Balancing innovation and safety
There’s a lot unimaginable promise in AI proper now but additionally unimaginable peril. Customers and enterprises must belief that the AI dream gained’t change into a safety nightmare. As I’ve famous, we frequently sideline safety within the rush to innovate. We will’t try this with AI. The price of getting it flawed is colossally excessive.
The excellent news is that sensible options are rising. Oso’s permissions mannequin for AI is one such resolution, turning the idea of “least privilege” into actionable actuality for LLM apps. By baking authorization into the DNA of AI programs, we will stop most of the worst-case eventualities, like an AI that cheerfully serves up personal 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 all the time have some unpredictability, however with layered defenses we will scale back that threat to a suitable degree.