Ensuring safe and responsible AI
The deployment of LLM-based agentic systems introduces unique safety and responsibility challenges that go beyond those of traditional generative AI. While generative AI primarily focuses on content creation, agentic systems can autonomously plan, decide, and act, making their safe deployment significantly more complex and critical. Core safety considerations for agentic systems include the following:
- Action boundaries: Defining strict action boundaries is critical to ensuring that agentic systems operate within safe and ethical constraints. These boundaries can be enforced using policy-based governance frameworks such as OpenAI’s Function Calling API and Amazon Bedrock Guardrails, which allow agents to interact with external systems while adhering to predefined operational limits. Additionally, role-based access control (RBAC) and context-aware permissions can be implemented to restrict agents from taking unauthorized actions, particularly...
