paper-with-me

Papers

Fair lending needs explainable models for responsible recommendation

2018-09-12 · Jiahao Chen

The financial services industry has unique explainability and fairness challenges arising from compliance and ethical considerations in credit decisioning. These challenges complicate the use of model machine learning and artificial intelligence methods in business decision processes.

📄 PDF Abstract BibTeX arXiv:1809.04684

Code (0)

등록된 구현이 없습니다.

Tasks

BIG-bench Machine LearningExplainable ModelsFairness

Similar Papers 제목 키워드 기반

Explainable Fairness in Recommendation

2022-04-24 · Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia 외

Existing research on fairness-aware recommendation has mainly focused on the quantification of fairness and the development of fair recommendation models, neither of which studies a more substantial problem--identifying …

counterfactualFairnessRecommendation Systems

Towards Responsible AI in Education: Hybrid Recommendation System for K-12 Students Case Study

2025-02-27 · Nazarii Drushchak, Vladyslava Tyshchenko, Nataliya Polyakovska

The growth of Educational Technology (EdTech) has enabled highly personalized learning experiences through Artificial Intelligence (AI)-based recommendation systems tailored to each student needs. However, these systems …

FairnessRecommendation Systems

Fairness-Aware Explainable Recommendation over Knowledge Graphs

2020-06-03 · Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao 외

There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems. Explainable recommendation systems, in particular, may suffer from both explanation …

Collaborative FilteringDecision MakingExplainable RecommendationFairness+3

FAIR: Fairness-Aware Information Retrieval Evaluation

2021-06-16 · Ruoyuan Gao, Yingqiang Ge, Chirag Shah

With the emerging needs of creating fairness-aware solutions for search and recommendation systems, a daunting challenge exists of evaluating such solutions. While many of the traditional information retrieval (IR) metri…

DiversityFairnessInformation RetrievalRecommendation Systems+1

A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations

2020-10-09 · Andrea Ferrario, Michele Loi

Counterfactual explanations are a prominent example of post-hoc interpretability methods in the explainable Artificial Intelligence research domain. They provide individuals with alternative scenarios and a set of recomm…

BIG-bench Machine LearningcounterfactualCounterfactual ExplanationExplainable artificial intelligence