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The Agentic Turn

Designing things in times of immersive AI

A write-up of my talk at the Design Thinkers Academy, 28 May 2026

I was invited to speak at the Design Thinkers Academy about where Cities of Things sits today, and I used the occasion to do something I’d been circling for a while: take the temperature of the whole project. What does it mean now that generative AI is everywhere — and what happens when that intelligence stops living on our screens and moves into the things and spaces around us? That shift is what I’ve come to call the agentic turn, and it’s the thread running through everything below.

Where this comes from

Cities of Things began in 2017–2018 as a research initiative and design lab at TU Delft, set up by Professor Elisa Giaccardi and myself as visiting professor. We weren’t interested in the smart city as a story about data collection, sensors, and dashboards. We were interested in a different question: what does it mean to live together with intelligent things, objects, and systems? In 2021 the work became an independent foundation — the Cities of Things expertise center for physical and embodied AI — which is now my main focus.

The premise has stayed remarkably stable. We treat things as a kind of citizen. Not just as devices that sense and collect data in real time, but as data-enabled artefacts that can act proactively and, crucially, begin to behave socially. As designers we found that an irresistible question: if a thing starts to behave like a social entity, how do we relate to it?

Five dilemmas

Before any of the prototyping, we mapped the tensions that this raises. Five dilemmas have guided us ever since, each a spectrum rather than a yes/no:

  • Responsibility — private versus public
  • Priority — does the human or the system come first?
  • Relationship — is the thing a tool or a social partner?
  • Adaptation — does the thing adapt to the human, or sometimes the other way around?
  • Delegation — do we hand over a single task, or everything?

You can see these dilemmas play out in the wild already. We don’t really have delivery bots on Dutch streets yet — only a few experiments — but in the US and China they’re common, and the TikTok and Reels footage of them is telling. People form an emotional connection, or they get angry, or — most interesting to me — they help. When one of these things gets stuck on the pavement and a passer-by frees it, and the thing responds well to that help, there’s a small moment of joy there. That tells you something about the relationship we’re building.

Civic prototyping: the Wijkbot

The way we study this is not by sketching it out but by building it. Credit here goes to Tomasz Jaśkiewicz, lector of civic prototyping at Rotterdam University of Applied Sciences, who came up with a beautifully simple hack: a hoverboard platform you can stand on, turn into a remote-controlled base, and quickly build a robot on top of. That became the Wijkbot (Hoodbot).

We took it everywhere — hackathons, half-day workshops, and out onto the street, including the big market in the Afrikaanderwijk, where we ran a project for a year and a half. The method is wonderfully direct: you stand at a distance, you mimic the robot’s behaviour, and you watch how people relate to it in real time. We did this with students, with professionals, in Rotterdam and as far as Hamburg, often together with the systemic co-design network, and we developed it into a workshop format that digs into the deeper layers of people’s motivations.

The driver underneath all of it: not technology built for us by big tech, but technology we can build ourselves, as citizens.

From things to systems

In the last couple of years the questions have grown outward — from the single thing to the system. If a community builds a commons-based, bottom-up form of governance around both human and non-human actors, what economic models start to appear, and how do we design for them? This is the strand that increasingly defines the work.

The ChatGPT moment

When we started, we understood machine learning and could reason about these things, but the technology wasn’t there yet. The transformer arrived around 2018, but it became legible to everyone only with the release of ChatGPT in November 2022. After that, everyone understood what generative AI could mean — for conversation, text, images, search.

If you sketch the arc, you move from textual and conversational, through images, search and reasoning, into multimodal combinations — and then into the two stages that interest me most: agentic AI, and physical AI.

Agentic is the threshold. An agent is something you delegate a task to. Something becomes agentic when it starts to act proactively — taking actions you didn’t explicitly ask for, because its rules and knowledge lead it to. That’s the moment we start building genuinely new relationships with things, especially once those things are embodied in our environment.

Co-performance, and the sweet spot

I keep coming back to the concept of co-performance, introduced by Kuijer and Giaccardi in 2018. When we live alongside AI on these surfaces, we have a choice of strategies: delegate everything; treat the AI as a tool that must follow us; let it take over the human role; and so on. None of the extremes is interesting. The interesting work is finding the sweet spot in between — what does AI do best, what do humans do best, and how do we choreograph a co-performance that may itself shift over time?

Immersive AI — and its shadow

That’s the optimistic reading. There’s a shadow too. I describe the emerging condition as immersive AI: intelligence that is everywhere and connected to the things in our environment. But we already live in a state of mind addicted to small chunks of media, needing a continuous drip of the new. So I sketched a small model — partly prompted by a group of Unilever marketers asking about exactly this.

Put three forces together — immediacy culture, agentic AI, and the physical environment — and they form a super-stimulus effect: a flywheel of dopamine dependency and environmental triggers, personalised, which is a potentially dangerous mix. We should be aware that we risk building a world where we live inside immediacy and AI black boxes, using intelligence built into everything without understanding how it came about.

The way I frame the whole landscape: physical AI is the fixed environment turning computational — a lamp post, a bin, anything with an algorithm in it becomes part of a “mirror world” of opportunities. Embodied AI is the moving things, the city bots, now carrying that same generative capability. Where they meet — when we interact with embodied things inside a physical-AI context — that’s immersive AI. New affordances, new services, and new consequences to think through.

Four conditions of interplay

How we experience this depends on the kind of interaction we have. There are four conditions, along two axes — one-time versus ongoing, and a single thing versus a system of things:

A brief brush with one object is an encounter; a brush with a coordinated system is a passage. An ongoing bond with one thing is companionship; living inside the system is inhabitation.

The manifesto: a seven-year reflection

Around last November, seven years in, I decided to reflect on Cities of Things itself — what is its state in 2026? So I interviewed around thirty people: academics, designers, practitioners, former students, anyone with an opinion and a role. The conclusions are gathered in a new manifesto, and a few threads from those conversations shaped the thinking that follows.

One interviewee talked about emerging milieus of intelligence — systems built from the bottom up — and argued that design should stop focusing only on the object and attend to the supporting environment. Don’t start by designing a nice thing and its insides; start with what it touches and what surrounds it.

This sent me back to my own unfinished 2018 research on predictive relations. Our interplay with a thing is shaped by the mental model we hold of it — we expect a certain response. That response is shaped by the thing’s intelligence, and by our own history and profile, which we can understand. But there’s an extra layer: it’s also shaped by every interaction every other person has had with that thing, anywhere in the world, at any time, because these systems are continuously connected. What does that do to the relationship? That’s the open question I’d parked, and immersive AI reopens it.

And it deepens further with agency. Is an object a single agent? Or, as Simone Rebaudengo put it in our conversation, is an object an assembly of different agents working at different tasks?

A story from the (near) future: The Grid

To make this tangible, I told a speculative story set in 2033.

Two pressures shape its world. An energy crisis has made us far more deliberate about how we use and organise energy. And a loss of trust in the centralised internet has pushed people toward bottom-up mesh networks, node to node. Imagine a phone company — say, Fairphone — that doesn’t just make a phone but a module you can drop into anything to spin up a mesh easily. Call it Fairmesh, a service.

Meet Lena. She enters the building where she lives and immediately feels its state — the building gives her feedback through the device she wears. Inside, all the things are connected in a mesh; and the buildings themselves mesh together across the city, a hypermesh layered on top.

What I find compelling here is the counter-movement to centralised intelligence. Alongside the big models — the OpenAIs and Geminis — there’s a push toward small, dedicated language models. The heat pump has its own tiny LLM, tuned only for its task; so does the solar panel. They’re conversational and intelligent within their narrow remit, and through the mesh they begin to talk to each other, generating new knowledge and behaviour in the space between them.

The residents organise too. In the story they’re a cooperative — De Warren — that holds a quarterly assembly to decide their shared goals: use less energy this quarter, or give away the surplus they’ve saved; who governs whom; what the rules are. And into that assembly the things contribute as well, each offering its own overview of what it has done.

None of this is wholly invented. In Amsterdam, the Schoonschip project — a community of floating houses connected to the grid through a single plug — already runs its own internal energy economy: batteries, solar panels, residents buying and selling surplus among themselves and with the outside. The Grid simply asks what happens when those balancing systems stop being merely algorithmic and start becoming intelligent. (I even fed the scenario text into NotebookLM and got back a two-minute film — and it captured nicely how, in this world, the things become genuine players in the equation. Who rules whom?)

Ten design considerations — the Manifesto 2026

This brings me to the heart of it: ten design considerations for working in immersive AI. I prefer “considerations” to “commandments.” They fall into four rough groups.

Understand and be honest — the first five.

  • Design for Legibility of Agency (LA) — make the intelligence readable.
  • Provide Predictive Symmetry (PS) — arrange a relationship between human and thing that is genuinely trustworthy.
  • Emerge Relational Integrity (RI) — let the relationship hold together honestly.
  • Keep Peripheral Presence (PP) — use the intelligence only when it’s actually needed.
  • Reveil Assemblage Transparency (AT) — when multiple agents or stakeholders coordinate around a person, that coordination should be perceptible and its boundaries knowable. Be honest about it to the one human in the loop.

Friction leads to more engagement — the next two.

  • Appreciate Friction in Interactions (FI) — build friction in, deliberately. Don’t make things so smooth that people stop thinking.
  • Incorporate Temporal Honesty (TH) — a thing with vast knowledge can leap to conclusions you don’t follow and didn’t want. Respect the difference between a new encounter and an established relation; don’t simulate relational depth that hasn’t been earned; let people walk the path of a decision themselves.

Embed in new forms of governance — the commons layer.

  • Leverage Democratic Precedence (DP) — communities should define the kind of environment they want before agentic systems arrive. Governance infrastructure must precede technological infrastructure.
  • Ensure Distributed Sovereignty (DS) — keep control distributed rather than concentrated.

Be an open platform — the last one, which arches over the rest.

  • Open up to Build Back (BB) — people must be able to introduce their own agentic things, modify existing assemblages, and keep the possibility space open against closure. Don’t hand people a finished system to use; give them things they can build and rebuild. “Vibe coding” is a hot term, but the underlying principle — we can make this ourselves, fairly easily — is a powerful one.

These are still in development; there’s a card set to think with, and an open discussion about whether to fold in the resource and societal impact of these systems too. The current set is mostly about how we design once we’re in this situation — how to make things that are genuine, good and honest.

What remains human

My personal conviction is that a real shift is underway in how AI is embedded in the things we use. Since ChatGPT we’ve treated it as a tool we reach for. But what happens when AI is embedded in everything, always there, and able to become agentic — to initiate interactions with us? That always-on intelligence is a new form of relationship with our environment, and it isn’t only technical or functional. It’s social. It’s about what just happened, socially, between us and the thing.

We have always designed for humans — to serve us, to be usable. The extra quest now is to design not only what works best for us, but what keeps us human — what prevents us from becoming less so. With all the convenience these systems offer, if we’re not aware of how much of the human part of ourselves we’re delegating away, we lose some humanity in the bargain.

I’ll close where one interviewee pointed me, to Donna Haraway. I’m critical precisely because I’m optimistic. I can only be optimistic about the usefulness of all this if I’m also willing to be critical and look hard at where the dangers are.

Cties of Things is an independent expertise center for physical and embodied AI. More on the manifesto and the research behind this talk at citiesofthings.nl. — Iskander Smit, iskander@citiesofthings.nl

This write-up is written by Claude Opus 4.8, based on the transcription of me presenting the deck, combined with the PDF of the slidedeck. Let me know if you like the whole story 🙂

Categories
reflections research

Cities of Things affordances

In the process of creating a new Cities of Things manifesto for 2026 and beyond, as a reflection of the state of Cities of Things, an explorative research project was started. Through interviewing 30 experts the first outlines of thinking about the shift from a cities of things with agency, towards living in a reality of immersive AI, where given more depth.

The State of Cities of Things

Living with things, part of the city fabric, as residents, as citizens. It was what we envisioned back in 2017, resulting in a set of dilemmas that still hold true in current relations with AI. But what has changed in that almost decade? Machine learning and AI became generative AI. And we evolve in a society where we increasingly partner with other intelligences. Both ‘in your face’ while using the gen AI tools for creating and even communicating as a coach or a shrink. Trust in the systems changed. Critique is also serious. Big tech has shifted attention to generative AI, and new big tech players have taken a defining role. OpenAI, Anthropic, and next to the existing ones like Google and Meta. And even if seemingly lagging behind like Apple, it is the core of the attention. 

This all focuses on the backend, the infrastructure, and the screenbased interactions – with extension to other forms of communicating with images and sound. The physical angle is still early in development. Physical AI start to be a thing in 2026 for sure, and robotics is accelerating with humanoids and doganoids. It is still fresh and experimental. 

You could say that these forms of physical AI are the fully embodied ones. Another form are the autonomous vehicles that get more and more agency to make decisions by themselves, operate with less instructions. The latest version of FSD (Full Self-Driving) is illustrative. Comparing videos over the years give you trust that the current version is capable to deal with all regular situations, and only has flaws in edge cases. You might even say that it still has human characteristics; it sometimes misses a sign or is confused. The forgiveness of humans is however quite different. 

From the beginning of the Cities of Things research we think that things are not the same as objects. We like to see things more as assembles of meaning and behavior. With that, it can also be a static thing or system as a whole. In the thirty interviews that serve as the point of departure for reflecting on the state of Cities of Things, this notion is common. And it goes behind that, looking at the other intelligences and more-than-human actors and systems. New -or changing- forms of community and governance are a topic. And new types of infrastructure. One thing that we foresaw but was still very conceptual is the fact that these things that form the city are an assembly of layers of states, in the sense: the physical layer, the regulatory layer, the digital layer, the data layer, the object layer, the citizen layer, the relational layer. And within these layers, iterations happen, evolutions take place. The layers are responding to each other in different ways. Are entangled better said. How these entanglements are shaped differs and changes over time. A thing is, in that sense, a moment in time, entangling different aspects from the layers in a performative expression that is taking space in its environment. An abstract description, but in other words, the essence is that things are not static, given. 

A story from a possible future

Before diving deeper, I like to sketch a possible future of the state of Cities of Things that encapsules some concepts that are discussed and we find important to unpack later, using the expert opinions.

1st act, the context

Everything that can be a computer will become a computer. Chips are flocking the things we use. In our house, in our cars, the phones were the first ones maybe, and are an enabling platform for those things that are still lagging behind. Things become sensors of their environment. Not for direct services, but at least for informing maintenance. The iPhone was introduced in 2017 as a marriage of a communicator, a music player, and an internet device. The word “communicator” is another word for “phone”; using it makes the narrative correct (a phone that is a phone sounds less interesting). The aspect that this device became a communicator and connector of all other aspects of our life, of our physical and digital realities, literally, might not have been foreseen back then. 

It is a known change in society, in human interactions and daily life. We are disconnected from our direct reality and live more prominently in our own chosen digital reality. We all carry our personal bubbles and live inside these. It is seen as a problem for our social intelligence, for our healthy human-to-human connections. These can be separated, though; the phone’s enabling capability for creating new infrastructure and new types of embedded intelligence in a network. That is a capability in its own right. The other capability is serving as the hub in our social fabric. Social on all levels of friendship: from deep commitment to loosely one-time contact while doing a transaction, or even just an interaction. 

The big shift that is happening now in the second half of the 20s is the extension of this enabling layer with AI and, more importantly, agentic capabilities. That is not a new function or system added, but an evolution of existing intelligent systems. Or better, of all existing nodes in systems, aka things. What might happen next is that these agentic capabilities will also get more agency. Not forced by the producers or providers, but grow from the opportunities on a functional level. We will have different conversations with the things we use, the services we experience. Services that can be more autonomous. 

The next possible step is the forming of new networks, new communities, and new societies. Among the things, but especially among gatherings of things and humans. And other non-human lifeforms. 

The weak signals are the digital systems and especially the agent-based assistants that have their after-work gathering. It is a meme, but one that might make sense.

Next to the autonomous things, the level of agency is increasing. Who is taking the agency? Are we delegating more and more out of convenience and losing agency without being fully aware?

Next step after agency per things, is a type of organizing layer formed by the things, the communication between things, creating their own governance structures, with or without humans in the loop. 

The term humans in the loop is already an indication how this can evolve. A human in the lead or in the loop? Democratizing things? How far?

Some aspects that are interesting: What is driving this, and what are scenarios for this evolution? Who is the owner, and ownership Related to public spaces, governance, democracies? New infrastructures? Organizing scales (family, building, neighborhood, etc)?

2nd act, a story from the near future

In 2033, Apple is still organizing its yearly WWDC. And for the 2033 edition, people are already getting excited with the first announcements in April. There is expected to be a major update to the immersive device after it launched last year. It seems they have found their mojo again after years of downfall and doubts about their relevance in the current state of digital life.

The rise of a small player, such as Fairphone, in the late 20s was not to be expected. The pivot towards a community device, rather than a communication device, was so new that it shook the whole industry. The uptake from the mesh-based communication ate in the business of all players, and although Apple was not that affected in the first years, it started to compete with the 2029 introduced connector-hub-puck, as people started to combine this with all kinds of services in a new open platform that emerged from the mesh networks. 

It was not a surprise that Fairmesh was acquired by a big player, but Apple is usually not in the business of acquiring complete service brands. With the rapid growth of Fairmesh, it almost felt like a reverse takeover, and, officially, it is a collaboration, not a takeover, with Apple adding the Fairmesh protocol and chip to their AirTag devices.

More about Fairmesh

In 2029 the small mobile phone company Fairphone introduced a new device that was aimed at local communities. Already in 2025, the first local initiatives to build mesh networks for communicating text-based messages began experimenting. On the one hand, it focused on disaster-based communication needs, a hot topic as the several wars were increasingly developing into a worldwide conflict. A pivotal moment was when mesh networks began connecting to edge devices, such as phones, enabling simple messages to be integrated into richer content through smart use of AI. With the latest open source models with a smaller footprint, it became common to download AI models to personal devices and build a local personal assistant. 

The device that Fairphone introduced used a low-end computing architecture, and the core was the chip for the mesh-networking aimed at peer-to-peer. As they had integrated this chip also in the existing phones, they kickstarted a local-based network. And they offered a device for local communities, a kind of router/antenne that makes it possible for all kind of communities to create local networks with messaging services. 

The device gained traction as the liminal state of the world, moving from crisis to crisis, made people receptive to a new robust network that was not run by big tech. In just one year, millions of devices were distributed, and, more importantly, it has been possible since 2030 to connect from the Nordkapp to Tarifa and from rural Ireland to the Donbas, even reaching into Asia. And it is the first network to show similar uptake in the global south.

Apple 

With all the economic crises that followed in 2026, the US-Iran conflict, the already-started trend toward a declining market for premium phones, Apple had some rough years. They had been planning for a new type of device in the early 2020s that moved away from the phone as a form factor; the first signal was the iPhone Air, which proved that the core technical ingredients fit a small footprint, the camera bump. After the bust of the Apple Vision devices, the company can capitalize on its new success, and with the new AirTag, it launched a personal device that fully leverages the cloud services infrastructure. A special T1 chip was launched to create a platform for physical AI, a form that emerged in the late 20s as a new form of AI. With the Tag, services can be connected to every device you like. One thing that is not possible yet is to connect to the internet without a phone nearby. 

In 2032, Apple decided to start a collaboration with Fairmesh, not by fully acquiring but by opening their AirTag with a mesh chip and an AirTag Plus with voice-based communication devices. The Fairmesh is also expected to be added to a new version of the Apple Watch.

About

These are rough thoughts about the state of cities of things, as part of making sense of the current state, and part of the process of formulating a new manifesto and design principles for Cities of Things that aimed to be completed in May 2026. Written between 10-17 April, and used as resource for the first version is discussed at the event on 24 April.

More to follow!

Categories
reflections research

How AI Reflects on the Hoodbot, Civic Prototyping and Fifth Order Design

As a little experiment and a way to reflect on a part of the research from the last 7 years of Cities of Things, I used the (in)famous Notebook LM tool to create a podcast discussing research sources. The result was rather pleasing, in the sense that based on four sources it gave a rather accurate description of the backgrounds of the Hoodbot research and the link with concepts we are exploring with Fifth Order Design.

The research sources were:

Lupetti, M. L., Smit, I., & Cila, N. (2018, September). Near future cities of things: addressing dilemmas through design fiction. In Proceedings of the 10th Nordic Conference on Human-Computer Interaction (pp. 787-800).

Lupetti, M. L., & Cila, N. (2019, October). Envisioning and questioning near future urban robotics. In Design and Semantics of Form and Movement. Conference: Desform.

Jaśkiewicz, T., & Smit, I. (2024). Between experiments leveraging prototypes to trigger, articulate, and share informal knowledge: Case of the cities of things living lab. In Applied Design Research in Living Labs and Other Experimental Learning and Innovation Environments (pp. 210-233). CRC Press.

Stompff, G., Jaskiewicz, T., Nachtigall, T., & Smit, I. (2025). Design in the Real World: Facilitating Collective Learning through Design. In Applied Design Research (pp. 290-308). CRC Press.

Notebook can also create infographics now, but this is not that good. The visual references would not pass my creative direction 🙂

In the latest NADR publication, we wrote about the potential role of AI-image generation in Civic Prototyping:

Scaffolds of Imagination: Partnering with AI-image generation in Civic Prototyping (Tomasz Jaśkiewicz, Iskander Smit, Peter van Waart, Manon Mostert van der Sar, Evin Wijninga)

Categories
field lab Cities of Things Lab010 research

Chapter “Between Experiments” in NADR book

The learnings of developing and applying the WijkbotKit in the last years is captured in a chapter in the book of the Network of Applied Design Research that was published at Dutch Design Week 2024: Applied Design Research in Living Labs and Other Experimental Learning and Innovation Environments. The article is result of the fruitful partnership with Creating010 and especially the research on Civic Prototyping by professor Tomasz Jaskiewicz.

Find the article here: Between Experiments; Leveraging Prototypes to Trigger, Articulate, and Share Informal Knowledge

The digital version of the book can be downloaded via the NADR website.

Abstract

Living Labs are ‘open innovation ecosystems’ (ENoLL, 2024), offering unique opportunities for conducting scientific experiments ‘in the wild’ (Romero Herrera, 2017; Ballon & Schuurman, 2015). Yet, Living Labs also support the generation of other, informal, types of knowledge: often tacit and difficult to capture and share, acquired outside of rigorous academic research frames (Schuurman & Tiinurist, 2017), and comprising insights, ideas and know-how gained through experience, serendipity, and sometimes ad-hoc and playful explorations aaskiewicz, 2021). This chapter focuses on the significant, yet often overlooked, role that prototypes play in triggering, articulating and sharing such informal knowledge. Grounded in the discourse on the role of prototypes in Research through Design (RtD), the chapter brings forth that prototypes are not just valuable as artefacts to be studied through formalised research but are also crucial in supporting the generation of rich, contextual insights, ideas and know-how, sharing them across experiments, disciplines and stakeholders, while often facing the challenge of legitimisation and generalisation of such knowledge.

Jaśkiewicz, T., & Smit, I. Between Experiments Leveraging Prototypes to Trigger, Articulate, and Share Informal Knowledge: Case of the Cities of Things Living Lab. In Applied Design Research in Living Labs and Other Experimental Learning and Innovation Environments (pp. 210-233). CRC Press.

Categories
research

Building a collaborative relationship with a travel buddy for multimodal journey planning

Yeonju Jeon finished her graduation 31st of August 2021. I invited to describe her findings.

Life is a series of choices from a small decision such as choosing what to have for dinner to a major decision that will change the course of life ahead. And we are handing over many simple and repetitive decisions to computers. We used to depict a dystopian future where the world is taken over by machines and robots. To this day, where we get recommended with new content by the algorithm and automatically filtering out spam by machine learning, we are still concerned about the negative impact that technology will bring in our lives. If we can’t stop machines from mimicking what we do, then wouldn’t it be our job to give it the right intention that will benefit us?

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Categories
research

Research – predictive behaviors of vacuum robots

Last 2nd of August Peicheng Guo graduated with his master research project “Towards an active predictive relation by reconceptualizing a vacuum robot”.

Peicheng not only used the proposed method for designing things that predict, but he also added a couple of valuable models both on the level of relations with domestic products as with autonomous objects in general. Via a Research through Design approach, he developed new insights and brings the knowledge on predictive relations a step further. To illustrate possible future collaborations with objects we use he redesigned the user manual in a guidebook for learning to understand each other’s (human owner and object) intentions.

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Categories
research

Exploring urban farming futures

Introduction 

There is no place left on earth that has remained untouched by humans. We are living in the Anthropocene; an unofficial geologic epoch, yet commonly used term to describe the time wherein the impact of humankind on the planet is substantial. We have become the single, most dominant species on the planet, causing global environmental and ecological changes. One of these changes (though not the only one) is global warming. Ecological theorist Timothy Morton deems global warming to be what he calls a hyperobject: an object that exists on too large of a scale for human perception. As a result, we can only observe the effects of the problems such as extreme weather, melting glaciers, a reduction in crop yield, etc. but never grasp and “prove” the object as such [1]. 

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Categories
research

Designing Connected Experiences of intelligent citythings

Last couple of months 8 teams of bachelor students of IDE have been working on a design for things that predict in the cities of things. The Delft Design Lab Cities of Things commissioned the assignment to explore design experiences with the use of predictive knowledge as design material. The 8 teams did a great job in coming up with very different concepts. In this report I will introduce the projects, you can find the project videos and I will give a short reflection per project.

The kick-off of the project was 10 February with a kick-off presentation for the teams explaining the Cities of Things paradigm and the concept of predictive knowledge. See the slides below.

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Categories
research

Designing predictive relations in more-than-human partnerships

This article is also available as PDF.

Introduction

With the rise of the Internet of Things and the shift from single products to decentralized systems, the functional working of artifacts will be defined for a great part in the digital layer. With the addition of Artificial Intelligence and Machine Learning capabilities, predictive relations are added to the mechanics of designing connected products, with implications for the agency users have in an algorithmic society. 

The potential impact on the design space is explored through a design case of an intelligent object becoming a networked object with added predictive knowledge. This chapter introduces what will be the change that predictions will make to the relation of users and contemporary things[1] on a conceptual level and proposes an approach to how to translate this to new activities in designing networked objects.

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Categories
research

The alienating consequences of things that predict

A specific research topic that I have been looking into the last year is the design for predictive relations. What happens when predictive knowledge is emerging from networked objects and does this influence the design practice of the future designer of intelligent things and services. In 2019 he gave a couple of presentations (at IoT Rotterdam, Digital Society School Amsterdam, Sensemakers AMS, Behavior Design AMS) and published a chapter in the ThingsCon RIOT-publication December 2019. The latter gives a good overview of the research topic.

Things become networks, autonomous things with their own agency as result of the developments in artificial intelligence. The character of things is changing into things that predict, that have more knowledge than the human where it interacts with. Things are building a new kind of relations with humans, predictive relations. What is the consequence of these predictive relations on the interaction with humans? Will the things that know more than we humans do, help us understand the complex world, or will the things start to prescribe behavior to us without we even know? What is the role of predictive relations in the design practice of the future designer?

from ‘The Alienated Consequences of Things that Predict’

Read the whole chapter online or download the PDF.

Work in progress model for predictive relations