Concerns about the misuse of AI are increasing.
AI governance provides a framework for responsible development and deployment.
CEOs play a crucial role in AI governance.
This field is rapidly evolving, driven by various stakeholders.
This article provides guidance for business leaders to address the complex issues in AI governance.
Introduction
- Concerns about the misuse of AI are increasing.
- AI governance provides a framework for responsible development and deployment.
- CEOs play a crucial role in AI governance.
- This field is rapidly evolving, driven by various stakeholders.
- This article provides guidance for business leaders to address the complex issues in AI governance.
Navigating AI Governance
Foundations & Principles:
- The social technology nature of AI requires ethical considerations beyond traditional risks.
- Current frameworks such as the OECD AI Principles and the Asilomar AI Principles establish fundamental principles regarding fairness, privacy, and explainability.
- These principles serve as guiding lights but require deeper guidance on practical implementation and trade-off management.
Frameworks & Laws:
- Frameworks like NIST's AI RMF provide structures and risk concepts but do not offer specific guidelines.
- The OECD AI classification framework helps understand AI components and categorize potential harms.
- Existing laws and regulations, such as general privacy laws, still apply to AI usage, although their interpretations may need clarification.
- Governments like the U.S. and EU are enacting AI-focused laws either sector-specific or horizontally, with the EU AI Act being a prominent example.
- Voluntary guidelines from governments and industries provide best practices and insights into policymakers' thinking.
Standards & Certification:
- Standardization bodies like ISO/IEC develop AI standards from governance methods to context-specific assessments.
- Organizations review specific standards to ensure compliance and best practices.
- Certification programs reference relevant standards to simplify navigation and demonstrate compliance.
Organizing AI Governance:
- Every organization involved with AI, regardless of maturity, needs a responsible AI program.
- This program involves a multidisciplinary team establishing principles, policies, evaluation mechanisms, product development processes, risk assessments, and continuous monitoring.
- Such activities help mitigate internal and external risks, prepare for regulations, and align AI usage with corporate values and social responsibilities.
How to Integrate Everything Together
- AI governance is essential for every organization.
- Start building your program now, as it takes time to refine.
- Focus on governance, leadership commitment, principles, risk assessments, and integration with existing structures.
- Taking these initial steps helps prepare for future regulations and protect your customers.
About the RAI Institute
The RAI Institute (Responsible AI Institute) is a global nonprofit organization governed by its members, dedicated to supporting successful responsible AI efforts within organizations. The RAI Institute's compliance assessments and certifications for AI systems assist practitioners as they navigate the complex landscape of AI products.
