Explainable Agency in Artificial Intelligence: Research and Practice

·
· CRC Press
Libro electrónico
170
Páxinas
Apto

Acerca deste libro electrónico

This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from interpretable machine learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users), where the explanations provided by EA agents are best evaluated in the context of human subject studies.

The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems.

Features:

  • Contributes to the topic of explainable artificial intelligence (XAI)
  • Focuses on the XAI subtopic of explainable agency
  • Includes an introductory chapter, a survey, and five other original contributions
This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for...

Descubrir máis

Acerca do autor

Dr. Silvia Tulli is an Assistant Professor at Sorbonne University. She received her Marie Curie ITN research fellowship and completed her Ph.D. at Instituto Superior Técnico. Her research interests lie at the intersection of explainable AI, interactive machine learning, and reinforcement learning.

Dr. David W. Aha (UC Irvine, 1990) serves as the Director of the AI Center at the Naval Research Laboratory in Washington, DC. His research interests include goal reasoning agents, deliberative autonomy, case-based reasoning, explainable AI, machine learning (ML), reproducible studies, and related topics.

Dr. Silvia Tulli is an Assistant Professor at Sorbonne University. She received her Marie Curie ITN research fellowship and completed her Ph.D. at Instituto Superior Técnico. Her research interests lie at the intersection of explainable AI, interactive machine learning, and reinforcement learning...

Valora este libro electrónico

Dános a túa opinión.

Información de lectura

Smartphones e tabletas
Instala a aplicación Google Play Libros para Android e iPad/iPhone. Sincronízase automaticamente coa túa conta e permíteche ler contido en liña ou sen conexión desde calquera lugar.
Portátiles e ordenadores de escritorio
Podes escoitar os audiolibros comprados en Google Play a través do navegador web do ordenador.
Lectores de libros electrónicos e outros dispositivos
Para ler contido en dispositivos de tinta electrónica, como os lectores de libros electrónicos Kobo, é necesario descargar un ficheiro e transferilo ao dispositivo. Sigue as instrucións detalladas do Centro de axuda para transferir ficheiros a lectores electrónicos admitidos.