Michael Schmid is a Technology Architect and Loss Prevention Specialist in the field of autonomous systems. His research focuses on preventing losses related to the use of Artificial Intelligence (AI) and making AI safe for use in everyday technology.
Previously, Michael has worked on automation features in cars, self-driving software, and has developed a certification approach for automated vehicles. Michael has a Master‘s degree from the Massachusetts Institute of Technology (MIT) and is currently a PhD candidate in the Group for System Safety and Cybersecurity at MIT. He is the second time guest in this podcast.
In this episode, Michael gave a thorough introduction to STAMP and STPA. STAMP is an accident causality model that was developed by prof. Nancy Leveson at MIT. It is based on systems theory and systems thinking. It is well-suited to addresses the challenges in engineering when working with critical complex systems. STPA is an analysis method based on STAMP to analyze systems to proactively avoid accidents. In comparison, CAST is the a method to analyse accidents that already happened.
Additional sources of information:
- To learn more about Michael, his projects and current work, or to download his Master‘s thesis on the certification of automated vehicles visit his webpage: michael.systems
- For info about STAMP and the next STAMP workshop go to: PSAS website
- The STPA-handbook can be found here: STPA-handbook
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This is the basic STAMP model element that is used to set up a control structure during an STPA analysis. - Photo credit: Hanan Altabbakh, Mohammad A. AlKazimi, Susan Murray, Katie Grantham