18 research outputs found
“Hey SyRI, tell me about algorithmic accountability”: Lessons from a landmark case
No full textThe promised merits of data-driven innovation in general and algorithmic systems in particular hardly need enumeration. However, as decision-making tasks are increasingly delegated to algorithmic systems, this raises questions about accountability. These pressing questions of algorithmic accountability, particularly with regard to data-driven innovation in the public sector, deserve ample scholarly attention. Therefore, this paper brings together perspectives from governance studies and critical algorithm studies to assess how algorithmic accountability succeeds or falls short in practice and analyses the Dutch System Risk Indication (SyRI) as an empirical case. Dissecting a concrete case teases out to which degree archetypical accountability practices and processes function in relation to algorithmic decision-making processes, and which new questions concerning algorithmic accountability emerge therein. The case is approached through the analysis of “scavenged” material. It was found that while these archetypical accountability processes and practices can be incredibly productive in dealing with algorithmic systems they are simultaneously at risk. The current accountability configurations hinge predominantly on the ex ante sensitivity and responsiveness of the political fora. When these prove insufficient, mitigation in medias res/ex post is very difficult for other actants. In part, this is not a new phenomenon, but it is amplified in relation to algorithmic systems. Different fora ask different kinds of medium-specific questions to the actor, from different perspectives with varying power relations. These algorithm-specific considerations relate to the decision-making around an algorithmic system, their functionality, and their deployment. Strengthening ex ante political accountability fora to these algorithm-specific considerations could help mitigate this
Making Sense of the Data-driven: SETUP’s Algorithmic History Museum and Its Relevance for Contemporary Reflection
No full textReview of The Algorithmic History Museum, an installation created by SETUP. It was on display at the Dutch Design Week 2017 (21– 29 October 2017, Eindhoven, the Netherlands)
Responsible data science is a responsibility for all
No full textIn a collaboration between TU Delft and Utrecht University, the authors recently wrote a qualitative study on the gap between regulatory (ethical and legal) frameworks and the daily practices of data professionals. This People of Data highlights the importance of collaboration in the success of interdisciplinary research and the responsibility of data scientists in safeguarding the public and ethical values.Organisation & Governanc
Paper vs. Practice?: How legal and ethical frameworks influence public sector data professionals in the Netherlands
No full textRecent years have seen a massive growth in ethical and legal frameworks to govern data science practices. Yet one of the core questions associated with ethical and legal frameworks is the extent to which they are implemented in practice. A particularly interesting case in this context comes to public officials, for whom higher standards typically exist. We are thus trying to understand how ethical and legal frameworks influence the everyday practices on data and algorithms of public sector data professionals. The following paper looks at two cases: public sector data professionals (1) at municipalities in the Netherlands and (2) at the Netherlands Police. We compare these two cases based on an analytical research framework we develop in this article to help understanding of everyday professional practices. We conclude that there is a wide gap between legal and ethical governance rules and the everyday practices.Organisation & Governanc
Approaching data visualizations as interfaces : An empirical demonstration of how data are imag(in)ed
No full textThis chapter points out data visualization’s double role as explorative and communicative means in humanities research. We draw from science and technology studies looking at the mediation process at stake: the interaction between visualization tool and researcher. To emphasize this mediation process and expose the various decisions at its heart we introduce the term ‘data interface’. We highlight how visualizations function as data interfaces and visualization practices allow for interfacing with data biographing a network graph’s ‘life’. Using the lens of the ‘data interface’ underscores that a particular (network) visualization provides just one perspective on the data. Moreover, we examine if and how the used data interfaces encourage scholars to critically position their investigative work, during research processes and communication
Tool criticism and the computational turn: A 'Methodological Moment' in Media and Communication Studies
No full textAs ever more data becomes available to work with, the use of digital tools within thehumanities and social sciences is becoming increasingly common. These digital tools areoften imported from other institutional contexts and were originally developed for otherpurposes. They may harbour concepts and techniques that stand in tension with traditionsin the humanities and social sciences. Moreover, there are many easy-to-use tools for thecollection, processing and analysis of data that require no knowledge of their limitations.Problematically, these tools are often assigned such values as reliability and transparencywhen in fact they are active mediators caught up in the epistemic process. In this paper,we highlight the need for a critical, reflexive attitude toward the tools we use in digitalmethods. It is a plea for what we call “tool criticism” and an attempt to think throughwhat this mode of criticism would entail in practice for the academic field. The need fortool criticism is contextualised in view of the emerging ideological and methodologicalcritique toward digital methods. Touching on the so-called science wars we exploreknowledge as a construction and consider the importance of accounting for knowledgeclaims. These considerations open up an assessment of the accountability measures thatare being discussed and developed in our field by individuals and institutions alike. Inconclusion, we underscore the urgency of this endeavour and its vital role for media andcommunication scholars
Data, algorithms, text, critical data literacies, identity
No full textIn recent years, a debate has emerged around the question which data competencies students in higher education need in order to be able to adequately study contemporary social and cultural phenomena. Answers to this question depend on contributors’ perspectives, and range from basic and more instrumental (e.g. the ability to operationalize data for research or argumentation) to more complex and reflexive (e.g. to assess how data and its assemblages areepistemically, politically, or ethically ‘entangled’). In this paper, we zoom in on the latter type of competencies, approaching them from a pedagogical angle. More specifically, we look at practices of ‘data walking’, exploring their affordances as a means for creating awareness of, and inciting reflection on, how data are (unnoticeably) embedded in the spaces we inhabit, and what this implies for how we live our lives and understand our world. To this end, we survey four walking varieties, paying particular attention to how they align with the objectives of the scholarly field of Critical Data Studies (CDS). In doing so, we highlight the particular educational merits of each method, but also try to round out what sort of competencies a CDS requires
Exposing Civic Normativity: Applying the Persona-Based Walkthrough Method to the Dutch Happiness Meter
No full textThis study analyzes the Dutch Happiness Meter (HM) – a digital tool employed by the government to quantify citizens’ happiness – through the lens of critical data studies. We introduce the “persona-based walkthrough method” to explore the HM’s algorithmic underpinnings and its socio technical construction of happiness. By navigating diverse personas through the HM’s interface, we answer the following questions: RQ1: How does the Dutch Happiness Meter (HM) embed socio-cultural norms and biases within its algorithmic design, and how do these translate to the quantification and representation of citizen happiness across diverse demographic groups? RQ2: How does the persona-based walkthrough method reveal the limitations and exclusions of black-boxed e-government applications such as the Happiness Meter, and how can this method contribute to algorithmic accountability and transparency in digital governance? and RQ3: What are the implications of datafying subjective well-being through tools like the Happiness Meter on public perceptions of happiness, and how does algorithmic governance influence the epistemologies of well-being in the context of policy-making and societal inclusion? The analysis untangles cultural and computational synergies, examining their influence on civic normativity and quantified well-being. Our contribution shows how such data-driven systems construct a normative understanding of happiness which impacts governmental strategies and public accountability. The findings reveal critical insights into the underlying assumptions and biases in the HM, particularly how socio-technical systems shape user experience and influence perceptions of well-being. By employing personas, especially “anti-personas”, the study exposes civic normativity as mechanisms of exclusions and inequality. This study aims to contribute to discussions on digital governance’s role in shaping societal perceptions of well-being, highlighting the need for algorithmic accountability, transparency and inclusivity in algorithmic e-governmental infrastructures
