Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities
357
Zitationen
4
Autoren
2020
Jahr
Abstract
Artificial Intelligence (AI) has diffused into many areas of our private and professional life. In this research note, we describe exemplary risks of black-box AI, the consequent need for explainability, and previous research on Explainable AI (XAI) in information systems research. Moreover, we discuss the origin of the term XAI, generalized XAI objectives, and stakeholder groups, as well as quality criteria of personalized explanations. We conclude with an outlook to future research on XAI.
Ähnliche Arbeiten
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
2017 · 20.436 Zit.
Generative Adversarial Nets
2023 · 19.843 Zit.
Visualizing and Understanding Convolutional Networks
2014 · 15.256 Zit.
"Why Should I Trust You?"
2016 · 14.294 Zit.
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
2024 · 13.133 Zit.