"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.

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.In this episode, 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. Read the episode transcript here.Read the article Strategy For and With AI.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: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.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.  

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.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. Read the episode transcript here.Read more about our show and follow along with the series at https://sloanreview.mit.edu/audio-series/me-myself-and-ai.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: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.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.

Will Grannis, founder of Google Cloud’s CTO Office, shares how his early love for gaming shaped his tech career. He discusses the importance of defining problems for success in AI projects, emphasizing a user-first mindset and collaboration across diverse perspectives. Grannis highlights the intricate balance between human teamwork and machine integration, particularly in customer support contexts. He also underlines that focusing on business impact rather than just technology is crucial for effective machine learning solutions, drawing valuable parallels from gaming.

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.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. Read the episode transcript here.Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.To find out more about the movie Coded Bias, which Craig mentions during the interview, visit https://www.codedbias.com. To learn more about the work of MIT Media Lab researcher Joy Buolamwini, visit her page on the lab's website: https://www.media.mit.edu/people/joyab/overview/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: 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 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.

Kay Firth-Butterfield, head of AI and machine learning at the World Economic Forum, dives into the complexities of AI governance and ethics. With her background in human rights law, she emphasizes the necessity of education and collaboration in technology to address power dynamics and drive innovation. Kay discusses how AI can enhance innovation in sectors like healthcare and environmental solutions while advocating for empathetic human interactions with machines. She also highlights the importance of diverse backgrounds in shaping future leaders who can ethically navigate the AI landscape.