B The Way Forward

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

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

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

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

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