Sam Ransbotham and Shervin Khodabandeh

Why do only 10% of companies succeed with AI? In this series by MIT SMR and BCG, we talk to the leaders who've achieved big wins with AI in their companies and learn how they did it. Hear what gets experts from companies like Walmart, DHL, and others excited to do their jobs every day and what they consider the keys to their success.

Season 1

Prakhar Mehrotra, Walmart

Sam Ransbotham and Shervin Khodabandeh

Walmart’s Prakhar Mehrotra discusses leading AI teams and workstreams in this episode of the Me, Myself, and AI podcast.

In this episode of the Me, Myself, and AI podcast, Prakhar Mehrotra, vice president of machine learning at Walmart, discusses his background and explains how it helped prepare him to lead an AI team at a $500 billion retailer.

As vice president of machine learning, Prakhar Mehrotra is one of the top executives for AI and machine learning at Walmart and an internationally recognized leader and innovator in the field. He was recently awarded The Franz Edelman Medal by INFORMS for significant contributions in data science and advanced analytics. He is a senior member of the Institute of Electrical and Electronics Engineers and serves as a peer reviewer for top conferences and journals in AI, including the Association for the Advancement of Artificial Intelligence conference, the Conference on Computer Vision and Pattern Recognition, and the International Conference on Autonomous Agents and Multiagent Systems.

Before joining Walmart, Prakhar led data scientists and developed stochastic models at Uber and Twitter, where he learned how to move quickly and scale AI. (Fun fact: He even drove for Uber to better understand the driver experience — a perfect example of the role empathy plays in AI.) Now tasked with using artificial intelligence to help with decision-making and enhance the business, Prakhar focuses on the technology that improves store merchandising, which includes pricing, inventory management, and financial planning.

Hear Prakhar share stories on rallying and educating teams on AI, the relationship between AI and business intelligence, and what it means to make big bets in an enterprise setting.

Slawek Kierner, Humana

Sam Ransbotham and Shervin Khodabandeh

Using AI and simulations in health care can help doctors better serve patients.

Sam Ransbotham and Shervin Khodabandeh

Slawek Kierner, senior vice president of enterprise data and analytics at Humana, has been immersed in data for as long as he can remember. His fascination with process simulations began with his first PC, running Matlab and Simulink, and it later led him to innovative roles at Procter & Gamble and Nokia. Slawek’s desire to use data for a noble purpose brought him to Humana, where he uses AI to solve problems around medication adherence and predict population health outcomes.

Slawek Kierner is Humana’s senior vice president, digital health and analytics. He is responsible for enabling data governance, analytics platforms, data science, and artificial intelligence integration across the enterprise to foster innovative solutions that help Humana’s communities, members, care teams, and employees more easily take actions for better health outcomes.

Slawek has previously served as the chief data and analytics officer for the Microsoft Business Applications Group and has led digital marketing operations and information systems for Procter & Gamble’s European business. He also served as a board member and CIO for P&G’s Central Europe division.

In this episode of Me, Myself, and AI, Slawek describes how re-creating synthetic individual profiles indistinguishable from those of real humans can help physicians better predict patient admissions and behaviors. He also shares stories on how his team created an internal machine learning platform that gives data scientists access to open-source capabilities — all in pursuit of helping human beings live longer, healthier lives.

Gina Chung, DHL

Sam Ransbotham and Shervin Khodabandeh

AI is a powerful tool for innovation when leaders communicate its benefits.

Sam Ransbotham and Shervin Khodabandeh

As vice president of innovation at logistics company DHL, Gina Chung oversees a 28,000-square-foot innovation facility in Chicago. Fascinated with supply chains since college (“I think it’s something to do with the fact that I’m from New Zealand and grew up in a pretty isolated part of the world,” she explains), she spearheads AI and robotics projects focused on front-line operations — like automated pallet inspection and stacking, delivery route optimization, and aircraft utilization.

Gina Chung is vice president, Innovation Americas, at DHL, where she is responsible for DHL’s Americas Innovation Center, a purpose-built platform to engage customers, startups, and industries on the future of logistics. She manages a portfolio of projects focused on the rapid testing and adoption of technologies such as collaborative robotics and artificial intelligence across logistics operations.

Gina notes that “the first day for AI is the worst day”: The technology improves with human input over time, achieving accuracy to a level where people trust and embrace it. She describes how success requires closely collaborating with key stakeholders, integrating change management, bringing teams along when introducing new technology, and designing solutions with the end user in mind.

Mattias Ulbrich, Porsche

Sam Ransbotham and Shervin Khodabandeh

Porsche is accelerating innovation by emphasizing the need for collaboration between humans and AI technology.

Mattias Ulbrich has always been interested in new technology. As CIO of Porsche and CEO of Porsche Digital, he runs a subsidiary focused on the “new stuff” — new ideas, new models, and new opportunities. That means implementing innovations in AI, cloud technology, and blockchain in local markets around the world, and instilling a culture of continuous learning within his own cross-functional workforce.

Mattias Ulbrich has been CIO at Dr. Ing. h.c. F. Porsche AG since October 2018 and CEO of Porsche Digital GmbH since April 2019. After studying electrical engineering at the Technical University of Braunschweig, Mattias began his career in the sales division of American IT company Hewlett-Packard in 1993. He joined Audi AG in 1998, working at the Neckarsulm, Germany, site until 2003. Mattias was subsequently appointed CIO at SEAT in Barcelona, Spain, and then joined Volkswagen in 2006. From 2012-2018, Mattias was CIO at Audi AG.

In this episode, Mattias shares examples of how AI is accelerating innovation at Porsche — by enhancing product design and the driving experience, improving production and sustainability efforts, and better managing the global supply chain. He has also connected some unlikely dots from other spaces — for example, by using the sound of an espresso machine to inform car component design.

Arti Zeighami, H&M Group

Sam Ransbotham and Shervin Khodabandeh

The fashion retailer’s chief data and analytics officer uses agile pilots to assess and scale technology initiatives.

Arti Zeighami’s interest in artificial intelligence started when he read science fiction as a teen. Yet as head of advanced analytics and AI for global retailer H&M Group, his leadership style focuses on reality: first building a business case and a proof of concept, and then undergoing an agile process of iteration and scaling, failure and success, measurement and improvement.

Arti Zeighami is a senior executive and a business leader at H&M Group. As chief data and analytics officer, he is responsible for all AI, analytics, and data capabilities across all of the company’s brands.

In this episode, Arti talks about weaving AI into the value chain in the fashion industry — specifically around personalization, pricing, merchandising and forecasting. He has coined the term amplified intelligence — where humans and machines work together — and in this episode shares stories and practical tips on how teams can get started and scale successfully.

Kay Firth-Butterfield, World Economic Forum

Sam Ransbotham and Shervin Khodabandeh

Business — and society — should think of the governance of AI as an enabler rather than a constraint.

Kay Firth-Butterfield was teaching AI, ethics, law, and international relations when a chance meeting on an airplane landed her a job as chief AI ethics officer. In 2017, Kay became head of AI and machine learning at the World Economic Forum, where her team develops tools and on-the-ground programs to improve AI understanding and governance across the globe.

Kay Firth-Butterfield is head of AI and machine learning and a member of the executive committee of the World Economic Forum. In the United Kingdom, she is a barrister with Doughty Street Chambers and has worked as a mediator, arbitrator, part-time judge, business owner, and professor. She is vice chair of the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems and serves on the Polaris Council of the U.S. Government Accountability Office advising on AI.

In the final episode of the first season of the Me, Myself, and AI podcast, Kay joins cohosts Sam Ransbotham and Shervin Khodabandeh to discuss the democratization of AI, the values of good governance and ethics in technology, and the importance of having people understand the technology across their organizations — and society. She also weighs in on other themes our hosts have discussed this season, including education, collaboration, and innovation.

Season 2

Craig Martell, Lyft

Sam Ransbotham and Shervin Khodabandeh

As algorithms become commodities, their application demands rigorous thinking..

Craig Martell says he won the career lottery. After studying logic, philosophy, political science, and political theory, he completed a Ph.D. in computer science and found his way to machine learning, a field he thoroughly enjoys. After spending time at Dropbox and LinkedIn, Craig headed to Lyft, where he runs the LyftML engineering team. He’s also an adjunct professor at Northeastern University in Seattle.

Craig Martell is head of machine learning at Lyft and an adjunct professor of machine learning for Northeastern University’s Align program in Seattle. Before joining Lyft, he was head of machine intelligence at Dropbox, led a number of AI teams and initiatives at LinkedIn, and was a tenured professor at the Naval Postgraduate School in Monterey, California. Martell has a Ph.D. in computer science from the University of Pennsylvania and is coauthor of Great Principles of Computing (MIT Press, 2015).

We kick off Season 2 of Me, Myself, and AI discussing a particular trend Craig has seen in the AI and machine learning space: As organizations depend more on technology-driven solutions to solve business problems, algorithms themselves are less important than how they fit into an overall engineering product pipeline and product development road map. Craig shares his thoughts about what this shift means for academic education and cross-functional collaboration in organizations, and the hosts pick his brain about how to combat unconscious bias.

Will Grannis, Google Cloud

Sam Ransbotham and Shervin Khodabandeh

Success with AI — as with games — depends on defining the problem you’re trying to solve.

Will Grannis discovered his love for technology playing Tron and Oregon Trail as a child. After attending West Point and The Wharton School at the University of Pennsylvania, he translated his passion for game theory into an aptitude for solving problems for companies, a central component of his role as founder and leader of the Office of the CTO at Google Cloud. Will leads a team of customer-facing technology leaders who, while tasked with bringing machine learning solutions to market, approach their projects with a user-first mindset, ensuring that they first identify the problem to be solved.

Will Grannis is the founder and leader of Google Cloud’s CTO Office, a team of senior engineers whose mission is to foster collaborative innovation between Google and its largest customers. Prior to joining Google in 2015, Grannis spent the last two decades as an entrepreneur, enterprise technology executive, and investor, building and scaling technical platforms that today power commerce, transportation, and the public sector. He’s been a developer, product manager, CTO, SVP of Engineering, and CEO, building a wide variety of platforms and teams along the way.

In Season 2, Episode 2, of Me, Myself, and AI, Will makes it clear that great ideas don’t only come from the obvious subject-area experts in the room; diverse perspectives, coupled with a codified approach to innovation, lead to the best ideas. The collaboration principles and processes Google Cloud relies on can be applied at other organizations across industries.

Amit Shah, 1-800-Flowers

Sam Ransbotham and Shervin Khodabandeh

Success with AI depends more on mindsets than skill sets.

1-800-Flowers faces the same cold-start problem any consumer-facing business might face: It doesn’t know exactly what its customers need when they first come to its website. What’s more unique to the platform, which operates through a network of local florists and affiliates worldwide, though, is that each time a customer comes to its site, they may have a different end goal in mind. Consumers shop for gifts and floral arrangements for different occasions — as varied as funerals, birthdays, and holidays — which can make it difficult for technology to recommend the best product during a specific online shopping session.

Amit Shah has a proven track record for leading e-commerce marketing strategies while rapidly scaling user acquisition and revenue streams. As president of 1-800-Flowers.com (since August 2020), he is responsible for leading the operations and management of the 1-800-Flowers.com brand. Since joining the company in September 2011, Shah has held several roles of increasing responsibility, most recently serving as chief marketing officer from March 2017 to August 2020.

In Season 2, Episode 3, of the Me, Myself, and AI podcast, 1-800-Flowers president Amit Shah explains the company’s unique challenge as a platform business and engagement brand facing this perennial cold-start problem. He also shares his insights into why marketers may have a leg up in working with AI and machine learning, how to foster a team of curious learners, and why it’s important to tolerate failures.

JoAnn Stonier, Mastercard

Sam Ransbotham and Shervin Khodabandeh

Mastercard’s chief data officer explains how constraints can enable technology leaders to design better solutions to business problems.

JoAnn Stonier can’t deny that her role as chief data officer at Mastercard isn’t easy. Advising the company on the mitigation of current and future risk while guiding her team to think critically about the problems they’re using AI to solve is challenging — but, she says, it’s also fun.

JoAnn Stonier serves as chief data officer for Mastercard, leading the organization’s data innovation efforts while navigating current and future data risks. Stonier and her team design and operationalize Mastercard’s global data strategy, ensure governance and data quality, and guide enterprise deployment of cutting-edge data solutions, including advanced analytics and AI and the development of enterprise data platforms.

In Season 2, Episode 4, of the Me, Myself, and AI podcast, JoAnn talks with Sam Ransbotham and Shervin Khodabandeh about the elements of her job that are both demanding and rewarding. She also touches on the skill sets she finds most valuable in her colleagues and shares how her work in interior design helps her reframe technology challenges at work.

Chris Couch, Cooper Standard

Sam Ransbotham and Shervin Khodabandeh

AI helps the automotive supplier develop products that benefit consumers every day in unseen ways.

Chris Couch has a unique role, serving as senior vice president and CTO of automotive supplier Cooper Standard as well as CEO of Liveline Technologies, a startup born from the CS Open Innovation initiative. Both organizations use AI to manufacture products the average consumer likely never thinks twice about, such as brake fluid and polymer seals for car doors.

With more than 21 years of global automotive manufacturing experience, Christopher Couch serves as senior vice president and CTO for Cooper Standard, where he leads R&D, product development and engineering, product strategy, and program management. He also has P&L responsibility for Applied Materials Science, a venture business unit focused on the commercialization of unique materials developed by the company. Couch also leads the CS Open Innovation initiative, which aims to position Cooper Standard as the partner of choice for open innovation with startups, universities, and other suppliers.

In Season 2, Episode 5, of the Me, Myself, and AI podcast, we talk with Chris about open innovation, automating rote processes without displacing human workers, and attracting talent by fostering a startup culture.

Huiming Qu, The Home Depot

Sam Ransbotham and Shervin Khodabandeh

The global retailer uses machine learning to help customers find the right tools for their home improvement projects.

Huiming Qu didn’t plan to work in data science, a nascent field at the time she was pursuing a Ph.D. in computer science, but one course in data mining changed all of that. She started her career in the research department at IBM, transitioned to a 50-person Huiming Qu didn’t plan to work in data science, a nascent field at the time she was pursuing a Ph.D. in computer science, but one course in data mining changed all of that. She started her career in the research department at IBM, transitioned to a 50-person startup, spent some time in the financial services industry, and today leads data science and machine learning in the marketing and online functions at The Home Depot.

Huiming Qu leads the online data science and platform team enabling search, product recommendations, real-time personalization, visual shopping, and various other innovations for The Home Depot’s digital channels. She is a technical leader with deep expertise in artificial intelligence, data science, engineering, and product leadership, with a proven record of driving billion-dollar contributions with scalable machine learning solutions and strategic innovation. Qu has more than 10 years of experience managing large AI and data science programs at IBM’s Watson research lab, Distillery, and American Express. She earned a Ph.D. in computer science from the University of Pittsburgh; holds six patents and has others pending approval; and has published more than a dozen academic papers around data management, machine learning, and optimization.

In Season 2, Episode 6, of the Me, Myself, and AI podcast, Huiming explains the similarities and differences between her previous experiences and her current role, in which she is tasked with helping customers more easily find the products and services they need as they embark on home improvement projects. (And who hasn’t started at least one of those since the COVID-19 pandemic shifted many of us to working from home?) She also outlines some of the challenges of managing a data set of over 2 million product SKUs and getting pilot programs to market quickly, and she explains why she champions the need for cross-functional teams to execute complex technology projects.

Colin Lenaghan, PepsiCo

Sam Ransbotham and Shervin Khodabandeh

It’s a myth that you need to hire individuals who can do it all. What you need is a cross-functional AI team.

Colin Lenaghan says he wakes up every Monday morning looking forward to the week ahead and what he’ll learn as he continues to lead digital transformation and artificial intelligence projects at work. With nearly a quarter-century under his belt working in revenue management at PepsiCo, these technology implementation projects keep him and his team on their toes while positioning the consumer packaged goods company for continued success long into the future.

Colin Lenaghan is global senior vice president for net revenue management at PepsiCo. In his 24-year career at PepsiCo, Lenaghan has held positions across the company’s strategy, finance, insights, and commercial groups and gained deep experience across all categories in the PepsiCo portfolio. He spearheads digital transformation to leverage artificial intelligence and machine learning capabilities to drive improved performance across the value chain, including a project to set up a technology venture unit in Israel.

In this episode of the Me, Myself, and AI podcast, we speak with Colin about some of the AI projects his team is working on and get his take on the skills and competencies organizations should foster to set up technology implementations for success.

Elizabeth Renieris, Notre Dame-IBM Technology Ethics Lab

Sam Ransbotham and Shervin Khodabandeh

The founding director of the Notre Dame-IBM Technology Ethics Lab shares her views on corporate data governance.

Technology presents many opportunities, but it also comes with risks. Elizabeth Renieris is uniquely positioned to advise the public and private sectors on ethical AI practices, so we invited her to join us for the final episode of Season 2 of the Me, Myself, and AI podcast.

Elizabeth Renieris is the founding director of the Notre Dame-IBM Technology Ethics Lab, the applied research and development arm of the University of Notre Dame’s Technology Ethics Center, where she helps develop and oversee projects to promote human values in technology. She is also a technology and human rights fellow at the Carr Center for Human Rights Policy at Harvard’s Kennedy School of Government, a practitioner fellow at Stanford’s Digital Civil Society Lab, and an affiliate at the Berkman Klein Center for Internet and Society. Renieris’s work is focused on cross-border data governance as well as the ethical challenges and human rights implications of digital identity, blockchain, and other new and advanced technologies.

As the founder and CEO of Hackylawyer, a consultancy focused on law and policy engineering, Renieris has advised the World Bank, the U.K. Parliament, the European Commission, and a variety of international and nongovernmental organizations on these subjects. She is also working on a forthcoming book about the future of data governance through MIT Press.

Renieris holds a master of laws degree from the London School of Economics, a Juris Doctor from Vanderbilt University, and a bachelor of arts degree from Harvard College.

Elizabeth has worked for the Department of Homeland Security and private organizations in Silicon Valley, and she founded the legal advisory firm Hackylawyer. She now serves as founding director of the Notre Dame-IBM Technology Ethics Lab, which is focused on convening leading academic thinkers and technology executives to help develop policies for the stronger governance of AI and machine learning initiatives. In this episode, Elizabeth shares her views on what public and private organizations can do to better regulate their technology initiatives.

Dave Johnson, Moderna

Sam Ransbotham and Shervin Khodabandeh

The pharma company’s chief data and artificial intelligence officer discusses the digital biotech’s platform approach to data science.

“We tend not to be a company of half measures,” notes Dave Johnson, chief data and artificial intelligence officer at Moderna, “so when we decide we’re going to do something, we’re going to do it.” This characterization certainly seems to fit the Cambridge, Massachusetts-based biotech company that made a name for itself in 2020 upon releasing one of the first COVID-19 vaccines approved by the U.S. Food and Drug Administration for emergency use to combat the coronavirus.

Dave Johnson is chief data and artificial intelligence officer at Moderna, where he is responsible for all enterprise data capabilities, including data engineering, data integration, data science, and software engineering. Johnson earned a doctorate in information physics and has more than 15 years of experience in software engineering and data science. He has spent more than a decade working exclusively in enterprise pharma and biotech companies.

In this bonus episode of the Me, Myself, and AI podcast, our hosts learn how Moderna used artificial intelligence to speed up development of the vaccine and how the technology has helped to automate other key systems and processes to build efficiencies across the organization. Dave also describes Moderna’s digital-first culture and offers insights around collaboration that can be applied across industries.

Season 3

Kartik Hosanagar, Jumpcut

Sam Ransbotham and Shervin Khodabandeh

Learn how an AI-powered startup is helping new entertainment industry talent get discovered.

Kartik Hosanagar wasn’t your typical Hollywood hopeful. He didn’t pack his life into a sedan, drive to Los Angeles, and work a series of part-time jobs while trying to make it big in the film industry. Kartik is a professor of business and marketing at the University of Pennsylvania’s Wharton School who penned a screenplay while on sabbatical. When he started pitching it to potential producers, he quickly discovered that the film industry can be hesitant to take risks on new writers and directors — which often means that diverse talent is overlooked. So, to help unknown talent to break into the entertainment industry, he got to work founding Jumpcut, a venture-funded startup that aims to uncover new voices.

Kartik Hosanagar is the John C. Hower Professor of Technology and Digital Business and a professor of marketing at The Wharton School of the University of Pennsylvania. His research focuses on the digital economy and the impact of analytics and algorithms on consumers and society.

Hosanagar is a 10-time recipient of MBA or undergraduate teaching excellence awards at The Wharton School. He is a serial entrepreneur who most recently founded Jumpcut Media, a startup that is using data to democratize opportunities in film and TV. Hosanagar has served as a department editor at the journal Management Science and has previously served as a senior editor at the journals Information Systems Research and MIS Quarterly.

Sarah Karthigan, ExxonMobil

Sam Ransbotham and Shervin Khodabandeh

Offering proof-of-concept projects to business units can boost their interest in and understanding of the value of AI.

ExxonMobil is an energy company that’s existed since 1870, well before artificial intelligence. So, what does an AI manager at ExxonMobil do? In the latest episode of the Me, Myself, and AI podcasts, hosts Sam Ransbotham and Shervin Khodabandeh interview Sarah Karthigan, AI operations manager for IT, to find out.

Sarah Karthigan is a reputed leader with a demonstrated history of leading digital transformation initiatives in the energy industry. She was named one of 2021’s 25 Influential Women in Energy in recognition of her outstanding work to accelerate the adoption of data science to enable data-driven decision-making across the integrated oil and gas value chain.

Karthigan started her career at ExxonMobil over a decade ago and has since held various roles of increasing responsibility in the areas of strategic planning, project management, scientific computing, and data science. She currently leads the AI operations practice, which is focused on realizing self-healing strategies, and is also responsible for managing external relationships with multiple technical business partners.

Sarah leads a data science team tasked with making use of large volumes of data, with the goal of offering reliable and affordable energy to a variety of populations. A major focus of Sarah’s efforts has been around self-healing, a method for internal process improvement. Listen in to learn how her group secures buy-in for various technology initiatives and works to continually improve human-machine collaboration for the organization.

Douglas Hamilton, Nasdaq

Sam Ransbotham and Shervin Khodabandeh

How can artificial intelligence be used for prediction and risk mitigation?

Douglas Hamilton works across business units at Nasdaq to deploy artificial intelligence anywhere the technology can expedite or improve processes related to global trading. In this episode of Me, Myself, and AI, he joins hosts Sam Ransbotham and Shervin Khodabandeh to explain how the global financial services and technology company uses AI to predict high-volatility indexes specifically and to offer more general advice for those working with high-risk scenarios.

A data scientist by trade, Douglas Hamilton is the head of AI research at Nasdaq’s Machine Intelligence Lab, which is dedicated to clarifying and improving financial markets with machine learning. He joined Nasdaq in 2017 as a data scientist and developed AI solutions focusing on rapid adaptation, reinforcement learning, and efficient market principles as solutions to predictive control problems. Before joining the financial technology industry and spearheading Nasdaq’s machine intelligence initiatives, Hamilton led an advanced manufacturing analytics group at Boeing Commercial Airplanes and built customer relationship management systems at Fast Enterprises. He is a veteran of the U.S. Air Force and a member of the advisory board of The Data Science Conference. Hamilton holds a master of science degree in systems engineering from MIT and a bachelor’s degree in mathematics from the University of Illinois Springfield.

Paula Goldman, Salesforce

Sam Ransbotham and Shervin Khodabandeh

Learn how Salesforce considers ethics when designing technology solutions.

Paula Goldman has been a passionate advocate for the responsible use of technology for her entire career. Since joining Salesforce as its first chief ethical and humane use officer, she’s helped the company design and build technology solutions for its customers, with a focus on ethics, fairness, and responsible use.

Paula Goldman is Salesforce’s first chief ethical and humane use officer. In her role, she leads Salesforce in creating a framework to build and deploy ethical technology that optimizes social benefit. Previously, Goldman served as vice president, global lead, for the Tech and Society Solutions Lab at Omidyar Network, a social impact investment firm established by eBay founder Pierre Omidyar. Goldman also served as the global lead for impact investing, where she created and led Omidyar Network’s global efforts to build the impact investing movement through its investment portfolio, industry partnerships, and thought leadership. Goldman earned a Ph.D. from Harvard University, a master’s degree in public affairs from Princeton, and a bachelor’s degree with highest honors from the University of California, Berkeley.

In this episode of the Me, Myself, and AI podcast, Paula joins hosts Sam Ransbotham and Shervin Khodabandeh to discuss her specific role leading the ethical development of technology solutions, as well as the role technology companies play in society at large.

Ranjeet Banerjee, Cold Chain Technologies

Sam Ransbotham and Shervin Khodabandeh

This transportation and logistics company relies on AI to deliver COVID-19 vaccines safely and efficiently.

When Ranjeet Banerjee talks about the work his organization, Cold Chain Technologies (CCT), does to transport vaccines and other biologics that must be temperature controlled, he stresses that the company doesn’t solely rely on technology. CCT approaches its work by first considering what problems it’s trying to solve, developing use cases, and then considering whether a technology solution might be the best way forward.

Ranjeet Banerjee is the CEO of Cold Chain Technologies (CCT), a leading global provider of comprehensive thermal assurance solutions for temperature-sensitive drugs, vaccines, and biologics. Under his leadership, CCT is playing a key role in the COVID-19 pandemic response, with both the Moderna and Johnson & Johnson vaccines exclusively using CCT’s thermal assurance packaging solutions across the U.S. CCT is also supporting the in-transit cold chain needs for vaccine distribution across the globe. Previously, Banerjee spent 25 years at global medical technology company Becton Dickinson, most recently serving as corporate executive vice president as well as president of the U.S. and Canada regions, with responsibility for more than $6 billion in revenue. Banerjee is a member of the Advisory Board for the CEO Leadership Alliance of Orange County. He earned a bachelor’s degree in chemical engineering from the Indian Institute of Technology.

In this episode of the Me, Myself, and AI podcast, we learn how a combination of Ranjeet’s background in chemical engineering, his experience working in the health care space, and a holistic approach to leadership and problem-solving enable him to lead CCT to constantly innovate in the supply chain space. Ranjeet also discusses the benefits of a customer-first mindset and shares insights applicable to leaders in industries beyond health care.

Gerri Martin-Flickinger, Starbucks

Sam Ransbotham and Shervin Khodabandeh

Starbucks’s former chief technology officer explains how to lead a successful digital transformation.

Why does how you describe your team — down to its name — matter? Gerri Martin-Flickinger, former executive vice president CTO at Starbucks, joins the Me, Myself, and AI podcast to describe some of the technology initiatives the coffeehouse chain has been able to pursue since rebranding its technology team and articulating its mission.

As executive vice president and CTO at Starbucks, Gerri Martin-Flickinger led the Starbucks Technology team through a transformation into a best-in-class retail technology organization. She was the passionate leader behind the technology strategy that plays a critical role in propelling the Starbucks mission — “empowering partners and delighting customers, globally.”

Before joining Starbucks in 2015, Martin-Flickinger was senior vice president and CIO at Adobe, where she led portions of its technology transformation to a cloud-based subscription services business. Previously, she served as CIO at Verisign, McAfee, and Network Associates and held numerous senior leadership roles at Chevron, where she began her career.

Martin-Flickinger currently sits on Charles Schwab’s board of directors and serves as a member of Arizona State University’s Fulton School of Engineering Advisory Board, Sierra Ventures’ CIO Advisory Board, and The Wall Street Journal CIO Network.

In her conversation with hosts Sam Ransbotham and Shervin Khodabandeh, Gerri recaps a decades-spanning career working in technology leadership roles at Chevron, McAfee, and Adobe, then explains some recent employee- and customer-facing projects Starbucks has undertaken using AI and machine learning.

Barbara Martin Coppola, IKEA Retail

Sam Ransbotham and Shervin Khodabandeh

The global furniture retailer uses AI for customer-facing and back-of-house applications, as well as increasing customer engagement.

Drawing on previous experience working in nine countries for organizations like Google and Samsung, Barbara Martin Coppola joined IKEA Retail as its chief digital officer to oversee the furniture retailer’s digital transformation, improve its customer experience, and foster the company’s ongoing commitment to sustainability.

Barbara Martin Coppola is the chief digital officer for Ingka Group (IKEA), the world’s largest home furnishings retailer.

Martin Coppola started her career with IKEA in 2018 and has overall responsibility for leading the company’s digital technology capabilities and transformation. She has over 20 years of experience in the technology sector and has lived and worked in more than nine countries. Before joining IKEA, she held leading positions in several global businesses, including Google, YouTube, Samsung, and Texas Instruments.

Martin Coppola holds a master of science degree in telecommunications engineering from Universidad Politécnica de Madrid, a master of science in mobile communications from Télécom Paris, and an MBA in business administration and management from INSEAD. She is also a graduate of the Advanced Management Program at Harvard Business School.

In this episode of the Me, Myself, and AI podcast, hosts Sam Ransbotham and Shervin Khodabandeh speak with Barbara about how she empowers cross-functional collaboration and “testing, and iterating, and trying, failing, and starting again” to realize successful technology projects. She also shares the context behind some recent customer-facing AI tools the company has launched to assist customers through the buying process and free up front-line workers to focus on customer engagement instead of operational tasks.

Sidney Madison Prescott, Spotify

Sam Ransbotham and Shervin Khodabandeh

The streaming service’s global head of intelligent automation explains how technology helps employees make use of vast amounts of customer data.

After earning her undergraduate degree in philosophy, political science, and ethics, with aspirations to become a lawyer, Sidney Madison Prescott was drawn to technology jobs that specifically emphasized data quality and governance. In 2020, she joined music streaming service Spotify as the global head of intelligent process automation, where she uses robotic process automation to automate tasks and free up workers to focus on higher-value-added and more creative work. For Sidney and her team at Spotify, AI and machine learning are not tools to replace jobs; they enable humans and machines to work together for increased efficiency and productivity.

Sidney Madison Prescott is a keynote speaker, author, and robotics evangelist specializing in the creation of robotic process automation centers of excellence for Fortune 250 companies. She heads up the Global Intelligent Automation initiative at music streaming powerhouse Spotify. In August 2021, she received her Master of Business Administration as a part of the country’s first Executive Women’s MBA cohort at Brenau University.

Madison Prescott is also coauthor of the book Robotic Process Automation Using UiPath StudioX: A Citizen Developer’s Guide to Hyperautomation (Apress, 2021), which explains how to build robots using real-world prototypes.

In the final episode of Season 3 of the Me, Myself, and AI podcast, Sidney joins hosts Sam Ransbotham and Shervin Khodabandeh to share her views on automation, augmentation, and fostering engineering talent.

Season 4

Mark Maybury, Stanley Black & Decker

Sam Ransbotham and Shervin Khodabandeh

At Stanley Black & Decker, innovation with AI ranges from robotic process automation to virtual assistants.

Stanley Black & Decker is best known as the manufacturer of tools for home improvement projects, but it also makes products the average consumer seldom notices, like fasteners to keep car parts secure and the electronic doors typically used at retail stores. Me, Myself, and AI podcast hosts Sam Ransbotham and Shervin Khodabandeh sat down with Mark Maybury, the company’s first chief technology officer, to learn how artificial intelligence factors into this 179-year-old brand’s story.

As Stanley Black & Decker’s CTO, Mark Maybury manages a team across the company’s businesses and functions, advises on technological threats and opportunities, and provides access to all elements of the global technology ecosystem.

Previously, Maybury spent 27 years at The Mitre Corporation, where he held a variety of strategic technology roles, including vice president of intelligence portfolios and chief security officer. Before joining Mitre, he was an officer in the U.S. Air Force, where he also served as chief scientist from 2010 to 2013.

Maybury is on the Defense Science Board and the Connecticut Science Center Board and served on the Air Force Scientific Advisory Board and the Homeland Security Science and Technology Advisory Committee for several years. He is a fellow in IEEE and the Association for the Advancement of Artificial Intelligence. Maybury has a doctorate degree in AI from Cambridge University.

During their conversation, Mark described how categorizing the technology-infused innovation projects he leads across the company into six levels, ranging from incremental improvements to radical innovations, helps Stanley Black & Decker balance its product development portfolio. He also shared some insights for organizations thinking about responsible AI guidelines and discussed how Stanley Black & Decker is increasing its focus on sustainability.

Sanjay Nichani, Peloton Interactive

Sam Ransbotham and Shervin Khodabandeh

How the fitness brand uses AI and computer vision to help people stay healthy.

Consumers have invited AI into their lives with voice-activated personal assistants like Siri and Alexa, but how do they feel about computer vision technologies that can provide visual coaching and feedback in their homes? Sanjay Nichani, vice president of artificial intelligence and computer vision at Peloton Interactive, describes one compelling use case in the at-home fitness space.

Sanjay Nichani is vice president of artificial intelligence and computer vision at Peloton Interactive. In that role, he leads an AI/computer vision team focused on human pose estimation, activity recognition, and movement-tracking technologies for the fitness domain. He also leads the ongoing development of Peloton Guide, a new camera-based interactive strength-training product.

Previously, Nichani was vice president of the computer vision and machine learning team at Acuant, working on document forensics technologies for detecting fraud. Before that, he was vice president of the Mitek Labs R&D group, where he led the development of a deep learning-based image-processing pipeline for identity verification. He also founded 3D sensor technology company Merakona and cofounded Pelfunc, developer of a photo-sharing app/service. He has advanced degrees in business from Babson College and computer science from the University of South Florida.

Sanjay joins hosts Sam Ransbotham and Shervin Khodabandeh in this episode of the Me, Myself, and AI podcast to discuss how the company best known for its bikes and treadmills relied on AI and computer vision to develop Peloton Guide, a new offering that uses AI to coach at-home participants through strength-focused workouts. He also describes how Peloton approaches developing new technology-infused products with user experience and data privacy in mind, and outlines what he looks for in technical talent.

Katia Walsh, Levi Strauss & Co.

Sam Ransbotham and Shervin Khodabandeh

The chief global strategy and AI officer explains how the clothing company’s machine learning boot camp is driving employee skills and innovation.

Katia Walsh began her career as a journalist in her native Bulgaria and is now the global chief strategy and AI officer at retailer Levi Strauss & Co. Over the course of her career, she has developed a passion for three things: the power of information, the power of technology, and the power of machine learning. Her enthusiasm for these subjects is evident as she describes how she is ensuring that a well-known legacy clothing brand remains relevant through technological transformation.

Katia Walsh is senior vice president and chief global strategy and AI officer at Levi Strauss & Co., where she focuses on setting the clothing company’s holistic digital and corporate strategy. Previously, she was the first chief global data and analytics officer of Vodafone Group and held strategic data analytics leadership positions at Prudential Financial, Fidelity Investments, and Forrester Research. Walsh was named the U.K.’s Data Leader of the Year for three consecutive years by the Women in IT Awards series. She holds a doctoral degree in strategic communication from the University of Missouri-Columbia.

In this episode of the Me, Myself, and AI podcast, Katia explains how she has organized digital transformation and employee engagement at Levi Strauss around five C’s: connections with consumers, commerce, creation, careers, and culture. She also describes the machine learning boot camps the retailer has offered to nontech employees to boost innovation and outlines how the company thinks about responsible AI practices.

Kobi Abayomi, Warner Music Group

Sam Ransbotham and Shervin Khodabandeh

The music entertainment company’s head of data science explains how his team is leveraging AI to help customers continually discover new songs and artists.

Specialized teams — particularly technology teams — often face challenges as they strive to work cross-functionally, especially at legacy organizations. For Kobi Abayomi, vice president of data science at Warner Music Group, addressing such challenges starts with hiring strong talent into the technology function.

Kobi Abayomi is the senior vice president for data science at Warner Music Group, where he and his team enable the company to understand, respond to, and predict trends and opportunities in listening.

Abayomi has authored novel work in statistics (multivariate data imputation), econometrics (measures of inequality), and probability (distributions with fixed marginal and information theoretic measures) and has two patents pending in fraud detection and audience activation. Abayomi serves on the Data Science Advisory Council at Seton Hall University and on the Ivan Allen College Advisory Board at the Georgia Institute of Technology.

In this episode of the Me, Myself, and AI podcast, Kobi joins hosts Sam Ransbotham and Shervin Khodabandeh to explain how the music company is moving its infrastructure into the digital era, how it leverages vast amounts of consumer data to make informed decisions in an increasingly challenging landscape, and how AI is helping customers discover new music they’ll love.

Ya Xu, LinkedIn

Sam Ransbotham and Shervin Khodabandeh

The online networking platform has three primary marketplace functions, all of which depend on data and technology.

Over the course of her nine-year tenure at LinkedIn, Ya Xu has held technology roles with increasing responsibility. Today, she heads the data function for the online professional networking platform.

Ya Xu has been a driving force in transforming LinkedIn into a data-first company since she first joined the organization in 2013. As head of data, she leads a global team of about 1,000 data scientists and AI engineers whose work is at the core of delivering economic opportunities to LinkedIn’s members and customers. Xu’s emphasis on responsible AI and data science ensures that LinkedIn’s AI systems put people first and enables the company to empower its members, better serve its customers, and benefit society.

In addition to her work at LinkedIn, Xu has coauthored the book Trustworthy Online Controlled Experiments (Cambridge University Press, 2020), has been named to Fortune’s 40 under 40 in tech, and was nominated for VentureBeat’s Women in AI Awards. She has delivered countless speeches, including a commencement speech to Stanford’s class of 2019 in mathematics, statistics, and mathematical and computational science. Previously, Xu worked at Microsoft and earned a Ph.D. in statistics from Stanford University.

Ya joins hosts Sam Ransbotham and Shervin Khodabandeh in this episode of the Me, Myself, and AI podcast, where she discusses AI’s essential role in helping LinkedIn create the best “matches” — content creators with content consumers, job seekers with employers, and buyers with sellers — within its three key marketplaces. Ya also describes how the company has fostered a data-first culture from the top down, and how its vast amount of economic activity data is helping governments and policy makers worldwide.

Nitzan Mekel-Bobrov, eBay

Sam Ransbotham and Shervin Khodabandeh

The e-commerce platform’s chief AI officer brings a neuroscience background to online retail.

EBay is familiar as an e-commerce site that facilitates transactions between buyers and sellers. But as eBay’s first chief AI officer, Nitzan Mekel-Bobrov is focused on the role artificial intelligence technology can play in enhancing the user experience for everyone who engages with the platform.

Nitzan Mekel-Bobrov is chief AI officer at eBay. He leads the company’s vision and strategy for transforming how it delivers value to sellers and buyers around the globe through AI-led experiences, such as semantic recommenders, reasoning systems, visual understanding, and immersive visual experiences. Mekel-Bobrov has led the AI organizations at some of the largest brands in health care, financial services, and e-commerce, spanning AI science, engineering, and product development. He holds a doctorate in computational genomics and a master’s degree in computer science from the University of Chicago.

In this episode of the Me, Myself, and AI podcast, Nitzan shares examples of the AI tools eBay is building, such as a 3D visualization tool for sellers create their own models, and intent detection tools to enhance customer service. He also discusses his academic background in biology and neuroscience, his purposeful progression from health care to financial services to online travel and finally to e-commerce, and the challenges of scaling up AI capabilities organizationwide to drive transformational value.

Helen H. Lee, Boeing

Sam Ransbotham and Shervin Khodabandeh

The aircraft manufacturer is exploring using artificial intelligence to improve air traffic communications, quality control, and the in-flight experience.

As Boeing China’s regional director of airspace and airport programs, Helen Lee is helping the aerospace giant work toward improving airport and airspace operational efficiency and enhancing flight safety for its aviation customers. In this episode of the Me, Myself, and AI podcast, Helen discusses ongoing research that involves using AI to analyze the wake turbulence of aircraft with computer vision systems, using speech recognition to analyze interactions between pilots and air controllers to minimize the potential for human error, and using image recognition to scan planes for needed repairs. Helen also talks about the challenges of implementing such technology across a complex industry in which there’s no tolerance for error and systems must be impenetrable to hackers.

Helen H. Lee is responsible for managing and coordinating Boeing’s airport, airspace, and air traffic management programs in the Greater China region. She also initiates and provides technical guidance and insight to related programs in the region. She is the first China-based employee to be selected as a Boeing Technical Fellow, the company’s most elite team of technical experts.

Previously, Lee served as air traffic management (ATM) research lead for Boeing Research & Technology-China, where she planned and managed all ATM-related research projects involving Chinese domestic research partners. Before joining Boeing, she was a senior consultant at Boeing Jeppesen Airspace and Airport Services Group, where she led a project team that provided simulation and consulting services in support of major airport and airspace modernization efforts worldwide. Lee earned a doctoral degree in aerospace engineering from the University of Minnesota.

Sowmya Gottipati, Estée Lauder

Sam Ransbotham and Shervin Khodabandeh

Artificial intelligence enables customers to try on cosmetics and even find a new favorite fragrance virtually.

It might seem like cosmetics and perfume are products shoppers need to try out in person before buying, but artificial intelligence is opening up new avenues for reaching and understanding consumers — as well as new ways to manage supply chains.

In this episode of the Me, Myself, and AI podcast, we learn how Estée Lauder’s Sowmya Gottipati leveraged her earlier technology leadership experience in telecommunications and broadcast media to deploy brand technology projects for a portfolio of cosmetics, fragrances, and skin and hair care product brands. She talks about AI’s role in product development, a virtual try-on tool for lipsticks and foundations, and a fragrance recommendation engine, as well as an application for supply and demand planning. Sowmya also explains why, despite AI’s power, she believes human-machine interaction will always be necessary.

Sowmya Gottipati is an accomplished business and technology leader who has managed and delivered products across the telecom, media, and retail industries. She is currently vice president of global supply chain technology at Estée Lauder, leading digital transformation and providing oversight of all technology solutions globally. Previously, she was the company’s vice president of technology in the capacity of brand CIO.

Before joining Estée Lauder, Gottipati was vice president of digital and emerging technologies at NBCUniversal. She also served as a technology leader at AT&T, where she managed and delivered products in data, web, mobile, and cloud services. Gottipati has a master’s degree in engineering from North Carolina State University and MBA from Columbia Business School, as well as a private pilot license.

Season 5

Frank O. Nestle, Sanofi

Sam Ransbotham and Shervin Khodabandeh

The pharmaceutical company uses automation to enable more efficient drug discovery processes for vaccine development.

Frank Nestle, Sanofi’s global head of research and chief scientific officer, was inspired to enter the health sciences field after reading an Albert Camus novel and realizing his calling was to help others. In his current role, Frank oversees the pharmaceutical company’s transition from primary care to specialty care, which includes developing medicines for immunology, oncology, and rare diseases. In this episode of the Me, Myself, and AI podcast, Frank explains how artificial intelligence enables Sanofi to work toward drug discovery in more agile ways.

Dr. Frank O. Nestle is global head of research and chief scientific officer at Sanofi, with responsibility for its main therapeutic research areas of immunology and inflammation, oncology, neurology, rare diseases, hematology, and genomic medicine. Before joining Sanofi in 2016, Nestle was a professor and chair of cutaneous medicine and immunotherapy at King’s College London and practiced medicine at Guy’s and St. Thomas’ Hospital. At King’s College, he led research, translational clinical trials, and teams in dermatology, allergology, and immunology. He also held several executive roles, in particular at the Guy’s and St Thomas’ Biomedical Research Center.

Nestle is a fellow of the Academy of Medical Sciences, a senior investigator emeritus at the National Institute for Health Research, and past president of the Federation of Clinical Immunology Societies. He has published over 220 scientific articles and has received several awards and honors, including the Alfred Marchionini Research Award at the 20th World Congress of Dermatology.

Stéphane Lannuzel, L’Oréal

Sam Ransbotham and Shervin Khodabandeh

The cosmetics, skin care, and hair products company uses artificial intelligence to monitor for — and stay ahead of — new trends in the beauty space.

Stéphane Lannuzel has worked in the beauty industry for 15 years and now directs the Beauty Tech program at L’Oréal. His team uses artificial intelligence to improve customer experience in a variety of ways, including helping consumers try on cosmetics virtually and providing product recommendations. L’Oréal recently developed TrendSpotter, an AI-based social listening tool that tracks macro-influencer posts and other online content and informs the cosmetics, skin care, and hair products company of upcoming trends that can then inform new product development. Listen to this episode to learn how Stéphane sees AI, and technology more broadly, as a force of good and the enabler of more meaningful professional and customer experiences.

Stéphane Lannuzel is director of L’Oréal Groupe’s Beauty Tech program, which aims to personalize the customer experience through technology. He started his career in project finance in Australia at Caisse des Dépôts et Consignations, a large French bank, after graduating from École Nationale des Ponts et Chaussées (Paris) and Imperial College (London). He then spent seven years with Kearney, a consulting firm specializing in the luxury and consumer goods industries.

For the past 15 years, Lannuzel has been working in the beauty industry, first for Shiseido and then for L’Oréal, where he has been for the past seven years. He has held various positions in the role of operations director, most recently serving as chief digital officer in charge of Operations 4.0, a large-scale digital and tech transformation program within L’Oréal Operations. Lannuzel is also a member of the GS1 management board.

Teddy Bekele, Land O’Lakes

Sam Ransbotham and Shervin Khodabandeh

The farm-to-fork cooperative uses artificial intelligence to improve agricultural yields.

You might have seen Land O’Lakes’ dairy products on store shelves without giving much thought to how they got there, but that’s something CTO Teddy Bekele thinks about every day. While the farmers and agricultural retailers of Land O’Lakes work to produce the cooperative’s products, starting from the seeds used to grow animal feed, Teddy Bekele is focused on supporting agriculture’s “fourth revolution” — one that’s embracing technologies like artificial intelligence. On this episode of the Me, Myself, and AI podcast, Teddy explains how Land O’Lakes uses predictive analytics and AI to help farmers and other agricultural producers be more productive and make better decisions about the business of farming.

Teddy Bekele is the CTO of Land O’Lakes, leading the organization’s digital transformation by leveraging existing and emerging technologies to discover, implement, and deliver solutions and ecosystems. Previously, Bekele served as vice president of ag technology for WinField United. Bekele holds an MBA from Indiana University and a bachelor of science degree in mechanical engineering from North Carolina State University. His community leadership includes serving as chair of the Minnesota Broadband Task Force and the Federal Task Force on Precision Ag Connectivity, and as a board member for Stella Health, Genesys Works Twin Cities, and the Minnesota Technology Association.

Tonia Sideri, Novo Nordisk

Sam Ransbotham and Shervin Khodabandeh

One pharma company uses design thinking and cross-functional collaboration to help it prioritize technology projects.

Tonia Sideri was a data scientist herself before taking on her role as head of Novo Nordisk’s AI and Analytics Center of Excellence. Now she’s putting her experience to use helping the Danish pharmaceutical company in its quest to develop medicines and delivery systems to treat diabetes and other chronic diseases, such as hemophilia, obesity, and growth disorders.

In a highly regulated industry where failures are costly, Tonia’s philosophy is to fail fast through what she calls “data-to-wisdom sprints.” These two-week hackathons enable her group to rapidly test the feasibility of new product ideas with input from their colleagues on the business side.

Tonia joins this episode of the Me, Myself, and AI podcast to discuss her team’s approach to hypothesis testing, the benefits of incorporating design thinking into building data and AI products, and why she believes empathy is the most important skill a data scientist can have.

Tonia Sideri is head of the AI and Analytics Center of Excellence (CoE) at Novo Nordisk, a global pharma company based in Denmark that develops diabetes care products, as well as solutions that target other chronic diseases, such as obesity, growth disorders, and hemophilia.

The CoE is a group of data scientists, machine learning engineers, and software developers located within Novo Nordisk’s Global IT group who work cross-functionally with the company’s machine learning/analytics systems and its machine learning operations platform.

Sideri was a data scientist before taking on a management role. She has years of experience in startup incubators and corporate transformation labs, where she helped unlock the potential of data across the banking, pharma, and biotechnology industries and across a variety of business models, including B2C, B2B, and digital native vertical brands.

Jack Berkowitz, ADP

Sam Ransbotham and Shervin Khodabandeh

The best way to build data products is to consider outcomes and goals from the outset.

As chief data officer of payroll and benefits management company ADP, Jack Berkowitz has three primary responsibilities. One is to oversee the organization’s data overall, ensuring that functions like data governance, security, and analytics, are running well. Another is to build ADP’s data products, such as people analytics and benchmark tools. But the responsibility that’s of most interest to Me, Myself, and AI hosts Sam Ransbotham and Shervin Khodabandeh is Jack’s oversight of the organization’s use of artificial intelligence.

In this episode of the podcast, Jack describes how focusing on the outcomes the organization wants to achieve leads to better processes and results. He also dives into the topic of AI ethics and outlines how other organizations might consider assembling an AI ethics board.

Jack Berkowitz is chief data officer at ADP, where he leads the company’s data security and governance, data platforms, and analytics/machine learning operations. His role also involves partnering with stakeholders to develop new data initiatives to improve clients’ experience and ADP’s competitive position.

Berkowitz joined ADP in 2018 as the senior vice president of product development for the DataCloud people analytics and compensation benchmarking solution. Before that, he was vice president of products and data science for Oracle’s Adaptive Intelligence program. Previously, he spent 20 years in product development and the implementation of intelligent information systems. He has been on the executive team of four startups involved in search, reasoning, or metadata-driven applications, and he cofounded Edapta, which enabled dynamic user interfaces and personalization for mobile and web clients.

Berkowitz has a master’s degree in industrial engineering and operations research from Virginia Tech and a bachelor’s degree in psychology from the College of William and Mary.

Ameen Kazerouni, Orangetheory Fitness

Sam Ransbotham and Shervin Khodabandeh

Group fitness class members get the most out of their workouts with some help from both AI and human coaches.

Ameen Kazerouni, chief data and analytics officer at Orangetheory Fitness (OTF), believes that AI’s role isn’t to replace human experts but rather to help them make better decisions. That’s why OTF collects heart rate and telemetry data during its in-studio fitness classes: so that AI algorithms can turn that data into feedback that empowers people to make real-time choices about their workouts and enables coaches to offer personalized recommendations.

On this episode of the Me, Myself, and AI podcast, Ameen joins Sam and Shervin to describe how OTF’s data collection and algorithms are used to create a curated fitness experience for its members, and he explains why it’s critical to keep humans in the feedback loop when implementing artificial intelligence.

Ameen Kazerouni is chief data and analytics officer at Orangetheory Fitness. Over the course of his career, Kazerouni has had the opportunity to use machine learning in a variety of fields, including clinical research, medical imaging, data warehouse design, e-commerce, and now health and wellness. He is currently focused on the challenges of operationalizing large volumes of data into scalable customer solutions and strategic initiatives.

A core belief of his is to “build experiences, not algorithms,” which drives his team to put forward scalable solutions with measurable impact on real-world use cases. In his free time, Kazerouni enjoys keeping up to date with the latest methods in artificial intelligence and the newest comedy specials on Netflix, burning his savings on expanding his smart home, and marching down the path of becoming bionic by quantifying himself with any and all wearable fitness tech.

Khatereh Khodavirdi, PayPal

Sam Ransbotham and Shervin Khodabandeh

A data science leader at the online payments company explains why focusing on the entire customer journey is critical when developing consumer-facing digital products.

Khatereh (KK) Khodavirdi is focused on using AI to create better customer experiences — a process she compares to creating an “AI Legoland,” in which various technology components fit together to build cohesive solutions for PayPal’s customers. This is an approach she is applying in her role as senior director of data science in the online payment systems company’s consumer products division, where she oversees data science teams for PayPal, its peer-to-peer payment app Venmo, and e-commerce coupon-finder Honey.

On this episode of the Me, Myself, and AI podcast, KK joins Sam Ransbotham and Shervin Khodabandeh to describe how PayPal’s various consumer products work together to help users have a seamless experience across its products. She also talks about AI’s role in further personalizing the customer experience across the company’s brand portfolio, data governance challenges following corporate acquisitions, and her approach to creating effective teams.

In her role as senior director of data science, Khatereh Khodavirdi leads a cross-functional team of data scientists, analytics experts, and strategists to help accelerate revenue growth through data and insights for PayPal, Venmo, and Honey. She was a founding member of eBay’s advertising data team and has spent her career building analytics functions to accelerate growth initiatives in commerce, advertising, monetization, and digital payments, with increasing levels of responsibility.

Fiona Tan, Wayfair

Sam Ransbotham and Shervin Khodabandeh

The e-commerce retailer uses artificial intelligence and machine learning to facilitate customer purchases while also managing its exposure to risk.

With a background in building enterprise platforms for organizations, including Oracle and Walmart, Wayfair CTO Fiona Tan oversees all of the technology initiatives for the Boston-based e-commerce company. As the home furnishings retailer begins to open brick-and-mortar stores, it’s taking lessons learned from the digital space to inform how it markets its home products to customers in physical locations.

On this episode of the Me, Myself, and AI podcast, Fiona joins Sam Ransbotham and Shervin Khodabandeh to discuss how artificial intelligence fuels nearly everything the retailer does, from ad purchasing to product pricing, and where human decision makers fit in. She also describes how AI enables Wayfair’s marketing automation technology, as well as some innovative new programs underway to help customers experience the company’s products virtually.

Fiona Tan is the chief technology officer at Wayfair, where she oversees a global innovation team responsible for creating market-leading experiences through the home furnishings retailer’s world-class e-commerce platform. Before joining Wayfair, Tan served as senior vice president of U.S. technology at Walmart, where she was responsible for innovation and engineering execution spanning its site, mobile app, and all associate and merchant-facing technology across its e-commerce business and retail stores in the United States.

Season 6

Ziad Obermeyer, UC Berkeley

Sam Ransbotham and Shervin Khodabandeh

An emergency physician turned researcher shares how two companies he founded are democratizing access to key health care data for machine learning applications.

When Ziad Obermeyer was a resident in an emergency medicine program, he found himself lying awake at night worrying about the complex elements of patient diagnoses that physicians could miss. He subsequently found his way to data science and research and has since coauthored numerous papers on algorithmic bias and the use of AI and machine learning in predictive analytics in health care.

Ziad joins Sam Ransbotham and Shervin Khodabandeh to talk about his career trajectory and highlight some of the potentially breakthrough research he has conducted that’s aimed at preventing death from cardiac events, preventing Alzheimer’s disease, and treating other acute and chronic conditions.

Dr. Ziad Obermeyer works at the intersection of machine learning and health. He is an associate professor and the Blue Cross of California Distinguished Professor at the University of California, Berkeley; a Chan Zuckerberg Biohub Investigator; and a faculty research fellow at the National Bureau of Economic Research. His papers have appeared in a wide range of journals, including Science, Nature Medicine, and The New England Journal of Medicine; his work on algorithmic bias is frequently cited in the public debate about artificial intelligence. He is a cofounder of Nightingale Open Science, a nonprofit that makes massive new medical imaging data sets available for research, and Dandelion, a platform for AI innovation in health. Obermeyer continues to practice emergency medicine in underserved communities.

Eric Boyd, Microsoft

Sam Ransbotham and Shervin Khodabandeh

The software company executive shares what’s most exciting to him about embedding artificial intelligence in new products.

As a partner with OpenAI — the company that recently wowed the tech world and the general public with its DALL-E image generator and ChatGPT chatbot — Microsoft helped to make those generative AI tools possible. But Microsoft has long invested in developing its own artificial intelligence technologies, for internal and external customers alike. And even when AI is not the centerpiece of a specific software program, it’s often driving how that tool — such as the company’s Bing search engine — works.

As corporate vice president of Microsoft’s AI platform, Eric Boyd oversees product and technology teams that build artificial intelligence and machine solutions for the company’s Azure platform and its AI services portfolio. Eric joins Sam Ransbotham and Shervin Khodabandeh on this episode of the Me, Myself, and AI podcast to talk about how Microsoft builds AI tools and embeds the technology in its various products, AI’s potential for helping to expand people’s creativity, and the democratization of AI.

Eric Boyd leads the AI platform team within Microsoft’s Cloud + AI division. This global organization includes Azure Machine Learning, Microsoft Cognitive Services, Azure Cognitive Search, and internal platforms that provide data, experimentation, and graphics processing units cluster management to groups across Microsoft.

Boyd joined the company in 2009 to create the Silicon Valley Search Ads team. In 2011, he moved to Bellevue, Washington, to lead the Bing Ads Development team before taking on his current role in 2015.

Before joining Microsoft, Boyd was the vice president of engineering at Mochi Media, an ads startup that was acquired by Shanda Games. Previously, he was vice president of platform engineering at Yahoo for 10 years.

Boyd has a bachelor’s degree in computer science from MIT.

Michelle McCrackin, Delta Air Lines

Sam Ransbotham and Shervin Khodabandeh

The airline is upskilling its front-line workers by offering them data and analytics training and then hiring them for hard-to-fill roles.

Michelle McCrackin, senior manager of analytics learning and development at Delta Air Lines, never imagined that she’d be an analytics leader when she first joined the airline as an HR business partner. But, faced with the challenge of hiring outside analytics talent, she proposed a solution that would change her career path along with the paths of other Delta employees: an internal analytics training program. Delta Analytics Academy (DAA) enables front-line employees to gain in-demand tech skills and the opportunity to advance within the organization. In December 2022, DAA graduated its first cohort of 12 students, selected from a pool of 750 applicants that included gate agents, baggage handlers, flight attendants, and other operational experts interested in learning how data and analytics can be applied to process-improvement challenges.

In this episode of the Me, Myself, and AI podcast, Michelle joins Sam Ransbotham and Shervin Khodabandeh to discuss how the program, started in partnership with Georgia State University, fits into the airline’s talent development and retention strategy.

Michelle McCrackin is a strategy and analytics leader with over 13 years of experience in the corporate space. She worked in the consumer packaged goods and automotive industries before moving into the field of aviation, where she is currently senior manager of analytics, learning, and development at Delta Air Lines. McCrackin’s passion for raising the analytics capability across the operations and commercial functions at Delta is exhibited in creation and development of Delta Analytics Academy (DAA), a program with the objective of producing an internal talent pipeline and closing the talent gap within the analytics skill set. DAA was developed in partnership with Georgia State University based on the hypothesis that taking an industry expert and providing them with a wraparound analytics education in a condensed format would produce top-performing analytics professionals.

Anders Butzbach Christensen, The Lego Group

Sam Ransbotham and Shervin Khodabandeh

Many organizations liken their technology implementation strategy to building with Lego bricks — and the toy company itself employs a similar approach.

Anders Butzbach Christensen began his career in product management before landing his dream job working for the Lego Group in Denmark. Today, as head of data engineering, he’s leading Lego’s digital transformation with a specific focus on designing and building data products, including self-service applications that technology and business teams can all use to better serve their customers.

In this episode of the Me, Myself, and AI podcast, Anders joins Sam Ransbotham and Shervin Khodabandeh to describe how the Lego Group is approaching digital transformation, and how the toymaker is empowering its product teams by becoming a product-, architecture-, and engineering-led company.

As head of data engineering at the Lego Group, Anders Butzbach Christensen is responsible for building up a strong competency area and great data products that will enable the company to become more data-driven. The product teams he leads are currently building a self-service core data platform to ensure that employees can discover and use data across the organization.

Rathi Murthy, Expedia Group

Sam Ransbotham and Shervin Khodabandeh

The travel company relies on artificial intelligence to deliver personalized recommendations, limit customer-service call times, and mitigate risks around natural disasters and other disruptions.

Rathi Murthy has always been passionate about technology roles that allow her to drive business transformation and improve customer experience. In her current role as CTO and president of Product & Technology for Expedia Group, she’s able to do both. One of her key goals is to enhance and unify the end-user experience across Expedia’s many brands, among them Hotels.com, Vrbo, and Travelocity. Another transformation goal: helping to modernize the entire travel industry by making Expedia’s AI technology available to B2B partners throughout the travel ecosystem, such as hotels, airlines, car rental companies, and cruise lines.

Expedia Group’s travel platform processes more than 600 billion AI predictions each year and relies on AI and machine learning technology to provide a range of services, including fraud prevention, customer service through virtual agents, flight price comparisons, and quick and seamless travel booking. Rathi joins Sam Ransbotham and Shervin Khodabandeh on this episode of the Me, Myself, and AI podcast to explain how Expedia Group is using artificial intelligence to continually improve the customer experience for travelers and travel providers alike.

Rathi Murthy is CTO and president of Expedia Product & Technology. In this role, she focuses on accelerating Expedia Group’s Open World platform, developing accessible and equitable products, and delivering quality experiences for travelers, partners, and developers.

Previously, as CTO, she oversaw Verizon Media’s global technology strategy, including its platform technology and infrastructure and innovations in 5G. As CTO at Gap Inc., she developed an end-to-end technology strategy for its portfolio of brands. She has also held senior technology leadership roles at American Express, eBay, Yahoo, Sun Microsystems, and WebMD.

Murthy currently sits on the board of directors for PagerDuty. She has a master’s degree in computer engineering from Santa Clara University.

Dave Thau, World Wildlife Fund

Sam Ransbotham and Shervin Khodabandeh

The wildlife conservation organization relies on partnerships to implement technology solutions to protect our planet.

Wildlife conservation efforts may not be the first thing that comes to mind when one thinks about opportunities to use artificial intelligence and machine learning. But Dave Thau, data and technology lead scientist at the World Wildlife Fund (WWF), can share myriad examples of how these technologies are helping our planet.

On this episode of the Me, Myself, and AI podcast, Dave joins Sam Ransbotham and Shervin Khodabandeh to discuss WWF’s many uses of AI and machine learning. Among them are applications that predict deforestation, analyze images from motion-sensitive cameras to identify species, optimize wildlife patrols to catch poachers, and reduce the illegal wildlife trade online. These conservation efforts are not only supported by nonprofit partners with shared goals but by tech-company partners that are sharing advanced AI technologies.

Dave Thau is the World Wildlife Fund’s data and technology global lead scientist, focusing on applying artificial intelligence in conservation and using technology for long-term impact monitoring.

Previously, he worked at Google, where he helped launch Google Earth Engine and managed developer relations. He also helped to develop the Global Forest Watch nature monitoring platform with the World Resources Institute, and the Map of Life species data platform.

Thau’s work in data management, sustainability, AI, and remote sensing has been published in several journals. He is also a member of the Knowledge and Data Task Force for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

Thau has a doctorate in computer science from the University of California, Davis.

Stephanie Moyerman, Instagram

Sam Ransbotham and Shervin Khodabandeh

A physicist turned technology leader talks about the risks — and opportunities — social media platforms offer and how AI can enable better user experiences.

Stephanie Moyerman’s background in cosmology and astrophysics — where she worked with large data sets, looking for a signal among what was mostly noise — prepared her well for a career in data science and ethics. Today, she is the data science director of well-being at Instagram, where she works to enhance trust, safety, and integrity for users of the social media platform.

Stephanie joins hosts Sam Ransbotham and Shervin Khodabandeh on this episode of the Me, Myself, and AI podcast to discuss how applying artificial intelligence to social media enables Instagram to detect fraud and abuse at scale to help protect users, as well as the importance of human input in AI feedback loops and the need for more experienced practitioners in the field.

Stephanie Moyerman is the data science director of well-being at Instagram, where she works to minimize negative experiences and maximize positive experiences on the platform. Previously, she was the senior director of risk and trust science at eBay and a senior science manager in Amazon’s Customer Trust and Partner Support unit, where she worked to protect the e-commerce platforms from bad actors.

Moyerman has a doctorate in physics (experimental cosmology) and a master’s in computational science, math, and engineering from the University of California, San Diego. She also has dual bachelor’s degrees in mathematics and physics from Harvey Mudd College.

Moyerman enjoys many hobbies, including running, hiking, surfing, snowboarding, judo, jujitsu, glassblowing, flying airplanes, and racing cars.

Shelia Anderson, Aflac

Sam Ransbotham and Shervin Khodabandeh

The insurance company values inquisitive, continuous learners on its technology teams.

Shelia Anderson parlayed a love of learning into studying the emerging field of engineering when she began her undergraduate education. After gaining experience leading IT teams in the technology, airline, and insurance industries, she joined Aflac in the summer of 2022.

Shelia joins this episode of the Me, Myself, and AI podcast to share how using artificial intelligence and machine learning to automate the processing of somewhat routine insurance claims frees up staff members to spend more time serving customers and processing more complex, higher-value claims. She also discusses the types of skills she looks for in data science and engineering talent beyond technical capabilities, and why she believes the insurance industry offers a great opportunity for people interested in a career working with AI and machine learning.

Shelia Anderson joined Aflac in July 2022 as senior vice president and CIO. She oversees the insurer’s digital services division and drives technology strategy in support of its U.S. business. Anderson has a rich history as an executive leading the IT functions at Fortune 500 global organizations, including Liberty Mutual, USAA, HP, and Electronic Data Systems.

Season 7

Hina Dixit, Samsung Next

Sam Ransbotham and Shervin Khodabandeh

A technology leader shares her criteria for evaluating investments in new AI-driven ventures.

Hina Dixit’s interest in supporting people and solving problems has its roots in her family’s call office business, where she helped people place telephone calls when she was growing up in India. Later, after earning her bachelor’s degree in computer science, she was quickly recruited into the tech space, where her problem-solving and customer service skills have served her well as both a software engineer and tech investor. From a developer role at Symantec, to project leader at Apple, to an AI investor role at Samsung Next, Hina continues to leverage her communication and connection skills in seeking out and supporting innovations in artificial intelligence, as well as robotics, Web3, and other tech sectors.

On this episode of the Me, Myself, and AI podcast, Hina shares the criteria she considers when making investments in new entrepreneurial ventures. She also highlights the focus areas that are of most interest right now, explains why she enjoys mentoring other technologists, and shares her views on what the future of AI looks like.

Hina Dixit is a venture capitalist and software engineering leader with more than 13 years of experience. She is currently an investor at Samsung Next, focusing on the AI, augmented reality, Web3, and infrastructure sectors.

Before she joined Samsung Next, Dixit led a team at Apple that worked on a variety of projects, including security, iCloud, artificial intelligence, developer tools, and data integrity, for eight years. She is an investor in several companies, including Stability AI, MosaicML, and Space and Time.

Elizabeth Anne Watkins, Intel

Sam Ransbotham and Shervin Khodabandeh

The semiconductor manufacturer’s social scientists are helping technicians learn how artificial intelligence can enhance — not take over — complex assembly work.

When Elizabeth Anne Watkins started her doctoral program, she landed a research role studying journalists’ use of security and privacy technologies — but she found the security tools confusing and difficult to use. Today, as a research scientist in the social science of AI at Intel Labs, she advocates for other end users faced with understanding and working with new technologies.

Elizabeth employs social science to understand the concerns of technicians performing complex chip manufacturing processes so that new AI systems will be developed to better serve those human experts. During this process, she also helps the technicians recognize AI’s role as a supporting technology — even a coworker — rather than a human replacement.

She joins this episode of the Me, Myself, and AI podcast to discuss her role as a social scientist working in tech and some of the ways Intel is applying AI technologies like computer vision and natural language processing to improve semiconductor manufacturing processes.

Elizabeth Anne Watkins is a research scientist at Intel Labs and a member of its Responsible AI Advisory Council. She drives strategy and execution of social science methods to amplify human potential in human-AI collaboration and conducts research on trustworthiness, explainability, transparency, and agency in the design, deployment, and governance of AI tools like computer vision, natural language processing, and robotics.

Watkins is an affiliate with AI on the Ground at the Data and Society Research Institute and has worked, consulted, and collaborated with research centers across academia and industry. She earned a doctorate at Columbia and a master’s at MIT and was a postdoctoral fellow at Princeton’s Center for Information Technology Policy and with its Human-Computer Interaction group.

David Hardoon, Aboitiz Data Innovation

Sam Ransbotham and Shervin Khodabandeh

The leader of an Asia-based technology conglomerate explains why he believes regulation helps rather than hinders AI innovation.

As CEO of Aboitiz Data Innovation, David Hardoon oversees the operations of a technology conglomerate focused on using data science and AI to support its businesses in a range of sectors, including banking, financial services, utilities, agriculture, and construction in Singapore and the Philippines. In his role, David is leading some unexpected — but practical — uses of artificial intelligence, including using voice and image recognition to detect stress in livestock, and analyzing internet-of-things data to reduce waste and CO2 emissions in the cement R&D process.

David joins this episode of the Me, Myself, and AI podcast to discuss the broad scope of the organizations he’s responsible for, the role of AI regulation and governance in helping to spur innovation, humans’ sometimes problematic role in shaping AI outputs, and how a high school detention led to a career in artificial intelligence.

David Hardoon is the CEO of Aboitiz Data Innovation and chief data and AI officer of Union Bank of the Philippines. He is concurrently the chief data and innovation officer of the Aboitiz Group and chief data officer of UnionDigital Bank. Previously, he was the Monetary Authority of Singapore’s first appointed chief data officer and head of the Data Analytics Group, as well as a special adviser on AI. Hardoon has a doctorate in computer science (machine learning) from the University of Southampton and a bachelor’s degree from Royal Holloway, University of London, in computer science and AI.

Naba Banerjee, Airbnb

Sam Ransbotham and Shervin Khodabandeh

Machine learning helps the travel platform flag suspicious bookings to protect hosts and guests from bad actors.

Naba Banerjee’s identity as a “forever learner” led to her become the first female engineer in her family. That curiosity has informed her career choices as well, leading her to companies as varied as Tata, Cognizant, AAA, and Walmart. Now, as director of trust product and operations at vacation rental platform Airbnb, she continues to let curiosity be her guide as she applies her previous data science experience to the travel industry.

On this episode of the Me, Myself, and AI podcast, Naba joins hosts Shervin Khodabandeh and Sam Ransbotham to talk about how she and her team use AI and machine learning to increase the safety of the guests and hosts who use Airbnb’s platform. She also discusses collaboration between humans and machines and the importance of recognizing that neither is an infallible decision maker.

Naba Banerjee is the director of trust product and operations at Airbnb, overseeing the company’s efforts to combat fraud, build trust between hosts and guests, and stop bad actors from using the platform. Her most recent work includes the development of Airbnb’s reservation screening technology, which helps to identify users making potentially high-risk reservations and prevent them from taking advantage of the platform.

Banerjee has over two decades of experience building products that deliver innovative, customer-centric solutions. She joined Airbnb after spending 13 years at Walmart.com, where she played an instrumental role in the evolution of product management, including shipping packages to customers more quickly and building mobile apps to enable customers to check out faster.

Zan Gilani, Duolingo

Sam Ransbotham and Shervin Khodabandeh

A product manager describes how the use of generative AI has been embedded in his company’s language-learning product since its inception.

When Zan Gilani came to the U.S. from Pakistan to complete his undergraduate studies, he chose to study Chinese because it was rumored to be a difficult language. At the time, the tech industry was booming, and he quickly became interested in applying his passion for foreign languages and learning more generally in a technology-rich environment.

Those interests led Zan to Duolingo, where he has been working in product management for eight years and now oversees the app company’s experiential AI team. What excites him about working at the language-learning app company is his ability to help build solutions that enable personalized education at scale: The app boasts over 16 million daily active users, and AI-driven functionality motivates them through frequent notifications, personalizes learning experiences by adjusting the difficulty of questions in practice sessions, and observes and critiques learners’ performance.

Zan joins the Me, Myself, and AI podcast to outline the specific ways Duolingo uses AI and machine learning to drive user engagement, and discuss how the technology can be used to support learning more generally.

Zan Gilani is a principal product manager at Duolingo. For the past eight years, he has helped grow the company’s learner base from 3 million to 16 million daily active users by working on retention, acquisition, growth in Asia, gamification, and the new-user experience.

He currently leads Duolingo’s Experimental AI team, which uses generative AI to build features that teach learners more effectively. More broadly, Gilani is working on setting Duolingo up for success using generative AI, through external partnerships and internal education.

Gilani grew up in Karachi, Pakistan, and is currently based in New York City. He has bachelor’s degrees in political science and East Asian studies from Columbia University.

Jeremy King, Pinterest

Sam Ransbotham and Shervin Khodabandeh

Built on machine learning technology, the image-based social media platform continues to incorporate advances in AI to improve the customer experience.

Jeremy King leads a team of 1,400 passionate engineers working on the continuous improvement of Pinterest’s image-driven platform. With a background that includes heading up a translation team at eBay and overseeing the technology behind Walmart’s U.S. retail stores and e-commerce business, Jeremy is now responsible for technology operations at Pinterest. To support the company’s mission to inspire people to “create a life that they love,” he and his team rely on advanced AI, machine learning, and a graph database to index and build a network of images so that users can find inspiration — particularly when they aren’t completely sure what they’re looking for.

On this episode of the Me, Myself, and AI podcast, Jeremy joins hosts Sam Ransbotham and Shervin Khodabandeh to talk about some recent advances Pinterest has made in the image-recognition space and shares his views on how generative AI will transform image-based content like Pinterest’s.

Jeremy King is senior vice president of technology at Pinterest, where he leads the company’s technical vision and the engineering organization responsible for building and scaling a visual discovery engine.

Before joining Pinterest, he was CTO and senior vice president at Walmart, where he led the team responsible for the technology behind U.S. retail stores and e-commerce for Walmart and Jet, and oversaw customer, merchant, and supply chain technologies across cloud and data platforms. King has also held executive-level technology roles at Walmart Labs, LiveOps, and eBay.

Matt Mahmoudi and Damini Satija, Amnesty International

Sam Ransbotham and Shervin Khodabandeh

Two researchers from the human rights organization discuss the intersection of social policy and technology, as well as problems with AI use in the public sector.

Amnesty International brings together more than 10 million staff members and volunteers worldwide to advocate for social justice. Damini Satija and Matt Mahmoudi work with Amnesty Tech, a division of the human rights organization that focuses on the role of government, Big Tech, and technologies like artificial intelligence in areas like surveillance, discrimination, and bias.

On this episode of the Me, Myself, and AI podcast, Matt and Damini join hosts Sam Ransbotham and Shervin Khodabandeh to highlight scenarios in which AI tools can put human rights at risk, such as when governments and public-sector agencies use facial recognition systems to track social activists or algorithms to make automated decisions about public housing access and child welfare. Damini and Matt caution that AI technology cannot fix human problems like bias, discrimination, and inequality; that will take human intervention and changes to public policy.

For more on what organizations can do to combat the unintended negative consequences arising from the use of automated technologies, tune in to our next episode, Part 2 of our conversation with Matt and Damini.

Matt Mahmoudi is a lecturer, researcher, and organizer. He’s been leading Amnesty International’s research and advocacy efforts on banning facial recognition technologies and exposing their uses against racialized communities, from New York City to the occupied Palestinian territories. He was the inaugural recipient of the Jo Cox Ph.D. scholarship at the University of Cambridge, where he studied digital urban infrastructures as new frontiers for racial capitalism and remains an affiliated lecturer in sociology. His work has appeared in the journals The Sociological Review and International Political Sociology and the book Digital Witness (Oxford University Press, 2020). His forthcoming book is Migrants in the Digital Periphery: New Urban Frontiers of Control (University of California Press, 2023).

Damini Satija is a human rights and public policy expert working on data and artificial intelligence, with a focus on algorithmic discrimination, welfare automation, government surveillance, and tech equity. She is head of the Algorithmic Accountability Lab and a deputy director at Amnesty Tech. She previously worked as an adviser to the U.K. government on data and AI ethics and represented the U.K. as a policy expert on AI and human rights at the Council of Europe. She has a master’s degree in public administration from Columbia University’s School of International and Public Affairs.

Matt Mahmoudi and Damini Satija, Amnesty International

Sam Ransbotham and Shervin Khodabandeh

Two researchers from the human rights organization discuss the intersection of social policy and technology, as well as problems with AI use in the public sector.

At Amnesty Tech, a division of human rights organization Amnesty International, Damini Satija and Matt Mahmoudi leverage their expertise in technology and public policy to examine the use of AI in the public sector and its impact on citizens worldwide.

In Part 1 of Matt and Damini’s conversation with Me, Myself, and AI hosts Sam Ransbotham and Shervin Khodabandeh, they described scenarios in which AI tools can put human rights at risk and how their work is helping to expose those risks and protect people from the technology’s misuse.

In this episode, they resume their conversation and dig deeper into the ways AI regulations can limit the negative use of AI at scale. Matt and Damini also caution us about what a dystopian future might hold and point to specific ways leaders in the corporate world can help limit the harms of AI.

Matt Mahmoudi is a lecturer, researcher, and organizer. He’s been leading Amnesty International’s research and advocacy efforts on banning facial recognition technologies and exposing their uses against racialized communities, from New York City to the occupied Palestinian territories. He was the inaugural recipient of the Jo Cox Ph.D. scholarship at the University of Cambridge, where he studied digital urban infrastructures as new frontiers for racial capitalism and remains an affiliated lecturer in sociology. His work has appeared in the journals The Sociological Review and International Political Sociology and the book Digital Witness (Oxford University Press, 2020). His forthcoming book is Migrants in the Digital Periphery: New Urban Frontiers of Control (University of California Press, 2023).

Damini Satija is a human rights and public policy expert working on data and artificial intelligence, with a focus on algorithmic discrimination, welfare automation, government surveillance, and tech equity. She is head of the Algorithmic Accountability Lab and a deputy director at Amnesty Tech. She previously worked as an adviser to the U.K. government on data and AI ethics and represented the U.K. as a policy expert on AI and human rights at the Council of Europe. She has a master’s degree in public administration from Columbia University’s School of International and Public Affairs.

Season 8

Anders Sjögren, Volvo Cars

Sam Ransbotham and Shervin Khodabandeh

Volvo cars have long had a reputation for safety. Today’s engineers are using technologies like artificial intelligence to continue enhancing vehicle safety.

Starting a career with the ambition of becoming a medical doctor and ending up a technical leader for a major automaker might seem an unlikely path, but for Anders Sjögren, who leads data and AI innovation projects for Volvo Cars, it was a perfect trajectory.

On this episode of the Me, Myself, and AI podcast, Anders joins hosts Sam Ransbotham and Shervin Khodabandeh to explain the ways the carmaker uses data and artificial intelligence to inform manufacturing — ensuring that parts are made consistently and as efficiently as possible — as well as driver experience and safety. He also outlines some specific ways smart technology keeps drivers alert and aware of conditions around them and describes Volvo’s approach to technology-driven innovation.

Anders Sjögren is senior technical leader for Volvo Cars. He focuses on strategy, research, innovation, and transformation, with the key objective of ensuring that the automaker understands and executes within the continuously emerging areas of data, analytics, and artificial intelligence. Application areas include creating AI-enabled intelligent customer functionality and using AI to reform Volvo’s operations and development activities. Sjögren has an academic background in mathematical statistics (large-scale and computational aspects) and an industrial background in data-centric methods development and software product development.

Shilpa Prasad, LG Nova

Sam Ransbotham and Shervin Khodabandeh

LG Electronics’ startup incubator seeks out innovative companies — particularly those working with AI — with an eye toward supporting their growth and identifying new business opportunities.

A former startup employee herself, Shilpa Prasad knows the level of commitment and effort required to begin a new venture. That’s what led her to join LG Nova, electronics manufacturer LG’s innovation incubator, as an entrepreneur in residence. In her role, Shilpa identifies promising startups — particularly those working with AI — and coaches and nurtures entrepreneurs while keeping a close eye on the products that might one day find their way into LG’s ecosystem.

On this episode of the Me, Myself, and AI podcast, Shilpa explains how keeping a finger on the pulse of startups helps LG Electronics stay open to innovation and new business opportunities. She also discusses why artificial intelligence is at the forefront of her work with startups, and the promising future she sees for using augmented reality and AI technologies to change how skills training is delivered.

Shilpa Prasad is an experienced leader in the startup ecosystem with a strong passion for entrepreneurship and corporate startup engagement/innovation. She brings over 15 years of global experience in corporate startup strategy and venture-building to her role as entrepreneur in residence at LG Nova, where she is helping the company identify market trends and build partnerships.

Prasad has been instrumental in driving innovation for various open innovation projects across corporations, governments, and accelerators and in establishing new partnerships across the global startup ecosystem. An experienced founder, she has also contributed her time to mentoring and advising startups.

Ayelet Israeli, Harvard Business School

Sam Ransbotham and Shervin Khodabandeh

A new study looks at generative AI’s potential as a substitute for human participants in marketing studies and focus groups.

As an associate professor at Harvard Business School and cofounder of the Customer Intelligence Lab at the school’s Digital Data Design Institute, Ayelet Israeli’s work is focused on how data and technology can inform marketing strategy, as well as how generative AI can be a useful tool in eliminating algorithmic bias. One of the products of her recent work is a paper she coauthored with two Microsoft economists and researchers on how generative AI could be used to simulate focus groups and surveys to determine customer preferences.

Ayelet joins the Me, Myself, and AI podcast to discuss the opportunities and limitations of generative AI in market research. She details how the research was conducted and how artificial intelligence technology could help marketers reduce the time, cost, and complexity associated with traditional customer research methods.

Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration in Harvard Business School’s Marketing Unit. She is also the cofounder of the school’s Customer Intelligence Lab at the Digital Data Design Institute. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their internal data, customer data, and market data to improve outcomes. Her research interests include retail, pricing strategy, channel management, marketing analytics, and algorithmic bias. Israeli has a Ph.D. in marketing from the Kellogg School of Management at Northwestern University.

Miqdad Jaffer, Shopify

Sam Ransbotham and Shervin Khodabandeh

The digital commerce platform is helping entrepreneurs get their products to market faster by giving them tools built on generative AI.

Miqdad Jaffer brings a background in engineering to his role as director of product for digital marketplace platform Shopify. Users might recognize the commerce platform as one that enables a fast and secure online checkout experience. On the merchant side, Shopify enables business owners to set up e-commerce sites where they can list and sell their products.

Using generative AI, the platform also now offers merchants the ability to complete administrative tasks much more quickly, including writing product descriptions and customizing their sites. As Miqdad explains on this episode of the Me, Myself, and AI podcast, a key to enhancing Shopify’s offerings with generative AI technology is ensuring that users always remain in control. He shares Shopify’s approach to doing this while incorporating cutting-edge tools to help entrepreneurs start, operate, and grow their businesses more efficiently.

Miqdad Jaffer is the director of product for Shopify, where he is responsible for the oversight and development of the company’s AI-powered offerings. He joined the company in 2018 and has overseen the launch of Shopify Magic, its suite of AI-powered tools, and Shop.AI, an AI-powered shopping assistant. Before joining Shopify, Jaffer was the director of product management for the mobile consumer marketplace app Flipp. He has more than 15 years of product development and oversight experience.

Ellen Nielsen, Chevron

Sam Ransbotham and Shervin Khodabandeh

The integrated energy company is using AI to enhance efficiency and relieve workers of time-consuming and potentially dangerous tasks.

Ellen Nielsen, Chevron’s first chief data officer, sees data as the common thread throughout a career that has spanned systems, digital data, procurement, and supply chain. In her current role, she applies what she’s learned to Chevron’s wide-ranging AI and machine learning initiatives, including the use of robots and computer vision to inspect tanks, digital twins to simulate operations, and sensors to monitor equipment in refineries.

On this episode of the Me, Myself, and AI podcast, Ellen shares examples of the integrated energy giant’s use cases for machine learning and generative AI, and she describes the company’s citizen development program, which puts safe, secured AI and machine learning tools in the hands of employees throughout Chevron.

Ellen Nielsen is the chief data officer at Chevron, where she focuses on creating a data-oriented culture partnered with value-chain thinking. A multidisciplinary leader, Nielsen has over 30 years of global experience as an executive in IT, digital, data, procurement, and supply chain. She has worked with industry leaders in oil and gas, fast-moving consumer goods, automotive, manufacturing, retail, and banking and insurance.

Nielsen is a regular speaker at industry events and has received numerous awards and recognitions, including being named to CDO Magazine’s 2023 Global Data Power Women list. She was also ranked fifth on the 2023 DataIQ 100 list of the most influential people in data in the United States.

She also serves on a variety of boards, including PIDX (Petroleum Industry Data Exchange) International and Women Leaders in Data & AI.

Vandi Verma, NASA

Sam Ransbotham and Shervin Khodabandeh

Most organizations aren’t executing space missions, but NASA’s use of AI and robotics offers lessons relevant to their more earthly applications.

When Vandi Verma saw the Spirit and Opportunity rovers land on Mars while she was working toward a Ph.D. in robotics, it set her on a path toward working at NASA in space exploration. Perhaps unsurprisingly, today, as chief engineer for robotic operations at NASA’s Jet Propulsion Laboratory (JPL), Vandi sees the biggest opportunities for artificial intelligence in robotics and automation.

On this episode of the Me, Myself, and AI podcast, she describes the ways in which the Mars rovers rely on AI, including the technology’s use in digital twin simulations that enable JPL scientists to practice their driving skills before actually controlling the rovers on Mars. She also discusses with hosts Shervin Khodabandeh and Sam Ransbotham how NASA’s use of AI — and its approach to risk — offer lessons for organizations that are looking to simulate real-world scenarios here on Earth.

Vandi Verma is a principal engineer and the deputy section manager for the Mobility & Robotics section at the NASA Jet Propulsion Laboratory. She also serves as chief engineer of robotic operations for the Mars 2020 Perseverance rover. She was previously the assistant section manager of the Mobility & Robotics section, the supervisor of the section staff group, and the supervisor of the Operable Robotics group.

Verma works on new robotics capabilities, including R&D; mission design; prototyping; flight development, testing, and launch; and landing and surface operations. She has been engaged in robotic operations on Mars since 2008 with the Mars Exploration Rover mission’s Spirit and Opportunity, Curiosity rover, Perseverance rover, and Ingenuity helicopter.

Before joining JPL, she led the NASA Ames Research Center team that developed PLEXIL (Plan Execution Interchange Language) for operating autonomous systems, as well as the development of technology that has been deployed on rovers and human spaceflight projects.

Verma earned a Ph.D. in robotics from Carnegie Mellon University in 2005.

Prem Natarajan, Capital One

Sam Ransbotham and Shervin Khodabandeh

The financial services company’s head of enterprise AI explains how AI and machine learning are contributing to the creation of magical customer experiences.

Growing up in a multilingual community, Prem Natarajan became interested in language at a young age. Eventually that interest, aptitude, and curiosity translated into an interest in machine learning and technical development, and today Prem works as the chief scientist and head of enterprise AI at financial services company Capital One.

Prem joins this episode of the Me, Myself, and AI podcast to share how Capital One’s technology teams are delivering value to customers by applying artificial intelligence in areas like fraud detection, how generative AI’s strengths stand to transform the developer experience, and why the right combination of product, science, and engineering expertise is key to successful AI and machine learning initiatives.

As chief scientist and head of enterprise AI at Capital One, Prem Natarajan leads technology strategy, architecture, and development for the company’s enterprise data, analytics, and AI and machine learning initiatives, including advancing its AI capabilities, tools, and research efforts. Natarajan has more than two decades of experience leading science, technology, and commercialization efforts in natural language processing, speech recognition, computer vision, forecasting, and other applications of machine learning.

Mark Surman, Mozilla Foundation

Sam Ransbotham and Shervin Khodabandeh

The nonprofit’s president is working to ensure that open-source AI remains trustworthy and accessible to all users.

When Mark Surman produced a pro-peace public service announcement for his local TV station as a self-proclaimed “punk rock kid” in the 1980s, he wasn’t thinking about a future career evangelizing fair, equitable, and trustworthy technology access for everyone. But today, as president of the Mozilla Foundation, he is focused on exactly that.

Mark went on to study filmmaking and has parlayed his communications expertise into technology leadership roles, where he has continued to work to “change hearts and minds by telling the truth.” On this episode of the Me, Myself, and AI podcast, Mark shares his take on the roles of both big tech and startups in the responsible AI conversation and also previews a forthcoming report on trustworthy AI from the Mozilla Foundation.

Mark Surman is president of the Mozilla Foundation, a global nonprofit that does everything from developing the Firefox web browser to advocating for a more open, equitable internet. His current focus is fueling Mozilla’s efforts to invest in responsible tech startups (via Mozilla Ventures) and to create foundational technology for more trustworthy AI (via Mozilla.ai). Before joining Mozilla, Surman spent 15 years leading organizations and projects that promoted the use of the internet and open-source technology for social empowerment.

Season 9

Daniele Petecchi, Pirelli

Sam Ransbotham and Shervin Khodabandeh

The tiremaker is using artificial intelligence to expedite its R&D processes and make production more efficient.

Daniele Petecchi didn’t realize how complex the process of producing tires was until he joined Pirelli, a company that’s been in the business of manufacturing tires for more than 150 years. But now, as head of data management and AI, he’s focused on leveraging the company’s wealth of data to meet the stringent technical, quality, and performance requirements of the Formula One racers and luxury vehicle makers — like Ferrari, Lamborghini, and BMW — that rely on Pirelli’s premium tires.

In this episode of the Me, Myself, and AI podcast, Daniele explains why virtualization and data are key to managing the complexity of an R&D and production cycle that includes using digital twins to predict how a tire will sound on the road and maximizing efficiency at plants that manufacture millions of tires each year.

Daniele Petecchi is head of data management and AI at Pirelli, where he leads critical initiatives that harness artificial intelligence technology to drive innovation and efficiency for the premium tire manufacturer. Petecchi earned his degree in telecommunications engineering, specializing in digital signal processing, which laid the foundation for his career in technology. He subsequently earned a Master of Science degree in information management, which equipped him with a strong strategic perspective. In 2018, he further reinforced his skill set by completing the General Management Program at ESCP Business School, enabling him to navigate the intricate intersection of technology and business.

Jackie Rocca, Slack

Sam Ransbotham and Shervin Khodabandeh

The collaboration platform is using artificial intelligence to address long-standing user pain points..

Like many product leaders in the technology space, Jackie Rocca took a somewhat circuitous path to that role. After beginning her career in management consulting with Bain, she earned her MBA at Stanford and then worked at Google, where she helped launch YouTube TV. Now, she serves as vice president of product at Slack, where she focuses on the collaboration platform’s Slack AI product.

As a product leader, Jackie had continually heard from users that they were experiencing a common challenge: It was a struggle to keep up with the pace of information and prioritize where to focus their attention and energy. So she looked to AI as a potential source of solutions and is now leading a team that’s focused on launching AI-driven features to address user pain points. The Slack AI team’s work is already helping customers take advantage of the wealth of knowledge within Slack exchanges by providing features such as channel recaps, thread summaries, and the ability to ask questions to surface information that’s embedded within conversations.

On this episode of the Me, Myself, and AI podcast, Jackie describes how her team approaches new product design in the generative AI space and offers up some predictions for what lies ahead.

Jackie Rocca is vice president of product at Slack. In that role, she oversees the vision and execution of Slack AI, which brings generative AI natively and securely into the collaboration platform’s user experience. Rocca has delivered on a number of AI initiatives in her five years with the company and is now on a mission to help customers further accelerate their productivity and get even more value out of their conversations, data, and collective knowledge.

Before joining Slack, Rocca spent more than six years as a product manager at Google, where she helped launch and grow YouTube TV.