B The Way Forward

Oct 20, 2026 · 37m

What happens when we stop asking what AI can do and start asking what it should do? Shama Pagarkar has spent more than two decades at the crossroads of technology, product, and people, culminating in leading AI transformation work at PayPal.In this episode of B the Way Forward, Brenda sits down with Shama to talk about building products people actually need, why "AI isn't a strategy," and how PayPal's Maya initiative turned a weeks-long merchant integration into a few hours. Shama also makes the case that as answers get cheaper, human judgment becomes the whole job, and shares what she told her team when she asked them to trade old-school PRDs for hands-on prototypes.If you're leading through change, building your career in tech, or wondering which human skills will matter most in the age of AI, this conversation is for you.We Talked AboutWhy you should obsess over the customer and the problem, not your solutionWhat's truly different about generative AI, and why it can be "confidently wrong"Good friction vs. bad friction in product designTaste, judgment, and creativity as the human skills that grow in value as AI advancesConnect with Shama on LinkedInChapters:00:00 Introduction01:55 Meet Shama Pagarkar of PayPal02:55 Early Career Lessons: Be Brave and Try Hard Things05:10 Entrepreneur vs. Product Leader06:15 Focus on the Problem, Not Your Solution09:05 What Makes an Idea Worth Pursuing10:10 Strategy vs. Iteration11:05 What Failure Teaches You12:30 What Makes Generative AI Different14:50 What Companies Get Wrong About AI18:00 PayPal's Maya: Making the Complex Simple19:40 Good Friction vs. Bad Friction21:00 How AI Changes the Human at Work23:30 Taste, Judgment, and Creativity25:30 What We Should Be Teaching Young People26:55 Skills That Will Seem Outdated in 10 Years28:25 Leading Through Uncertainty31:10 An Uncomfortable Truth for Young Professionals32:15 What Future Are We Building?34:40 What "B the Way Forward" Means to Shama36:20 Closing Thoughts#BTheWayForward #AnitaB #WomenInTech #AILeadership #ProductManagement #GenerativeAI #FutureOfWork #TechLeadership #PayPal #Innovation

Oct 13, 2026 · 1h 6m

What happens when your imagination shows up decades before the technology does?Adam Cheyer built his first version of Siri in 1993, before the web existed. He went on to co-found Siri and Viv Labs and was the first developer at Change.org. Now he’s saying something many people in tech won’t: 2025 was the year programming died.Brenda talks with Adam about why boredom made him creative as a kid, and how cardboard became software. They also get into Doug Engelbart’s idea that people and tools have to change together. Adam explains why he thinks we’re in a “golden moment” with AI, and why the thing that scares him most isn’t machines taking over but people losing their sense of purpose.If you’re excited about AI but uneasy about where it’s going, this one’s for you.We Talked About:Why boredom and “active vs. passive” time build creativity in kids and adultsHow Adam built 50 versions of Siri over 15 years before the world was readyWhat the AI hype of the 1980s can teach us about today’s boomWhy collective intelligence, or people deciding things together, may be the biggest opportunity after AIWhy Adam is calling for a global slowdown while humans are still in chargeConnect with Adam on LinkedInChapters:00:00 Cold open01:05 Meet Adam Cheyer03:00 Magic as storytelling04:20 Boredom, cardboard and creativity07:55 Active vs. passive time10:20 Software as the new cardboard12:15 "2025 was the year programming died"15:20 Studying the human mind at Brandeis21:30 Why AI favors generalists26:20 Doug Engelbart and human-tool co-evolution32:00 When imagination arrives before technology34:30 The first Siri, built in 199337:55 AI in the 1980s: expert systems in France41:30 Augmented intelligence and collective intelligence48:20 What technologists miss about human behavior54:45 A golden moment for AI56:30 The real risk: losing human purpose58:00 Why the slowdown has to be global1:02:00 Reasons for optimism 10 years out1:04:50 Closing thoughts#BTheWayForward #AdamCheyer #Siri #ArtificialIntelligence #FutureOfWork #CollectiveIntelligence #WomenInTech #AnitaB

Oct 6, 2026 · 53m

What if the most important question in AI is not how intelligent we can make machines, but what we want that intelligence to do for us? In this episode of B The Way Forward, Brenda Darden Wilkerson sits down with Francesca Rossi, IBM Fellow and IBM's Global Leader for Responsible AI and AI Governance at the T.J. Watson Research Center, for a conversation about AI ethics, AI governance, and the human decisions behind every system we build. Francesca spent more than 20 years as a computer science professor advancing AI capability, before a year at Harvard's Radcliffe Institute changed the questions she was asking. She explains why AI ethics is really human ethics, why governance works like brakes and seat belts rather than a speed limit on innovation, and why the language fluency of large language models should never be confused with reasoning. She and Brenda dig into whose values get embedded in a model and who gets to fine tune them, what happens to democracy and the legal system when people can no longer tell what is true, and why the greatest threat to human agency may be the steady accumulation of small decisions we hand over without noticing. This is a conversation that sits right at the center of this season's theme of presence, passion, and purpose, because the future of artificial intelligence is not something arriving on its own. It is something we are building, one choice at a time.Connect with Francesca on LinkedInWe Learned About: Human agency as a measure of progressGaps in training data How AI ethics is Human ethics What AI is teaching us about ourselves Chapters: 00:00 Just because we can build it, should we?02:09 The bigger question behind 20 years of AI research05:28 Leaving a tenured professorship for IBM06:28 AI ethics is human ethics10:45 Governance is the brakes, not the speed limit12:19 What do we actually mean by intelligence?15:13 Fluency is not reasoning17:30 Why we anthropomorphize machines21:36 What technologists miss about consequences24:09 Business, government, research, and community in one room29:15 Whose values get built into the model32:44 The maieutic machine: AI that asks us questions35:26 Serving humanity means expanding human agency40:59 What gives Francesca hope43:01 Deepfakes, jobs, and the risk of AI rejection46:10 What AI is doing to how we learn48:23 What working on AI taught her about humanity#BTheWayForward #AnitaB #FrancescaRossi #AIEthics #ResponsibleAI #AIGovernance #IBM #ArtificialIntelligence #HumanAgency #TrustworthyAI #GenerativeAI #AgenticAI #TechLeadership #WomenInTech #WomenInAI #FutureOfWork #AIandSociety #EthicalTech

Sep 29, 2026 · 1h 4m

In this episode, Brenda is joined by Prasanna Gopalakrishnan, former Global Chief Product & AI Officer at ADP and a veteran executive with over 25 years of experience leading digital transformation across tech, banking, and media.While much of today's conversation around Artificial Intelligence focuses on what machines will replace, Prasanna shifts the narrative toward a far more empowering question: What can AI make possible for human beings?Prasanna also shares where her optimism lands ten years out, from democratized superintelligence to breakthroughs in mental health and drug discovery, and what still keeps her up at night. If you're a leader, product builder, or HR decision maker trying to bring people along through AI change instead of running them over with it, this episode is for you.Connect with Prasanna on LinkedInWe Learned About Designing for PeopleThe Human AdvantageResponsible AI & TrustLeading Through TransformationChapters: 00:00 Welcome back to Be the Way Forward01:51 Meet Prasanna Gopalakrishnan02:06 When technology actually works for people05:08 Three questions to ask before you build anything07:00 Just because AI can, should it?08:49 What stays true about people across every industry12:11 Better at transformation, or just moving faster?15:03 Customers want a kill switch, and that's okay16:23 What she listens for when she walks into a company19:34 How do you measure people when AI does the work?21:28 The wrong question: what will AI replace?26:18 Superintelligence in everyone's hands28:30 The divide forming inside organizations31:34 Sprint thinking in the middle of a marathon35:36 The what, the how, and what actually gets rewarded37:19 Work, roles, and tasks are not the same thing44:43 Giving people room to figure it out46:42 The moment leadership became a philosophy50:19 The moral compass she never gave up53:01 Straight talk and why women hear it differently55:41 Ten years from now58:42 What keeps her up at night1:00:38 What being the way forward means#BTheWayForward #AnitaB #WomenInTech #AIEthics #FutureOfWork #Leadership #ArtificialIntelligence #ProductManagement #DigitalTransformation #InclusiveLeadership

Sep 22, 2026 · 1h 6m

Machines can now write, create, diagnose disease, generate art, and carry on a conversation. Which raises a question bigger than technology itself: if machines can increasingly do what humans do, what makes us uniquely human?In this episode of B The Way Forward, host Brenda Darden Wilkerson sits down with Dr. Vivienne Ming, a theoretical neuroscientist, serial entrepreneur, and one of the world's leading thinkers on artificial intelligence and human potential. She has built AI that improves healthcare, reduces bias in hiring, predicts mental health crises, and reunites orphaned refugees with their families. But the through line of her career isn't machines. It's people.Brenda pushes on the hardest part: how any of this reaches policy, education, and the systems that keep flattening people into something simpler than they are. Dr. Ming's answer is characteristically unsentimental and characteristically hopeful: tension is the reality of a healthy world, all real problems are messy human problems, and the one thing you actually control is you.Because meaningful innovation begins with internal alignment. Before we reshape industries or build remarkable technology, we decide what kind of people we want to become.Connect with Vivienne on LinkedIn We Learned About1. Algorithmic bias is a mirror, and that's what makes it useful.2. Credentials predict far less than we think3. There is no such thing as a problem-solving skill.4. The cyborg finding: our advantage is exploring the unknown.5. Depth is engineerable, and so is a better AI.Chapters: 00:00 Welcome Back: What Makes Us Uniquely Human?01:47 Meet Dr. Vivienne Ming03:02 Sci-Fi Nerd to Neuroscientist: Where the Philosophy Began05:18 Real Smiles, Fake Smiles, and the Tip of the Tongue07:43 Why Algorithmic Bias Tells Us About Ourselves08:21 Facial Analysis for Hiring: Absolutely Not08:52 Intelligence Isn't Fixed09:35 Two Scientists, an EdTech Company, and 2008 Venture Capital10:33 Ending High-Stakes Testing with AI12:59 Foundational Skills, Not "Soft" Skills14:58 People Can Change — And It's Measurable17:23 Zero-Sum, Positive-Sum, and Peer Role Models18:08 When Systems Treat the Most Complex Thing as Fixed19:42 It's an Ecosystem Problem20:11 Productization, Not Science, Is the Problem22:38 Why Politicians Are So Vile Online23:07 The Human Trust and the French Pluralism Project24:05 You Aren't Your Shallowest Self25:31 Allostasis: Beware Anyone Selling a Simple Rule26:31 Finding the Happy Tension28:58 There Is No Such Thing as a Problem-Solving Skill30:33 Everyone's a Mashup — And Everyone's Bad at Something32:34 When Scale Becomes a Flattening Word33:41 Flattening Produces Divergence, Not Sameness34:41 Three Levers: Technology, People, and Policy37:03 From Thirty Parameters to Eight Billion37:32 When the Worst AI Beats the Best Human38:28 The World's Slowest Copy-Paste Function39:26 Meet the Cyborgs41:24 Our Advantage Is Exploring the Unknown42:23 Why Don't We Take Courses on Curiosity?43:21 Socrates: The AI That Refuses to Answer43:52 Hybrid Intelligence — and Why the Students Hated It44:12 Getting This Into Education Policy46:22 Thirty Years of AI and a Thirteenth Company46:46 Refugee Reunification, Autism, and Repurposed Tech49:30 Building AI That Leaves You Better50:56 Don't Wait Until You Have Wrinkles51:27 The World Gets Better When Old Men Plant Trees53:52 Diverse Teams, Flat Hierarchies, and Reading People You Disagree With56:49 Tension Is at the Heart of Everything57:46 The One Thing You Control Is You58:48 Character and the Building of a Citizenry01:00:12 Kuala Lumpur: The Question She Read Completely Wrong01:02:40 What She Hopes She's Remembered For01:02:50 Closing Reflections#BTheWayForward #AnitaB #VivienneMing #RobotProof #HumanPotential #AIandEducation #ResponsibleAI #FutureOfWork

Sep 15, 2026 · 1h 0m

We ask AI questions. We trust its recommendations. We increasingly let it shape decisions about our work, our health, our money, and our futures. But there's a question we don't ask nearly often enough: who taught AI what it knows and who was missing from the room while it learned?In this episode of B The Way Forward, host Brenda Darden Wilkerson sits down with Shubhi Rao, founder and CEO of Uplevyl, and a leader who spent decades at the highest levels of global business (Ford, PwC, Tesco, and Alphabet) where she became the first woman and first person of color to serve as treasurer. From that vantage point, she saw a problem that never appeared on anyone's balance sheet: It wasn't only that women were underrepresented in the rooms where technology gets built. It was that the data powering artificial intelligence didn't really understand women's lives at all.If you build with AI, fund it, govern it, or simply rely on it, this conversation will change what you ask of it. Because behind every algorithm is a series of human choices, and the most important question isn't what AI can do. It's “Who is AI being built to serve?”Connect with Shubhi on LinkedInWe Learned About:1. Data is only half the equation; the algorithm is the other half.2. Foundational models are remarkable, and they're the wrong tool for specialized guidance.3. The internet is a skewed teacher, so Uplevyl built its own corpus.4. A woman is not a homogeneous group and that's precisely the design problem5. This isn't about replacing human advocates, entrepreneurship is a three-person job.Chapters:00:00 Welcome Back: Who Taught AI What It Knows?00:57 Meet Shubhi Rao: Ford, PwC, Tesco, and Alphabet02:27 The Problem That Wasn't on Anyone's Balance Sheet03:18 The Google Project Where the Data Wouldn't Come Clean04:57 Why Who Builds AI Matters05:28 Two Halves of the Equation: Data and the Algorithm06:43 Why Workforce Representation Alone Isn't Enough07:23 Foundational Models vs. Specialized Domain Models09:28 The Missing Middle Layer10:49 The Internet as AI's Largest Teacher11:19 A Very Western Internet — and How to Rebuild It Cleanly13:37 The Smithsonian, Women Artists, and Voices with No Webpage14:20 From Blame to Responsibility: The Consequence of Defaults15:16 What We Missed When ChatGPT Launched16:18 Now Everyone Can Be a Builder17:39 Grace Hopper and "We've Always Done It That Way"18:08 Seeing the Problem — and Leaving Corporate to Solve It19:01 A Problem Solver First, an Entrepreneur Second21:01 What Uplevyl Actually Solves22:26 Workplace Rights Across 23,000+ Jurisdictions23:25 A Woman Is Not a Homogeneous Group24:50 Widowhood, Advisors, and the Great Wealth Transfer25:50 Trauma-Informed vs. Grief-Informed Algorithms27:26 Why General Models Hallucinate on Lived Experience28:40 Founding Uplevyl Before ChatGPT29:28 Pattern Recognition as a Superpower31:42 Why Build a First-Party Knowledge Base from Scratch32:28 Uplevyl Studios and Hundreds of Women Experts35:11 Craft and Care: Protecting the Algorithm37:03 When People Questioned the Vision41:11 Building Every Line — and Choosing Europe for Privacy42:43 Entrepreneurship Is a Three-Person Job45:07 Taking Your Fingers Out of the Cookie Jars46:09 AI for Empowerment, Not Replacement46:36 Financial Flows, Human Capital, and Unsolved Human Problems49:21 Technology Should Reflect Our Priorities50:21 What She Hopes We See in the Mirror in Five Years51:48 Leadership in the Unknown Unknowns54:17 Presence, Passion, and Purpose55:04 The 10,000 Days Question56:22 Closing Reflections#BTheWayForward #AnitaB #ShubhiRao #Uplevyl #WomenInAI #AIBias #WomenInTech #ResponsibleAI

Sep 8, 2026 · 1h 5m

For years, we were told that algorithms were neutral. Just math. Just code. Dr. Safiya Umoja Noble asked a different question, and it changed the way the world thinks about technology.In this episode of B The Way Forward, host Brenda Darden Wilkerson sits down with the scholar, author, and educator whose groundbreaking book Algorithms of Oppression helped spark a global conversation about algorithmic bias years before most of us had the language for it. Dr. Noble takes us back to the beginning: a working-poor childhood full of questions about how the world really works, fifteen years inside corporate telecom, a front-row seat to the dot-com boom and bust, and a PhD earned at forty-one; proof that the timeline you were handed is not the only timeline available to you.She also gets honest about the cost. About Black women stepping back from leadership because they turn around and find no one behind them. About the online violence pushing women and girls out of public life. And about why, right now, retreat is a luxury none of us can afford.Connect with Safiya on InstagramWe Learned AboutThe search that exposed a system.Code is a language — and languages are subjective.Technology and humanity were separated by design.There are now two education systems, and AI is deepening the divide.Everyone has a lane, and everyone has leverage.Chapters:​​00:00 Welcome Back: Presence, Passion, and Purpose01:28 Meet Dr. Safiya Umoja Noble02:17 Curiosity, a Working-Poor Childhood, and a PhD at 4104:23 Corporate Tech, the Dot-Com Bust, and a Skeptic's Eye08:00 Why We Ever Believed Technology Was Neutral09:53 From Chat Rooms to Search Engines12:45 Gen Z Doesn't Trust Search Anymore13:44 The Search That Started It All16:33 Designing the Study: What the Data Revealed19:22 Algorithms Are Not "Just Math"20:53 The Bifurcation of Technology and the Humanities22:20 What If Women Had Held the Power and the Resources?24:35 Eugenics, Race Science, and the History of CS26:25 Techno-Solutionism and the Defunding of the Humanities28:15 Sabbatical, Stand-Up Comedy, and Staying Present30:03 The Cognitive Cost of AI Dependence33:22 When Being Device-Free Becomes a Luxury34:49 Who Gets Chatbots and Who Gets Teachers37:23 Data Centers, Water Bills, and Community Pushback40:58 "We Are the Optimists"42:19 Tell the Truth44:17 An Ecosystem of Truth-Tellers47:16 Find Your Lane: Where Everyday People Have Power49:51 Pensions, Portfolios, and Pro-Social Technology51:53 Trained vs. Educated54:02 Advice for the Exhausted Changemaker56:08 Building "Data in Society" at UCLA57:26 Gen Z and Values-Aligned Work58:59 Black Women, Leadership, and the Cost of Retreat01:02:31 Closing Reflections#BTheWayForward #AnitaB #SafiyaNoble #AlgorithmsOfOppression #AlgorithmicBias #WomenInTech #ResponsibleAI #TechEquity

Sep 1, 2026 · 1h 0m

What does it really mean to lead with purpose in a world that rewards speed over intention?In this episode of B the Way Forward, host Brenda Darden Wilkerson sits down with Betsy Ziegler, CEO of 1871, one of the nation's premier startup incubators and innovation hubs in Chicago. From her early days at McKinsey and GE to leading innovation at Northwestern University's Kellogg School of Management and now championing thousands of founders through 1871, Betsy has built a career defined not by a linear plan, but by a learner's mindset, radical authenticity, and an unwavering commitment to expanding what people believe is possible for themselves.Brenda and Betsy dig into what it takes to lead through ambiguity, how to stay grounded in your identity when your title becomes your identity, and why the future will be shaped by whoever has the courage to grab the pen. This is a conversation about redefining leadership, reimagining success, and building something that lasts beyond yourself.Connect with Betsy on Twitter (@betsyzeo) and LinkedInWe Learned AboutStaying present as a leader while operating in environments that are constantly looking aheadWhy non-linear career paths are the norm, not the exception, and why that's actually a competitive advantageThe "40 by 40" list framework Betsy used to reorient her life around living, not just achievingHow authentic leadership can cost you power in some rooms while building deep trust in othersThe danger of defining your self-worth through your job titleChapters:0:00 Introduction & Season Theme1:44 Welcome to B the Way Forward – Meet Betsy Ziegler3:11 Betsy's Response: Partnership Between 1871 and AnitaB.org4:02 Leading in the Present While Focused on What's Next8:26 Was Your Career Path Linear? Betsy's Honest Answer13:10 The "40 by 40" List That Changed Everything16:08 Letting Go of Certainty to Step Into Something New19:42 Trusting Yourself Through Major Career Reinventions21:53 The Danger of Giving Too Much of Yourself Away25:07 How Betsy Separates Urgency From Importance29:56 Authenticity in Leadership: Where It Costs You and Where It Pays37:16 What Really Motivates Founders (It's Not the Metrics)43:24 A Founder Story That Shifted Betsy's View on Impact46:00 What People Misunderstand About Failure50:20 Advice for Anyone Struggling to Believe in Themselves Right Now54:05 AI, Abundance, and Who's Grabbing the Pen1:00:05 Closing Thoughts and Defining Integrity#BTheWayForward #WomenInLeadership #StartupEcosystem #Leadership #Innovation1871 #AuthenticLeadership #AIandInnovation

Aug 25, 2026 · 39m

What does it actually take to lead AI transformation inside a global industrial enterprise, and do it with both technical rigor and radical humanity?In this episode of B the Way Forward, host Brenda Darden Wilkerson sits down with Ambica Rajagopal, Group Chief Data and AI Officer at Michigan, where she leads enterprise-wide data strategy to optimize manufacturing, services, and industrial operations through advanced analytics and AI. Ambica has built her career transforming large-scale organizations across pharmaceuticals, energy, and manufacturing, and her through-line has never been the technology itself. It has always been the people.In this conversation, Brenda and Ambica dig into what happens when the urgency of AI meets the human cost of change, why empathy is the most underrated technical skill, what a brutal performance review 15 years ago taught Ambica about the difference between expertise and leadership, and why she believes the most courageous thing a woman in tech can do right now is invest in her own resilience.This is a conversation about clarity, transformation, and what it really means to make your path the evidence of the change you believe in.Connect with Ambica on LinkedInWe Learned About:Why empathy, not speed, is the real foundation of successful enterprise AI deploymentThe critical distinction between self-expression and authenticity, and why getting it wrong costs you influence in the roomAmbica's leadership mantra "Clarity wins the day" and what it actually looks like to apply it inside high-stakes, fast-moving organizationsHow a 15-year-old performance review that said "your team doesn't like you much" became one of the most transformative moments of her careerThe difference between being a journey person and a goal person, and why knowing which one you are changes everything about how you leadChapters:0:00 Introduction & Season Theme1:00 Meet Ambica Rajagopal, Group Chief Data and AI Officer2:30 Why Empathy Is the Only Way to Get AI Transformation Right5:30 Empathy as Active Common Ground, Not Passive Sympathy7:00 What Has Remained Constant Across Industries: Clarity and People10:00 How Ambica Stays Grounded When Performance Metrics Are Always On11:00 Meditation, Mental Space, and the "Room of One's Own" Framework13:30 Has Leading with Balance Ever Cost You Anything?15:00 The Shift from Showing Up as an Expert to Showing Up as a Leader17:30 Journey Person vs. Goal Person: How Ambica Defines Her Own Motivation19:30 When Personal Transformation Gets Tested the Most20:30 The Performance Review That Changed Everything23:00 Vulnerability in Leadership and Why It Takes More Courage Than Being Right24:30 Authenticity vs. Self-Expression: A Framework Worth Knowing27:00 Who Is Most at Risk of Burnout in the AI Era30:00 Advice for Early-Career Women in Data Science Who Are Already Exhausted32:00 Building Resilience and Finding Your Sources of Courage33:30 What Integrity in Leadership Actually Looks Like34:30 "Make Your Path the Evidence of the Change You Believe In"36:00 Closing Thoughts: People Always Come Before the Technology#BTheWayForward #WomenInAI #AITransformation #EmpathyInLeadership #WomenInTech #DataAndAI #TechLeadership #CourageToTransform