(Un)explainable Technology

This book explores the issue of (un)explainable technology. As we face technologies, mostly autonomous, machine-learned algorithms (AI) that elude a seamless explanation on how they work (black boxes), several issues both from an epistemological as well as ethical perspectives emerge. It is thus not surprising that there are plenty of technological attempts in illuminating the black box as well as philosophical efforts in conceptualizing and re- assessing our concepts of an explanation and understanding, as well emerging ethical questions on how to deal with this unexplainable technology. This book thus offers a succinct and comprehensive, opinionated but fair view on the emerging ethical debate on explainability of AI and its relevance for using AI for different more or less sensitive decision-making procedures. As a short book, the goal is to introduce the reader to the issues at hand while also offering normative arguments from different sides that motivate, complicate, and resolve these issues.

Concisely summarizes the dynamic field of AI ethics Offers an accessible, interdisciplinary approach to (un)explainable AI applications Focus on the relevance of using AI for a variety of decision-making procedures

Autorentext

Hendrik Kempt is a Postdoctoral Researcher at the Applied Ethics Group, RWTH Aachen University, where he received his PhD in 2023. His work focuses mainly on questions of the ethics of human-machine interaction, of artificial intelligence and other emerging technologies, and of technology in general. He has previously published the monographs "Chatbots and the Domestication of AI" (2020) as well as "Synthetic Friends - A Philosophy of Human-Machine Friendship" (2022), edited a book with Megan Volpert on "RuPaul's Drag Race and Philosophy", and has written several journal articles and book chapters on the issues of ethics of technology.

Inhalt

Chapter 1: Introduction.- Chapter 2: Conceptual Clarification.- Chapter 3: Epistemological Conditions.- Chapter 4: The Ethics of Explainability.- Chapter 5: Applied Cases.- Chapter 6: Explainability Debunked?.- Chapter 7: Conclusions.