# How are chagras rewarded? This protocol treats chagras as a *black box* system. In other words, we can see the inputs and the outputs, but we can't measure what is happening inside the system. There are lots of systems like this in the world. For instance, machine learning is a type of AI that uses inputs and outputs to train and operate. We don't necessarily have to understand things fully to reward or work with them. And sometimes taking things down into their component parts actually destroys the understanding (this is called reductionism). The reality is that yes, most Indigenous Peoples have a very good understanding of the internal operations of chagras, but this understanding takes a lifetime to learn and properly teach, which is why elders are usually the ones teaching. We also respect community and cultural privacy, and as a core policy do not store traditional ecological knowledge (TEK) when it's not required for trade protocols. Which is to say simply that chagras are rewarded by peer-validation on a time-bound protoco. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://sexytrees.savimbo.com/practice-guide/chagras/reward-protocol.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.