What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research

Explainability as a non-functional requirement: challenges and recommendations

(2020) Larissa Chazette et al.   REQUIREMENTS ENGINEERING

Explainability in human–agent systems

(2019) Avi Rosenfeld et al.   AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS

The Pragmatic Turn in Explainable Artificial Intelligence (XAI)

(2019) Andrés Páez   MINDS AND MACHINES

Causability and explainabilty of artificial intelligence in medicine

(2019) Andreas Holzinger et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

A Misdirected Principle with a Catch: Explicability for AI

(2019) Scott Robbins   MINDS AND MACHINES

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Methods for interpreting and understanding deep neural networks

(2018) Grégoire Montavon et al.   DIGITAL SIGNAL PROCESSING

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

The mythos of model interpretability

(2018) Zachary C. Lipton   COMMUNICATIONS OF THE ACM

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Automation Transparency: Implications of Uncertainty Communication for Human-Automation Interaction and Interfaces

(2018) Alexander Kunze et al.   ERGONOMICS

Peeking Inside the Black Box: A New Kind of Scientific Visualization

(2018) Michael T. Stuart et al.   MINDS AND MACHINES

AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations

(2018) Luciano Floridi et al.   MINDS AND MACHINES

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Semantics derived automatically from language corpora contain human-like biases

(2017) Aylin Caliskan et al.   SCIENCE

A systematic review and taxonomy of explanations in decision support and recommender systems

(2017) Ingrid Nunes et al.   USER MODELING AND USER-ADAPTED INTERACTION

From Here to Autonomy

(2016) Mica R. Endsley   HUMAN FACTORS

The social dilemma of autonomous vehicles

(2016) J.-F. Bonnefon et al.   SCIENCE

Providing awareness, explanation and control of personalized filtering in a social networking site

(2015) Sayooran Nagulendra et al.   INFORMATION SYSTEMS FRONTIERS

Understanding phenomena

(2015) Christoph Kelp   SYNTHESE

Trust in Automation

(2014) Kevin Anthony Hoff et al.   HUMAN FACTORS

Functional explaining: a new approach to the philosophy of explanation

(2014) Daniel A. Wilkenfeld   SYNTHESE

Functions in biological kind classification

(2012) Tania Lombrozo et al.   COGNITIVE PSYCHOLOGY

Explanation and prior knowledge interact to guide learning

(2012) Joseph J. Williams et al.   COGNITIVE PSYCHOLOGY

Task complexity: A review and conceptualization framework

(2012) Peng Liu et al.   INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS

Complacency and Bias in Human Use of Automation: An Attentional Integration

(2010) Raja Parasuraman et al.   HUMAN FACTORS

Explanations in Software Engineering: The Pragmatic Point of View

(2010) Jan De Winter   MINDS AND MACHINES

Anticipatory stress influences decision making under explicit risk conditions.

(2008) Katrin Starcke et al.   BEHAVIORAL NEUROSCIENCE

The effects of transparency on trust in and acceptance of a content-based art recommender

(2008) Henriette Cramer et al.   USER MODELING AND USER-ADAPTED INTERACTION