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 systematic review and taxonomy of explanations in decision support and recommender systems
With the recent advances in the field of artificial intelligence, an increasing number of
decision-making tasks are delegated to software systems. A key requirement for the success …
decision-making tasks are delegated to software systems. A key requirement for the success …
What do we want from Explainable Artificial Intelligence (XAI)?–A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research
Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …
Argumentation and explainable artificial intelligence: a survey
Argumentation and eXplainable Artificial Intelligence (XAI) are closely related, as in the
recent years, Argumentation has been used for providing Explainability to AI. Argumentation …
recent years, Argumentation has been used for providing Explainability to AI. Argumentation …
Explanations as mechanisms for supporting algorithmic transparency
Transparency can empower users to make informed choices about how they use an
algorithmic decision-making system and judge its potential consequences. However …
algorithmic decision-making system and judge its potential consequences. However …
Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision‐making
S Grimmelikhuijsen - Public Administration Review, 2023 - Wiley Online Library
Abstract Algorithms based on Artificial Intelligence technologies are slowly transforming
street‐level bureaucracies, yet a lack of algorithmic transparency may jeopardize citizen …
street‐level bureaucracies, yet a lack of algorithmic transparency may jeopardize citizen …
Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges
Over the past two decades, a large amount of research effort has been devoted to
developing algorithms that generate recommendations. The resulting research progress has …
developing algorithms that generate recommendations. The resulting research progress has …
Multi-armed bandits in recommendation systems: A survey of the state-of-the-art and future directions
Abstract Recommender Systems (RSs) have assumed a crucial role in several digital
companies by directly affecting their key performance indicators. Nowadays, in this era of big …
companies by directly affecting their key performance indicators. Nowadays, in this era of big …
Explore, exploit, and explain: personalizing explainable recommendations with bandits
J McInerney, B Lacker, S Hansen, K Higley… - Proceedings of the 12th …, 2018 - dl.acm.org
The multi-armed bandit is an important framework for balancing exploration with exploitation
in recommendation. Exploitation recommends content (eg, products, movies, music playlists) …
in recommendation. Exploitation recommends content (eg, products, movies, music playlists) …
Measuring the business value of recommender systems
Recommender Systems are nowadays successfully used by all major web sites—from e-
commerce to social media—to filter content and make suggestions in a personalized way …
commerce to social media—to filter content and make suggestions in a personalized way …