B The Way Forward

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 About 1. Algorithmic bias is a mirror, and that's what makes it useful. 2. Credentials predict far less than we think 3. 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 Ming 03:02 Sci-Fi Nerd to Neuroscientist: Where the Philosophy Began 05:18 Real Smiles, Fake Smiles, and the Tip of the Tongue 07:43 Why Algorithmic Bias Tells Us About Ourselves 08:21 Facial Analysis for Hiring: Absolutely Not 08:52 Intelligence Isn't Fixed 09:35 Two Scientists, an EdTech Company, and 2008 Venture Capital 10:33 Ending High-Stakes Testing with AI 12:59 Foundational Skills, Not "Soft" Skills 14:58 People Can Change — And It's Measurable 17:23 Zero-Sum, Positive-Sum, and Peer Role Models 18:08 When Systems Treat the Most Complex Thing as Fixed 19:42 It's an Ecosystem Problem 20:11 Productization, Not Science, Is the Problem 22:38 Why Politicians Are So Vile Online 23:07 The Human Trust and the French Pluralism Project 24:05 You Aren't Your Shallowest Self 25:31 Allostasis: Beware Anyone Selling a Simple Rule 26:31 Finding the Happy Tension 28:58 There Is No Such Thing as a Problem-Solving Skill 30:33 Everyone's a Mashup — And Everyone's Bad at Something 32:34 When Scale Becomes a Flattening Word 33:41 Flattening Produces Divergence, Not Sameness 34:41 Three Levers: Technology, People, and Policy 37:03 From Thirty Parameters to Eight Billion 37:32 When the Worst AI Beats the Best Human 38:28 The World's Slowest Copy-Paste Function 39:26 Meet the Cyborgs 41:24 Our Advantage Is Exploring the Unknown 42:23 Why Don't We Take Courses on Curiosity? 43:21 Socrates: The AI That Refuses to Answer 43:52 Hybrid Intelligence — and Why the Students Hated It 44:12 Getting This Into Education Policy 46:22 Thirty Years of AI and a Thirteenth Company 46:46 Refugee Reunification, Autism, and Repurposed Tech 49:30 Building AI That Leaves You Better 50:56 Don't Wait Until You Have Wrinkles 51:27 The World Gets Better When Old Men Plant Trees 53:52 Diverse Teams, Flat Hierarchies, and Reading People You Disagree With 56:49 Tension Is at the Heart of Everything 57:46 The One Thing You Control Is You 58:48 Character and the Building of a Citizenry 01:00:12 Kuala Lumpur: The Question She Read Completely Wrong 01:02:40 What She Hopes She's Remembered For 01:02:50 Closing Reflections #BTheWayForward #AnitaB #VivienneMing #RobotProof #HumanPotential #AIandEducation #ResponsibleAI #FutureOfWork

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 LinkedIn We 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 problem 5. 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 Alphabet 02:27 The Problem That Wasn't on Anyone's Balance Sheet 03:18 The Google Project Where the Data Wouldn't Come Clean 04:57 Why Who Builds AI Matters 05:28 Two Halves of the Equation: Data and the Algorithm 06:43 Why Workforce Representation Alone Isn't Enough 07:23 Foundational Models vs. Specialized Domain Models 09:28 The Missing Middle Layer 10:49 The Internet as AI's Largest Teacher 11:19 A Very Western Internet — and How to Rebuild It Cleanly 13:37 The Smithsonian, Women Artists, and Voices with No Webpage 14:20 From Blame to Responsibility: The Consequence of Defaults 15:16 What We Missed When ChatGPT Launched 16:18 Now Everyone Can Be a Builder 17:39 Grace Hopper and "We've Always Done It That Way" 18:08 Seeing the Problem — and Leaving Corporate to Solve It 19:01 A Problem Solver First, an Entrepreneur Second 21:01 What Uplevyl Actually Solves 22:26 Workplace Rights Across 23,000+ Jurisdictions 23:25 A Woman Is Not a Homogeneous Group 24:50 Widowhood, Advisors, and the Great Wealth Transfer 25:50 Trauma-Informed vs. Grief-Informed Algorithms 27:26 Why General Models Hallucinate on Lived Experience 28:40 Founding Uplevyl Before ChatGPT 29:28 Pattern Recognition as a Superpower 31:42 Why Build a First-Party Knowledge Base from Scratch 32:28 Uplevyl Studios and Hundreds of Women Experts 35:11 Craft and Care: Protecting the Algorithm 37:03 When People Questioned the Vision 41:11 Building Every Line — and Choosing Europe for Privacy 42:43 Entrepreneurship Is a Three-Person Job 45:07 Taking Your Fingers Out of the Cookie Jars 46:09 AI for Empowerment, Not Replacement 46:36 Financial Flows, Human Capital, and Unsolved Human Problems 49:21 Technology Should Reflect Our Priorities 50:21 What She Hopes We See in the Mirror in Five Years 51:48 Leadership in the Unknown Unknowns 54:17 Presence, Passion, and Purpose 55:04 The 10,000 Days Question 56:22 Closing Reflections #BTheWayForward #AnitaB #ShubhiRao #Uplevyl #WomenInAI #AIBias #WomenInTech #ResponsibleAI

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 Instagram We Learned About The 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 Purpose 01:28 Meet Dr. Safiya Umoja Noble 02:17 Curiosity, a Working-Poor Childhood, and a PhD at 41 04:23 Corporate Tech, the Dot-Com Bust, and a Skeptic's Eye 08:00 Why We Ever Believed Technology Was Neutral 09:53 From Chat Rooms to Search Engines 12:45 Gen Z Doesn't Trust Search Anymore 13:44 The Search That Started It All 16:33 Designing the Study: What the Data Revealed 19:22 Algorithms Are Not "Just Math" 20:53 The Bifurcation of Technology and the Humanities 22:20 What If Women Had Held the Power and the Resources? 24:35 Eugenics, Race Science, and the History of CS 26:25 Techno-Solutionism and the Defunding of the Humanities 28:15 Sabbatical, Stand-Up Comedy, and Staying Present 30:03 The Cognitive Cost of AI Dependence 33:22 When Being Device-Free Becomes a Luxury 34:49 Who Gets Chatbots and Who Gets Teachers 37:23 Data Centers, Water Bills, and Community Pushback 40:58 "We Are the Optimists" 42:19 Tell the Truth 44:17 An Ecosystem of Truth-Tellers 47:16 Find Your Lane: Where Everyday People Have Power 49:51 Pensions, Portfolios, and Pro-Social Technology 51:53 Trained vs. Educated 54:02 Advice for the Exhausted Changemaker 56:08 Building "Data in Society" at UCLA 57:26 Gen Z and Values-Aligned Work 58:59 Black Women, Leadership, and the Cost of Retreat 01:02:31 Closing Reflections #BTheWayForward #AnitaB #SafiyaNoble #AlgorithmsOfOppression #AlgorithmicBias #WomenInTech #ResponsibleAI #TechEquity

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 LinkedIn We Learned About Staying present as a leader while operating in environments that are constantly looking ahead Why non-linear career paths are the norm, not the exception, and why that's actually a competitive advantage The "40 by 40" list framework Betsy used to reorient her life around living, not just achieving How authentic leadership can cost you power in some rooms while building deep trust in others The danger of defining your self-worth through your job title Chapters: 0:00 Introduction & Season Theme 1:44 Welcome to B the Way Forward – Meet Betsy Ziegler 3:11 Betsy's Response: Partnership Between 1871 and AnitaB.org 4:02 Leading in the Present While Focused on What's Next 8:26 Was Your Career Path Linear? Betsy's Honest Answer 13:10 The "40 by 40" List That Changed Everything 16:08 Letting Go of Certainty to Step Into Something New 19:42 Trusting Yourself Through Major Career Reinventions 21:53 The Danger of Giving Too Much of Yourself Away 25:07 How Betsy Separates Urgency From Importance 29:56 Authenticity in Leadership: Where It Costs You and Where It Pays 37:16 What Really Motivates Founders (It's Not the Metrics) 43:24 A Founder Story That Shifted Betsy's View on Impact 46:00 What People Misunderstand About Failure 50:20 Advice for Anyone Struggling to Believe in Themselves Right Now 54:05 AI, Abundance, and Who's Grabbing the Pen 1:00:05 Closing Thoughts and Defining Integrity #BTheWayForward #WomenInLeadership #StartupEcosystem #Leadership #Innovation1871 #AuthenticLeadership #AIandInnovation

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 LinkedIn We Learned About: Why empathy, not speed, is the real foundation of successful enterprise AI deployment The critical distinction between self-expression and authenticity, and why getting it wrong costs you influence in the room Ambica's leadership mantra "Clarity wins the day" and what it actually looks like to apply it inside high-stakes, fast-moving organizations How a 15-year-old performance review that said "your team doesn't like you much" became one of the most transformative moments of her career The difference between being a journey person and a goal person, and why knowing which one you are changes everything about how you lead Chapters: 0:00 Introduction & Season Theme 1:00 Meet Ambica Rajagopal, Group Chief Data and AI Officer 2:30 Why Empathy Is the Only Way to Get AI Transformation Right 5:30 Empathy as Active Common Ground, Not Passive Sympathy 7:00 What Has Remained Constant Across Industries: Clarity and People 10:00 How Ambica Stays Grounded When Performance Metrics Are Always On 11:00 Meditation, Mental Space, and the "Room of One's Own" Framework 13:30 Has Leading with Balance Ever Cost You Anything? 15:00 The Shift from Showing Up as an Expert to Showing Up as a Leader 17:30 Journey Person vs. Goal Person: How Ambica Defines Her Own Motivation 19:30 When Personal Transformation Gets Tested the Most 20:30 The Performance Review That Changed Everything 23:00 Vulnerability in Leadership and Why It Takes More Courage Than Being Right 24:30 Authenticity vs. Self-Expression: A Framework Worth Knowing 27:00 Who Is Most at Risk of Burnout in the AI Era 30:00 Advice for Early-Career Women in Data Science Who Are Already Exhausted 32:00 Building Resilience and Finding Your Sources of Courage 33:30 What Integrity in Leadership Actually Looks Like 34:30 "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