Explainable and Safe AI Research Landscape Map

Még több ilyen

Código de ética Universidad de Guayaquil

Szerző: Ingrid Zamora Delgado

Reading Comprehension

Szerző: Lor Lor

Should College Athletes be paid?

Szerző: jonathan greve

Canada PWGSC IA v2.0

Szerző: Albert Novikov

Explainable and Safe AI Research Landscape Map

Theory of Explanations

Definitions

Transparency vs Explanations

Z. C. Lipton, “The mythos of model interpretability,”

Philosophy

Good Explanations

Shane T. Mueller "Explanation in Human-AI Systems: A Literature Meta-Review Synopsis of Key Ideas and Publications and Bibliography for Explainable AI"

Responsibility

Morality

Requirements and needs

Technical

Safety

User Needs

Legality

R. Budishet al., “Accountability of ai under the law: The role of ex-planation,”

GDPR (Goodman & Flaxman)

Machine Learning

Applications

Autonomous Vehicles

Health Care

A. Avati, K. Jung, S. Harman, L. Downing, A. Ng, and N. H. Shah, “Im-proving palliative care with deep learning,”

ML Methods

Classifiers

L. A. Hendricks, Z. Akata, M. Rohrbach, J. Donahue, B. Schiele,and T. D. and, “Generating visual explanations,”

C. Otte, “Safe and interpretable machine learning a methodologicalreview,”

Unsupervised Learning

Supervised Learning

Neural Nets

C. Olah, L. Schubert, and A. Mordvintsev, “Feature visualization how neural networks build up their understanding of images

T. Zahavy, N. B. Zrihem, and S. Mannor, “Graying the black box:Understanding dqns

RL

Safety Critical Systems

Assurance

Safety Cases

Interpretability methods

Evaluation of Explanation

Transparancy

Explanations

Global

Local

Saliency maps

T. Zahavy, N. B. Zrihem, and S. Mannor, “Graying the black box:Understanding dqns,”https://arxiv.org/abs/1602.02658, 2016.

M. T. Ribeiro, S. Singh, and C. Guestrin,“why should i trust you? explaining the predictions of any classifier, ” https://arxiv.org/abs/1602.04938, 2016.

Surveys

Theory

S. Mohseni, N. Zarei, and E. D. Ragan, “A survey of evaluation methods and measures for interpretable machine learning

T. Miller, “Explanation in artificial intelligence: Insights from the social sciences,”

Ex. Techniques

F. K. Dosilovi, M. Brci, and N. Hlupi, “Explainable artificial intelli-gence: A survey,”

Mohseni et al "Explainable Artificial Intelligence: A Survey."

O. Biran and C. Cotton, “Explanation and justification in machine learning

R. Ashmore, R. Calinescu, and C. Paterson, “Assuring the machine learning lifecycle

A. Adadi and M. Berrada, “Peeking inside the black-box"