Thijs Kleinpaste heeft een mooie boekbespreking van Michael Young’s De opkomst van de meritocratie in de Nederlandse Boekengids. Een paar passages die ik vooral sterk vond hieronder.
De grote verdienste van Young is dat hij inzichtelijk maakt hoe onschuldige principes als ‘beloning naar verdienste’ volkomen kunnen ontsporen als ze worden ingezet binnen een verder onveranderd sociaal en economisch stelsel. Concreet: sommigen een uitverkoren positie geven in een maatschappelijke hiërarchie en anderen opdragen om hun plek te kennen.
Het klassenbelang van de meritocratie is abstracter. Het belangrijkste is om allereerst een klasse of kaste te blijven om zo de voordelen daarvan te kunnen blijven oogsten. In iedere moderne staat wordt macht uitgeoefend – of meritocratischer gezegd: moet er bestuurd worden – en als er dan toch een kaste moet zijn die deze taak vervult, laat dat die van de hoogst gediplomeerden zijn. De meritocratie reproduceert zichzelf door deze gedachte mee te geven aan elke nieuwe lichting die tot haar uitverkoren rangen toetreedt: dat zij de juiste, met recht geroepen groep is om de wereld te ordenen. Niet de arbeidersklasse, niet de ongeleide democratie, niet het gekrioel van belangengroepjes – maar zij. Alle materiële voordelen van de meritocratie vloeien voort uit het in stand houden van die uitverkoren status.
Te vaak lijkt de gedachte te zijn dat vertegenwoordiging en het bedienen van belangen onproblematisch in elkaars verlengde liggen. Om die zelfgenoegzaamheid te doorbreken is kennelijk iets stelligers nodig, zoals de gedachte dat waar managers en bestuurders zijn, er gestaakt moet kunnen worden: dat waar macht wordt uitgeoefend en waar aanwijzingen worden gegeven, zij die de aanwijzingen moeten opvolgen kunnen stemmen met hun voeten. Dat conflict omarmd wordt en niet wordt gezien als iets wat gevaarlijk is voor de maatschappelijke lieve vrede, de ‘economie’, of zelfs de democratie. Conflict is ongetwijfeld gevaarlijk voor de hegemonie van de manager en diens klasse van droomkoninkjes, en daarmee voor de soevereiniteit van de meritocratische orde, maar dat gevaar is zowel heilzaam als noodzakelijk. Een van de lessen van het boek van Young is immers ook dat je moet kiezen: zelf een revolutie maken, of wachten tot die uitbreekt.
Seven months since the last update. Much better than the gap of three years between the previous two. These past months I feel like I have begun to reap the rewards of the grunt work of the last couple of years. Two papers finally saw the light of day, as well as a course syllabus. Read on for some more details.
Things that happened:
First, a pair of talks. In February I presented on “Contestable AI& Civic Co-Design” as part of a panel chaired by Roy Bendor at Reinventing the City. A PDF of my slides is available on the contestable.ai website, here. In March, I presented at the AiTech Agora. The title of the talk is “Meaningful Human Control Through Contestability by Design” and the slides are available here.
In February a short interview was published by Bold Cities, a smart city research center I am loosely affiliated with.
Then, in March, came a big moment for me, with the publication of my first journal article in AI& Society. Here’s the abstract, and reference. It’s available open access.
The increasing use of artificial intelligence (AI) by public actors has led to a push for more transparency. Previous research has conceptualized AI transparency as knowledge that empowers citizens and experts to make informed choices about the use and governance of AI. Conversely, in this paper, we critically examine if transparency-as-knowledge is an appropriate concept for a public realm where private interests intersect with democratic concerns. We conduct a practice-based design research study in which we prototype and evaluate a transparent smart electric vehicle charge point, and investigate experts’ and citizens’ understanding of AI transparency. We find that citizens experience transparency as burdensome; experts hope transparency ensures acceptance, while citizens are mostly indifferent to AI; and with absent means of control, citizens question transparency’s relevance. The tensions we identify suggest transparency cannot be reduced to a product feature, but should be seen as a mediator of debate between experts and citizens.
Alfrink, Kars, Ianus Keller, Neelke Doorn, and Gerd Kortuem. “Tensions in Transparent Urban AI: Designing a Smart Electric Vehicle Charge Point.” AI&SOCIETY, March 31, 2022. https://doi.org/10/gpszwh.
In April, the Responsible Sensing Lab published a report on “Responsible Drones”, to which I contributed a little as participant on workshops that lead up to it.
Artificial Intelligence (AI) is increasingly used by a variety of organizations in ways that impact society at scale. This 6 EC master elective course aims to equip students with tools and methods for the responsible design of public AI. During seven weeks students attend a full-day session of lectures and workshops. Students collaborate on a group design project throughout. At the end, students individually deliver a short paper.
The third big milestone was the publication of my second journal article in Minds & Machines. It is the theoretical cornerstone of my thesis, a provisional framework for designing contestability into AI systems. Abstract and reference follow. This one is also open access.
As the use of AI systems continues to increase, so do concerns over their lack of fairness, legitimacy and accountability. Such harmful automated decision-making can be guarded against by ensuring AI systems are contestable by design: responsive to human intervention throughout the system lifecycle. Contestable AI by design is a small but growing field of research. However, most available knowledge requires a significant amount of translation to be applicable in practice. A proven way of conveying intermediate-level, generative design knowledge is in the form of frameworks. In this article we use qualitative-interpretative methods and visual mapping techniques to extract from the literature sociotechnical features and practices that contribute to contestable AI, and synthesize these into a design framework.
Alfrink, Kars, Ianus Keller, Gerd Kortuem, and Neelke Doorn. “Contestable AI by Design: Towards a Framework.” Minds and Machines, August 13, 2022. https://doi.org/10/gqnjcs.
And finally, as these things were going on, I have been quietly chipping away at a third paper that applies the contestable AI by design framework to the phenomenon of camera cars used by municipalities. My aim was to create an example of what I mean by contestable AI, and use the example to interview civil servants about their views on the challenges facing implementation of contestability in the public AI systems they are involved with. I’ve submitted the manuscript, titled “Contestable Camera Cars: A speculative design exploration of public AI that is open and responsive to dispute”, to CHI, and will hear back early November. Fingers crossed for that one.
So what’s next? Well, I have little under a year left on my PhD contract, so I should really begin wrapping up. I am considering a final publication, but have not settled on any topic in particular yet. Current interests include AI system monitoring, visual methods, and more besides. Once that final paper is in the can I will turn my attention to putting together the thesis itself, which is paper-based, so mostly requires writing an overall introduction and conclusion to bookend the included publications. Should be a piece of cake, right?
And after the PhD? I am not sure yet, but I hope to remain involved in research and teaching, while at the same time perhaps getting a bit more back into design practice besides. If at all possible, hopefully in the domain of public sector applications of AI.
That’s it for this update. I will be back at some point when there is more news to share.
It has been three years since I last wrote an update on my PhD. I guess another post is in order.
My PhD plan was formally green-lit in October 2019. I am now over three years into this thing. There are roughly two more years left on the clock. I update my plans on a rolling basis. By my latest estimation, I should be ready to request a date for my defense in May 2023.
Of course, the pandemic forced me to adjust course. I am lucky enough not to be locked into particular methods or cases that are fundamentally incompatible with our current predicament. But still, I had to change up my methods, and reconsider the sequencing of my planned studies.
The conference paper I mentioned in the previous update, using the MX3D bridge to explore smart cities’ logic of control and cityness, was rejected by DIS. I performed a rewrite, but then came to the conclusion it was kind of a false start. These kinds of things are all in the game, of course.
The second paper I wrote uses the Transparent Charging Station to investigate how notions of transparent AI differ between experts and citizens. It was finally accepted late last year and should see publication in AI& Society soon. It is titled Tensions in Transparent Urban AI: Designing A Smart Electric Vehicle Charge Point. This piece went through multiple major revisions and was previously rejected by DIS and CHI.
A third paper, Contestable AI by Design: Towards A Framework, uses a systematic literature review of AI contestability to construct a preliminary design framework, is currently under review at a major philosophy of technology journal. Fingers crossed.
And currently, I am working on my fourth publication, tangentially titled Contestable Camera Cars: A Speculative Design Exploration of Public AI Systems Responsive to Value Change, which will be based on empirical work that uses speculative design as a way to develop guidelines and examples for the aforementioned design framework, and to investigate civil servants’ views on the pathways towards contestable AI systems in public administration.
Once that one is done, I intend to do one more study, probably looking into monitoring and traceability as potential leverage points for contestability, after which I will turn my attention to completing my thesis.
Aside from my research, in 2021 was allowed to develop and teach a master elective centered around my PhD topic, titled AI& Society. In it, students are equipped with technical knowledge of AI, and tools for thinking about AI ethics. They apply these to a design studio project focused on conceptualizing a responsible AI-enabled service that addresses a social issue the city of Amsterdam might conceivably struggle with. Students also write a brief paper reflecting on and critiquing their group design work. You can see me on Vimeo do a brief video introduction for students who are considering the course. I will be running the course again this year starting end of February.
I also mentored a number of brilliant master graduation students: Xueyao Wang (with Jacky Bourgeois as chair) Jooyoung Park, Loes Sloetjes (both with Roy Bendor as chair) and currently Fabian Geiser (with Euiyoung Kim as chair). Working with students is one of the best parts of being in academia.
All of the above would not have been possible without the great support from my supervisory team: Ianus Keller, Neelke Doorn and Gerd Kortuem. I should also give special mention to Thijs Turel at AMS Institute’s Responsible Sensing Lab, where most of my empirical work is situated.
If you want to dig a little deeper into some of this, I recently set up a website for my PhD project over at contestable.ai.
Ik had laatst contact met een internationale “thought leader” op het gebied van “tech ethics”. Hij vertelde mij dat hij heel dankbaar is voor het bestaan van de transparante laadpaal omdat het zo’n goed voorbeeld is van hoe design kan bijdragen aan eerlijke technologie.
Dat is natuurlijk ontzettend leuk om te horen. En het past in een bredere trend in de industrie gericht op het transparant en uitlegbaar maken van algoritmes. Inmiddels is het zelfs zo ver dat wetgeving uitlegbaarheid (in sommige gevallen) verplicht stelt.
In de documentaire hoor je meerdere mensen vertellen (mijzelf inbegrepen) waarom het belangrijk is dat stedelijke algoritmes transparant zijn. Thijs benoemt heel mooi twee redenen: Enerzijds het collectieve belang om democratische controle op de ontwikkeling van stedelijke algoritmes mogelijk te maken. Anderzijds is er het individuele belang om je recht te kunnen halen als een systeem een beslissing maakt waarmee je het (om wat voor reden dan ook) niet eens bent.
En inderdaad, in beide gevallen (collectieve controle en individuele remedie) is transparantie een randvoorwaarde. Ik denk dat we met dit project een hoop problemen qua design en techniek hebben opgelost die daarbij komen kijken. Tegelijkertijd doemt er een nieuwe vraag aan de horizon op: Als we begrijpen hoe een slim systeem werkt, en we zijn het er niet mee eens, wat dan? Hoe krijg je vervolgens daadwerkelijk invloed op de werking van het systeem?
Ik denk dat we onze focus zullen moeten gaan verleggen van transparantie naar wat ik tegenspraak of in goed Engels “contestability” noem.
Ontwerpen voor tegenspraak betekent dat we na moeten gaan denken over de middelen die mensen nodig hebben voor het uitoefenen van hun recht op menselijke interventie. Ja, dit betekent dat we informatie moeten aanleveren over het hoe en waarom van individuele beslissingen. Transparantie dus. Maar het betekent ook dat we nieuwe kanalen en processen moeten inrichten waarmee mensen verzoeken kunnen indienen voor het herzien van een beslissing. We zullen na moeten gaan denken over hoe we dergelijke verzoeken beoordelen, en hoe we er voor zorgen dat het slimme systeem in kwestie “leert” van de signalen die we op deze manier oppikken uit de samenleving.
Je zou kunnen zeggen dat ontwerpen van transparantie eenrichtingsverkeer is. Informatie stroomt van de ontwikkelende partij, naar de eindgebruiker. Bij het ontwerpen voor tegenspraak gaat het om het creëren van een dialoog tussen ontwikkelaars en burgers.
Ik zeg burgers want niet alleen klassieke eindgebruikers worden geraakt door slimme systemen. Allerlei andere groepen worden ook, vaak indirect beïnvloed.
Dat is ook een nieuwe ontwerp uitdaging. Hoe ontwerp je niet alleen voor de eindgebruiker (zoals bij de transparante laadpaal de EV bestuurder) maar ook voor zogenaamde indirecte belanghebbenden, bijvoorbeeld bewoners van straten waar laadpalen geplaatst worden, die geen EV rijden, of zelfs geen auto, maar evengoed een belang hebben bij hoe stoepen en straten worden ingericht.
Deze verbreding van het blikveld betekent dat we bij het ontwerpen voor tegenspraak nóg een stap verder kunnen en zelfs moeten gaan dan het mogelijk maken van remedie bij individuele beslissingen.
Want ontwerpen voor tegenspraak bij individuele beslissingen van een reeds uitgerold systeem is noodzakelijkerwijs post-hoc en reactief, en beperkt zich tot één enkele groep belanghebbenden.
Zoals Thijs ook min of meer benoemt in de documentaire beïnvloed slimme stedelijke infrastructuur de levens van ons allemaal, en je zou kunnen zeggen dat de design en technische keuzes die bij de ontwikkeling daarvan gemaakt worden intrinsiek ook politieke keuzes zijn.
Daarom denk ik dat we er niet omheen kunnen om het proces dat ten grondslag ligt aan deze systemen zelf, ook zo in te richten dat er ruimte is voor tegenspraak. In mijn ideale wereld is de ontwikkeling van een volgende generatie slimme laadpalen daarom participatief, pluriform en inclusief, net als onze democratie dat zelf ook streeft te zijn.
Hoe we dit soort “contestable” algoritmes precies vorm moeten geven, hoe ontwerpen voor tegenspraak moeten gaan werken, is een open vraag. Maar een aantal jaren geleden wist niemand nog hoe een transparante laadpaal er uit zou moeten zien, en dat hebben we ook voor elkaar gekregen.
I’ll be at Beyond Smart Cities Today the next couple of days (18–19 September). Below is the abstract I submitted, plus a bibliography of some of the stuff that went into my thinking for this and related matters that I won’t have the time to get into.
In the actually existing smart city, algorithmic systems are increasingly used for the purposes of automated decision-making, including as part of public infrastructure. Algorithmic systems raise a range of ethical concerns, many of which stem from their opacity. As a result, prescriptions for improving the accountability, trustworthiness and legitimacy of algorithmic systems are often based on a transparency ideal. The thinking goes that if the functioning and ownership of an algorithmic system is made perceivable, people understand them and are in turn able to supervise them. However, there are limits to this approach. Algorithmic systems are complex and ever-changing socio-technical assemblages. Rendering them visible is not a straightforward design and engineering task. Furthermore such transparency does not necessarily lead to understanding or, crucially, the ability to act on this understanding. We believe legitimate smart public infrastructure needs to include the possibility for subjects to articulate objections to procedures and outcomes. The resulting “contestable infrastructure” would create spaces that open up the possibility for expressing conflicting views on the smart city. Our project is to explore the design implications of this line of reasoning for the physical assets that citizens encounter in the city. Because after all, these are the perceivable elements of the larger infrastructural systems that recede from view.
Alkhatib, A., & Bernstein, M. (2019). Street-Level Algorithms. 1–13. https://doi.org/10.1145/3290605.3300760
Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media and Society, 20(3), 973–989. https://doi.org/10.1177/1461444816676645
Centivany, A., & Glushko, B. (2016). “Popcorn tastes good”: Participatory policymaking and Reddit’s “AMAgeddon.” Conference on Human Factors in Computing Systems — Proceedings, 1126–1137. https://doi.org/10.1145/2858036.2858516
Crawford, K. (2016). Can an Algorithm be Agonistic? Ten Scenes from Life in Calculated Publics. Science Technology and Human Values, 41(1), 77–92. https://doi.org/10.1177/0162243915589635
DiSalvo, C. (2010). Design, Democracy and Agonistic Pluralism. Proceedings of the Design Research Society Conference, 366–371.
Hildebrandt, M. (2017). Privacy As Protection of the Incomputable Self: Agonistic Machine Learning. SSRN Electronic Journal, 1–33. https://doi.org/10.2139/ssrn.3081776
Jackson, S. J., Gillespie, T., & Payette, S. (2014). The Policy Knot: Re-integrating Policy, Practice and Design. CSCW Studies of Social Computing, 588–602. https://doi.org/10.1145/2531602.2531674
Jewell, M. (2018). Contesting the decision: living in (and living with) the smart city. International Review of Law, Computers and Technology. https://doi.org/10.1080/13600869.2018.1457000
Lindblom, L. (2019). Consent, Contestability, and Unions. Business Ethics Quarterly. https://doi.org/10.1017/beq.2018.25
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 205395171667967. https://doi.org/10.1177/2053951716679679
Van de Poel, I. (2016). An ethical framework for evaluating experimental technology. Science and Engineering Ethics, 22(3), 667–686. https://doi.org/10.1007/s11948-015‑9724‑3
Thijs Turèl of AMS Institute and myself presented a version of the talk below at the Cities for Digital Rights conference on June 19 in Amsterdam during the We Make the City festival. The talk is an attempt to articulate some of the ideas we both have been developing for some time around contestability in smart public infrastructure. As always with this sort of thing, this is intended as a conversation piece so I welcome any thoughts you may have.
The basic message of the talk is that when we start to do automated decision-making in public infrastructure using algorithmic systems, we need to design for the inevitable disagreements that may arise and furthermore, we suggest there is an opportunity to focus on designing for such disagreements in the physical objects that people encounter in urban space as they make use of infrastructure.
We set the scene by showing a number of examples of smart public infrastructure. A cyclist crossing that adapts to weather conditions. If it’s raining cyclists more frequently get a green light. A pedestrian crossing in Tilburg where elderly can use their mobile to get more time to cross. And finally, the case we are involved with ourselves: smart EV charging in the city of Amsterdam, about which more later.
We identify three trends in smart public infrastructure: (1) where previously algorithms were used to inform policy, now they are employed to perform automated decision-making on an individual case basis. This raises the stakes; (2) distributed ownership of these systems as the result of public-private partnerships and other complex collaboration schemes leads to unclear responsibility; and finally (3) the increasing use of machine learning leads to opaque decision-making.
These trends, and algorithmic systems more generally, raise a number of ethical concerns. They include but are not limited to: the use of inductive correlations (for example in the case of machine learning) leads to unjustified results; lack of access to and comprehension of a system’s inner workings produces opacity, which in turn leads to a lack of trust in the systems themselves and the organisations that use them; bias is introduced by a number of factors, including development team prejudices, technical flaws, bad data and unforeseen interactions with other systems; and finally the use of profiling, nudging and personalisation leads to diminished human agency. (We highly recommend the article by Mittelstadt et al. for a comprehensive overview of ethical concerns raised by algorithms.)
So for us, the question that emerges from all this is: How do we organise the supervision of smart public infrastructure in a democratic and lawful way?
There are a number of existing approaches to this question. These include legal and regulatory (e.g. the right to explanation in the GDPR); auditing (e.g. KPMG’s “AI in Control” method, BKZ’s transparantielab); procurement (e.g. open source clauses); insourcing (e.g. GOV.UK) and design and engineering (e.g. our own work on the transparent charging station).
We feel there are two important limitations with these existing approaches. The first is a focus on professionals and the second is a focus on prediction. We’ll discuss each in turn.
First of all, many solutions target a professional class, be it accountants, civil servants, supervisory boards, as well as technologists, designers and so on. But we feel there is a role for the citizen as well, because the supervision of these systems is simply too important to be left to a privileged few. This role would include identifying wrongdoing, and suggesting alternatives.
There is a tension here, which is that from the perspective of the public sector one should only ask citizens for their opinion when you have the intention and the resources to actually act on their suggestions. It can also be a challenge to identify legitimate concerns in the flood of feedback that can sometimes occur. From our point of view though, such concerns should not be used as an excuse to not engage the public. If citizen participation is considered necessary, the focus should be on freeing up resources and setting up structures that make it feasible and effective.
The second limitation is prediction. This is best illustrated with the Collinridge dilemma: in the early phases of new technology, when a technology and its social embedding are still malleable, there is uncertainty about the social effects of that technology. In later phases, social effects may be clear but then often the technology has become so well entrenched in society that it is hard to overcome negative social effects. (This summary is taken from an excellent van de Poel article on the ethics of experimental technology.)
Many solutions disregard the Collingridge dilemma and try to predict and prevent adverse effects of new systems at design-time. One example of this approach would be value-sensitive design. Our focus in stead is on use-time. Considering the fact that smart public infrastructure tends to be developed on an ongoing basis, the question becomes how to make citizens a partner in this process. And even more specifically we are interested in how this can be made part of the design of the “touchpoints” people actually encounter in the streets, as well as their backstage processes.
Why do we focus on these physical objects? Because this is where people actually meet the infrastructural systems, of which large parts recede from view. These are the places where they become aware of their presence. They are the proverbial tip of the iceberg.
The use of automated decision-making in infrastructure reduces people’s agency. For this reason, resources for agency need to be designed back into these systems. Frequently the answer to this question is premised on a transparency ideal. This may be a prerequisite for agency, but it is not sufficient. Transparency may help you become aware of what is going on, but it will not necessarily help you to act on that knowledge. This is why we propose a shift from transparency to contestability. (We can highly recommend Ananny and Crawford’s article for more on why transparency is insufficient.)
To clarify what we mean by contestability, consider the following three examples: When you see the lights on your router blink in the middle of the night when no-one in your household is using the internet you can act on this knowledge by yanking out the device’s power cord. You may never use the emergency brake in a train but its presence does give you a sense of control. And finally, the cash register receipt provides you with a view into both the procedure and the outcome of the supermarket checkout procedure and it offers a resource with which you can dispute them if something appears to be wrong.
None of these examples is a perfect illustration of contestability but they hint at something more than transparency, or perhaps even something wholly separate from it. We’ve been investigating what their equivalents would be in the context of smart public infrastructure.
To illustrate this point further let us come back to the smart EV charging project we mentioned earlier. In Amsterdam, public EV charging stations are becoming “smart” which in this case means they automatically adapt the speed of charging to a number of factors. These include grid capacity, and the availability of solar energy. Additional factors can be added in future, one of which under consideration is to give priority to shared cars over privately owned cars. We are involved with an ongoing effort to consider how such charging stations can be redesigned so that people understand what’s going on behind the scenes and can act on this understanding. The motivation for this is that if not designed carefully, the opacity of smart EV charging infrastructure may be detrimental to social acceptance of the technology. (A first outcome of these efforts is the Transparent Charging Station designed by The Incredible Machine. A follow-up project is ongoing.)
We have identified a number of different ways in which people may object to smart EV charging. They are listed in the table below. These types of objections can lead us to feature requirements for making the system contestable.
Because the list is preliminary, we asked the audience if they could imagine additional objections, if those examples represented new categories, and if they would require additional features for people to be able to act on them. One particularly interesting suggestion that emerged was to give local communities control over the policies enacted by the charge points in their vicinity. That’s something to further consider the implications of.
And that’s where we left it. So to summarise:
Algorithmic systems are becoming part of public infrastructure.
Smart public infrastructure raises new ethical concerns.
Many solutions to ethical concerns are premised on a transparency ideal, but do not address the issue of diminished agency.
There are different categories of objections people may have to an algorithmic system’s workings.
Making a system contestable means creating resources for people to object, opening up a space for the exploration of meaningful alternatives to its current implementation.
After posting the list of engineering ethics readings it occurred to me I also have a really nice collection of things to read from a course on research through design taught by Pieter Jan Stappers, which I took earlier this year. I figured some might get some use out of it and I like having it for my own reference here as well.
The backbone for this course is the chapter on research through design by Stappers and Giaccardi in the encyclopedia of human-computer interaction, which I highly recommend.
All of the readings below are referenced in that chapter. I’ve read some, quickly gutted others for meaning and the remainder is still on my to-read list. For me personally, the things on annotated portfolios and intermediate-level knowledge by Gaver and Löwgren were the most immediately useful and applicable. I’d read the Zimmerman paper earlier and although it’s pretty concrete in its prescriptions I did not really latch on to it.
Brandt, Eva, and Thomas Binder. “Experimental design research: genealogy, intervention, argument.” International Association of Societies of Design Research, Hong Kong 10 (2007).
Gaver, Bill, and John Bowers. “Annotated portfolios.” interactions 19.4 (2012): 40–49.
Gaver, William. “What should we expect from research through design?.” Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 2012.
Löwgren, Jonas. “Annotated portfolios and other forms of intermediate-level knowledge.” Interactions 20.1 (2013): 30–34.
Stappers, Pieter Jan, F. Sleeswijk Visser, and A. I. Keller. “The role of prototypes and frameworks for structuring explorations by research through design.” The Routledge Companion to Design Research (2014): 163–174.
Stappers, Pieter Jan. “Meta-levels in Design Research.”
Stappers, Pieter Jan. “Prototypes as central vein for knowledge development.” Prototype: Design and craft in the 21st century (2013): 85–97.
Wensveen, Stephan, and Ben Matthews. “Prototypes and prototyping in design research.” The Routledge Companion to Design Research. Taylor & Francis (2015).
Zimmerman, John, Jodi Forlizzi, and Shelley Evenson. “Research through design as a method for interaction design research in HCI.” Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 2007.
Bonus level: several items related to “muddling through”…
Flach, John M., and Fred Voorhorst. “What matters?: Putting common sense to work.” (2016).
Lindblom, Charles E. “Still Muddling, Not Yet Through.” Public Administration Review 39.6 (1979): 517–26.
Lindblom, Charles E. “The science of muddling through.” Public Administration Review 19.2 (1959): 79–88.
I recently followed an excellent three-day course on engineering ethics. It was offered by the TU Delft graduate school and taught by Behnam Taibi with guest lectures from several of our faculty.
I found it particularly helpful to get some suggestions for further reading that represent some of the foundational ideas in the field. I figured it would be useful to others as well to have a pointer to them.
So here they are. I’ve quickly gutted these for their meaning. The one by Van de Poel I did read entirely and can highly recommend for anyone who’s doing design of emerging technologies and wants to escape from the informed consent conundrum.
I intend to dig into the Doorn one, not just because she’s one of my promoters but also because resilience is a concept that is closely related to my own interests. I’ll also get into the Floridi one in detail but the concept of information quality and the care ethics perspective on the problem of information abundance and attention scarcity I found immediately applicable in interaction design.
Stilgoe, Jack, Richard Owen, and Phil Macnaghten. “Developing a framework for responsible innovation.” Research Policy 42.9 (2013): 1568–1580.
Van den Hoven, Jeroen. “Value sensitive design and responsible innovation.” Responsible innovation (2013): 75–83.
Hansson, Sven Ove. “Ethical criteria of risk acceptance.” Erkenntnis 59.3 (2003): 291–309.
Van de Poel, Ibo. “An ethical framework for evaluating experimental technology.” Science and engineering ethics22.3 (2016): 667–686.
Hansson, Sven Ove. “Philosophical problems in cost–benefit analysis.” Economics & Philosophy 23.2 (2007): 163–183.
Floridi, Luciano. “Big Data and information quality.” The philosophy of information quality. Springer, Cham, 2014. 303–315.
Doorn, Neelke, Paolo Gardoni, and Colleen Murphy. “A multidisciplinary definition and evaluation of resilience: The role of social justice in defining resilience.” Sustainable and Resilient Infrastructure (2018): 1–12.
We also got a draft of the intro chapter to a book on engineering and ethics that Behnam is writing. That looks very promising as well but I can’t share yet for obvious reasons.
In this workshop we will take a deep dive into some of the challenges of designing smart public infrastructure.
Smart city ideas are moving from hype into reality. The everyday things that our contemporary world runs on, such as roads, railways and canals are not immune to this development. Basic, “hard” infrastructure is being augmented with internet-connected sensing, processing and actuating capabilities. We are involved as practitioners and researchers in one such project: the MX3D smart bridge, a pedestrian bridge 3D printed from stainless steel and equipped with a network of sensors.
The question facing everyone involved with these developments, from citizens to professionals to policy makers is how to reap the potential benefits of these technologies, without degrading the urban fabric. For this to happen, information technology needs to become more like the city: open-ended, flexible and adaptable. And we need methods and tools for the diverse range of stakeholders to come together and collaborate on the design of truly intelligent public infrastructure.
We will explore these questions in this workshop by first walking you through the architecture of the MX3D smart bridge—offering a uniquely concrete and pragmatic view into a cutting edge smart city project. Subsequently we will together explore the question: What should a smart pedestrian bridge that is aware of itself and its surroundings be able to tell us? We will conclude by sharing some of the highlights from our conversation, and make note of particularly thorny questions that require further work.
The workshop’s structure was quite simple. After a round of introductions, Alec introduced the MX3D bridge to the participants. For a sense of what that introduction talk was like, I recommend viewing this recording of a presentation he delivered at a recent Pakhuis de Zwijger event.
We then ran three rounds of group discussion in the style of world cafe. each discussion was guided by one question. Participants were asked to write, draw and doodle on the large sheets of paper covering each table. At the end of each round, people moved to another table while one person remained to share the preceding round’s discussion with the new group.
The discussion questions were inspired by value-sensitive design. I was interested to see if people could come up with alternative uses for a sensor-equipped 3D-printed footbridge if they first considered what in their opinion made a city worth living in.
The questions we used were:
What specific things do you like about your town? (Places, things to do, etc. Be specific.)
What values underly those things? (A value is what a person or group of people consider important in life.)
How would you redesign the bridge to support those values?
At the end of the three discussion rounds we went around to each table and shared the highlights of what was produced. We then had a bit of a back and forth about the outcomes and the workshop approach, after which we wrapped up.
We did get to some interesting values by starting from personal experience. Participants came from a variety of countries and that was reflected in the range of examples and related values. The design ideas for the bridge remained somewhat abstract. It turned out to be quite a challenge to make the jump from values to different types of smart bridges. Despite this, we did get nice ideas such as having the bridge report on water quality of the canal it crosses, derived from the value of care for the environment.
The response from participants afterwards was positive. People found it thought-provoking, which was definitely the point. People were also eager to learn even more about the bridge project. It remains a thing that captures people’s imagination. For that reason alone, it continues to be a very productive case to use for the grounding of these sorts of discussions.