Cloud Security Alliance releases three papers offering guidance for AI implementation

May 6, 2024
The papers equip organizations with the knowledge they need to understand their current standing and navigate the ever-changing requirements for responsible and compliant GenAI use.

SAN FRANCISCO -- RSA Conference -- The Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining standards, certifications, and best practices to help ensure a secure cloud computing environment, today issued AI Organizational Responsibilities - Core Security ResponsibilitiesAI Resilience: A Revolutionary Benchmarking Model for AI, and Principles to Practice: Responsible AI in a Dynamic Regulatory Environment, a three-part series outlining recommendations across key areas of security and compliance in Artificial Intelligence (AI) that will guide enterprises in fulfilling their obligations for responsible and secure AI development and deployment.

“Thought leadership is the guiding force in the evolution of AI applications, shaping the trajectory of innovation and steering it towards ethical and impactful outcomes. Reports such as these reinforce CSA’s 15 years of cloud security leadership and going forward as thought leaders for one of the most consequential technologies of our lifetime,” said Jim Reavis, CEO and co-founder, Cloud Security Alliance.

"Our mission is to create practical and sensible frameworks and guidance for enterprise security teams on AI. This is the first part of many of these deliverables to come in doing just that,” said Caleb Sima, Chair, CSA AI Safety Initiative.

The first report, AI Organizational Responsibilities - Core Security Responsibilities, focuses on what defines an enterprise's "core security responsibilities" around AI and Machine Learning (ML) and synthesizes expert-recommended best practices within these areas – specifically data protection mechanisms, model vulnerability management, MLOps pipeline hardening, and governance policies for training and deploying AI responsibly.

Drawing lessons from past AI failures through case studies and analysis across a wide range of industries, AI Resilience: A Revolutionary Benchmarking Model for AI Safety integrates diverse perspectives with regulatory guidelines to provide businesses with practical insights and actionable guidance in the development of more ethical and trustworthy AI applications. The white paper empowers key decision makers – including government officials, regulatory bodies, and industry leaders – to establish AI governance frameworks that ensure ethical AI development, deployment, and use and addresses the urgent need for a more holistic perspective on AI governance and compliance.

Lastly, Principles to Practice: Responsible AI in a Dynamic Regulatory Environment provides an overview of the legal and regulatory landscape surrounding AI and Generative AI (GenAI), highlighting the challenges of navigating a complex and dynamic landscape due to the diverse applications of GenAI and the slow adaptation of existing regulations.

The paper equips organizations with the knowledge they need to understand their current standing and navigate the ever-changing requirements for responsible and compliant GenAI use, exploring a selection of existing regulations, considerations for the future, and best practices for developing responsible AI across national, regional, and international levels.

Read the white papers, and learn more about CSA’s AI Safety Initiative and its research.