This paper explores whether trust, developed in one context, transfers into another, distinct context and, if so, attempts to quantify the influence this prior trust exerts. Specifically, we investigate the effects of artificially stimulated prior trust as it transfers across disparate contexts and whether this prior trust can compensate for negative objective information. To study such incidents, we leveraged Berg’s investment game to stimulate varying degrees of trust between a human and a set of automated agents. We then observed how trust in these agents transferred to a new game by observing teammate selection in a modified, four-player extension of the well-known board game, Battleship. Following this initial experiment, we included new information regarding agent proficiency in the Battleship game during teammate selection to see how prior trust and new objective information interact. Deploying these experiments on Amazon’s Mechanical Turk platform further allowed us to study these phenomena across a broad range of participants. Our results demonstrate trust does transfer across disparate contexts and this inter-contextual trust transfer exerts a stronger influence over human behavior than objective performance data. That is, humans show a strong tendency to select teammates based on their prior experiences with each teammate, and proficiency information in the new context seems to matter only when the differences in prior trust between potential teammates are small.