FUTUREPROOF.

Jeremy Goldman
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Welcome to FUTUREPROOF. We're the podcast that delves into the future. From Augmented Reality to Artificial Intelligence to Smart Cities to Internet of Things to Virtual Reality, we speak with some of the sharpest minds to better help you understand what the next few years may look like.Brought to you by author Jeremy Goldman (Going Social, Getting to Like).For booking inquiries: vie@futureproofshow.com

  1. 6月16日

    AI Won't Burn Out...But *You* Might. (ft. Fredric Marshall, author, THRIVE)

    Send us Fan Mail We're living through the fastest technological acceleration in human history. Every week brings a new AI model, a new productivity tool, and a new prediction that everything is about to change forever. And yet somehow, most people feel less focused, less certain, and more overwhelmed than ever. In this episode of FUTUREPROOF., I sit down with Fredric Marshall, author of THRIVE: The Antidote to Future Shock, to explore a possibility we don't talk about enough: What if the biggest risk of AI isn't that it replaces humans? What if it's that it exhausts them? Fred has spent decades helping organizations like Apple, Pfizer, and Genentech navigate periods of intense change. His argument is that most organizations aren't suffering from a technology problem. They're suffering from an attention problem. We're surrounded by tools designed to save time, yet nobody seems to have any. We have more information than ever, yet many leaders feel less certain. And we keep calling it a productivity problem when it may actually be a human capacity problem. We discuss:  Why "future shock" may be the defining leadership challenge of the AI era  How AI can reduce friction—or quietly create more of it  Why burnout is often a systems problem disguised as a personal one  The hidden cost of constant context switching  Why clarity may become more valuable than speed  How leaders can separate signal from noise  What it actually means to thrive during exponential change Because if every problem gets solved with another app, another dashboard, or another AI assistant... At some point, someone has to manage all those solutions.

    23分

  2. 5月27日

    From Data-Driven to Data-Inspired (ft. Dr. Sebastian Wernicke, data scientist & author)

    Send us Fan Mail Every company today says it’s data-driven. Billions are spent on analytics. AI pilots are everywhere. Dashboards glow with real-time metrics. And yet, only a small fraction of organizations actually transform. In this episode of FUTUREPROOF., I sit down with Sebastian Wernicke — author of DATA INSPIRED: Building an Organizational Culture of Inquiry for Lasting Transformation—to unpack why. Sebastian argues that the problem isn’t a lack of data. It’s a lack of inquiry. Most companies use data to optimize what already exists. Few use it to question assumptions, rethink business models, or challenge leadership narratives. That’s the difference between being data-driven and being data-inspired. We explore:  Why data doesn’t “speak for itself”  How organizations become excellent at staying the same  The dangers of data-resistant minds  Why psychological safety is foundational for real AI success  What “radical data integrity” actually requires  And how to navigate AI’s “jagged frontier,” where human judgment still matters This isn’t a conversation about tools; it’s about whether your culture is equipped to learn — especially when the evidence is uncomfortable. Because AI won’t transform your company. It will amplify whatever culture you already have.

    26分

  3. 5月12日

    Product Design' Accessibility Mandate in the AI Age

    Send us Fan Mail We talk a lot about AI reshaping the future. We talk less about who gets to participate in it. In this episode of FUTUREPROOF., I sit down with Corbb O’Connor, who leads accessibility advocacy at Level Access. Corbb is blind. He’s spent years consulting enterprise teams — from financial institutions to global brands — helping them design digital experiences that are actually usable by people with disabilities. This isn’t a compliance conversation. It’s a systems conversation. As AI systems increasingly generate interfaces, content, decisions, and workflows at scale, accessibility can no longer be an afterthought. If accessibility isn’t embedded upstream — in product design, in data pipelines, in AI outputs — exclusion compounds just as quickly as innovation. Corbb argues that inclusion is not a moral add-on. It’s infrastructure. It’s economics. It’s risk management. And increasingly, it’s competitive advantage. We explore:  Why accessibility should be treated like cybersecurity — a non-negotiable requirement, not a retroactive fix  The difference between “AI for accessibility” and “accessible AI”  Why automated scanning tools can’t replace human testing  How poor product design quietly excludes users without teams even realizing it  Why psychological safety and culture matter just as much as tooling  And whether AI will widen or narrow accessibility gaps over the next five years If digital products define access to banking, healthcare, employment, and civic life, then accessibility isn’t a feature. It’s participation. And as AI becomes core infrastructure, the question becomes sharper: Are we scaling inclusion — or scaling exclusion?

    26分

  4. 4月21日

    The $1.4 Trillion Meeting Problem (ft. Dr. Rebecca Hinds, author)

    Send us Fan Mail We talk constantly about the future of work — AI agents, automation, leaner teams, productivity gains. But what if the real drag on performance isn’t technology — it’s coordination? Unproductive and unnecessary meetings cost companies up to $1.4 trillion every year. Seventy-one percent of senior leaders say meetings are inefficient. The average knowledge worker now spends around 11 hours a week in meetings. And nearly half admit to faking excuses to avoid them. This isn’t a scheduling issue. It’s a systems issue. Dr. Rebecca Hinds — founder of the Work Innovation Lab at Asana, the Work AI Institute at Glean, and author of YOUR BEST MEETING EVER: 7 Principles for Designing Meetings That Get Things Done — argues that meetings are organizational “junk drawers.” Instead of asking whether a meeting is necessary, companies simply default to adding another recurring invite. Her solution is radical in its simplicity: treat meetings like products. Define the user. Clarify the outcome. Design the experience. Measure performance. Iterate. In this episode, we zoom out beyond tactics and ask deeper questions: Why are humans so inefficient at coordinating with one another?  What do broken meetings reveal about incentives, trust, and accountability?  Does AI meaningfully solve meeting dysfunction — or simply automate it?  And in a world pushing toward automation, what is the human role in collaboration? If coordination is broken, no productivity tool can save us. And if meetings are the canary in the coal mine, we should probably pay attention.

    27分

  5. 4月14日

    The Science of Disagreeing Better (ft. author Julia Minson)

    Send us Fan Mail We live in a moment where disagreement feels dangerous. Politics is polarized. Social media amplifies outrage. Inside companies, dissent is often muted — not because people agree, but because they assume speaking up will damage relationships or reputations. But what if most of that fear is wrong? Julia Minson, decision scientist at Harvard Kennedy School, studies the psychology of disagreement. Her research on “conversational receptiveness” reveals something counterintuitive: people systematically overestimate how much disagreement will harm a relationship and underestimate how much thoughtful dissent earns respect. That miscalculation has consequences. When leaders avoid disagreement, bad ideas survive. When teams confuse persuasion with understanding, trust erodes. When we treat conflict as a character flaw rather than a cognitive process, we weaken our institutions. In this episode, we explore why humans are wired to assume they’re objectively right, how subtle language shifts can dramatically increase receptiveness, and why polarization may be less about ideology and more about judgment errors. And in an era where AI systems increasingly summarize, mediate, and even “assist” in conflict, what happens if our tools inherit our biases? And if healthy disagreement is essential to good decision-making, how do we preserve it inside organizations that prize alignment over friction? This isn’t a conversation about compromise. It’s about whether we still know how to disagree in ways that make us smarter.

    27分

  6. 3月31日

    The Workforce Is *Not* AI-Ready (ft. Ben Tasker, AI education leader)

    Send us Fan Mail Everyone says they’re “AI-first.” Very few organizations are AI-ready. In this episode of FUTUREPROOF., we sit down with Ben Tasker, who is leading one of the largest workforce-scale AI education efforts in the public utility sector — upskilling 36,000 employees while advising global organizations on certification and governance. Ben calls this moment the “AI Between Times.” The tools are evolving rapidly, but the AI-driven economy they promise hasn’t fully stabilized. That gap creates risk — and opportunity. We unpack what actually breaks when companies try to move beyond pilot projects: Why buying AI tools is easy — and building internal capability isn’tThe tension between augmentation and displacementWhat the 70/30 rule means in cost-constrained environmentsWhy governance must precede implementationAnd how AI fluency is quietly becoming a new form of institutional powerBen argues that AI strategy lives or dies at the human level. Not because technology isn’t powerful, but because incentives, culture, and leadership determine whether that power compounds or fractures an organization. This conversation isn’t about hype cycles. It’s about whether institutions can transform fast enough — without breaking trust in the process. Because the future of work won’t be defined by who bought the best tools. It will be defined by who prepared their people.

    23分

  7. 3月26日

    The Storytelling Revolution: Why Humanity's Earliest Innovation Still Matters (ft. author Kevin Ashton)

    Send us Fan Mail In this episode of FUTUREPROOF., we sit down with Kevin Ashton—the technologist who coined the term Internet of Things and helped usher in the smartphone era—to talk about something even more foundational than AI. Stories. In his new book, The Story of Stories, Kevin traces a million-year arc—from the first fires where early humans gathered, to the invention of writing and printing, to electricity, electronics, and the smartphone. His thesis is provocative: language did not create stories. Stories created language. Every major storytelling revolution has followed a simple pattern: it increases the number of people who can tell stories—and the number of people who can hear them. For the first time in history, anyone can tell stories to everyone. But there’s a catch. While AI cannot understand meaning, algorithms now determine which stories we see, amplifying bias, shaping belief, and influencing behavior at scale. The power of storytelling has never been more democratized—or more intermediated. We explore:  Why storytelling is innate, not cultural  The eight great revolutions of human communication  Why machines can generate content but not meaning  The risks of algorithmic amplification  The role of critical thinking in a post-scarcity information world  Whether the next storytelling revolution is technological—or cognitive This conversation isn’t about nostalgia.  It’s about understanding the oldest human technology in a moment when the newest one is accelerating everything. If we think in stories—and we always will—the question becomes:  Who shapes the stories that shape us?

    24分

  8. 3月10日

    GLP-1s, AI, and the New Health Economy (ft. Rajiv Leventhal, health analyst)

    Send us Fan Mail Healthcare is colliding with technology faster than most people realize. In this episode of FUTUREPROOF., I sit down with analyst Rajiv Leventhal, who covers the intersection of healthcare, pharma, and tech, to unpack three forces reshaping the system at once: AI, GLP-1 weight loss drugs, and the mental health impact of digital life. We start with AI as a health tool. Nearly a quarter of ChatGPT’s global weekly users now use it for health-related prompts. That’s not a niche behavior. It’s a mainstream one. The question isn’t whether people will turn to AI for medical guidance. They already are. The real tension is trust and liability. General-purpose AI tools aren’t bound by HIPAA in the same way healthcare providers are. Yet they’re increasingly acting as digital concierges — answering late-night pediatric questions, explaining lab results, and helping people prepare for appointments in a system where access is strained. And that system is strained. Even in major cities, patients can wait months — sometimes a year — to see specialists. When access gaps widen, alternative tools step in. AI isn’t replacing doctors. It’s filling holes. We then turn to GLP-1 drugs and the weight-loss explosion. What began as diabetes treatment became a cultural and commercial wave driven by social media, FDA approvals, and aggressive advertising. But beneath the surface is a regulatory gray market of compounded versions, patent battles, and telehealth platforms monetizing demand. Finally, we tackle social media’s impact on mental health. The evidence linking heavy use — especially among teens — to anxiety and depression is growing, even if causation remains complex. Is this a regulation problem? A parental problem? A public health issue? Or another example of technology moving faster than governance? This episode isn’t about hype. It’s about what happens when broken systems create openings — and tech companies move into the space. Because when trust erodes and access declines, people don’t wait. They improvise.

    27分
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番組について

Welcome to FUTUREPROOF. We're the podcast that delves into the future. From Augmented Reality to Artificial Intelligence to Smart Cities to Internet of Things to Virtual Reality, we speak with some of the sharpest minds to better help you understand what the next few years may look like.Brought to you by author Jeremy Goldman (Going Social, Getting to Like).For booking inquiries: vie@futureproofshow.com

情報

  • クリエイター
    Jeremy Goldman
  • 配信期間
    17年 - 26年
  • エピソード
    30
  • 制限指定
    不適切な内容を含まない
  • Copyright
    © 2026 FUTUREPROOF.
  • 番組のWebサイト
    FUTUREPROOF.

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