Authors from various backgrounds collaborate to develop a shared principle and framework for AI safety agendas, focusing on deconfusion and creating a clear framework inspired by civil engineering. The chapter explores the shift towards quantifiable safety assurances in AI, emphasizing the importance of strong theoretical foundations and empirical testing for precise risk estimates and guaranteed safety.

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