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Zoekresultaat: 5 artikelen

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Jaar 2020 x
Thema-artikel

Verantwoorde algoritmisering: zorgen waardengevoeligheid en transparantie voor meer vertrouwen in algoritmische besluitvorming?

Tijdschrift Bestuurskunde, Aflevering 4 2020
Trefwoorden algorithms, algorithmization, value-sensitivity, transparency, trust
Auteurs Dr. Stephan Grimmelikhuijsen en Prof. dr. Albert Meijer
SamenvattingAuteursinformatie

    Algorithms are starting to play an increasingly prominent role in government organizations. The argument is that algorithms can make more objective and efficient decisions than humans. At the same time, recent scandals have highlighted that there are still many problems connected to algorithms in the public sector. There is an increasing emphasis on ethical requirements for algorithms and we aim to connect these requirements to insights from public administration on the use of technologies in the public sector. We stress the need for responsible algorithmization – responsible organizational practices around the use of algorithms – and argue that this is needed to maintain the trust of citizens. We present two key components of responsible algorithmization – value-sensitivity and transparency – and show how these components connect to algorithmization and can contribute to citizen trust. We end the article with an agenda for research into the relation between responsible algorithmization and trust.


Dr. Stephan Grimmelikhuijsen
Dr. S.G. Grimmelikhuijsen is universitair hoofddocent Publiek Management aan de Universiteit Utrecht, Departement Bestuurs- en Organisatiewetenschap.

Prof. dr. Albert Meijer
Prof. dr. A.J. Meijer is hoogleraar Publiek Management aan de Universiteit Utrecht, Departement Bestuurs- en Organisatiewetenschap.
Thema-artikel

Access_open Transparantie van algoritmen: naar een empirische onderzoeksagenda

Tijdschrift Bestuurskunde, Aflevering 4 2020
Auteurs Dr. Haiko van der Voort en Joanna Strycharz Msc
Auteursinformatie

Dr. Haiko van der Voort
Dr. H.G. van der Voort is universitair docent Organisatie & Governance aan de TU Delft, Faculteit Techniek, Bestuur en Management.

Joanna Strycharz Msc
J. Strycharz, Msc is universitair docent Persuasive Communication aan de Universiteit van Amsterdam, Faculteit Maatschappij- en Gedragswetenschappen.
Thema-artikel

Een transparant debat over algoritmen

Tijdschrift Bestuurskunde, Aflevering 4 2020
Trefwoorden AI, ethics, Big Data, human rights, governance
Auteurs Dr. Oskar J. Gstrein en Prof. dr. Andrej Zwitter
SamenvattingAuteursinformatie

    The police use all sorts of information to fulfil their tasks. Whereas collection and interpretation of information traditionally could only be done by humans, the emergence of ‘Big Data’ creates new opportunities and dilemmas. On the one hand, large amounts of data can be used to train algorithms. This allows them to ‘predict’ offenses such as bicycle theft, burglary, or even serious crimes such as murder and terrorist attacks. On the other hand, highly relevant questions on purpose, effectiveness, and legitimacy of the application of machine learning/‘artificial intelligence’ drown all too often in the ocean of Big Data. This is particularly problematic if such systems are used in the public sector in democracies, where the rule of law applies, and where accountability, as well as the possibility for judicial review, are guaranteed. In this article, we explore the role transparency could play in reconciling these opportunities and dilemmas. While some propose making the systems and data they use themselves transparent, we submit that an open and broad discussion on purpose and objectives should be held during the design process. This might be a more effective way of embedding ethical and legal principles in the technology, and of ensuring legitimacy during application.


Dr. Oskar J. Gstrein
Dr. O.J. Gstrein is universitair docent Governance & Innovation aan de Rijksuniversiteit Groningen, Campus Fryslân, Data Research Centre.

Prof. dr. Andrej Zwitter
Prof. dr. A.J. Zwitter is hoogleraar Governance & Innovation aan de Rijksuniversiteit Groningen, Campus Fryslân, Data Research Centre.

Dr. Bart van der Sloot
Dr. Bart van der Sloot is associate professor aan het Tilburg Institute for Law, Technology and Society (TILT), Tilburg University.
Artikel

Access_open ‘Garbage in, garbage out’

Over predictive policing en vuile data

Tijdschrift Beleid en Maatschappij, Aflevering 3 2020
Trefwoorden dirty data, predictive policing, CAS, discrimination, ethnic profiling
Auteurs Mr. Abhijit Das en Mr. dr. Marc Schuilenburg
SamenvattingAuteursinformatie

    Predictive tools as instruments for understanding and responding to risky behaviour as early as possible are increasingly becoming a normal feature in local and state agencies. A risk that arises from the implementation of these predictive tools is the problem of dirty data. The input of incorrect or illegally obtained information (‘dirty data’) can influence the quality of the predictions used by local and state agencies, such as the police. The article focuses on the risks of dirty data in predictive policing by the Dutch Police. It describes the possibilities to prevent dirty data from being used in predictive policing tools, such as the Criminality Anticipation System (CAS). It concludes by emphasizing the importance of transparency for any serious solution looking to eliminate the use of dirty data in predictive policing.


Mr. Abhijit Das
Mr. Abhijit Das is docent/onderzoeker straf(proces)recht aan de afdeling Strafrecht en Criminologie van de Vrije Universiteit Amsterdam.

Mr. dr. Marc Schuilenburg
Mr. dr. Marc Schuilenburg is universitair docent criminologie aan de afdeling Strafrecht en Criminologie van de Vrije Universiteit Amsterdam.
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