The Public Playground Paradox: "Child’s Joy" or Heterotopia of Fear?

Literature depicts children of the Global North withdrawing from public space to“acceptable islands”. Driven by fears both of and for children, the publicplayground – one such island – provides clear-cut distinctions between childhoodand adulthood. Extending this argument, this paper takes the original approach oftheoretically framing the playground as a heterotopia of deviance, examining –for the first time – three Greek public playground sites in relation to adjacentpublic space. Drawing on an ethnographic study in Athens, findings show fear tounderpin surveillance, control and playground boundary porosity. Normativeclassification as “children’s space” discourages adult engagement. However, in anovel and significant finding, a paradoxical phenomenon sees the playground’spresence simultaneously legitimizing playful behaviour in adjacent public spacefor children and adults. Extended playground play creates alternate orderings andnegotiates norms and hierarchies, suggesting significant wider potential toreconceptualise playground-urban design for an intergenerational public realm

Contestable Artificial Intelligence: Constructive design research for public artificial intelligence systems that are open and responsive to dispute

This thesis investigates the use of artificial intelligence (AI) in public policy execution. To contribute to preserving citizen autonomy, it introduces the concept of ‘contestability’—a system quality that ensures citizens retain control over their lives in the face of AI systems and can influence AI system development. The central research aim is to explore sociotechnical design interventions that enhance the contestability of public AI systems.Utilizing constructive design research, the thesis reports on several studies in which researchers collaborate with design practitioners to create artifacts that function as data generation instruments. Methods encompass interaction design, speculative design, and information design, with case studies in smart electric vehicle charging, urban monitoring camera cars, and fraud risk models, all situated in Amsterdam.Key findings include varying perceptions of AI transparency between citizens and experts, a design framework for contestable AI, challenges in local government implementation, and the metaphors designers use for public AI.The research advocates for integrating citizen feedback into AI systems, promoting dialogue between citizens and system controllers, and enhancing democratic involvement in AI development. It also highlights the importance of design in AI implementation, emphasizing speculative design as a method for generating relevant data and guiding ideation and specification processes.Concluding, the thesis calls for a greater engagement of design researchers and practitioners with political philosophy to understand the democratic implications of their work in AI and related fields.Internet of Thing

Contestable Camera Cars:: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute

Local governments increasingly use artificial intelligence (AI) for automated decision-making. Contestability, making systems responsive to dispute, is a way to ensure they respect human rights to autonomy and dignity. We investigate the design of public urban AI systems for contestability through the example of camera cars: human-driven vehicles equipped with image sensors. Applying a provisional framework for contestable AI, we use speculative design to create a concept video of a contestable camera car. Using this concept video, we then conduct semi-structured interviews with 17 civil servants who work with AI employed by a large northwestern European city. The resulting data is analyzed using reflexive thematic analysis to identify the main challenges facing the implementation of contestability in public AI. We describe how civic participation faces issues of representation, public AI systems should integrate with existing democratic practices, and cities must expand capacities for responsible AI development and operation

Contestable AI by Design: Towards a Framework

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 frameworkInternet of ThingsDesign Conceptualization and CommunicationEthics & Philosophy of Technolog

Designing a Smart Electric Vehicle Charge Point of Algorithmic Transparency: Doing Harm by Doing Good?

The increasing use of algorithms in cities has come under scrutiny. Transparency is widely seen as a way to ensure their fairness and accountability. We investigate how al- gorithmic transparency helps citizens understand smart electric vehicle charge points and how its conception differs between experts and citizens. Using a research-through-design approach we collaborated over a 10-month period with companies and Amsterdam municipality to prototype and evaluate a transparent smart electric vehicle chargepoint. We find that experts believe transparency is pro- duced by truthful information about inputs, processes and outcomes, that this information aids understanding and isactionable. We also find that citizens are indifferent to al-gorithmic decision-making when it serves common interests. Furthermore, transparency invites gaming, createsexpectations of control, and adds to the cognitive burden of an already stressful task. Our findings suggest algorithmic transparency benefits professional stakeholders more thanthe citizens it is claimed to serve.Internet of ThingsEthics & Philosophy of TechnologyDesign Conceptualization and Communicatio

Tensions in transparent urban AI: designing a smart electric vehicle charge point

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.Internet of ThingsDesign Conceptualization and CommunicationEthics & Philosophy of Technolog

Data Underlying the Publication: Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute

Data and materials that accompany the paper "Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute".&nbsp;Applying a provisional framework for contestable AI, we use speculative design to create a concept video of a contestable camera car. Using this concept video, we then conduct semi-structured interviews with 17 civil servants who work with AI employed by a large northwestern European city. The resulting data is analyzed using reflexive thematic analysis to identify the main challenges facing the implementation of contestability in public AI.This study was approved by TU Delft Human Research Ethics Committee.The data consists of:Concept video design brief (PDF)Concept video script (PDF)Concept video storyboards (PNG)Concept video (MP4)Expert assessment interview guide (PDF)Expert assessment grading form (PDF)Expert assessment completed grading forms (PDF)Expert assessment tabulated scores (XLSX)Expert assessment informal analysis report (PDF)Civil servant interviews guide (PDF)Civil servant interviews summaries (TXT)Civil servant interviews code book (PDF)</ol

Data Underlying the Publication: Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute

Data and materials that accompany the paper "Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute".&nbsp;Applying a provisional framework for contestable AI, we use speculative design to create a concept video of a contestable camera car. Using this concept video, we then conduct semi-structured interviews with 17 civil servants who work with AI employed by a large northwestern European city. The resulting data is analyzed using reflexive thematic analysis to identify the main challenges facing the implementation of contestability in public AI.This study was approved by TU Delft Human Research Ethics Committee.The data consists of:Concept video design brief (PDF)Concept video script (PDF)Concept video storyboards (PNG)Concept video (MP4)Expert assessment interview guide (PDF)Expert assessment grading form (PDF)Expert assessment completed grading forms (PDF)Expert assessment tabulated scores (XLSX)Expert assessment informal analysis report (PDF)Civil servant interviews guide (PDF)Civil servant interviews summaries (TXT)Civil servant interviews code book (PDF)</ol

Data Underlying the Publication: Contestable AI by Design: Towards a Framework

Data and materials that accompany the article "Contestable AI by Design: Towards A Framework". Consists of an export of articles with inclusion decisions and reasons from systematic review software Rayyan; and an export of the codebook from qualitative analysis software Atlas.ti. Files appended with "-revision" relate to major revision of the original manuscript.</p