  System assurance is confronted by significant challenges. Some of these are
new, for example, autonomous systems with major functions driven by machine
learning and AI, and ultra-rapid system development, while others are the
familiar, persistent issues of the need for efficient, effective and timely
assurance. Traditional assurance is seen as a brake on innovation and often
costly and time consuming. We therefore propose a modernized framework,
Assurance 2.0, as an enabler that supports innovation and continuous
incremental assurance. Perhaps unexpectedly, it does so by making assurance
more rigorous, with increased focus on the reasoning and evidence employed, and
explicit identification of defeaters and counterevidence.
