Towards an Epistemology of Interdependence Among the Orthogonal Roles in Human–Machine Teams

Rational social theorists (e.g., game and decision theorists) have failed to confirm that observations of social reality equal social reality. Yet they argue that teams, organizations and social systems should minimize interdependence and competition, echoed by social psychologists to make data iid (i.e., independent and factorable). But the evidence indicates that competitive teams maximize interdependence; self-reports of social reality correlate poorly with social behavior; and only competition measures interdependent social states. Rational expectations aside, we report progress towards a science of interdependence for human–machine teams. Our model of interdependence works like an uncertainty principle in the sense that tradeoffs arise from the uncertainty caused by measuring interdependent actors in orthogonal roles; e.g., in the tradeoff between teams and individuals, teams are more productive but more opaque. Previously, we described interdependence as bistable stories of social reality; the motivation to reject alternative interpretations, increasing uncertainty and errors; and the inability to factor social states. Now we explore education as a surrogate for intelligence in teams. We hypothesized that teams rely on the education (a trained intellect) of its members to produce more patents (a team’s goals). We found that the average schooling in a nation is significantly related to its total patents produced.