Fr. 159.00

Computer Ethics Across Disciplines - Deborah G. Johnson and Algorithmic Accountability

Anglais · Livre Relié

Expédition généralement dans un délai de 6 à 7 semaines

Description

En savoir plus

This edited volume brings together philosophers and scholars in disparate fields who have engaged in Professor Deborah G. Johnson's body of work throughout her long career.  It appeals to both students and researchers and introduces Johnson's thought to a broader audience.  This text shows how with due to the resurgence of AI research, her work is more relevant than ever.  The volume will help a new generation of scholars benefit from the conceptual insights that Johnson has provided.  Her work on algorithmic accountability sets the tone in particular. Chapters illustrate how combining philosophy of technology across disciplines helps clarify the complex intricacies of AI and societies, in particular the topic of accountability. Other themes covered include moral agency and responsibility, transparency, gender and technology as well as ethics education.

Table des matières

1. Introduction.- 2. Constituting Algorithmic Accountability.- 3. Algorithmic Accountability Gets the Deborah Johnson Treatment.- 4.Johnson s Algorithmic Accountability and Corporate Accountability Dissonance.- 5.Opening the Black Box of AI, Only to Be Disappointed.- 6.The Governance of AI Technologies.- 7.The Nature of Algorithms and their Relation to Accountability.- 8. Prospective Algorithmic Accountability and the Role of the News Media.- 9. Understanding Sociotechnical Systems.

Commentaires des clients

Aucune analyse n'a été rédigée sur cet article pour le moment. Sois le premier à donner ton avis et aide les autres utilisateurs à prendre leur décision d'achat.

Écris un commentaire

Super ou nul ? Donne ton propre avis.

Pour les messages à CeDe.ch, veuillez utiliser le formulaire de contact.

Il faut impérativement remplir les champs de saisie marqués d'une *.

En soumettant ce formulaire, tu acceptes notre déclaration de protection des données.