Best Practices for Generative AI Risk Management and Prevention

💡Generative AI is a general-purpose technology with broad potential that goes beyond traditional machine learning use cases.

🔐Generative AI faces distinct security issues compared to other forms of AI, including security in the development process, operation, and training of models.

🌐The risks associated with generative AI include data leakage, exfiltration, and output risks such as the manipulation of input and generating malicious content.

🏛️The industry and researchers are actively working on identifying vulnerabilities and mitigating AI risks, with ongoing efforts in AI red teaming and continuous testing.

👥Robust Intelligence, a startup focused on AI risk management, provides AI security solutions through continuous testing and validation.

What are the main security challenges in generative AI?

—Generative AI faces unique security challenges, including security in the development process, operation, and training of models. Risks include data leakage, exfiltration, and the generation of malicious content.

How is generative AI different from traditional machine learning?

—Generative AI is a general-purpose technology with broad potential, while traditional machine learning focuses on specific use cases. Generative AI has the capacity to learn and produce unique outputs, introducing dynamic security threats.

How is the industry addressing AI security risks?

—The industry and researchers are actively working on identifying vulnerabilities and mitigating AI risks. Efforts include AI red teaming, continuous testing, and real-time validation to ensure the security and integrity of AI systems.

What is Robust Intelligence's role in AI risk management?

—Robust Intelligence is a startup focused on AI risk management. They provide AI security solutions through continuous testing and validation, helping organizations mitigate risks and ensure the reliability of their AI systems.

What are the key insights from this webinar?

—The key insights from this webinar are: 1) Generative AI is a general-purpose technology with broad potential. 2) Generative AI faces distinct security challenges compared to traditional machine learning. 3) Risks include data leakage, exfiltration, and the generation of malicious content. 4) The industry and researchers are actively working on identifying vulnerabilities and mitigating AI risks. 5) Robust Intelligence provides AI security solutions through continuous testing and validation.

00:00The webinar discusses best practices for managing and preventing risks associated with generative AI.

03:40Generative AI is a general-purpose technology with broad potential that goes beyond traditional machine learning use cases.

06:31Generative AI faces distinct security issues compared to other forms of AI, including security in the development process, operation, and training of models.

09:58The risks associated with generative AI include data leakage, exfiltration, and output risks such as the manipulation of input and generating malicious content.

14:26The industry and researchers are actively working on identifying vulnerabilities and mitigating AI risks, with ongoing efforts in AI red teaming and continuous testing.

18:54Robust Intelligence, a startup focused on AI risk management, provides AI security solutions through continuous testing and validation.