Twitter is a Bad Game : Taming the Machines – Governance and Regulatory Challenges

Link:
  • https://lecture2go.uni-hamburg.de/l2go/-/get/v/48619
Autor/in:
Beteiligte Person:
  • Regionales Rechenzentrum der Universität Hamburg/ MCC/ Lecture2Go
Verlag/Körperschaft:
Universität Hamburg
Erscheinungsjahr:
2021
Medientyp:
Audiovisuell
Schlagwort:
  • Öffentliche Vorlesungen
Beschreibung:
  • About the lecture series Witnessing the harm done by online disinformation campaigns, algorithmic discrimination, and digital surveillance, there are increasing calls for regulation of artificial intelligence and other related digital technologies. Indeed, a recent article in Nature Machine Intelligence reported that there are over 70 sets of principles and guidelines on AI Ethics issued by companies, academic institutions and public organizations around the world in the last five years, which demonstrate the urgency of proper regulation of AI and digital technologies. The governance and regulation of AI and digital technologies, however, cannot be limited to principles and guidelines on AI Ethics. To achieve good AI governance and regulation, there is a variety of challenges: One challenge is how to put principles into practice, and how to coordinate and mediate conflicting principles in concrete contexts. Another challenge is the danger of 'ethics washing', where the implementation of governance and regulatory frameworks is delayed by 'ethical debates' or replaced by the instalment of Ethics Review Boards without clear mandate and supervisory power. There are also questions about power and legitimacy—who get to decide and on what basis the decision is justified. These are some of the questions any satisfactory account of AI governance and regulation must address. The public lecture series invites internationally renowned scholars to explore major questions about the governance and regulation of artificial intelligence and digital technologies.
Beziehungen:
URL https://lecture2go.uni-hamburg.de/l2go/-/get/l/6165
Lizenz:
  • UHH-L2G
Quellsystem:
Lecture2Go UHH

Interne Metadaten
Quelldatensatz
oai:lecture2go.uni-hamburg.de:48619