How to assure the safety of your machine learning component

We have developed the first methodology for the Assurance of Machine Learning for use in Autonomous Systems (AMLAS).

AMLAS has six stages, which complement the machine learning (ML) development process. It incorporates a set of safety case patterns and a process for systematically integrating safety assurance into your development of ML components.

Click the 'browse' box below for an overview of the six stages of the AMLAS process.

For an ML component in a particular system context, the AMLAS process supports the development of an explicit safety case for the component. The AMLAS process requires as input the system safety requirements generated from the system safety process. The assurance activities are performed in parallel to the development process of the ML component. Further, the AMLAS process is iterative and each stage could trigger the need to reconsider information generated or consumed by other stages.