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].
Looking back at last month there were two interesting articles that deserve a closer look in relation to the Cities of Things. It connects to some of the basic concepts, and triggers deeper exploring that I probably do later.
One of the core concepts that inspire Cities of Things is the relationships we as humans have with the technology that gets more agency, will make their own decisions, will have more responsibility in taking decisions. The things that are becoming citizens. Things are still representing systems of designed agency, often by organizations. They might however become more learning creatures on their own. We strive for a harmonious society living together with these things, where we can perform in co-performance with the things reaching a shared goal, using each-others best characteristics.
I think I cannot avoid talking about the launch of Apple’s AirTags. I ordered a set but they will not arrive before half of May I think. But that does not matter, the actual experience of using them is not the key point I want to address here. The basic premise of having a tag connected to a valuable object is not so exciting and definitely not new; my tile is still in my bag, just in case. The battery is worn out I think and with the first edition I have, you cannot charge it or replace it. A bad design choice they recognized themselves in the second generation.
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.
This post is also sent as an update via the monthly newsletter. Around the end of a month, I share learning on the Cities of Things. More on the backgrounds of Cities of Things and the current research projects via the website. In my personal weeknotes newsletter Target_is_new I keep track of the news of the week.
Reading back the weekly updates, it is noticeable that there are continuous introductions of new robot-dog applications, mostly Spot from Boston Dynamics; from policing to being a doctor. The last mile delivery pods are also now adopted by new players every week, so it seems, driven by pandemic lockdowns probably. The pods could see these as typically the creatures inhabiting the cities of things, but it is interesting to reflect on some differences.
From an outside perspective, the way they resemble human characteristics is very different. The last mile vehicles resemble other types of vehicles that we use for transport, while the robot-dogs are a new type of living creatures and touch upon more human-animal interactions often. The robot dogs are also a kind of democratization of industrial robots to a smaller and easier to adopt form factor. The new Stretch robot of Boston Dynamics, introduced last month, is another interesting example. It is positioned as a moveable logistics robot, taking stuff from a truck to the warehouse and vice versa. It is like a combination of a human worker with a tool like a forklift. That make these robots into three types of support connected to human capacities: replacing a delivery person with an autonomous moving bag, replacing the warehouse worker with autonomous lifting gear, and a human guarding or communicating position with an autonomous living object.
All of these are staying close to the objects or tools they replace. That is needed for the acceptance and for the transparency in what they do. Here we touch an important aspect; for acceptance in our regular life we need autonomous operating devices that are readable archetypes. For now.
Will this change? Will we give the autonomous operating citythings more credits for their own character, the authentic choices they might start making. Like the painting robots that create art, that is even sold as NFT. If the autonomous thing is just a predictable extension of human-operated things, there is no character to recognise, and would it be also not likely it will produce interesting art. So might it be a virtue to have non-explainable AI driving these characterful citythings, creating a kind of non-transparent working? In that situation, the relations we have are not are based on our human representations in the autonomous things but in the embodiment of the decisions the robotic things make…
This notion is opening up lots of new questions of course. To connect two interesting reads to dive into it more. First, in her trend presentation at SXSW, Amy Webb introduced the You of Things, where the personal connector is important in the context of networked objects. It is a nice capture of weak signals but deserves also more thinking. The translation into examples is quite basic still. A fundamental exploration on the change of what living things are, was done in this extensive article: “Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior“. New definitions of machines, robots, programs, software/hardware are proposed.
The science of behavior, applied to embodied computation in physical media that can be evolved or designed or both, is a new emerging field that will help us map and explore the enormous and fascinating space of possible machines across many scales of autonomy and composition.
Interesting to see how it plays out, also in relation to more hybrid systems, especially in a city context. That is something for another edition though.
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.
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’
Dear visitor, welcome to this compact website dedicated to the research activities under the label Cities of Things. As described in the About-page we (Elisa Giaccardi and myself) started shaping this research program at TU Delft Connected Everyday Lab in early 2017, at that moment still as PACT (Partnership in Cities of Things). The post-doc research of Maria Luce Lupetti and Nazli Cila delivered interesting research insights in the form of a workshop-format and papers (see more on Research page). In 2018 we established the Cities of Things Delft Design Lab, mainly to cater to master research projects with industry partners and building more research knowledge.
We noticed more and more attention to the research topic and now in 2020, we are looking into other forms of supporting services in different partnerships. That is one of the main reasons to start this separate website that is a switchboard to current and future initiatives around the theme. Next to being a start page to jump to other places, we will share in this section remarkable results of research and projects. To begin with, thinking about predictive relations, the more specific research I’m running.
To close this welcome, I like to invite you to contact me if you have any idea for corporations, projects, or partnerships. Also if your organisation is looking for exploring the domain of living together with new autonomous things or systems through the research and prototyping by a master student graduation project.
