Advancing accountability in AI

This report presents research and findings on accountability risk in AI systems by providing an overview of how risk-management frameworks the system lifecycle can be integrated to promote trustworthy AI. It also explores processes technical attributes that facilitate implementation values-based principles for identifies tools mechanisms define, assess, treat, govern risks at each stage lifecycle. leverages OECD – including Principles, lifecycle, framework classifying recognised due-diligence like ISO 31000 framework, Due Diligence Guidance Responsible Business Conduct, US National Institute Standards Technology’s framework.