The working paper Balancing Cooperation and Competition in Groups through Emotional Algorithms by Christoph H. Loch, INSEAD, Susan Schneider of HEC Genève, and INSEAD's Charles Galunic, examines emotional algorithms and their role in a fundamental dilemma that confronts human groups-whether actors should take care of "me" (compete) or "we" (cooperate). The authors posit that a predominantly rational view of this dilemma is too restricted. The decision to compete or cooperate is traditionally presumed to be a question of reason, not emotion, based on the notion of a rational decision-maker weighing the trade-off between cooperative and competitive behavior ("Do I reap the immediate benefits of being selfish, or do I invest in a good reputation or relationship now to harvest them later?").
The authors argue that there is much more that informs human decision-making when it comes to questions of cooperation or competition and that it is precisely the role of emotions that has largely been neglected in social dilemmas. Experiments in brain medicine have shown that patients with brain damage whose emotional systems have been impaired, leaving their intelligence intact, are no longer able to successfully navigate the subtle trade-offs of delayed gratification and social interactions. Conscious intelligence is not enough for intelligent behavior; rather, our social interactions are guided by emotional "rules of thumb."
The purpose of this paper is to depict how each of us is endowed with specialized emotional algorithms that enable us to balance our personal interests with group interests-so helping to resolve the dilemma of cooperative behavior-without having to make a fully conscious and calculative appraisal of each social situation. These emotional algorithms include short-term (myopic) pursuit of material goods and status-seeking behaviors which encourage competition, as well as reciprocity and group identification which encourage cooperation.
The authors argue that it is likely that these balanced, hard-wired emotional algorithms have an evolutionary explanation and that emotional algorithms have become programmed through evolution to manage the dilemma of taking care of 'me vs. we'. Survival as a group seemingly requires that both self-interest and group interest must be balanced in dynamic interaction (if the group does not cooperate it will be beaten by other groups, but at the same time the most competitive members of the group do better than the less competitive members - as has been shown in animal populations, human tribes, and modern organizational groups).
Four emotional algorithms seem to be at the basis of cultural development - cultures all revolve around status, reciprocity (relationships) and group identity, but each culture offers differing definitions and triggers of the emotional algorithms. Thus, the emotional algorithms may form an "open-ended system" that channels cultural variety while at the same time allowing an almost infinite number of variants (a function that the "universal grammar" has in linguistics, allowing many languages to emerge while having a deep common structure that makes learning a language feasible for small children). This interaction between emotional algorithms and the evolution of cultural rules is an exciting open research area that may illuminate the link between culture and human nature. An important aspect of this research lies in being aware that emotional algorithms can help managers to maintain a constructive balance of competition and cooperation in organizational groups.