Podcast
Humans + AI
Hosted by Ross Dawson · EN
Exploring and unlocking the potential of AI for individuals, organizations, and humanity
22episodes
Episodes
Newest firstAll episodes
Daniel Fallmann on democratizing expertise, dynamic interfaces, judgment amplification, and organizational intelligence (AC Ep48)
1w ago00:27:00Tap to summarizeIn this episode, Mindbreeze CEO Daniel Fallmann explores the evolution of AI from automation to the augmentation of human expertise, focusing on how organizations can leverage agentic workflows, context-aware decision support, and collective intelligence. Listeners will learn strategies for balancing human judgment and AI in complex decisions, how connecting distributed knowledge across organizational silos empowers better outcomes, and the importance of explainability and traceable audit trails. Gain insights into judgment amplification, enterprise simulations, and the future of end-to-end agentic AI for informed, transparent decision making.
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Natalie Buda Smith on AI in libraries, human at the center, deeper storytelling, and language recreation (AC Ep47)
2w ago00:33:57Tap to summarizeJoin Natalie Buda Smith, Director of AI at the Library of Congress, as she explores how digital interfaces and AI are revolutionizing access to human knowledge and cultural memory. In this episode, you'll learn about the shift from primary source access to information intermediated by AI, the importance of preserving historical context through multiple digitization versions, and the challenges of navigating proprietary data and open APIs. Natalie Buda Smith shares firsthand insights into empowering staff with AI tools, fostering personalized information delivery, and how collaborative, AI-powered projects are surfacing new connections and creative storytelling across diverse collections.
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Scott Wolfson on cognitive fitness, System 3 thinking, mastery skill games, and Strategic Imagination Machines (AC Ep46)
3w ago00:35:41Tap to summarizeIn this episode, CentaurianAI Co-Founder shares how becoming 'unbottable' is essential in the age of AI and explores the Centaur chess mindset for thriving alongside intelligent machines. Listeners will discover practical techniques—like brain dumping, ignorance mapping, and the 'think, prompt, check' approach—to boost cognitive fitness, foster independent thinking, and future-proof their unique value. The conversation delves into mastery skill games, motivational intelligence, and the power of collective, connected intelligence for building a truly wisdom-driven future with AI.
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Hala Nelson on human machine coexistence, ontology first, AI driven digital twins, and bidirectional connections to reality (AC Ep45)
Jun 300:32:26Tap to summarizeExplore how AI is redefining the boundaries between uniquely human intelligence and machine capabilities, and discover which aspects of intelligence remain distinctly human. This episode delves into building smarter, more efficient organizations by leveraging the complementary strengths of people and AI—focusing on the critical role of an ontology-first approach, knowledge graphs, and live digital twins in digital transformation. Listeners will gain actionable insights into integrating dynamic processes for real-time decision-making, structuring enterprise knowledge, and eliminating organizational inefficiencies using practical, AI-powered solutions.
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Ross Dawson on cognitive friction, beyond Human-in-the-loop, and AI-augmented strategy (AC Ep44)
May 2700:17:48Tap to summarize“The value is created in the friction, in the engagement between humans and AI—the pushing back by the humans, the pushing back by the machines.” –Ross Dawson About Ross Dawson Ross Dawson is a futurist, keynote speaker, strategy advisor, author, and host of Amplifying Cognition podcast. He is Chairman of the Advanced Human Technologies group of companies and Founder of Humans + AI startup Informivity. He has delivered keynote speeches and strategy workshops in 33 countries and is the bestselling author of 5 books, most recently Thriving on Overload. Website: rossdawson.com LinkedIn Profile: Ross Dawson What you will learn The dangers of aiming for a frictionless experience between humans and AI Why meaningful engagement—rather than passive approval—between humans and AI is crucial for cognitive augmentation How human judgment and reasoning differ, and where AI excels versus where humans add irreplaceable value The four key pitfalls of the traditional ‘human in the loop’ approach to decision-making with AI Why too much delegation to AI can erode human vigilance, judgment, and accountability The importance of adversarial, not just assistive, collaboration with AI for complex, high-stakes tasks How ‘living strategy’—AI-augmented, continuously updated organizational strategy—addresses the limitations of static strategic planning The role of AI in surfacing diverse perspectives, supporting dialogue, and enabling truly adaptive decision-making Episode Resources Transcript Ross Dawson: I love speaking to the wonderful guests I have on my podcast. I always learn an enormous amount, but in this episode, I’ll share a little bit of an update for myself and delve into a few interesting things I’ve been seeing and doing lately, including some of the most interesting research papers I’ve seen on humans plus AI lately, looking at human in the loop and the ways in which we should be thinking about that, and AI and strategy. So, just a quick scan of what’s going on in humans plus AI. I’ve been traveling quite a bit, doing a lot of keynotes as much as possible on humans plus AI, and the resonance around the theme is really rising very rapidly. In fact, somebody recently mentioned that humans plus AI was a cliché, or just overworn at the moment. Since I first started using the phrase three and a half years ago, I think it’s wonderful that now it is gaining a lot of currency. People are talking about it, framing that. Yes, some phrases outlive their usefulness, but I think I’ll stick with humans plus AI for the foreseeable future. The research papers I’ve been looking at are focused on essentially cognitive augmentation and erosion, and that’s this critical domain where it’s not really clear around whether, or in which circumstances, our cognition erodes, and what it is we can do to make it augmenting. One of the excellent papers is titled Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction. It’s a bit dense, but it has some great research and analysis in it. The key finding, which it begins with, is that in human-computer interface research literature over the last while, we saw that last year, 2025, there was a big, big rise in this idea of driving human sovereignty in how it is we interact with computers. However, since last year to the first part of this year, we’ve in fact seen that fall dramatically, where the human sovereignty paradigm is reducing dramatically, and we are seeing this big rise in what is called the frictionless paradigm, saying: how do we get as little friction as possible between humans and AI? There are a number of really important points made in the paper, and really, the starting point is saying that we should stop treating frictionless AI as the goal. If we start to be frictionless, that is starting to essentially take the human out of the loop. The nature of humans is that we need to engage, we need to think, so we need to start building devil’s advocate agents into the systems and to aim for this thing where we start to have both this high degree of engagement with the AI, but also high friction. That friction is where we are trying to, essentially, the more complex one rising, having more and more friction, and in lower frictions, it’s just more so. Label tasks, but where we’re not just showing the reasoning, giving people the ability to think through tasks and how they think about that, but ...
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Kathleen deLaski on reimagining higher education, generational mobility, building AI skills, and human originality (AC Ep43)
May 1300:38:36Tap to summarize“There’s a real ‘skillification’ movement where you just want to get the training you need when you need it.” –Kathleen deLaski About Kathleen deLaski Kathleen deLaski is the founder and board chair of Education Design Lab, which helps reimagine higher education. She is a senior advisor to Harvard’s Project on the Workforce and on the advisory board of the Taubman Center at the Harvard Kennedy School of Government. Kathleen is author of Who Needs College Anymore? Imagining a Future Where Degrees Won’t Matter. Website: whoneedscollegeanymore.org eddesignlab.org LinkedIn Profile: Kathleen deLaski What you will learn The evolving value of college degrees in a rapidly changing economy Who benefits most from higher education, including four key learner profiles The rise of ‘skillification’ and alternative pathways to career readiness How employers assess degrees and non-degree credentials in today’s job market The impact of AI on both education and workplace expectations Why AI literacy—and understanding its limits—matters for career success The growing divide between technical and non-technical learners regarding AI adoption Practical strategies for maximizing uniquely human skills—like originality and judgment—in an AI-powered world Episode Resources Transcript Ross Dawson: Kathleen, it’s a delight to have you on the show. Kathleen deLaski: Thanks for having me, Ross. Ross: So, amongst many other things to your name, you have a fairly recent book out called “Who Needs College Anymore?” So, does anyone need college anymore? Kathleen: Yes, the answer is yes. There are people who are looking to bash the notion of a three- or four-year university degree, but they need to look somewhere else. What I try to do in the book is serve two audiences. One is universities—what we call colleges in the US—who are actually in a state of panic right now about surveys showing that people are not valuing degrees anymore. It’s a perfect moment to reassess: what does a degree need to deliver as we approach the mid-21st century? That’s the hot topic, the debate that’s raging. To frame the question, “Who needs college anymore?” is to say, “Wow, you need to step up your value proposition in this age,” especially when, at least here, the number of 18-year-olds is dwindling and we have AI and technological solutions that allow people to get skills as needed. There’s a real ‘skillification’ movement where you just want to get the training you need when you need it. There’s also a questioning of hanging around to learn about the liberal arts, to do your philosophy, English, or history required classes—can’t we get right to the skills? That’s the debate that’s raging. So, colleges need to hear this message; that was one audience. Secondly, I know so many students—even in my own family—who are trying to parse the different messages they’re hearing. One message is, “You absolutely need a four-year degree if you want to get a ‘good job.'” The other message is, “College isn’t worth it anymore; you can just get the skills you need and get the job.” Meanwhile, families think the price tag is going up and up. Here, it’s staggering—although, in reality, universities in the US have actually begun to hold prices and even give a lot of discounts because they’re short on the number of folks coming through the door. So, all these confusing messages—I think families also need to understand who exactly, among different types of learners, does need a degree and who doesn’t. Which jobs, which age groups, which learning types? I actually walk through all those using a human-centered design approach. Ross: Human-centered is a good way to go. So I and others have talked about the unbundling of higher education, and there are a number of elements to that, including the educational processes, the social connections, sometimes the physical place, the links with employers and credentials. Of all the facets bundled together in a degree, the real focus, of course, is on the certification—you’...
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David Vivancos on the end of knowledge, cognitive flourishing, resilient societies, and artificial democracy (AC Ep42)
May 600:35:59Tap to summarize“Delegating knowledge is not the same as delegating wisdom. You learn by experience, and if you don’t have any experiences…you will get cognitive atrophy.” –David Vivancos About David Vivancos David Vivancos is an AI, data, and neuroscience serial entrepreneur, having cofounded five startups since 1995. He is a frequent keynote speaker and is the author of six books, including the Artificiology series. Website: vivancos.com LinkedIn Profile: David Vivancos What you will learn Why embracing advanced AI is crucial for human progress How shifting from digitization to automation and datification redefines value The evolving distinction between human-acquired and AI-generated knowledge How to avoid cognitive atrophy and actively exercise your mind alongside AI What cognitive flourishing means in a world of widespread AI augmentation Ways AI can transform and personalize education across all levels The importance of coexistence training as we prepare for AGI’s societal integration Why rethinking human identity, humility, and social structures is essential for a future with machine citizens Episode Resources Transcript Ross Dawson: David, it is wonderful to have you on the show. David Vivancos: Thank you very much, Ross. Glad to be here. Ross: So you have a more developed, or some would say, extreme view of the relative role of humans plus AI. I’d love to dig into where you think things are going, and how we can best respond. Perhaps the starting point is, you say that we should not be resisting or pushing back. We should fully embrace the shift towards very high levels of AI capability, or at some point, AGI. David: Yeah, that’s fully my point. I think we are in a moment in history where we are really building this technology that one day is not going to be a technology anymore. So, the sooner we start to embrace it, to teach it, and to be really in sync with what we are creating day by day, the better off we will be. So yes, my point of view is that we should embrace it. We should start building as soon as possible. We should fix most of the problems that humans have had over the last millennia, and some of these problems could be solved by using AI. So basically, our “fourth brain”—we have the three-part brain, but in reality, there’s only one brain—this fourth brain, AI, will help us solve all of these issues. So yes, it’s an opportunity. Ross: Yes. I mean, I think there’s always two sides—as in, every opportunity has a challenge, every challenge has an opportunity. So I always think we need to acknowledge challenges and focus on opportunities. I think we’ll get onto that in discussing some of the cognitive implications. You have a series of books which have really told the story over time around this. One of them was “Automate or Be Automated.” This idea of saying, well, there are things which machines, in the broader sense, can do in automating things. So, how would you frame that now, in terms of what it is that can be automated, and how do we position ourselves relative to that? Where do machines start to do what humans have done? David: Yep. I’ve been in this business of trying to build the impossible for the last 30-plus years. “Automate or Be Automated,” the book you mentioned, is from about six years ago. When I started creating and building technology, also about VR and many other things, about 30 years ago, the first companies were internet companies. Back then, what we did is what people now call digitization. But over the last 20–25 years, what we’ve mostly been doing is datification—gathering data and using that data for companies to grow and to understand what happens in the world. But over the last maybe 10 or 11 years, what I call the new golden age of AI, we are starting to build the capabilities to use that data to really build algorithms. Once we have that, we can start to automate, and with this automation, basically what we regain is time. I think time is our most precious asset, along with health and the people we love. Being able to stop doing these...
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Jon Husband on wirearchy, web weaving, the relational economy, and drift diving (AC Ep41)
Apr 2900:38:14Tap to summarize“What I’m really interested in and fascinated about is that, as AI penetrates and spreads throughout the workplace and gets placed into or integrated into workflows, the first thing that happens is that people in the mix are going to have to learn how to use AI and learn why to use AI when they do.” –Jon Husband About Jon Husband Jon Husband is the Founder and Principal of Wirearchy, a creative research and experimentation laboratory exploring the crossroads of AI and networked workplaces and society. He works as a coach, consultant, speaker and writer, and has co-authored three books, including Wirearchy. Website: wirearchy.com LinkedIn Profile: Jon Husband What you will learn The origins and evolution of wirearchy as a response to traditional organizational hierarchies How AI integration is reshaping knowledge work, workflows, and tacit knowledge within organizations The persistence of Taylorist job evaluation and why traditional work design remains resistant to change The rise of the relational economy and the increasing value of human judgment, trust, and relationships beyond financial exchange New approaches and tools for surfacing and mapping intangible or non-financial value exchanges in organizations The concept of emergence and the need to foster conditions for positive outcomes in complex adaptive systems Challenges and opportunities as organizations shift from rigid, control-based management to adaptive, networked, feedback-driven models Why coaching, facilitation, and skills like listening and allowing for emergence will be critical in navigating AI-augmented workplaces Episode Resources Transcript Ross Dawson: Jon, it is wonderful to have you on the show. Jon: Thank you very much, Ross, it’s good to see you again. Ross Dawson: We’ve known of each other and each other’s work for a very, very long time now from, I suppose, the roots of—yeah, I suppose you can crudely say—the intersection of knowledge and networks. So, as I think many of us who have come from that background, we now are thinking about humans and their relative role to AI. Some people will know of your wirearchy and a lot of your work of the past; others will not. So I’d love to just start off with: what is the concept of wirearchy? And then, how is that morphing or evolving, or are you building on that in how you’re thinking now? We’ll dig in and explore that. Jon: Okay, well, I started paying attention to knowledge work and work in organizations and so on as I changed careers in my early 30s, moving from banking, where I was in management, into management consulting. I ended up working for a large global HR consulting firm that, amongst several others—all the major consulting firms that address organizational issues—have services where they do what’s called job evaluation. What job evaluation does is put a size or a measure or a weight to a job, which then basically places it on the organization chart. I spent quite a few years writing thousands of job descriptions and helping streamline workflows and so on and so forth. So, when the internet came along, I had always been an avid reader, and I suppose a wannabe futurist—a wannabe Ross Dawson, if you will. I was reading all sorts of books back then. Instead of dating, because I was single in my mid-30s, I was spending Friday nights reading books about organizations, like “The Living Company” by Arie de Geus, the Tofflers’ work, “Powershift,” certainly Peter Drucker’s work. There was one day—well, I was reading all of these books, and all of the books were about the coming Information Age. The Information Age had not arrived yet; this was roughly late ’80s, early ’90s. All of a sudden, we hit 1994. I’m sitting in London, and I was just told by my team leader in my consulting firm that I was going to be proposed as one of the next global partners. Three weeks later, I quit my job in the consulting firm because I had begun to feel very uneasy about the work I was doing. If I was made a partner, your job becomes basically selling larger projects to keep the younger consultants employed. I realized that I would be selling methods that I had come to not believe in anymore, and the reason for that is that all of the job evaluation ...
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Michael Gebert on designing freedom, human self-determination, cognitive sovereignty, and systems of agency (AC Ep40)
Apr 2200:37:43Tap to summarize“Freedom no longer exists outside the systems, and it depends on the design. Coming back to the design, it’s about understanding that we need to distinguish between intelligent systems and agency.” –Dr Michael Gebert About Dr Michael Gebert Dr Michael Gebert is Chairman of the European Blockchain Association and co-founder of AI Expert Forum. He works at the intersection of artificial intelligence, digital sovereignty, and institutional responsibility. His book 2079 – Designing Freedom is just out. Website: 2079.life LinkedIn Profile: Dr Michael Gebert What you will learn How the concept of freedom extends beyond politics and economics to personal agency in an AI-driven world Why cognitive sovereignty is essential for maintaining individual responsibility and accountability as intelligent systems become more pervasive The shift from making decisions ourselves to designing the frameworks and conditions for decision-making with AI involvement How to distinguish optimization from true human empowerment when integrating AI tools into personal and organizational life Practical routines and metacognitive strategies for individuals to retain agency when collaborating with large language models and intelligent systems Why organizational leaders must prioritize cognitive sovereignty and human potential early in AI deployment, not just technical efficiency Insights into the challenges and importance of embedding frameworks for freedom and cognitive sovereignty within corporate, governmental, and policy structures The critical need for ambassadors of freedom within institutions to promote reflection, ongoing discussion, and the integration of responsible AI practices across all levels Episode Resources Transcript Ross Dawson: Michael. It is awesome to have you on the show. Michael Gebert: Hey, great to be on the show. Thanks for having me. Ross Dawson: So we connected first, probably around 15 years ago, and we were both involved in crowds, creating value from many people. And I think, you know, there’s one of the interesting points now is, I guess, you know, we still live in a world of many people. We’re trying to create collective value. AI is laid over that. So it’s interesting to see that journey from where we’ve come to where we are today. Michael Gebert: Absolutely, and I really remember visually when we first had contact about this very exciting topic of crowdsourcing and empowerment of the crowd, and really making people believe, not only in themselves, but really in communities. And therefore, not only strengths in terms of crowdfunding, crowd investing, their financial gains, but also being empowered in what they do. And this is a very fundamental, I would say, even a right for humanity to reflect on and do that. I think the methodology and technology back then helped a lot. And to be honest, I’m still partly involved in some of those efforts. Even the big crowdfunding platforms, also here in Europe and in Germany, are vital and really active. Of course, not in that dramatic media shift hype that we experienced, but they’re still there, and it proves that it’s a concept that should stay. Ross Dawson: Yep, absolutely. You know, there’s obviously collective intelligence, amongst other facets. But this goes to, I think, the frame of your new book, 2079, Designing Freedom. So freedom is an interesting word, and something which I hope we all aspire to. Michael Gebert: Yeah, you know, freedom, of course, is one of those very multifaceted words, right? It could be translated in a political context. It could be translated in an economic concept, meaning monetary-wise. It could be translated—and this is my translation—in a very personal, one-to-one reflection about how do I as a human being see myself in that surrounding, bombarded not only by information but by intelligent systems, basically AI as we describe them, and all that is behind those systems. Ross Dawson: So there’s a few things I want to dig into here. And I guess there’s another word there: designing. Obviously, at a societal infrastructure layer, we want to be able to design the systems whereby we can all individually have that f...
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Marshall Kirkpatrick on cognitive levers, combinatorial possibilities, symphonic thinking, and compound learning (AC Ep39)
Apr 800:39:41Tap to summarize“The technology we’re working with today really makes a lot of those best practices and mental models and the whole toolkit more accessible than ever to more people.” –Marshall Kirkpatrick About Marshall Kirkpatrick Marshall Kirkpatrick is founder of sustainabilty consultancy Earth Catalyst and AI thinking tool What’s Up With That. His many previous roles include founder of influence network analysis tool Little Bird, which was acquired by Sprinklr, where he was last Vice President Market Research. Website: whatsupwiththat.app LinkedIn Profile: Marshall Kirkpatrick What you will learn How generative AI transforms cognitive tools and lowers barriers to advanced thinking Techniques to combine human and AI-powered sensemaking for richer insights Practical strategies for filtering and extracting value from infinite information The importance and application of diverse mental models in modern decision-making Methods to balance manual cognitive work with AI assistance for optimal outcomes The role of adaptive interfaces in enhancing individual cognitive capacity Metacognitive approaches to networks and how AI can foster organizational awareness Ethical and societal implications of democratizing access to AI-powered cognitive enhancements Episode Resources Transcript Ross Dawson: Marshall, it is awesome to have you back on the show. Marshall Kirkpatrick: Oh, thank you, Ross. It’s such a pleasure to be reconnecting with you here. Thanks for having me on. Ross Dawson: So back you were very, very early on in the podcast when it was Thriving on Overload, and it was interviews with the book, and you got incorporated—some of the wonderful things you were doing in Thriving on Overload. So I think today, in this world of generative AI, which has transformed everything, including the way in which we think, the Thriving on Overload themes are still super, super relevant, and in a way, we need to be talking about them more. That theme at the time was finite cognition, infinite information. How do we work well with it? I don’t know if our cognition has become more finite, but the information has become more infinite, and there’s just more and more. But also, it cuts two ways, as in, what is the source of all the information? AI is also a tool. So anyway, let’s segue from some of your cognitive thinking tools, technology-enabled cognitive thinking tools and so on, which we looked at. So how do you—where are we? 2026, what do you think about human cognition in our current universe? Marshall Kirkpatrick: Well, especially when you frame it up in Thriving on Overload terms. I mean, those were four, five long years ago that we last spoke, and the book that came out of it was just fantastic. I think it has some timeless qualities, and I think that the technology we’re working with today really makes a lot of those best practices and mental models and the whole toolkit more accessible than ever to more people. That’s what I hope. I think that, yeah, between individuals and organizations, there’s so much that, historically, someone like you or me or the people closest in our networks were willing and able to do and excited to do, that many other people said, “That sounds like a lot of work.” The bar is lower now, because a lot of just the raw cognitive processing can be outsourced into a technology that serves as a lever. Ross Dawson: Well, I mean, that idea of levers for these cognitive tools is interesting. I guess, the very crude way of saying it is, we’ve got inputs into our human brain, and then we are processing information. I’m just thinking out loud a bit here, but it’s like, okay, we have tools to be able to filter, to present, to find what is most relevant, to present it to us in the ways which are most useful—very obvious, like summarization, visualization. Then as we are processing it ourselves, we have dialog, or we can have interlocutors who we can engage with and be able to refine and help our thinking. Does that sort of make sense, or how would you flesh that out? Marshall Kirkpatrick: Yeah, I mean, when you put it that way, i...
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