edoc

Foundations of Artificial Intelligence and Machine Learning

Früh, Alfred and Haux, Dario. (2022) Foundations of Artificial Intelligence and Machine Learning. Weizenbaum Series, 29. Berlin.

[img] PDF - Published Version
Available under License CC BY (Attribution).

573Kb

Official URL: https://edoc.unibas.ch/89766/

Downloads: Statistics Overview

Abstract

Today, artificial intelligence and machine learning play a crucial role in various fields of application. In one way or another, they influence our everyday lives. This current state of affairs and the suggestive power of these terms have triggered fundamental discussions in society. However, the technical basics have not received the attention they deserve - and need. This is especially true from a legal perspective, where groundwork on both the fundamental functionality as well as all the relevant terms surrounding the technology seems to be almost non-existent. This paper aims to fill this gap. We examine the technical background of artificial intelligence and machine learning from an interdisciplinary perspective and aim to develop common definitions that can be used for further research in legal academia. These findings provide a common starting point for a more differentiated treatment of legal (and technical) questions surrounding artificial intelligence and machine learning and allow legal academia to make reliable legal statements as well as to advance legal research in this field.
Faculties and Departments:02 Faculty of Law > Departement Rechtswissenschaften > Fachbereich Privatrecht > Professur für Privatrecht mit Schwerpunkt Life Sciences-Recht und Immaterialgüterrecht (Früh)
UniBasel Contributors:Früh, Alfred and Haux, Dario Henri
Item Type:Other
Publisher:Weizenbaum Institut
ISSN:2748-5587
Number of Pages:25
Note:Publication type according to Uni Basel Research Database: Other publications
Language:English
Identification Number:
edoc DOI:
Last Modified:13 Sep 2022 12:53
Deposited On:13 Sep 2022 12:53

Repository Staff Only: item control page