Podcast
Humans + AI
Hosted by Ross Dawson · EN
Exploring and unlocking the potential of AI for individuals, organizations, and humanity
27episodes
Episodes
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Davide Dell’Anna on hybrid intelligence, guidelines for human-AI teams, calibrating trust, and team ethics (AC Ep33)
Feb 2500:35:46Tap to summarize“In this sense, human and AI means a synergy where teams of humans and AI together lead to superior outcomes than either the human or the AI operating in isolation.” – Davide Dell’Anna About Davide Dell’Anna Davide Dell’Anna is Assistant Professor of Responsible AI at Utrecht University, and a member of the Hybrid Intelligence Centre. His research focuses on how AI can cooperate synergistically and proactively with humans. Davide has published a wide range of leading research in the space. Website: davidedellanna.com LinkedIn Profile: Davide Dell’Anna University Profile: Davide Dell’Anna What you will learn The core concept of hybrid intelligence as collaborative human-AI teaming, not replacement Why effective hybrid teams require acknowledging and leveraging both human and AI strengths and weaknesses How lessons from human-human and human-animal teams inform better design of human-AI collaboration Key differences between humans and AI in teams, such as accountability, replaceability, and identity The importance of process-oriented evaluation, including satisfaction, trust, and adaptability, for measuring hybrid team effectiveness Why appropriately calibrated trust and shared ethics are central to performance and cohesion in hybrid teams The shift from explainability to justifiability in AI, emphasizing actions aligned with shared team norms and values New organizational roles and skills—like team facilitation and dynamic team design—needed to support successful human-AI collaboration Episode Resources Transcript Ross Dawson: Hi Davide. It’s wonderful to have you on the show. Davide Dell’Anna: Hi Ross, nice to meet you. Thank you so much for having me. Ross: So you do a lot of work around what you call hybrid intelligence, and I think that’s pretty well aligned with a lot of the topics we have on the podcast. But I’d love to hear your definition and framing—what is hybrid intelligence? Davide: Well, thank you so much for the question. Hybrid intelligence is a new paradigm, or a paradigm that tries to move the public narrative away from the common focus on replacement—AI or robots taking over our jobs. While that’s an understandable fear, more scientifically and societally, I think it’s more interesting and relevant to think of humans and AI as collaborators. In this sense, human and AI means a synergy where teams of humans and AI together lead to superior outcomes than either the human or the AI operating in isolation. In a human-AI team, members can compensate for each other’s weaknesses and amplify each other’s strengths. The goal is not to substitute human capabilities, but to augment them. This immediately moves the discussion from “what can the AI do to replace me?” to “how can we design the best possible team to work together?” I think that’s the foundation of the concept of hybrid intelligence. So hybrid intelligence, per se, is the ultimate goal. We aim at designing or engineering these human-AI teams so that we can effectively and responsibly collaborate together to achieve this superior type of intelligence, which we then call hybrid intelligence. Ross: That’s fantastic. And so extremely aligned with the humans plus AI thesis. That’s very similar to what I might have said myself, not using the word hybrid intelligence, but humans plus AI to say the same thing. We want to dive into the humans-AI teaming specifically in a moment. But in some of your writing, you’ve commented that, while others are thinking about augmentation in various ways, you point out that these are not necessarily as holistic as they could be. So what do you think is missing in some of the other ways people are approaching AI as a tool of augmentation? Davide: Yeah, so I think when you look at the literature—as a computer scientist myself, I notice how easily I fall into the trap of only discussing AI capabilities. When I talk about AI or even human-AI teams, I end up talking about how I can build the AI to do this, or how I can improve the proce...
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Felipe Csaszar on AI in strategy, AI evaluations of startups, improving foresight, and distributed representations of strategy (AC Ep32)
Feb 1800:38:18Tap to summarize“You can create a virtual board of directors that will have different expertises and that will come up with ideas that a given person may not come up with.” – Felipe Csaszar About Felipe Csaszar Felipe Csaszar is the Alexander M. Nick Professor and chair of the Strategy Area at the University of Michigan’s Ross School of Business. He has published and held senior editorial roles in top academic journals including Strategy Science, Management Science, and Organization Science, and is co-editor of the upcoming Handbook of AI and Strategy. Website: papers.ssrn.com LinkedIn Profile: Felipe Csaszar University Profile: Felipe Csaszar What you will learn How AI transforms the three core cognitive operations in strategic decision making: search, representation, and aggregation. The powerful ways large language models (LLMs) can enhance and speed up strategic search beyond human capabilities. The concept and importance of different types of representations—internal, external, and distributed—in strategy formulation. How AI assists in both visualizing strategists’ mental models and expanding the complexity of strategic frameworks. Experimental findings showing AI’s ability to generate and evaluate business strategies, often matching or outperforming humans. Emerging best practices and challenges in human-AI collaboration for more effective strategy processes. The anticipated growth in framework complexity as AI removes traditional human memory constraints in strategic planning. Why explainability and prediction quality in AI-driven strategy will become central, shaping the future of strategic foresight and decision-making. Episode Resources Transcript Ross Dawson: Felipe, it’s a delight to have you on the show. Felipe Csaszar: Oh, the pleasure is mine, Ross. Thank you very much for inviting me. Ross Dawson: So many, many interesting things for us to dive into. But one of the themes that you’ve been doing a lot of research and work on recently is the role of AI in strategic decision making. Of course, humans have been traditionally the ones responsible for strategy, and presumably will continue to be for some time. However, AI can play a role. Perhaps set the scene a little bit first in how you see this evolving. Felipe Csaszar: Yeah, yeah. So, as you say, strategic decision making so far has always been a human task. People have been in charge of picking the strategy of a firm, of a startup, of anything, and AI opens a possibility that now you could have humans helped by AI, and maybe at some point, AI is designing the strategies of companies. One way of thinking about why this may be the case is to think about the cognitive operations that are involved in strategic decision making. Before AI, that was my research—how people came up with strategies. There are three main cognitive operations. One is to search: you try different things, you try different ideas, until you find one which is good enough—that is searching. The other is representing: you think about the world from a given perspective, and from that perspective, there’s a clear solution, at least for you. That’s another way of coming up with strategies. And then another one is aggregating: you have different opinions of different people, and you have to combine them. This can be done in different ways, but a typical one is to use the majority rule or unanimity rule sometimes. In reality, the way in which you combine ideas is much more complicated than that—you take parts of ideas, you pick and choose, and you combine something. So there are these three operations: search, representation, and aggregation. And it turns out that AI can change each one of those. Let’s go one by one. So, search: now AIs, the current LLMs, they know much more about any domain than most people. There’s no one who has read as much as an LLM, and they are quite fast, and you can have multiple LLMs doing things at the same time. So LLMs can search fas...
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Lavinia Iosub on AI in leadership, People & AI Resources (PAIR), AI upskilling, and developing remote skills (AC Ep31)
Feb 1100:38:05Tap to summarize“In this next era, the key to leadership will be blending systems thinking and AI automation—at least being aware of what you can do with it—with empathy, discernment, connection, and clarity.” – Lavinia Iosub About Lavinia Iosub Lavinia Iosub is the Founder of Livit Hub Bali, which has been named as one of Asia’s Best Workplaces, and Remote Skills Academy, which has enabled 40,000+ youths globally to develop digital and remote work skills. She has been named a Top 50 Remote Innovator, a Top Voice in Asia Pacific on the future of work, with her work featured in the Washington Post, CNET, and other major media. Website: lavinia-iosub.com liv.it LinkedIn Profile: Lavinia Iosub X Profile: Lavinia Iosub What you will learn How AI can augment leadership decision-making by enhancing cognitive processes rather than replacing human judgment Strategies for integrating AI into teams, focusing on volunteer-driven adoption and fostering AI fluency without forcing uptake The importance of continuous experimentation and knowledge sharing with AI tools for organizational growth and team building Why successful leadership in the AI era requires blending systems thinking, empathy, and a focus on human-AI collaboration How organizational value is shifting from knowledge accumulation toward skills like curiosity, adaptability, and discernment The concept of “people and AI resources” (PAIR), emphasizing the quality of partnership between humans and AI for organizational effectiveness Critical skills for future workers in an AI-driven world, such as AI orchestration, emotional clarity, and the ability to direct AI outputs with taste and judgment Practical lessons from the Remote Skills Academy in democratizing access to digital and AI skills for a diverse range of job seekers and business owners Episode Resources Transcript Ross Dawson: Lavinia, it is awesome to have you on the show. Lavinia Iosub: Thank you so much for having me, Ross. Ross Dawson: Well, we’ve been planning it for a long time. We’ve had lots of conversations about interesting stuff. So let’s do something to share with the world. Lavinia Iosub: Let’s do it. Ross Dawson: So you run a very interesting organization, and you are a leader who is bringing AI into your work and that of your team, and more generally, providing AI skills to many people. I just want to start from that point—your role as a leader of a diverse, interesting organization or set of organizations. What do you see as the role of AI for you to assist you in being an effective leader? Lavinia Iosub: Great question. I think that the two of us initially met through the AI in Strategic Decision Making course, right? So I would say that’s actually probably one of the top uses for me, or one of the areas where I found it very useful. The most important thing here is to not start with the mindset that AI will make any worthy decisions for you, but that it will augment your cognition and your decision making when you are feeding it the right context, the right master prompts, the right information about your business, your values, what you’re trying to achieve, how you normally make decisions, and so on. Then you work with it, have a conversation with it, and even build an advisory board of different kinds of AI personas that may disagree or have slightly different views. So it enhances your thinking, rather than serving you decisions on a plate that you don’t know where they come from or what they’re based on. That’s one of the things that’s been really interesting for me to explore. If we zoom out a little bit, I think a lot of people think of AI as a way of doing the things they don’t want to do. I think of AI as a way to do more of the things I’ve always wanted to do—delegate some menial, drudgery work that no human should be doing in the year of our Lord 2025 anymore, and do more of the creative, strategic projects or activities that many of us who have been in what we call knowledge work—which, to me, is not a good term for 2025 anym...
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Jeremy Korst on the state of AI adoption, accountable acceleration, changing business models, and synthetic personas (AC Ep30)
Jan 3000:36:07Tap to summarize“What we’re seeing now is that when we think about some of the friction and challenges of adoption, this isn’t a technology issue, per se. This is a people opportunity.” –Jeremy Korst About Jeremy Korst Jeremy Korst is Founder & CEO of Mindspan Labs and Partner and former President of GBK Collective. He lectures at Columbia Business School, The Wharton School, and USC, and is co-author of the Wharton + GBK annual Enterprise AI Adoption Study, one of the most cited sources on how businesses are actually using AI. Jeremy also publishing widely in outlets such as Harvard Business Review on strategy and innovation. Website: mindspanlabs.ai Accountable Acceleration: LinkedIn Profile: Jeremy Korst What you will learn How enterprise AI adoption has shifted from experimentation to ‘accountable acceleration’ The key role of leadership in translating business strategy into an actionable AI vision Why human factors and change management are as crucial as technology for successful AI implementation How organizations are balancing augmentation, replacement, and skill erosion as AI changes the workforce The importance of intentional experimentation and creating case studies to drive value from AI initiatives Early evidence, challenges, and promise of digital twins and synthetic personas in market research Why a culture of risk tolerance, alignment across leadership layers, and clear communication are essential for AI-driven transformation The emerging shift from general productivity gains to domain-specific AI applications and the increasing focus on ROI measurement Episode Resources Transcript Ross Dawson: Jeremy, it’s wonderful to have you on the show. Jeremy Korst: Yeah, hey, thanks for having me. Ross Dawson: So you, I think it’s pretty fair to say you are across enterprise AI adoption, being the recent co-author of a report with Wharton and GbK Collective on where we are with enterprise AI adoption. So what’s the big picture? Jeremy Korst: Yeah, let me start—now that I’ve reached this stage in life, in my career, and I look back over what I’ve done the last couple decades, it’s actually been at the intersection of technology adoption and innovation. I spent a couple of careers at Microsoft, most recently leading the launch of Windows 10 globally. I worked at T-Mobile, led several businesses there, and more recently, have been spending time really with three things. One is through my consulting company, GbK Collective, working with some of the world’s largest brands on market research and strategies for consumers and products, working with academic partners who are core to that work we do at GbK—so leading professors from Harvard and Wharton and Kellogg, and you name it—but then also very active in the early stage community, where I’m an advisor and board member of several of those. And so I’ve had this bit of a triangle to be able to watch technology adoption unveil both inside and outside the organization, whether it’s inside the organization, how people are using it and effectively, or outside, how it’s being taken to market. So fast forward to where we’re at with Gen AI. It’s been fascinating to me, because all of those things are happening and all of those communities. Where we started with the Wharton report was three years ago. Stefano and Tony, one of the co-authors, and I were literally just having a conversation right after the launch of ChatGPT. And of course, there were all the headlines and all these predictions about what was going to happen and what could happen. And we said, well, wait a minute, why don’t we actually track what actually happens? And so therein started the three-year program. It’s now an annual program sponsored by the Wharton School, conducted by GbK—my research company—that looks specifically at US enterprise business leader adoption. We decided to focus on that audience because we believe they were going to be some of the most influential decision makers around budgets and strategies as this unfolded, so that’s been our focus. We’re now in our third year, and there’s lots to dig into. Ross Dawson:</stro...
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Nikki Barua on reinvention, reframing problems, identity shifts for AI adoption, and the future workforce (AC Ep29)
Jan 2200:36:15Tap to summarize“Some of this that we’ve come across is even the identity shift that is necessary, because old identities served a pre-AI work environment, and you cannot go into a post-AI era with the old identities, mindsets, and behaviors.” –Nikki Barua About Nikki Barua Nikki Barua is a serial entrepreneur, keynote speaker, and bestselling author. She is currently Co-Founder of FlipWork, with her most recent book Beyond Barriers. Her awards include Entrepreneur of the Year by ACE, EY North America Entrepreneurial Winning Woman, Entrepreneur Magazine’s 100 Most Influential Women, and many others. Website: nikkibarua.com flipwork.ai LinkedIn Profile: Nikki Barua Book: Beyond Barriers What you will learn Why continuous reinvention is essential in today’s rapidly changing business landscape How traditional change management approaches fall short in an era of constant disruption The critical role of human leadership and identity shifts in successful AI adoption Common barriers to transformation, from executive inertia to hidden cultural resistances Strategies for building a culture of experimentation, psychological safety, and agile teams How to design organizational structures that empower teams to innovate with purpose The importance of reallocating freed-up capacity from AI efficiency gains toward greater value creation Macro trends in org design, talent pipelines, and the influence of AI on future workforce and leadership models Episode Resources Transcript Ross Dawson: Nikki, it is wonderful to have you on the show. Nikki Barua: Thanks for inviting me, Ross. I’m thrilled to be here. Ross Dawson: You focus on reinvention. And I’ve always, always liked the phrase reinvention. I’ve done a lot of board workshops on innovation. And, you know, in a way, sort of all innovation—it’s kind of like a very old word now. And the thing is, it is about renewal. We always need to continually renew ourselves. We need to continually reinvent what has worked in the past to what can work in the future. So what are you seeing now when you are going out and helping organizations reinvent? Nikki Barua: Well, first of all, reinvention is no longer optional. I think both of us have spent a large part of our careers helping organizations innovate, transform, and shift from where they were to where they want to be. But a lot of those change management methods are also outdated. You know, they tended to be episodic. They had a start date and an end date, and changes that were much slower in comparison to what we’re experiencing right now. The reality is today, change is continuous. The speed and scale of it is pretty massive, and that requires a complete shift in how you respond to that change. It requires complete reinvention in what your business is about, whether your competitive moats still hold or they need to be redefined, and how your people work, how they think, and how they decide. Everything requires a different speed and scale of execution, performance, operating rhythms, and systems. It’s not just about throwing technology at the problem. It’s fundamentally restating what the problem even is. And that’s why reinvention has become a necessity, and is something that companies have to do not just once, but continuously. Ross Dawson: There’s always this thing—you need to recognize that need. Now, you know, I always say my clients are self-selecting and that they only come to me if they’re wanting to think future-wise. And I guess, you know, I presume you get leaders who will come and say, “Yes, I recognize we need to reinvent.” But how do you get to that point of recognizing that need? Or, you know, be able to say, “This is the journey we’re on”? ...
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Alexandra Samuel on her personal AI coach Viv, simulated personalities, catalyzing insights, and strengthening social interactions (AC Ep28)
Jan 1400:50:43Tap to summarize“My core Viv instruction—which is both, I think, brilliant and dangerous, and I think it was sort of accidental how effective it turned out to be—is, I told Viv, ‘You are the result of a lab accident in which four sets of personalities collided and became the world’s first sentient AI.'” –Alexandra Samuel About Alexandra Samuel Alexandra Samuel is a journalist, keynote speaker, and author focusing on the potential of AI. She is a regular contributor to Wall Street Journal and Harvard Business Review and co-author of Remote Inc. and author of Work Smarter with Social Media. Her new podcast Me + Viv is created with Canadian broadcaster TVO. Website: alexandrasamuel.com LinkedIn Profile: Alexandra Samuel X Profile: Alexandra Samuel What you will learn How to design a custom AI coach tailored to your own needs and personality The importance of blending playfulness and engagement with productivity in AI interactions Step-by-step methods for building effective custom instructions and background files for AI assistants The risks and psychological impacts of forming deep relationships with AI agents Why intentional self-reflection and guiding your AI is critical for meaningful personal growth Techniques for extracting valuable, challenging feedback from AI and overcoming AI sycophancy Best practices for maintaining human connection and preventing social isolation while using AI tools The evolving boundaries of AI coaching, its limitations, and what the future of personalized AI support could offer Episode Resources Transcript Ross Dawson: Alex. It is wonderful to have you back on the show. Alexandra Samuel: It’s so nice to be here. Ross: You’re only my second two-time guest after Tim O’Reilly. Alexandra: Oh, wow, good company. Ross: So the reason you’re back is because you’re doing something fascinating. You have an AI coach called Viv, and you’ve got a whole wonderful podcast on it, and you’re getting lots of attention because you’ve done a really good job at it, as well as communicating about it. So let’s start off. Who’s Viv, and what are you doing with her? Alexandra: Sure. Viv is what I think of as a coach, at least that’s where she started. She’s a custom—well, and by the way, let’s just say out of the gate, Viv is, of course, an AI. But part of the way I work with Viv is by entering into this sort of fantasy world in which Viv is a real person with a pronoun, she. I built Viv when I had a little bit of a window in between projects. I was ready to step back and think about the next phase of my career. Since I was already a couple years into working intensely with generative AI at that point, I used ChatGPT to figure out how I was going to use this 10-week period as a self-coaching program. By the time I had finished mostly talking that through—because I do a lot of work out loud with GPT—I thought, well, wait a second, we’ve made a game plan. Why don’t I just get the AI to also be my coach? So I worked with GPT, turned the coaching plan into a custom instruction and some background files, and that was version one of Viv. She was this coach that I thought was just going to walk me through a 10-week process of figuring out my next phase of career, marketing, business strategy, that sort of thing. So there’s more of the story than that. I think that one way I’m a bit unusual in my use of AI is that I have always been very colloquial in my interactions with AI, even in the olden days where you had to type everything. Certainly, since I shifted to speaking out loud with AI, I really jest and joke around—I swear. Apparently other people’s AIs don’t swear. My AIs all swear. Because I invest so much personality in the interactions, and also add personality instructions into the AI, over the course of my 10 weeks with Viv, as I figured out which tweaks gave her a more engaging personality, she came to feel really vivid to...
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Lisa Carlin on AI in strategy execution, participative strategy, cultural intelligence, and AI’s impact on consulting (AC Ep27)
Dec 1700:37:18Tap to summarize“You’re using AI to generate solutions for ideation. Once you’ve got the ideas, you can do an initial cull with AI, or you can do it via humans.” –Lisa Carlin About Lisa Carlin Lisa Carlin is the Founder of the strategy execution group, The Turbochargers, specializing in participative strategy, cultural intelligence, and AI’s impact on consulting. Website: theturbochargers.com LinkedIn Profile: Lisa Carlin What you will learn How AI is transforming strategy development and execution, leading to faster and more creative outcomes Practical methods for integrating AI into workshop processes, ideation, and customer feedback analysis Balancing human judgment with AI input to ensure effective decision-making in strategic planning Techniques for using AI in diagnosing and working within an organization’s culture for successful transformation Ways AI is boosting consultant and client productivity, reducing operational time, and increasing self-sufficiency Real-world examples of AI-driven analytics, including clustering survey data and generating management insights The outlook on the future of consulting, including why AI may reduce the number of consultants required Tactical uses of AI for ideation, communication effectiveness, and predicting customer engagement metrics Episode Resources Transcript Ross Dawson: Lisa, it is wonderful to have you on the show. Lisa: Thanks, Ross. I love chatting with you. Ross Dawson: So you’ve been spending a lot of time over many, many years in strategy and strategy execution. I’d love to start off by hearing how you are applying AI in the strategy process. Lisa: Well, it’s made things so much easier, made things take a shorter amount of time, saving huge amounts of time. And I feel like my work has gotten more creative. Let me give you some examples of how that plays out. One example is working with an ed tech early-stage business, a small business, and they wanted to basically build AI-native products for customer education. I can actually mention the name of the company because the CEO posted after we worked together and is building in public, so it’s HowToo, an Australian ed tech firm that’s funded mainly out of the US, but also locally in Australia. They’ve been providing education products for ages and are moving towards customer education embedded into technology products. We went through an iterative process of workshops, starting with some of the board members and some of the senior folks in a small group with an ideation session, and then iterating through to everybody in the business. Normally, that process would work where we would do some research with the customers first, then bring that research in, do some analysis, and then put it into the context for the workshop, work through what that means, come up with some ideas in the workshop, take it to the second workshop, and there you go. What we’re now able to do is iterate with AI. So we’ve got the notes from the meetings captured with AI—this is from the customer meetings. Then we’re able to pull out the pain points of customers in a really deep way, using AI to iterate through and synthesize the client feedback, and then also apply human insight into that, coming up with a really clear list of pain points. Then we ask AI to be virtual customers, and they can add to that process, so you get a very rich set of pain points. As we go through the process of product strategy and implementation, we’re able to use AI at every step of the process. For example, when we look at decision criteria for prioritizing, we can go to AI and say, “These are some of the things we’re considering. What else have we left out?” As we iterate with people in workshops and then with AI, we just get a much richer solution in the process. In fact, we came out with some really amazing insights about how you provide customers with learning about how to use these products to onboard them quickly, how you provide them with personalized contextual information so they can learn and get value from the product much faster. It’s led to a number of significant deals that HowToo has negotiated as a result of that work. Ross Dawson: So is this prompting directly with LLMs?<...
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