Given the rapid proliferation of generative AI technology, it's imperative for organizations to establish a comprehensive data privacy and security strategy. Traditionally, companies address new security challenges with a triad of policy, process, and technology. In this blog, we delve into a layered approach to generative AI security.
Policy as the First Layer
A robust security policy serves as the foundational governance framework for all decisions and actions pertaining to the deployment and use of Generative AI. Such policies should delineate which models can be accessed, by whom, and the kind of data permissible for sharing. Crafting effective policies necessitates a deep understanding of the primary risks associated with generative AI. This understanding should resonate through the policy’s wording. Without processes in place, policies are only as potent as the users' ability and willingness to comply. Their effectiveness is bolstered by heightened awareness.
Process as the Second Layer
The second tier in a robust governance framework is defined by processes that amplify awareness of policies and ensure adherence. Regular training, consistent communication, and effective "human-in-the-loop" oversight can enhance policy adoption throughout the organization. It's pivotal to devise and execute processes that resonate with risk and security mandates to uphold the desired governance stance around generative AI. Embracing this layer enhances overall security, even amidst shifts in internal policy. While processes can notably enhance policy efficacy, technology fills the voids left by human oversights.
Technology as the Critical Third Layer
Policy and process are fundamental, but their success hinges on end-users' awareness, collaboration, and dedication. Even the most diligent employees can inadvertently disclose PII, PHI, PCI, Intellectual Property, or other sensitive data while interacting with generative AI. Technology emerges as the pivotal third layer in a comprehensive generative AI security governance approach.
Liminal stands as this third security layer for enterprises aiming to harness the capabilities of generative AI. As a unique horizontal security solution for generative AI, Liminal enables businesses to safely introduce and utilize generative AI across varied applications. With Liminal, cybersecurity and risk experts gain absolute control over data handling during interactions with generative AI—whether it's through direct engagements with expansive language models, like Google’s Bard or Chat GPT, via in-house built generative AI applications, or via off-the shelf software with gen AI functionalities. Liminal safeguards organizations against regulatory compliance risk, data security threats, and reputational damage.
Security is the First Step in Any Generative AI Journey
Data is the cornerstone of all organizations. With the escalating ubiquity of generative AI, the risk quotient of sensitive data being inadvertently shared amplifies. Adopting a layered governance strategy for generative AI (encompassing policy, process, and technology) equips risk and cybersecurity teams to greenlight the most promising projects on their radar. When executed effectively, enterprises can unleash the unparalleled potential of generative AI while adeptly curtailing inherent risks.
Reach out to the Liminal team to learn more about deploying generative AI securely within your organization.