Humans not only trust in the source, they trust the structure -you generally do not care about who wrote a diet article (even if a change in lifestyle can have lasting impact on health) as long as "structure" suggest the writer is not a charlatan. A similar behavior is observed in crypto markets, where traders and investors keep lists of Twitter accounts that they trust to rely accurate information about the state of the market, and that are facilitated by other traders: it does not count only who is saying it, but who is following -this is part of the social fabric of crypto markets, the structure of the network encodes tacit knowledge and reflects abstract conditions and boundaries. The distance trust metrics have very tangible implications for individual and corporate purposes; "a member of my group said " (even if he had materially different attributes) is generally better than what an outsider says. The implications in terms of the theory of the firm (Coase): you do business in the proximity of your circle (your trust space) where trust is secured; even if it is more expensive to produce in your inner circle, and it is cheaper to acquire in the boundary (e.g. potential partners). The AI should understand this human bias (as shown in Figure), and