Judgement-Proof Robots and Artificial Intelligence

A Comparative Law and Economics Approach

de

Éditeur :

Palgrave Macmillan


Paru le : 2020-09-03



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
68,56

Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description

This book addresses the role of public policy in regulating the autonomous artificial intelligence and related civil liability for damage caused by the robots (and any form of artificial intelligence). It is a very timely book, focusing on the consequences of judgment proofness of autonomous decision-making on tort law, risk and safety regulation, and the incentives stemming from these.  This book is extremely important as regulatory endeavours concerning AI are in their infancy at most, whereas the industry’s development is continuing in a strong way. It is an important scientific contribution that will bring scientific objectivity to a, to date, very one-sided academic treatment of legal scholarship on AI.
Pages
153 pages
Collection
n.c
Parution
2020-09-03
Marque
Palgrave Macmillan
EAN papier
9783030536435
EAN PDF
9783030536442

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
2324 Ko
Prix
68,56 €
EAN EPUB
9783030536442

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
369 Ko
Prix
68,56 €

Mitja Kovac is an Associate Professor at the University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia. He is also a visiting lecturer at the Erasmus University Rotterdam, The Netherlands, at University of Ghent, Belgium, at the ISM University of Management and Economics in Vilnius, Lithuania, and at University of Vienna, Austria. He publishes in the fields of comparative contract law and economics, new institutional economics, consumer protection, contract theory and competition law and economics.

Suggestions personnalisées