Bibliographic record
Abstract
Over the past twenty years, the smart city vision has gained popularity to the extent that it is now the dominant vision of the future city. Like any vision, however, the smart city holds a particular view on what the good life in the city entails and thereby raises various dilemmas and concerns. In particular, the smart city vision puts important public values at stake by portraying data technologies as neutral instruments towards an uncertain future. To navigate the emerging social and ethical implications of smart cities, citizens need to be included as experts on how they experience the city and what they find important in it. Specifically, we consider citizen engagement to be meaningful when it is embedded in the innovation processes of Responsible Innovation. This governance framework prescribes inclusive, anticipatory, reflexive, and responsive innovation processes to better align emerging technologies to societal wants and needs. Despite numerous citizen engagement initiatives in the smart city, however, citizens are hardly engaged in a meaningful way because the smart city vision makes it difficult to identify what is at stake, to include a broad range of publics, and to connect engagement outcomes to ongoing technological trajectories. The literature suggests that some of these challenges may be addressed with art-based citizen engagement methods. Yet, even though art-based engagement methods are increasingly used to engage citizens on controversial technologies, little is known about how it works and why. The aim of this thesis is, therefore to support Responsible Innovation in the smart city by examining the conditions for, as well as the processes and outcomes of, art-based citizen engagement. To this end, we performed two literature studies and three case studies. The literature studies explored the concept of responsible innovation, and the practice of art-based public engagement, respectively. The case studies followed an action-oriented methodology, which means that we developed and tested various theatre-based interventions in ‘smart city’ Amsterdam together with artists, smart city innovators, and citizens in vulnerable positions. “Art-based” in these case studies mainly takes the form of theatrical interventions, which are complemented with methods from interaction design and social research. In these case studies, the research team members doubled not only as social scientist and public engagement organizer, but also as interaction designer or theatre maker. Our findings suggest that the main contribution of art-based citizen engagement to responsible innovation is to make more tangible what is at stake for whom. In this way, art-based engagement enables the involvement of broader publics, the identification of strained public values, and the articulation of alternative visions of the future. At the same time, art-based engagement makes the challenges of embedding citizen engagement in technological trajectories more pronounced because it highlights the emergent character of citizen engagement as well as the significance of participant experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".