Artificial intelligence, in the form of machine learning, has the potential to transform many
safety-critical applications such as those in transportation and healthcare. However, despite …

Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …

Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems
that employ machine learning and deep learning models, such as automated driving …

Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …

Machine learning (ML) applications generate a continuous stream of success stories from
various domains. ML enables many novel applications, also in safety-critical contexts …

Machine Learning (ML) is now used in a range of systems with results that are reported to
exceed, under certain conditions, human performance. Many of these systems, in domains …

Purpose This study is a systematic literature review of the application of artificial intelligence
(AI) in safety-critical systems. The authors aim to present the current application status …

The adoption of artificial intelligence (AI) and machine learning (ML) in risk-sensitive
environments is still in its infancy because it lacks a systematic framework for reasoning …

Artificial Intelligence (AI), particularly current Machine Learning approaches, promises new
and innovative solutions also for realizing safety-critical functions. Assurance cases can …

There is increasing interest in the application of machine learning (ML) technologies to
safety-critical cyber-physical systems, with the promise of increased levels of autonomy due …