Assurance of Machine Learning for use in Autonomous Systems (AMLAS)

Here we present our leading methodology for the Assurance of Machine Learning for use in Autonomous Systems (AMLAS).

AMLAS comprises a set of safety case patterns and a process for systematically integrating safety assurance into the development of machine learnt (ML) components. This provides a compelling argument about your ML model to feed into your system safety case.

You can access AMLAS using the links below- either on our separate guidance website (www.assuringautonomy.com) or as a PDF download. We also have an AMLAS Tool that will help you work through the AMLAS process and create a safety case for your ML component.

Contact us

Assuring Autonomy International Programme

assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH

AMLAS PDF

Download the AMLAS methodology as a PDF.

AMLAS PDF

Image of guidance website - www.assuringautonomy.com

Guidance website

Use the interactive version of AMLAS on our new guidance website.

www.assuringautonomy.com

AMLAS Tool

The AMLAS Tool has been developed to help you work through the AMLAS process and create a safety case for your ML component.

AMLAS Tool

Contact us

Assuring Autonomy International Programme

assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH