Building trust: Foundations of security, safety, and transparency in AI

Abstract

This paper explores the rapidly evolving ecosystem of publicly available AI models and their potential implications on the security and safety landscape. Understanding their potential risks and vulnerabilities is crucial as AI models become increasingly prevalent. We review the current security and safety scenarios while highlighting challenges such as tracking issues, remediation, and the absence of AI model lifecycle and ownership processes. Comprehensive strategies to enhance security and safety for both model developers and end-users are proposed. This paper provides several foundational pieces for more standardized security, safety, and transparency in developing and operating generative AI models and the larger open ecosystems and communities forming around them.