The rise in the applications of artificial intelligence (AI) has resulted in a number of legal, ethical and safety concerns about its use, which are becoming increasingly important in business and society. Indeed, in response to these concerns, the field of AI ethics has emerged and aims to minimise the potential and actual harm that can come about through the use of AI. One way to do this is to audit and assure AI systems, particularly those that are high impact or high risk. In other words, the systems that can have a significant impact on individuals’ lives, such as those used in recruitment, healthcare, and housing. While auditing and assurance are related concepts and practises, they are distinct. In this blog, we give an overview of algorithm auditing and assurance, outlining the key components of each practice and how they link to each other.

What is an audit?