AI Safety and Security Checklist
Whether your organization is looking to develop, secure, or deploy AI or LLM, or you're hoping to ensure the security and ethical adherence of your existing model, we've compiled a checklist for implementing safe and secure AI.
As we edge closer to a future where AI is ubiquitous, it’s essential to consider its impact on various teams, including those focused on security, trust, and compliance. While GenAI offers tremendous opportunities to advance defensive use cases, cybercrime rings and malicious attackers will not let the AI opportunity pass either. Both developers and deployers of AI and LLMs are being encouraged to launch products at record speed — often at the expense of critical AI safety and security measures.
Safe and Secure AI Development and Deployment
Applicable to many different AI/LLM development and deployment use cases, the checklist includes:
- 6 AI safety measures: Steps to prevent AI systems from generating harmful content, ensuring responsible use of AI and adherence to ethical standards
- 7 AI security measures: How to test your AI systems with the goal of preventing bad actors from abusing the AI to compromise the confidentiality, integrity, or availability of the systems the AI are embedded in
- 6 Joint AI safety and security measures: Efforts that address both the safety and security of your AI/LLM developments and deployments