A Subconference of the World Design Cities Conference
Shanghai · September 26–29, 2026
Most conferences are occasions for talking: papers are delivered, panels perform, an audience listens, and everyone leaves with a tote bag and their opinions intact. This event is built on the opposite premise. There are no papers and no spectators — every person in the room (and every person joining remotely) is a working participant in a sustained, structured dialogue, supported by AI tools that handle the retrieval and synthesis so the humans can do what only humans can: question, judge, and decide. And the work aims at something usable. Over three days, each participant builds a concrete takeaway — an action plan for designing, in their own domain, the balance among three kinds of reliance: when to rely on AI, when to rely on human perception and judgment, and when to rely on the context and information particular to the situation at hand. The difference is what you leave with.
Every discipline now confronts the same recursive problem: AI systems are redesigning the people who are supposed to govern them. This conference refuses to treat that as a technical puzzle with a technical solution. Instead, we ask a design question — how do we draw boundaries that respect what only humans can do?
Hosted within the World Design Cities Conference, this three-day subconference brings together complexity scientists, philosophers of mind, AI researchers, educators, and a playwright to hold that question in dialogue — through Buberian dialogues, keynote exchanges, and AI-augmented working groups designed to produce insight that no single discipline could reach alone.
The intellectual engine is the concept of the AI Dramaturg: the recognition that every discipline has a dramaturgical function — the framing, staging, and interpretation of its own questions — that AI can partially supply but cannot replace. The irreducible remainder is situated human judgment.
Beneath that boundary lies a question about reasoning itself — about abduction, the act of deciding which explanation is worth reaching for. A model surveys an enormous field at once and weighs relevance in a single currency, learned similarity across everything in view: comprehensive, but flat. A person works from a small foreground, steered by something the model lacks — affect, bodily salience, the trained feel for what matters that can reframe a problem on a basis no text contains. A model can make the products of that judgment legible; it cannot perform the judgment. Drawing that line is the work of these three days.
In theater, the dramaturg is the person who holds the intellectual architecture of a production — researching context, questioning choices, ensuring coherence. The dramaturg doesn't direct, doesn't act, doesn't write. The dramaturg holds the space in which meaning is made.
AI is becoming every discipline's dramaturg. It can retrieve, synthesize, pattern-match, and propose — reasoning, in effect, over a learned surrogate of human practice. But it cannot make the situated judgment that transforms information into understanding. This conference asks: where exactly is that boundary, and how do we design systems that respect it?
The 26th opens with filmed provocations, Harry Collins's keynote, and a reciprocal Buberian trialogue; the DesignX working sessions then run across the 26th and 27th, building the takeaway with GraspingAI, and on the 28th the conversation reaches the WDCC main stage on the Bund, where David Snowden presents and then joins Lorenzo Magnani in a single Buberian dialogue whose two strands — abduction beyond the machine, and sensing before solving — interweave before the full WDCC audience.
For half a century, Harry Collins has been the definitive voice on what knowledge resists being made explicit. His work on tacit knowledge, expertise, and the sociology of scientific knowledge is the ground on which this conference's central question stands: what can a machine be told, and what can it never be told? His keynote opens the first day.
Creator of the Cynefin framework and the founder of naturalistic sense-making, David Snowden has spent decades mapping where ordered approaches to knowledge end and complexity begins. On 28 September he presents on the WDCC main stage at the Convention Center Riverside, carrying the subconference's question — what must remain situated human judgment — to the full WDCC audience on the Bund.
Lorenzo Magnani returned abduction — Peirce's logic of forming explanatory guesses — to the world in which it actually happens. His eco-cognitive model shows that abductive reasoning is not a formal calculus but an activity distributed across bodies, instruments, and environments: we think through doing, and our guesses carry the weight of lived consequence. That insight anchors the first of the working groups' six cases, and on 28 September he brings it to the WDCC main stage in a Buberian dialogue with David Snowden — two interweaving strands on whether abduction can, or should, be formalized computationally. He also serves as a learned listener in the opening day's trialogue.
Invitations are extended to the scholars, designers, and artists below; the roster will firm as acceptances arrive.
Every stage of inquiry now has its AI shortcut. Hypotheses arrive pre-formed. Meaning arrives pre-structured. Users arrive pre-simulated. Artifacts arrive pre-built. Judgments arrive pre-rendered. Decisions arrive pre-optimized. None of these shortcuts is the work of fools.
Each is the product of competent, well-intentioned practice — and each rests on presuppositions its practitioners rarely stop to examine. On the 27th, the working groups take six such practices seriously enough to question them, asking the same three questions of each: What is being uncritically presupposed? What human capacity is quietly being placed at risk? And what boundary would protect it? Together the six trace the full arc of knowledge-making — from generating a hypothesis to deciding what to do.
When a model proposes the hypothesis, the researcher receives something hypothesis-shaped — but has performed no abduction at all. Human abduction works from a limited base: cognitive constraint forces selection, and what we attend to carries valence earned through lived experience — the anomaly that nags, the guess that once failed. The constraint is the engine, not a defect. Ask a machine to abduct and both features vanish: nothing constrains attention, nothing is at stake, and valence is assigned by repetition across a corpus. Salience without a life behind it — relevance simulated by frequency.
Knowledge graphs and enterprise ontologies promise machine-readable meaning: entities fixed, relations typed, semantics settled. The promise is real — and so are its buried commitments, including an unexamined circularity now that AI builds the ontologies that then constrain the AI.
Synthetic user research replaces interviews, observation, and ethnography with simulated personas — built from the very expectations the designer brought to them. A simulated user can never resist you, contradict you, or reconfigure your understanding of the problem.
Prompt-to-product workflows deliver functioning artifacts whose makers never engaged the material. Yet craft has always fed theory — geometry itself grew from the practices of masons, carpenters, and surveyors — and friction in making, including the friction of debugging, is where tacit understanding forms. Experts who already carry such models wield generative tools powerfully; novices who begin with the tools may never build the models at all.
Journals, funders, schools, and firms are adopting AI screening and review — treating quality judgment as the application of criteria. But connoisseurship is tacit: it lives in trained judgment that cannot be fully codified, and it is acquired only by being exercised.
Decision-intelligence systems treat the future as a distribution over the past and deciding as optimizing. Genuine anticipation is something else: running internal models of possible futures while remaining able to re-perceive the situation itself — to notice that the model's ontology of the problem is not the problem.
We are not staging prosecutions. Each group is anchored by participants whose life's work names what is at risk, joined by practitioners of the very approaches under examination — invited not as defendants but as co-explorers. Each group produces a short statement of its presuppositions, its capacity at risk, and its proposed boundary. These statements become raw material for that evening's AI Dramaturg synthesis, for the overnight remote cohort, and for the Orthogonal Map drawn on the 29th.
Three protagonists engage through a facilitator. Distinguished listeners respond. The audience makes meaning. No debate — genuine encounter. The format is designed to produce insight that neither monologue nor panel discussion can reach.
Two thinkers, one question, one hour. Not a lecture followed by Q&A — a structured intellectual exchange in which both participants are changed by the conversation. The audience witnesses thinking in real time.
Participants receive access to three curated research corpora and a custom interface combining Claude and NotebookLM. Groups use AI as dramaturg — retrieval, synthesis, pattern-matching — while humans supply the judgment that turns information into insight.
Remote participation here is not a livestream. This is a dialogue conference, and a camera pointed at a conversation twelve time zones away produces spectators, not participants. So the remote program is designed as a working role — one that enacts the conference's own thesis. Each evening, an AI dramaturg synthesizes the day's dialogues: the retrieval, the pattern-matching, the 60%. The remote cohort supplies what it cannot — the questioning, the reframing, the situated judgment. You are not watching the conference. You are stress-testing its central claim.
Ninety minutes, live on Zoom, at 22:00 Shanghai time on the 26th, 27th, and 28th — hosted by Ken Friedman from Sweden and led by Hugo Letiche and Michael Lissack. The AI dramaturg presents its synthesis of the day. Two or three remote protagonists — roles rotating across the three nights — respond, question, and reframe. Open exchange follows. Capped at twenty-five participants so it remains an encounter, not an audience.
Because your working day begins as Shanghai's ends, the remote cohort works the night shift. You receive the same three curated corpora and the same Claude + NotebookLM interface as the in-room groups, and you apply the Orthogonal Map and the Journey Method to your own domain. A distillation of the overnight work is carried into the next day's sessions in Shanghai. The conference thinks around the clock.
Remote participants who complete the overnight loop are eligible, on the same footing as in-room participants, to develop contributions for the companion She Ji theory issue, “The AI Dramaturg,” supported by the same research infrastructure.
Sessions are held on Zoom; joining details follow acceptance. There is no fee for remote participation. To apply for a remote place, write to michael.lissack@gmail.com with a few lines on your domain and the question you would bring. Remote places are reviewed on the same rolling basis as in-room applications.
The conference is co-hosted by Shanghai University of Engineering Science (SUES) and Tongji University, situated in one of the world's great design cities. Shanghai's position at the intersection of Eastern and Western intellectual traditions makes it the natural home for a conversation about designing AI's boundaries.
The opening two days take place on campus — one at Tongji University's College of Design and Innovation, one at Shanghai University of Engineering Science. On 28 September the subconference moves to the WDCC main stage at the Convention Center Riverside, on the Bund, for the afternoon, and the closing day returns to campus. The assignment of specific days to Tongji and SUES is being finalized.
The ideas beneath the conference — tacit knowledge, abduction, trust, and the boundaries of the machine
Watch on YouTube →This conference is by invitation and application. We are seeking participants from design, complexity science, philosophy of mind, AI research, education, and the arts who want to spend three days thinking carefully about the boundaries between human and machine intelligence. No paper submissions required — bring your questions. And there are no fees: participation, whether in Shanghai or remote, is free of charge.
Apply to ParticipateApplications reviewed on a rolling basis. There is no registration fee.
For inquiries, contact Michael Lissack at michael.lissack@gmail.com
A companion theory issue of She Ji: The Journal of Design, Economics, and Innovation is in development, titled "The AI Dramaturg." The issue will explore the conference's central proposition: that AI's role across disciplines is best understood through the dramaturgical metaphor — and that the irreducible human contribution lies in the situated judgment that no model can replicate.
Participants in the conference's AI-augmented working groups will have the opportunity to develop contributions for this issue, supported by the same research infrastructure available during the conference itself.