Dr. Alexander Boer and Professor Dr. Tom van Engers of the Leibniz Center for Law have published Agile: a problem-based model of regulatory policy making , forthcoming in Artificial Intelligence and Law .
Here is the 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 cona 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.
Filed under: Applications, Articles and papers Tagged: AGILE, Alexander Boer, Artificial intelligence and law, Legal argument schemes, Modeling policy making as problem solving, Modeling regulatory change, Modeling regulatory change as problem solving, Modeling regulatory policy making, Modeling the regulatory process, Modeling the regulatory process as problem solving, Policy modeling, Problem solving models of policy, Problem solving models of policy making, Problem solving models of regulation, Problem-solving models of law, Regulatory argument schemes, Regulatory information systems, Tom van Engers
via Legal Informatics Blog http://legalinformatics.wordpress.com/2013/11/24/boer-and-van-engers-agile-a-problem-based-model-of-regulatory-policy-making/
Niciun comentariu:
Trimiteți un comentariu