# Confidence in Assurance 2.0 Cases

arXiv: https://arxiv.org/abs/2409.10665 · HTML: https://mlsanity.com/paper/2409.10665/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Sep 2024.

## Built on by (most cited first, 2 of 2)

- [Probabilistic Robustness in Deep Learning: A Concise yet Comprehensive Guide](https://mlsanity.com/paper/2502.14833/) (2025)
- [Where AI Assurance Might Go Wrong: Initial lessons from engineering of critical systems](https://mlsanity.com/paper/2502.03467/) (2025)

## Abstract (arXiv)

An assurance case should provide justifiable confidence in the truth of a claim about some critical property of a system or procedure, such as safety or security. We consider how confidence can be assessed in the rigorous approach we call Assurance 2.0. Our goal is indefeasible confidence and we approach it from four different perspectives: logical soundness, probabilistic assessment, dialectical examination, and residual risks.