Balancing innovation and safety
There may be a lot unimaginable promise in AI proper now but additionally unimaginable peril. Customers and enterprises have to belief that the AI dream received’t develop into a safety nightmare. As I’ve famous, we regularly sideline safety within the rush to innovate. We will’t try this with AI. The price of getting it fallacious is colossally excessive.
The excellent news is that sensible options are rising. Oso’s permissions mannequin for AI is one such answer, turning the idea of “least privilege” into actionable actuality for LLM apps. By baking authorization into the DNA of AI programs, we will forestall most of the worst-case situations, like an AI that cheerfully serves up non-public buyer information to a stranger.
In fact, Oso isn’t the one participant. Items of the puzzle come from the broader ecosystem, from LangChain to guardrail libraries to LLM safety testing instruments. Builders ought to take a holistic view: Use immediate hygiene, restrict the AI’s capabilities, monitor its outputs, and implement tight authorization on information and actions. The agentic nature of LLMs means they’ll at all times have some unpredictability, however with layered defenses we will scale back that threat to an appropriate stage.
