Regular users asking AI usually get straight-up conclusions. Can you access the vault? Is the risk high? AI gives a judgment, and users move forward. But the biggest issue with these conclusion-type answers isn’t just that they can be wrong; it’s that they can’t be cross-checked. Users don’t know which judgment is based on which data source, which claims are model-derived, and which info is already outdated. $币安人生
BR's role in this process is pretty narrow. It's not about making AI smarter, but about giving high-tier users an interface to trace the source. The same question allows advanced users to step back and see which data source AI pulled from, what parameters influenced the judgment, and how much of the response is directly taken from on-chain status versus common sense reasoning. $BTC
This creates a behavioral difference. Regular users hear the conclusion and can only choose to trust or not based on their gut; advanced users can see the source and pick a data point to verify on-chain themselves. The more points they verify, the understanding of the vault shifts from 'trusting AI' to 'having verified it themselves.'
However, source tracing also has its limits. Data sources have delays, on-chain status can change, and AI might still make mistakes in reasoning. Source tracing can’t eliminate risk; it just pulls the risk from a complete black box to a level where at least point-in-time checks are possible. If users look at the sources just for peace of mind, the utilization rate of this advanced feature will be high.
So, BR's approach is essentially downgrading AI from a conclusion provider to an information organizer, shifting decision-making power back to the users. AI answers that can’t be traced back are just half-baked, no matter how fluent they sound.
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