On February 21, 2024, the Centre for Information Policy Leadership at Hunton Andrews Kurth LLP (“CIPL”) published a white paper on Building Accountable AI Programs: Mapping Emerging Best Practices to the CIPL Accountability Framework. The white paper showcases how 20 leading organizations are developing accountable AI programs and best practices.
The white paper discusses how organizational accountability is fundamental to the responsible development and deployment of AI. Organizations recognize the need to demonstrate AI accountability as a business imperative, especially as the expectations of consumers, business partners, shareholders and regulators around responsible AI use continue to grow. They also recognize that AI governance works best when it leverages knowledge from other disciplines, including data protection, information security, human rights, cybersecurity and more.
The research revealed the following general findings and commonalities among project participants and accountable organizations:
- AI transformation, coupled with accountability in AI, is a top priority and business imperative.
- Accountable governance of AI is a smart business investment for long-term sustainable and competitive business.
- “Tone from the top” is crucial for responsible AI programs.
- Guidance from regulators and policymakers is welcome as organizations prepare to implement emerging standards and regulations.
- A risk-based technology-agnostic approach is the most effective and appropriate approach for AI governance.
- Organizations are adapting and updating their governance frameworks to address new issues and risks, including those raised by generative AI.
- Multidisciplinary and diverse teams are the foundation for building and implementing accountable AI governance programs.
- There is great value in building consensus on the appropriate elements of accountable AI governance and benchmarking against peers.
- Accountable development and deployment of AI is a continuous journey and an iterative process.