Read how I'm applying IA to my vocation
Imagine a long hallway of doors stretching out before you. Each door represents a choice, a challenge, or an opportunity. For Douglas Engelbart, the hallway wasn’t just a metaphor for life’s complexity—it was a call to action: how can we better navigate these choices? His answer, laid out in the "Mother of All Demos," was to create tools that augment human intelligence, enabling us to tackle complexity collaboratively. Today, as artificial intelligence (AI) dominates the conversation, Engelbart’s vision reminds us that the real promise lies not in replacing human intelligence but in augmenting it. How do our collective dispositions towards new computing paradigms change if we reframed AI to IA?
Whether you’ve heard the name Douglas Englebart or not you’ve most definitely been touched by his work. In 2018, various news, technology, and culture outlets, including Smithsonian and Wired, commemorated the 50th anniversary of what's come to be known as the "Mother of All Demos." On December 9, 1968, Douglas Engelbart and his team at the Augmentation Research Center (ARC) at the Stanford Research Institute (SRI) demonstrated a computer system that introduced concepts that set fundamental elements of modern personal computing, including windows, hypertext, graphics, efficient navigation and command input, video conferencing, the computer mouse, word processing, dynamic file linking, revision control, and a collaborative real-time editor (a la Google docs). (Wikipedia) This 90-minute presentation showcased a new computing paradigm focused on interactive, user-centered design, fundamentally shifting the trajectory of computer science away from the purview of an anointed few and into the hands of the masses.
Engelbart envisioned technology not as an autonomous force but as a partner in addressing humanity’s most pressing challenges. Some say that Silicon Valley's innovations over the past several decades have only been extensions of the groundbreaking work Engelbart and his team presented during this demonstration.
Despite the outsized success—nothing short of sparking a broad sweeping technological paradigm shift—there are those who argue that the true promise of Englbart's innovations have yet to be fulfilled. Englebart, among them. In the 2004 keynote address, mentioned above, he tells a story of how he found the door that led to this demo. He consciously selected a very particular and significant problem: What could he do to help humanity collectively address ever mounting complexity? He calls himself naive when looking back on this decision, because it was just so lofty a goal. He used the hallways metaphor as a way of describing an aimlessness he felt in his early career, and how he decided to address it with vigor: “Let me come up with a career goal that will maximize the contribution I can make to mankind” Naive though that may be, I admire his earnestness.
Card: Conscious EvolutionA purposeful shift in individual and collective awareness leading to intentional and responsible co-creation of the future.
In 1998 Englebart was interviewed about the unfinished revolution. “The unfinished revolution is about what we can do to change the way we face the future so that we can better cope with all that is now happening.” Today it’s just as easy to point to how information and computing technologies have created more problems than they’ve solved. The rise of surveillance capitalism, echo chambers, and fragmented communities shows how the tools once meant to augment our capabilities have, in many cases, undermined them. This disconnect highlights the need for a new paradigm—not AI as a detached problem-solver, but IA as a conversational partner in addressing complexity. Engelbart’s vision reminds us that progress isn’t just about building smarter machines but about fostering better collaborations between humans and machines. Having the technology available creates the possibility of new paradigms and modes of interactions, but good outcomes won’t happen all at once. As UX Research luminary Erika Hall has said, “the future spreads like cold butter” not only in access to technology, but also in the patterns and means technology is applied.
As we grapple with the unintended consequences of computing technologies, his vision offers a way forward: reimagining AI as IA—Intelligence Augmentation—to restore the tools meant to connect us to their original purpose: collaborative problem-solving. Engelbart’s hallway metaphor captures the aimless complexity of our era, but navigating this hallway demands more than just opening doors—it requires adaptive learning and meaningful dialogue. Gordon Pask’s Conversation Theory offers a powerful lens for understanding the difference between AI and IA. Where AI often focuses on answers, IA emphasizes dialogue—an iterative, reciprocal process of co-constructing solutions. Seen through this lens, AI systems become more than tools; they become partners in conversation, helping us refine our questions, navigate complexity, and co-create knowledge. This shift from directive to collaborative, from AI to IA, fulfills Engelbart’s vision of tools that truly augment human capability.
AI, seen through Pask’s lens, is not merely a problem-solver but a conversational partner. It learns with us, adapts to our needs, and participates in co-constructing solutions. This conversational dynamic highlights a fundamental shift in how we engage with technology: from directive to collaborative, from static systems to adaptive, relational agents. In this way, AI could help fulfill Engelbart’s vision by becoming an integral participant in tackling humanity’s mounting complexity by more readily meeting people where they are.
This iterative, conversational approach to AI has felt extremely natural to me and it’s one I’ve readily adapted to. It helps that I’ve spent years thinking, writing, and working in a conversational paradigm with the aid of cards, and the Conversations that Mind Cultivate and Matter (CMCM) group on Facebook. Truth be told, it’s been the only thing that’s kept me on the platform. It’s where I pulled the cards for this article, as I’ve done countless times during my professional career when I needed a jolt in thinking, a surge of inspiration, or a means to connect disparate ideas. I’ve found so much benefit that I’ve begun writing this series while launching new endeavors with the group’s founder around card play conversations. The ultimate goal is to bootstrap a platform of our own, where members can homestead and own their own corner of the platform.
Card: Social Web A modern string figure network, interlinking ideas, traditions, and societal innovations across the globe in real time.
The Social Web—an interconnected network of ideas, traditions, and innovations—embodies the ethos of participatory collaboration. Howard Rheingold’s vision of digital technologies as enablers of co-creation aligns with the shift from AI to IA. Where AI often centralizes decision-making, IA decentralizes it, empowering individuals to engage as active participants in shaping problem spaces and adjacent possibilities. This participatory approach transforms AI systems into modern tools of the mind, echoing the interplay of hands and strings in ancient string figure games. Indeed, my friend, collaborator, and founder of CMCM, John Kellden is a long standing member in Rheingold’s Brainstorming community. Howard is counted as a major inspiration behind our work.
This article and the series I’m working on is a demonstration of how social networks, AI/IA, and dynamic knowledge repositories (another Englebart concept) come to life. I’m using search terms derived from conversations with a GPT to plug search terms into the CMCM. Allowing me to draw from nearly a decade of card and pattern language play. A post in the CMCM features the Social Web card used above (request membership to the CMCM FB group to view it in context). I got there by searching “Generations” in the CMCM group’s search. I didn’t think that search term on my own, I happily admit. I got the idea by feeding my early notes and scribbles for this article into a bot I’ve been fine tuning called Insights Navigator GPT and asked for search term recommendations. The Insight Navigator has been an essential companion to assist me in researching, writing, and editing this work. It’s a true partnership.
The CMCM post mentioned above links to a paper on String Figure games. In the spirit of weaving understanding for the sake of insight, as Englebart, Pask, and Rhiengold encourage, let’s explore and connect these ideas. The ancient practice of string figure games, where people across cultures manipulated strands of string into intricate patterns, often in shared, playful acts of storytelling. The paper posits that string figure games weren’t just tools for play—they were tools of the mind, fostering mathematical reasoning and cultural transmission. In much the same way, IA systems can serve as tools for cultural and cognitive evolution. They enable us to stretch, twist, and connect ideas across domains, revealing patterns and possibilities that would otherwise remain hidden. To fully realize this potential, we must reimagine AI not as an isolated force but as IA—a partner in the collective process of co-evolution.
Rheingold’s vision of participatory media aligns with this tradition of shared engagement, where the act of creating together strengthens individual and collective intelligence. This is the unfinished revolution Engelbart spoke of—not merely developing smarter technologies but creating systems that enhance human intelligence and foster collaboration. It’s a shift from artificial intelligence to intelligence augmentation, from tools that automate to tools that amplify. Like the string figure games of old, IA systems offer a dynamic space where ideas are stretched, twisted, and connected, revealing new patterns of understanding.
But there’s a cautionary note: just as string figure traditions are at risk of cultural extinction, the participatory potential of digital technologies risks being overshadowed by extractive models of engagement. Surveillance capitalism, echo chambers, and the commodification of attention threaten to undermine the very connectivity these tools promise.
Card: Deep Transmission The preservation and sharing of cultural practices across generations, embedding ancient knowledge within the tapestry of modern societies and technologies.
To reclaim and reimagine these tools, we must adopt a new ethos—one that mirrors the interplay of hands, strings, and minds in the ancient games. This means fostering AI systems designed not for domination or distraction, but for dialogue and shared growth. Systems that, as Gordon Pask might suggest, don’t just solve problems but help us ask better questions and co-evolve as partners in learning. Strings connecting cards, posts, and ideas to form networks of knowledge—a dynamic knowledge repository (Englebart), an entailment matrix (Pask) and what Howard Rheingold might call a 'participatory knowledge ecosystem.' Rheingold’s Brainstorms community is a living example of the ideas of Pask and Englebart. Members contributed ideas, resources, and insights in an interconnected, peer-to-peer manner, creating a rich, evolving tapestry of collective intelligence.
The idea is to create networks that aren’t just repositories, but vibrant, adaptive systems where knowledge isn’t stored so much as shared, stretched, and refined in real time so much like the string games of our ancestors. Cards for Insight seeks to create a similar adjacent possible playground to carry on this ancient tradition. Sign up to be notified of open studio sessions where we can build on this essential cultural practice.
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