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dc.contributor.authorSchäfer, Mirko Tobias
dc.contributor.authorClausen, Nelly
dc.contributor.editorWienrich, Carolin
dc.contributor.editorWintersberger, Philipp
dc.contributor.editorWeyers, Benjamin
dc.date.accessioned2021-09-23T10:52:29Z
dc.date.available2021-09-23T10:52:29Z
dc.date.issued2021
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/37408
dc.description.abstractIn public administration, more and more processes are being digitised and data is being used to collect information, determine the probability of events, or directly support the work of civil servants through automated decision-making. This practice offers many opportunities, but also raises a number of issues. The complexity and opacity of datasets, analysis processes, models or proprietary software creates black boxes in public management and calls for checks and balances. Possible harms inflicted through automated decision-making processes, infringement on privacy, autonomy, and the right to information need to be prevented; proportionality, function creep and the competence and capacity of city employees to adequately apply these novel methods are called into question. While there is a lively discourse emphasizing the need for ethics in AI and data practices, many of the available guidelines fall short in providing an applicable framework for responsible data practices. The Utrecht Data School has developed a deliberately dialogic and participatory approach to data ethics. In this paper we show how our tools enable dialogue between different participants in a data or AI project and give concrete examples of the use of our Data Ethics Decision Aid (DEDA) in municipal data and digitisation projects. We argue that participatory research practices for investigating datafication and algorithmization are very much connected to participatory data ethics.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2021 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.subjectData ethics
dc.subjectvalue-sensitive design
dc.subjectaction research
dc.subjecttransdisciplinary methods
dc.titleParticipatory Data Ethicsen
dc.typeText/Conference Poster
dc.pubPlaceBonn
mci.document.qualitydigidoc
mci.conference.sessiontitleMCI-WS06: Partizipative und sozialverantwortliche Technikentwicklung
mci.conference.locationIngolstadt
mci.conference.date5.-8. September 2021
dc.identifier.doi10.18420/muc2021-mci-ws06-316


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