in developing or programming. In particular, These four areas support the need for business there is a need to train decision makers and leaders schools to train future leaders to be familiar with to understand the concepts and applications of AI AI and related technologies by including them in and how to use these in their enterprises. AI needs the curriculum. Today’s education systems have not to be more than a footnote in courses; a more com- kept up with the rapid pace of change. Too many of prehensive study is necessary. today’s graduates are not ready for the jobs that exist Master of business administration (MBA) stu- now and in the future. In the article “Implications dents do not have to be computer engineers, electrical of Artificial Intelligence on Business Schools and engineers, or data scientists, but they do have to Lifelong Learning” by Jennifer Stine, Anne Trumbore, understand that a significant part of the value cre- Toby Woll, and Heber Sambucetti (16), the authors ation in companies revolves around connectivity and point out the following threat. Every school they platforms (IoT and sensor networks) and interpret- investigated believed that creating or revising new ing massive amounts of data generated anywhere curricula so students would be prepared for “an and anytime connecting customers and products. AI-enabled workplace” was possible but that the “tra- Business graduates without a solid understanding ditional” preparation of faculty presents “barriers to of how technological solutions can generate value quick action.” However, they found that non-educa- will be hopelessly stuck in the 20th century and at a tional organizations, (e.g., “corporations and platform disadvantage on the field where competition really providers”) are adapting to the “new AI technolo- takes place in the 21st century. There is a need to gies” much faster.” An overall concern was about the develop curricula that reflect a mix of pedagogies ability of current faculty to adapt to the new environ- and approaches. ment and provide the needed skills. They also noted that AI in business requires technical expertise that ADAPTING THE BUSINESS SCHOOL TO not all current business students or faculty have and PREPARE FUTURE LEADERS that this may necessitate both more courses that are Will Business Students Educated Today Be technical and more technically-oriented students and Employable for Future Jobs? faculty. This was a topic of the Economic Forum Annual Tim Mescon, executive vice president and chief Meeting 2020. Knut Haanaes, dean of the Global officer of Europe, the Middle East, and Africa at Leadership Institute at the World Economic Forum, the Association to Advance Collegiate Schools of had identified the following four ways that univer- Business (AACSB) International, expressed similar sities must evolve to meet the demands of future concerns in a recent article. He states that business leadership needs in a January 2020 article in Forbes: in the future will be transformed by AI, and other embrace technology, create action-based learning emerging technologies, and that “technology literacy” models, understand the expanded role of business is a must for leaders (17). The means by which future in society, and support lifelong learning. He explains leaders develop technology literacy are as important 6 WISNIEWSKI as the knowledge itself. Indeed, those who control the next section. the research and training required to succeed in the AI-enabled workplace will define industry standards UNIVERSITY OF ALASKA ANCHORAGE for a new era in human history. Technology and tal- UAA’s CBPP is AACSB accredited. We are employ- ent must go hand in hand as we shape our collective ing a combination of approaches to train students industrial future. This puts educators at the forefront for the future workforce and to prepare future lead- of industrial transformation—and not just in tech- ers and decision makers. I also found that business nical fields. Business educators, too, must motivate students lacking a technical background were never- learners to embrace new technologies and under- theless able to grasp an understanding of the methods stand how they will be applied in future enterprises. and technologies. As AI systems sense, think, learn, and take action in shared workspaces, today’s business students must The First CBPP AI Course understand and successfully collaborate with AI in At UAA, I am a professor of entrepreneurship and their future professional roles. That’s why AACSB the chair of the Management, Marketing, Logistics and our accredited business schools are preparing and Business Analytics Department (MMLBA) and leaders for a “future that does not yet exist.” previously served as vice provost for research and dean of the UAA Graduate School for seven years. As A Combination of Approaches vice provost, I led and grew the research enterprise, Based on these articles and my experience in the established the first technology commercialization field of AI, as a professor and an executive in industry infrastructure at UAA, and dramatically increased the and government, I believe that an effective curricu- number of patents. I am also the founding director of lum in a school of business will employ a combination the Arctic Domain Awareness Center at UAA, which of approaches to prepare students for the future work- I created to improve situational awareness and crisis force. The combination of approaches could include response capabilities to Arctic maritime challenges. the following. My experience spans executive and leadership Separate courses in AI should not only provide a positions in industry, academia, and federal govern- foundation in AI concepts such as deep learning and ment as well as service on private and public boards of machine learning but also illustrate how these con- directors. While at DARPA, I identified and directed cepts are used to transform organizations. Business many breakthrough advances in science and engi- applications should not just be relegated to footnotes. neering, including AI—in particular, ANNs—as well Infusing AI into traditional business courses, such as facial recognition, image compression, and air- as leadership, accounting, and logistics and supply craft design as the program manager of the Applied chain management, is needed. Having faculty with and Computational Mathematics Program that I business experience teaching the AI with business started. I directed corporation-wide technology inno- applications course is a requirement. An effect of vations as an executive at the Lockheed Corporation the Fourth Industrial Revolution will be that busi- and as vice president at the Titan Corporation and ness schools will need to take a more collaborative, ANSER that included leading the development and interdisciplinary approach to curriculum to prepare applications of AI. Prior to UAA, I served as the students to be successful leaders in the workplace. vice president for university research and enterprise This collaborative approach will include business development at Stevens Institute of Technology. I am schools creating opportunities for industry part- a technological entrepreneur who has launched and nerships. Business schools will also have to rethink sold start-ups and coauthored the book Academic and incorporate a new paradigm of pedagogy that Entrepreneurship. I am also a Fellow of the National blends these approaches to be able to train students Academy of Inventors. for the future workforce. In the CBPP at the UAA, Recognizing the importance of AI instruction we are implementing these approaches. What we are in a college of business, I developed CBPP’s first AI doing and the impact of these efforts is the focus of course AI Concepts and Business Applications and WHAT IS THE BUSINESS WITH AI? 7 taught its initial class in 2019. A unique feature of the train the machines. Computer scientists at Google course is the extensive use of guest lectures by lead- built a neural network of 16,000 computer proces- ers in local and national enterprises who currently sors with one billion connections and let it browse use AI in their operations. This provides the student YouTube. Furthermore, business leaders can under- with up-to-date knowledge of the state of the art in stand how a computer is able to identify a particular business AI. person or image because of neural networks. Students discover how AI is producing some of For business leaders, it is important to grasp the the most effective and dramatic results in business truth behind some of AI’s promise. They need to today. The course provides an understanding of key obtain a sense of the basics of AI so that they can AI technologies, including neural networks, DNNs, determine if it is being applied correctly to solve ML, robotics, cyber security, and biometrics, and problems in their organizations. Business leaders shows how companies are using these technologies need relevant knowledge to discover opportunities to to transform into innovative, efficient, and sustain- drive innovation and efficiency in their organizations. able companies of the future. Students learn how to This knowledge will empower a business leader to leverage AI in business models to identify new oppor- ask the right questions about whether methods such tunities, competitive advantages, and more efficient as ML applications will benefit a particular business processes; probe the implications of using AI tech- problem or make their organization more efficient. nologies for business strategies as well as the social, To make informed decisions and strategies using AI, ethical, and economic issues they raise; ponder what they need to understand what business problems can is real and what is hype; and contemplate the future be solved using AI and understand the potential of of AI. The course starts with an overview of AI. AI as well as the limitations. They need to be able to Upon completion of the course, students are able determine whether an employee is correctly applying to demonstrate a fundamental understanding of key ML, understand questions that an employee might AI concepts and technologies, the state of AI in busi- have regarding a particular application, communi- ness today, and the future of AI. They have acquired cate effectively with technical teams, determine what the capability and knowledge to make informed stra- technical talent to hire in AI, and encourage their tegic decisions about how to use AI technologies in human resources organizations to consider using their areas of business as well as the ability to develop AI as part of the hiring process. A good understand- a plan to incorporate AI into their business strategies/ ing of ML will enable business leaders to determine models to identify new opportunities, competitive if the testing of ML is being done correctly and sug- advantages, and processes that are more efficient. gest ways to make testing more effective. They must They understand the skills required for implement- also understand how to avoid pitfalls associated with ing AI that will be assets in planning, management, AI technologies. and hiring. Some examples of companies whose leadership One area of AI that I would recommend for busi- have effectively used AI to achieve their visions and ness professionals to understand the basics of would create outstanding growth and market value are be ML, particularly neural networks. Neural net- Amazon, Apple, Tesla, and Microsoft. works are the basis for some of the most impressive AI applications and advances, including medical appli- Table 1. Student Learning Outcomes cations, autonomous vehicles, logistics and supply chain management, finance and investment, robotics, and facial recognition. Business leaders do not need to be able to code a neural network. However, they should be able to understand how it is used to train computers. As an example, recall the news that Google’s computers taught themselves to identify cats. It was not by magic but by using neural networks to 8 WISNIEWSKI

Course Topics and Student Learning Outcomes project plan will also identify roadblocks for imple- The topics for my course include the following: menting AI as well as how to eliminate them. It will • An overview, timeline, and background of AI consider whether there is a need to hire more talent to implement their plan and successfully integrate • An introduction to AI that included key con- AI into the organization/business. It will also address cepts and technologies and explanation of how any ethical issues. they have evolved to transform industry, busi- The project comprises three parts that are refined ness, and society during the course. Each part builds on the concepts • ANNs and DNNs—how they learn with appli- presented in the course as well as on the previous cations to business and other areas part. After the completion of each part, the students present their findings to the class for input using a • A look at the core concepts and applications of PowerPoint presentation, and they submit both the ML slideshow and a written report to the professor. The • Robotics, including examples of where and how final piece is a PowerPoint presentation and report, they are used in various business applications and the students give their presentations to the class and the benefits as well as to experts from industries in the commu- • Biometrics, especially facial recognition, and its nity. My students have chosen all three options for applications in business areas such as marketing their projects: companies they currently work for, other corporations, and entrepreneurial endeavors. • Leveraging data analytics for new business In part one, the organization/business/corporation opportunities is selected, a detailed outline of the problem is pro- • Applications of AI in business, as well as its ben- posed, and how AI might be a solution is discussed. efits, are presented throughout the course Also, what AI tools or techniques they would use is • Cyber security and privacy issues suggested. The approach may change or evolve during the course, and that is fine. • Ethical concerns and policy matters Part two elaborates on the outline from part one, and students begin to apply and incorporate some Throughout the course, guest lecturers from cor- actual AI tools, such as neural networks, robotics, or porations, government, and universities, who are other concepts that are appropriate to the applica- experts in various aspects of AI, provide presentation. They identify roadblocks to implementing AI tions. Table 1 presents the student learning outcomes as a solution, state how these can be overcome, and for the course. explain why AI technology will solve the problem. They present part two to the class for discussion and Student Projects input. To emphasize the applications of the concepts Part three incorporates parts one and two and learned in the course and give students a more demonstrates how the AI technologies selected can hands-on experience, the class divides into teams actually solve the problem. It states whether the solu- of four to five members each that develop and com- tion could benefit other organizations. In addition, plete a project. For this project, the teams have a few in part three, students discuss how the solution using options. They can develop a plan for how AI can be AI can be incorporated into a business strategy to used in their current organization, or some other identify new opportunities, competitive advantages, enterprise, to solve a problem that it faces and be and processes that could be made more efficient. The incorporated into their strategies/models to iden- students conclude the presentation with the specific tify new opportunities, competitive advantages, and benefits for the organization and identify some future processes that are more efficient. Another option is directions the organization may take due to imple- more entrepreneurial—to develop a new technology/ menting AI. For part three, a written final report business to benefit and fulfill a need in society. The and a PowerPoint presentation that each team makes WHAT IS THE BUSINESS WITH AI? 9 to the class are required. Individual team members Here are some examples of student success from must give a part of the presentation, and their roles both the initial course in Spring 2019 and the course in the project must be clearly defined. They present in Spring 2020. Based on their group projects, some part three to the class and community leaders for students are pursuing patents. One group from the discussion and input. 2019 class is filing a patent that could contribute to the The students receive a grade for each of the three next generation of Fitbit, and students from the 2020 parts that comprise the class project. These three class are filing a patent based on their “Smart Sports projects total 75% of the grade. In addition, class pre- and AI Athletics” project and are considering forming sentations, discussions, and case studies total 25% of a start-up. Another group was inspired to take their the grade. project further. In Spring of 2020, they took the MBA Individual Research Course, and I was their advi- The Course Evolution and Student Success sor for a research project. They completed the paper The initial course, taught in the Spring semester “Using Artificial Intelligence to Improve Efficiency of 2019, had ten students enrolled with various back- in Industrial Processing Business Decisions,” which grounds. The success of this course was evidenced applies AI to an industry they are familiar with and by the fact that the second time it was taught, the have experience in, and are submitting it for publi- enrollment more than doubled to 27 students. This cation this fall. A student in my Spring 2020 course was largely due to recommendations of students from was motivated to further apply concepts of the course the first course and included a student from a neigh- and take the MBA Individual Research course to boring university. write a paper on the ethics of AI. I will be her advi- It was a stacked course with both graduate stu- sor for the research. Other students applied concepts dents and upper-level undergraduates. The graduate learned to organizations for which they are working, students were pursuing MBAs and most did not have for example, how to use AI to meet various needs at technical backgrounds with the exception of two stu- their Boys and Girls Club or how to apply AI to a dents who had engineering degrees. This was a good satellite company one of their members worked for. representation to determine if the fears expressed by universities that students needed a technical back- Faculty with Business Experience Teaching the AI ground were founded. I found that was not the case. Course and Additional Experts I did not forgo the technology. I covered technical I am the professor for the course and share with areas such as neural networks, how they learn includ- the class my experiences, which include initiating and ing back propagation, and examples of DNNs. One directing the development and advancement of AI book for the course was AI and Machine Learning for methods and technology, in particular ANNs and the Business. I was not sure if the students without a tech- development of a neuro processor. While at DARPA, nical background would follow. However, I found that as the program manager of ACMP, I was also involved the students without a technical background were in the DARPA Strategic Computing Initiative that able to follow. Their response was that they were able significantly advanced research in AI and innovative to get a good appreciation of the importance of the computers. As part of my experience as a senior exec- mathematics and grateful that they did not have to utive at Lockheed, and as a vice president at ANSER, solve any partial differential equations. One student I led the development and application of AI meth- with an engineering undergraduate degree shared, ods to provide a competitive advantage, increase “So that is what partial differential equations are good customer satisfaction, and benefit society. For exam- for!” Some students actually wanted to do some cod- ple, at ANSER, I combined AI with biometrics to ing. I will plan to do this in another course. At the find missing and exploited children on the internet. end of the course, students were asked to answer I also used AI and methods that I developed in bio- questions anonymously that included the following: metrics when I was the CEO of Aurora Biometrics, Would you recommend this course to another stu- Inc., a company that I founded to provide facial rec- dent? The unanimous response was “yes.” ognition systems. I built the business and sold the 10 WISNIEWSKI company. Students appreciated my real-life experi- Capital Management (MCM). The lab is housed in ences and expertise in AI, which I shared through the CBPP and the College of Engineering at UAA. multiple examples and applications. However, since This interdisciplinary center draws on the talent and I have a Ph.D. in mathematics and previous experi- resources across the University of Alaska campuses ence in AI, especially neural networks, the following to advance both the science and technology of AI. question arises: How much mathematics or engi- The lab focuses on the application of those tools in neering knowledge is required for business faculty academic research and private industry to solve the to teach AI? challenges facing Alaska and the nation while train- In addition, the guest speakers that I have from ing the data scientists and AI researchers. industry and government are experts in the field The partnership with MCM focuses on AI applica- and apply and lead AI at their corporations or in tions in the financial industry. Traditionally, industry government. They provide live class lectures with data comes in the form of financial statements, earn- discussions. In these presentations, they illustrated ings announcements, and regulatory filings. However, how their organizations use AI as well as the benefits the future of investing is increasingly based on new and shortcomings of doing so. These organizations types of datasets, such as crowdsourced earnings included telecommunications (a VP from GCI and forecasts, web scraping, social media, satellite imag- some of his team), oil and gas (BP and Conoco ery, GPS geolocation data, and more, which were not Philips), investment firms (CEO and managers analyzed previously from a financial perspective. The from McKinley Capital Management), and govern- information gathered from these new avenues often ment agencies (retired NSA manager, who wrote an provides clues to consumer behavior and patterns award-winning book on cyber security). They also that can be analyzed to predict earnings. included an inventor at Columbia University who Harnessing this information and structuring it just released his work on a new robot, in 2019, that so it can be parsed into actionable data is the pri- modeled itself without prior knowledge of physics or mary function of the McKinley Data Science Team its shape and used the self-model to perform tasks, at MCM. Its search algorithms can read, synthesize, detect self-damage, and repair itself (18). In addition, and analyze tens of thousands of documents and then I included representatives from other UAA Colleges, further analyze millions of data points pulled from such as the dean of the College of Engineering, who the documents nearly instantly. What to scan for and presented aspects of ML with actual demonstrations. how to interpret the results defines the most critical Those from locations outside of Alaska pro- skills, a challenge that requires not only expertise but vide their live presentations via telepresence persistence and significant investment. robots. Speakers were also available for continued The partnership with MCM focuses on the applica- interactions with students and encouraged those tion of AI and ML skills and tools to solve real-world interactions. They also facilitated external collabo- problems and circumstances that arise in global ration with industries and government. financial markets. It includes internships at MCM To enhance concepts further and to provide for students at UAA. The CEO of MCM, Rob Gillam, demonstrations of the technology, I used videos that has stated: included demonstrations of new products, case stud- Our goal with students is to help develop their ies, and interviews with successful CEOs who had skills, oversee their senior projects where appro- implemented AI in their organizations. priate, and collaborate with staff on research across the spectrum of AI-related projects. We A More Collaborative Approach to Curriculum— value the university and its dedication to student Lab for Data Science and AI learning; as a company, we want to invest in our In 2019, we established the Lab for Data Science community’s most critical assets: the students and AI at UAA. This lab is a collaborative effort and the youth of Alaska who are our future. between CBPP and the College of Engineering in This partnership allows us to provide UA stu- partnership with an investment firm—McKinley dents a place where they can apply their talent WHAT IS THE BUSINESS WITH AI? 11

and create a future for themselves. It’s a really Module 4 was Supply Chain Management exciting partnership for us. (19) Technology Innovations. In the topics, I infused the role of AI. The topics included AI, IoT and technology In Spring 2019, the first group of interns was selected. for the physical internet, 5G, automatic identification, Growing the Data Science and AI Lab is a goal of functional automation, mobile connectivity, robot- CBPP. In addition, we are involving community lead- ics in the warehouse, wearable technology, picking ers as guest speakers from industry and government technology, autonomous fleets, and self-orchestrated and having students present their projects to com- supply chains. The learning objective for this mod- munity leaders as well. ule was that, at the completion of this module, the student would be able to have an understanding of Future Directions for the Course IoT, wearable technology, and related technologies; The first two classes were under the “Advanced how they are used; their interrelationships; and their Special Topics” category. However, given the suc- current impact and future implications for the sup- cesses of the classes and students, I am in the process ply chain. In addition, the student would acquire a of making it a permanent course starting in Spring further understanding of the role of AI and robot- 2021. The next class will include using software and ics on the supply chain. I did not find a book that inputting values to illustrate how they work. Even addressed GSCM and included in-depth understand- students who are not technical experts seemed inter- ing of AI, BI, robotics, IoT, 5G, and their impact and ested in such a direction. A second possible course importance to GSCM. Therefore, I created the presen- to follow this one is under consideration and will tations for the class, incorporated videos to illustrate involve simple programming techniques used in concepts, and included videos of interviews with many organizations to be collaborative with the leaders and decision makers in industry, for exam- College of Engineering at UAA. ple, the head of the Alaska Railroad, the head of the Ted Stevens Anchorage Airport, managers at FedEx, Integrating AI into Traditional Courses and our logistics Professor Darren Prokop. Professor Addressing the need to not only have standalone Prokop and I are now planning to collaborate and courses in AI but also integrate it into traditional write a book that can be used for this course. Students business, in Spring 2020, I integrated AI and data sci- who completed the course greatly appreciated the AI ence into the graduate course that I taught in Global and technology emphasis. Many are recommending Supply Chain Management (GSCM). The Master of the MS GSCM to colleagues where they work. Science (MS) GSCM degree is completely online, and CBPP has an undergraduate minor in entrepre- each course has multiple modules. In this class, I not neurship, so in addition to the MS GSCM, I integrated only taught a separate section in a particular mod- AI into the entrepreneurship courses that I taught. ule on concepts of AI but also integrated AI into the I did this through both a separate topic section various modules and topics throughout the course. devoted to an overview of some AI fundamentals The following are two examples using modules three and throughout various topics of the course to stress and four. the importance of technology innovation to entre- Module 3 was Tools for Facilitating the Supply preneurship. I have also done a similar inclusion in Chain, and the topics were AI, BI and business ana- the graduate level course as well. lytics (BA), and robotics in supply chain. I also In addition, my colleagues in CBPP and I have illustrated the use of AI in robotics and the relation- begun a dialogue about integrating AI into traditional ship between AI, BI, and BA. The learning objective business courses, such as leadership and accounting, for this module was that the student would be able as well as undergraduate courses in logistics. In par- to have an understanding of BI, analytics, AI, and ticular, we are investigating what the best way to have robotics, how they are implemented in the global it taught in traditional MBA courses is. Should it be supply chain, and their importance in the global sup- by developing specialized modules customized for ply chain. 12 WISNIEWSKI a particular class, team teaching, or having experts and leaders, it is vital that AI concepts and business present special lectures? For example, Associate Dean applications be integrated into curricula in business Terry Nelson invited me to be a guest speaker in her schools. class Leadership and Organization Behavior to dis- I believe that an effective curriculum in a school cuss how AI concepts apply to leadership. In addition, of business will employ a combination of approaches the following question surfaced: How much knowl- to prepare students for the future workforce. This edge about AI would a professor need to teach AI combination of approaches includes the following. concepts or applications to their field in their course? Separate courses in AI that not only provide a foundation in AI concepts such as deep learning and Business Analytics (BA) and AI Certificate machine learning but also illustrate how these con- To meet community needs for persons currently cepts are used to transform organizations are needed. not pursuing degrees but who have the desire to learn Business applications should not just be a footnote. more about AI and data science, we developed a The goal should be to incorporate AI into traditional graduate certificate in BA and AI. This was a recent business courses, such as leadership and accounting, collaborative effort led by the CBPP Associate Dean and other areas such as logistics and supply chain. Nelson, the CBPP Director of Graduate Programs Dr. Having faculty with business experience teaching Sandra Ehrlich Mathiesen, and me. It will be offered the AI with Business Applications course would be in the AY 2020/21. ideal. A more collaborative approach to curriculum This certificate prepares students to transform that includes industry partnerships, internal collab- company data into actionable insights. They will orations between the college of business and other develop skills for effectively gathering, analyzing, colleges in the university, and community engage- and applying information to improve decision-mak- ment is needed. ing and increase organizational performance and CBPP has employed these approaches with suc- competitiveness. The high demand for skills in BA cessful results. Furthermore, due to these successes, and AI will grow exponentially over the coming it expanded offerings and established a certificate in decades. These highly transferable skills will enable AI and Business Analytics. In addition, contrary to students to shift careers across industry sectors or fears expressed, I found that students did not need jumpstart a graduate degree. A total of twelve credits a technical background to understand and appreci- are required for the certificate, and it can be com- ate the technical areas such as neural networks and pleted within a year. Nine credits are from the courses ML. Colleagues in CBPP have begun discussions to Business Intelligence and Analytics, AI Concepts & integrate AI into their traditional courses, and some Business Applications, Advanced Data Analysis, or began doing so. Data Warehouse & Business Intelligence, and the I plan to continue to track the evolution of the final three credits are from a list of courses of their AI Concepts and Business Applications course for choice offered in the MBA, master of public admin- a more comprehensive case study of the course and istration, or logistics. to evaluate the success of implementing multiple approaches for integrating AI into the CBPP cur- CONCLUSION riculum as well as its contribution to increasing AI is reshaping and transforming the future of enrollment and student success. business. The speed of technological advances has no I will leave you with the following thoughts. In historical precedent, and the high demand for skills writing this paper, a few questions for future work in AI and data science will continue to grow drasti- surfaced. 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