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
Centre for Assuring Autonomy
assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH
![](/media/assuring-autonomy/images/Website guidance page - AMLAS PDF.png)
![Image of guidance website - www.assuringautonomy.com](/media/assuring-autonomy/bannerimages/Website guidance page - guidance website launch.png)
Guidance website
Use the interactive version of AMLAS on our new guidance website.
![](/media/assuring-autonomy/images/Website guidance page - AMLAS Tool launch.png)
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.
Contact us
Centre for Assuring Autonomy
assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH