Survey on explainable AI: From approaches, limitations and applications aspects
In recent years, artificial intelligence (AI) technology has been used in most if not all domains
and has greatly benefited our lives. While AI can accurately extract critical features and …
and has greatly benefited our lives. While AI can accurately extract critical features and …
Explainable ai: A review of machine learning interpretability methods
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …
with machine learning systems demonstrating superhuman performance in a significant …
Explainable artificial intelligence in cybersecurity: A survey
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
Interpretable machine learning: Fundamental principles and 10 grand challenges
Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …
Questioning the AI: informing design practices for explainable AI user experiences
A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on
the topic. While many recognize the necessity to incorporate explainability features in AI …
the topic. While many recognize the necessity to incorporate explainability features in AI …
Benchmarking and survey of explanation methods for black box models
The rise of sophisticated black-box machine learning models in Artificial Intelligence
systems has prompted the need for explanation methods that reveal how these models work …
systems has prompted the need for explanation methods that reveal how these models work …
[HTML][HTML] Machine learning interpretability: A survey on methods and metrics
DV Carvalho, EM Pereira, JS Cardoso - Electronics, 2019 - mdpi.com
Background: Open Access Editor's Choice Review Machine Learning Interpretability: A
Survey on Methods and Metrics by Diogo V. Carvalho 1, 2,*, Eduardo M. Pereira 1 and …
Survey on Methods and Metrics by Diogo V. Carvalho 1, 2,*, Eduardo M. Pereira 1 and …
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
C Rudin - Nature machine intelligence, 2019 - nature.com
Black box machine learning models are currently being used for high-stakes decision
making throughout society, causing problems in healthcare, criminal justice and other …
making throughout society, causing problems in healthcare, criminal justice and other …
One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques
As artificial intelligence and machine learning algorithms make further inroads into society,
calls are increasing from multiple stakeholders for these algorithms to explain their outputs …
calls are increasing from multiple stakeholders for these algorithms to explain their outputs …
Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus Explainability
AJ London - Hastings Center Report, 2019 - Wiley Online Library
Although decision‐making algorithms are not new to medicine, the availability of vast stores
of medical data, gains in computing power, and breakthroughs in machine learning are …
of medical data, gains in computing power, and breakthroughs in machine learning are …