A historical perspective of explainable Artificial Intelligence
Abstract Explainability in Artificial Intelligence (AI) has been revived as a topic of active
research by the need of conveying safety and trust to users in the “how” and “why” of …
research by the need of conveying safety and trust to users in the “how” and “why” of …
A survey of explanations in recommender systems
N Tintarev, J Masthoff - 2007 IEEE 23rd international …, 2007 - ieeexplore.ieee.org
This paper provides a comprehensive review of explanations in recommender systems. We
highlight seven possible advantages of an explanation facility, and describe how existing …
highlight seven possible advantages of an explanation facility, and describe how existing …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
Explaining recommendations: Design and evaluation
N Tintarev, J Masthoff - Recommender systems handbook, 2015 - Springer
In recent years, there has been an increased interest in more user-centered evaluation
metrics for recommender systems such as those mentioned in [49]. It has also been …
metrics for recommender systems such as those mentioned in [49]. It has also been …
Data-centric explanations: explaining training data of machine learning systems to promote transparency
Training datasets fundamentally impact the performance of machine learning (ML) systems.
Any biases introduced during training (implicit or explicit) are often reflected in the system's …
Any biases introduced during training (implicit or explicit) are often reflected in the system's …
Designing and evaluating explanations for recommender systems
N Tintarev, J Masthoff - Recommender systems handbook, 2010 - Springer
This chapter gives an overview of the area of explanations in recommender systems. We
approach the literature from the angle of evaluation: that is, we are interested in what makes …
approach the literature from the angle of evaluation: that is, we are interested in what makes …
Psychology-informed recommender systems
Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …
Most of today's recommendation algorithms are data-driven and based on behavioral data …
[HTML][HTML] Interpretable confidence measures for decision support systems
J van der Waa, T Schoonderwoerd… - International Journal of …, 2020 - Elsevier
Decision support systems (DSS) have improved significantly but are more complex due to
recent advances in Artificial Intelligence. Current XAI methods generate explanations on …
recent advances in Artificial Intelligence. Current XAI methods generate explanations on …
Examining the effect of explanation on satisfaction and trust in AI diagnostic systems
Abstract Background Artificial Intelligence has the potential to revolutionize healthcare, and
it is increasingly being deployed to support and assist medical diagnosis. One potential …
it is increasingly being deployed to support and assist medical diagnosis. One potential …
SAMAP: An user-oriented adaptive system for planning tourist visits
In this paper, we present samap, whose goal is to build a software tool to help different
people visit different cities. This tool integrates modules that dynamically capture user …
people visit different cities. This tool integrates modules that dynamically capture user …