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Artificial Intelligence and Law

Erschienen in:

01.11.2013

Agile: a problem-based model of regulatory policy making

verfasst von: Alexander Boer, Tom van Engers

Erschienen in: Artificial Intelligence and Law | Ausgabe 4/2013

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Abstract

We understand regulatory policy problems against the backdrop of existing implementations of a regulatory framework. There are argument schemes for proposing a policy and for criticising a proposal, rooted in a shared understanding that there is an existing regulatory framework which is implemented in social structures in society, yet has problems. The problems with the existing implementations may be attributed either to those implementations or to the constraints imposed by the regulatory framework. In this paper we propose that calls for change of regulatory policy, and case-based and statistical evidence produced in support of policy proposals, are based in model-based problem solving activities. This perspective suggests schemes for a good argument pro or con a policy proposal, while avoiding the problem of backing up claims and evidence on the policy level with a conjectural deep model of the policy domain.

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Titel: Agile: a problem-based model of regulatory policy making
verfasst von: Alexander Boer
Tom van Engers
Publikationsdatum: 01.11.2013
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence and Law / Ausgabe 4/2013
Print ISSN: 0924-8463
Elektronische ISSN: 1572-8382
DOI: https://doi.org/10.1007/s10506-013-9144-0

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