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Found 6 papers, 1 papers with code
AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms
The behaviours of a swarm are not explicitly engineered.
Review of the AMLAS Methodology for Application in Healthcare
In recent years, the number of machine learning (ML) technologies gaining regulatory approval for healthcare has increased significantly allowing them to be placed on the market.
A Principles-based Ethical Assurance Argument for AI and Autonomous Systems
Assurance cases are structured arguments, supported by evidence, that are often used to establish confidence that a software-intensive system, such as an aeroplane, will be acceptably safe in its intended context.
The Role of Explainability in Assuring Safety of Machine Learning in Healthcare
Established approaches to assuring safety-critical systems and software are difficult to apply to systems employing ML where there is no clear, pre-defined specification against which to assess validity.
Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)
Machine Learning (ML) is now used in a range of systems with results that are reported to exceed, under certain conditions, human performance.
A Framework for Assurance of Medication Safety using Machine Learning
As healthcare is now data rich, it is possible to augment safety analysis with machine learning to discover actual causes of medication error from the data, and to identify where they deviate from what was predicted in the safety analysis.
