B The Way Forward

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 About Why you should obsess over the customer and the problem, not your solution What's truly different about generative AI, and why it can be "confidently wrong" Good friction vs. bad friction in product design Taste, judgment, and creativity as the human skills that grow in value as AI advances Connect with Shama on LinkedIn Chapters: 00:00 Introduction 01:55 Meet Shama Pagarkar of PayPal 02:55 Early Career Lessons: Be Brave and Try Hard Things 05:10 Entrepreneur vs. Product Leader 06:15 Focus on the Problem, Not Your Solution 09:05 What Makes an Idea Worth Pursuing 10:10 Strategy vs. Iteration 11:05 What Failure Teaches You 12:30 What Makes Generative AI Different 14:50 What Companies Get Wrong About AI 18:00 PayPal's Maya: Making the Complex Simple 19:40 Good Friction vs. Bad Friction 21:00 How AI Changes the Human at Work 23:30 Taste, Judgment, and Creativity 25:30 What We Should Be Teaching Young People 26:55 Skills That Will Seem Outdated in 10 Years 28:25 Leading Through Uncertainty 31:10 An Uncomfortable Truth for Young Professionals 32:15 What Future Are We Building? 34:40 What "B the Way Forward" Means to Shama 36:20 Closing Thoughts #BTheWayForward #AnitaB #WomenInTech #AILeadership #ProductManagement #GenerativeAI #FutureOfWork #TechLeadership #PayPal #Innovation

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 adults How Adam built 50 versions of Siri over 15 years before the world was ready What the AI hype of the 1980s can teach us about today’s boom Why collective intelligence, or people deciding things together, may be the biggest opportunity after AI Why Adam is calling for a global slowdown while humans are still in charge Connect with Adam on LinkedIn Chapters: 00:00 Cold open 01:05 Meet Adam Cheyer 03:00 Magic as storytelling 04:20 Boredom, cardboard and creativity 07:55 Active vs. passive time 10:20 Software as the new cardboard 12:15 "2025 was the year programming died" 15:20 Studying the human mind at Brandeis 21:30 Why AI favors generalists 26:20 Doug Engelbart and human-tool co-evolution 32:00 When imagination arrives before technology 34:30 The first Siri, built in 1993 37:55 AI in the 1980s: expert systems in France 41:30 Augmented intelligence and collective intelligence 48:20 What technologists miss about human behavior 54:45 A golden moment for AI 56:30 The real risk: losing human purpose 58:00 Why the slowdown has to be global 1:02:00 Reasons for optimism 10 years out 1:04:50 Closing thoughts #BTheWayForward #AdamCheyer #Siri #ArtificialIntelligence #FutureOfWork #CollectiveIntelligence #WomenInTech #AnitaB

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 LinkedIn We Learned About: Human agency as a measure of progress Gaps 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 research 05:28 Leaving a tenured professorship for IBM 06:28 AI ethics is human ethics 10:45 Governance is the brakes, not the speed limit 12:19 What do we actually mean by intelligence? 15:13 Fluency is not reasoning 17:30 Why we anthropomorphize machines 21:36 What technologists miss about consequences 24:09 Business, government, research, and community in one room 29:15 Whose values get built into the model 32:44 The maieutic machine: AI that asks us questions 35:26 Serving humanity means expanding human agency 40:59 What gives Francesca hope 43:01 Deepfakes, jobs, and the risk of AI rejection 46:10 What AI is doing to how we learn 48:23 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

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 LinkedIn We Learned About Designing for People The Human Advantage Responsible AI & Trust Leading Through Transformation Chapters: 00:00 Welcome back to Be the Way Forward 01:51 Meet Prasanna Gopalakrishnan 02:06 When technology actually works for people 05:08 Three questions to ask before you build anything 07:00 Just because AI can, should it? 08:49 What stays true about people across every industry 12:11 Better at transformation, or just moving faster? 15:03 Customers want a kill switch, and that's okay 16:23 What she listens for when she walks into a company 19:34 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 hands 28:30 The divide forming inside organizations 31:34 Sprint thinking in the middle of a marathon 35:36 The what, the how, and what actually gets rewarded 37:19 Work, roles, and tasks are not the same thing 44:43 Giving people room to figure it out 46:42 The moment leadership became a philosophy 50:19 The moral compass she never gave up 53:01 Straight talk and why women hear it differently 55:41 Ten years from now 58:42 What keeps her up at night 1:00:38 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 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