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.In this episode, Paula joins hosts Sam and Shervin to discuss her specific role leading the ethical development of technology solutions, as well as the role technology companies play in society at large. Read the episode transcript here.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders.Read more about our show and follow along with the series at https://sloanreview.mit.edu/ai.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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. Read the episode transcript here.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders.Read more about our show and follow along with the series at https://sloanreview.mit.edu/ai.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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 podcast, hosts Sam Ransbotham and Shervin Khodabandeh interview Sarah Karthigan, AI operations manager for IT, to find out.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. Read the episode transcript here.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders.Read more about our show and follow along with the series at https://sloanreview.mit.edu/ai.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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.In the first episode of Season 3 of Me, Myself, and AI, our hosts talk with Kartik about how Jumpcut uses AI to identify creative individuals and help them develop their ideas into studio-ready productions. Read the episode transcript here.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders.Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast. Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Me, Myself, and AI is a podcast on artificial intelligence in business. Join us as we kick off Season 3 on October 19, 2021.Hear from three of our Season 3 guests in this short trailer: Douglas Hamilton, associate vice president and head of AI research for global exchange operator Nasdaq Sarah Karthigan, AI for IT operations manager at energy company ExxonMobil Kartik Hosanagar, professor at the University of Pennsylvania's The Wharton School and founder and CEO of Jumpcut, a data-driven film studio Read more about our series and follow along at https://sloanreview.mit.edu/ai.Join our growing community of AI leaders and enthusiasts on LinkedIn at mitsmr.com/AIforLeaders.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

"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.In this bonus episode, Sam and Shervin 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. Read the episode transcript here.Continue the conversation with us on LinkedIn at https://mitsmr.com/AIforLeaders.We’ve created a group called AI for Leaders specifically for audience members like you. You can catch up on back episodes of the show, meet show creators and hosts, tell us what you want to hear about in Season 3, and discuss key issues about AI implementation with other like-minded people.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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 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. Read the episode transcript here.Thank you for joining us for Season 2 of Me, Myself, and AI. We'll be back this fall with new episodes, and may have a bonus for you this summer. In the meantime, stay in touch by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders.Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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.In this episode, 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. Read the episode transcript here.Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Your reviews are essential to the success of Me, Myself, and AI. For a limited time, we’re offering a free download of MIT SMR’s best articles on artificial intelligence to listeners who review the show. Send a screenshot of your review to smrfeedback@mit.edu to receive the download.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

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.In this episode, 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. Read the episode transcript here. Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Your reviews are essential to the success of Me, Myself, and AI. For a limited time, we’re offering a free download of MIT SMR’s best articles on artificial intelligence to listeners who review the show. Send a screenshot of your review to smrfeedback@mit.edu to receive the download.Guest bio: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.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.  

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.In this episode, we talk with Chris about open innovation, automating rote processes without displacing human workers, and attracting talent by fostering a startup culture. Read the episode transcript here.For more on how humans and machines can collaborate successfully, read the 2020 Artificial Intelligence and Business Strategy report, “Expanding AI’s Impact With Organizational Learning."Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.Your reviews are essential to the success of Me, Myself, and AI. For a limited time, we’re offering a free download of MIT SMR’s best articles on artificial intelligence to listeners who review the show. Send a screenshot of your review to smrfeedback@mit.edu to receive the download.Guest bio: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.Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.