Our guidance is translated from sound academic research that is validated "in the wild" through empirical study. It provides you with proven, accessible methodologies and processes for assuring the safety of your autonomous system.
There are five essential pieces of guidance we are developing that you need to create a credible and compelling assurance case for your autonomous system. You can see these mapped to the autonomous system architecture on the right.
Our methodology for the assurance of machine learning is already available on this site. Guidance on each of these other areas will be added as it is written, reviewed and published.
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