To offer journalists and communicators basic notions about privacy and protection of personal data, the political and economic implications for democracy and the importance of preserving individuals' rights when reporting events of public interest. Produced mainly for Non - tech teams.

Promote use of AI that is innovative and trustworthy and that respects human rights and democratic values. Adopted in May 2019, they set standards for AI that are practical and flexible enough to stand the test of time. Produced mainly for Government and Ministerial Levels.

Findings from work by a group of partners in a project to explore the implementation of responsible AI principles, including Deutsche Bank, Linklaters, Microsoft, Standard Chartered, and Visa. Produced mainly for Managers & C levels.

Sets aspirational benchmarks to guide governments, the private sector and international organizations in developing data governance that take full account of children’s issues and rights, including in AI systems.

Aims to help developers and product managers design and implement algorithmic systems in publicly accountable ways. Accountability in this context includes an obligation to report, explain, or justify algorithmic decision-making as well as mitigate any negative social impacts or potential harms. Produced mainly for Managers & Tech teams.

An algorithmic audit identifies, addresses and corrects algorithmic bias so that you can act on informed and vetted AI-powered business recommendations.

Produced mainly for Companies using AI

Addition of industry examples in each section to illustrate how organizations have implemented AI governance practices. Produced mainly for Government

Povide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future. Produced mainly for everyone.

Provides detailed and readily-implementable guidance to private sector organisations to address key ethical and governance issues when deploying AI solutions. Produced mainly for Managers & C levels.

The work is intended to address practical considerations across the data lifecycle, including routine data collection and one-off data collections. It provides guidance, principles and practical case studies.

A discovery process tool for product teams to spot unconscious biases and structural inequalities in AI systems.

Produced mainly for Tech teams.

The IIF Data Ethics Charter outlines a set of principles for the ethical handling of customer data in the financial services industry and larger economy. Principles and examples of practice provide an overview of how financial institutions responsibly manage, protect, share, and use customer data.