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"OH WATERS, TEEM WITH MEDICINE TO KEEP MY BODY SAFE FROM HARM, SO THAT I MAY LONG SEE THE SUN." - Rig Veda
Understanding of the psychology of tyranny is dominated by classic studies from the 1960s and 1970s: Milgram's research on obedience to authority and Zimbardo's Stanford Prison Experiment. Supporting popular notions of the banality of evil, this research has been taken to show that people conform passively and unthinkingly to both the instructions and the roles that authorities provide, however malevolent these may be. Recently, though, this consensus has been challenged by empirical work informed by social identity theorizing. This suggests that individuals' willingness to follow authorities is conditional on identification with the authority in question and an associated belief that the authority is right.
Not only is it given prominence in social psychology textbooks , but so too it informs the thinking of historians political scientists , economists , and neuroscientists . Indeed, via a range of social commentators, it has shaped the public consciousness much more broadly , and, in this respect, can lay claim to being the most influential data-driven thesis in the whole of psychology.
Yet despite the breadth of this consensus,in recent years, we and others have reinterrogated its two principal underpinnings—the archival evidence pertaining to Eichmann and his ilk, and the specifics of Milgram and Zimbardo’s empirical demonstrations—in ways that tell a verydifferent story .First, a series of thoroughgoing historical examinations have challenged the idea that Nazi bureaucrats were ever simply
following orders [19,26,30]. This may,have been the defense they relied upon when seeking to minimize their culpability, but evidence suggests that functionarieslike Eichmann had a very good understanding of what they were doing and took pride in the energy and application that they brought to their work.
regime’s assumed goals and to overcomethe challenges associated with any given task . Emblematic of this, the practical details of ‘‘the final solution’’ were nothanded down from on high, but had to beelaborated by Eichmann himself. He thenfelt compelled to confront and disobey his superiors—most particularly Himmler—when he believed that they were not
Second, much the same analysis can be used to account for behavior in theStanford Prison Experiment. So while itmay be true that Zimbardo gave hisguards no direct orders, he certainly gavethem a general sense of how he expected them to behave . During the orientation session he told them, amongst other things, ‘‘You can create in the prisonersfeelings of boredom, a sense of fear to some degree, you can create a notion ofarbitrariness that their life is totallycontrolled by us, by the system, you, me… We’re going to take away theirindividuality in various ways. In generalwhat all this leads to is a sense of
powerlessness’’ . This contradicts Zimbardo’s assertion that ‘‘behavioral scriptsassociated with the oppositional roles of prisoner and guard [were] the sole sourceof guidance’’  and leads us to question the claim that conformity to these rolerelatedscripts was the primary cause ofguard brutality.
But even with such guidance, not all guards acted brutally. And those who didused ingenuity and initiative in responding to Zimbardo’s brief. Accordingly, after theexperiment was over, one prisoner confronted his chief tormentor with the observation that ‘‘If I had been a guard I don’t think it would have been such a masterpiece’’ . Contrary to the banalityof evil thesis, the Zimbardo-inspired tyranny was made possible by the active engagement of enthusiasts rather than the leaden conformity of automatons.
Invented at MIT some 60 years later and first offered in 2000, “Solving Complex Problems” is a class designed to do just that (2). A freshman-year elective for students with a wide range of backgrounds and prospective majors, it typically attracts between 5 and 10% of the MIT freshman class who develop through it an enthusiasm for tackling difficult, multifaceted problems. Students are presented in the first class with a challenge that can be stated simply, but that is deceptively complex and has no straightforward answer. Over the course of the semester, it is their job collectively to “imagineer” a proposed solution, to articulate their solution, and to explain how they arrived at it.
For example, the challenge presented to the first class in 2000 was to design a mission of exploration to Mars to search for signs of past or present life. Some students, who saw themselves as prospective aeronautics or astronautics majors, immediately interpreted this as a simple invitation to solve the ideal rocket equation for the appropriate thrust necessary to transfer a research payload to Mars and back. But it soon became clear that the simplicity of the problem statement masked a spectrum of challenges that would require the development and analysis of complicated decision matrices. Some of the implied questions were fundamental. How should we define “life” for the purpose of this mission? If one uses the life we know on Earth to establish what to look for, how can we be sure that a search for traditional biosignatures is sufficient to conclude that life does not exist on Mars? The phrase “past or present” life adds more complexity to the task. What do we regard as reliable evidence for fossil life? Other questions were more operational. Should the mission be manned or unmanned? How should the spacecraft be designed? What analytical instruments would be best for the required measurements? Still others were eminently practical, including the two most practical of all: How much will all this cost, and who will pay for it?
Regardless of topic, the students in a section of Solving Complex Problems all work together in the first few class sessions to predict what challenges will arise and to parse the overall problem into a series of 5 to 10 themes. For example, themes might include the environmental context of the problem, engineering challenges, public relations, budget development, and fund raising. Each student is then assigned, at random, not based on preference, to a team responsible for developing a knowledge base and making preliminary recommendations for their part of the overall solution. Perhaps surprisingly, we have found the approach of randomizing teams very effective because all teams ultimately have to work together on the final design concept; a student particularly interested in one theme—but not assigned to the team associated with it—is encouraged to act as a sounding board (and sometimes friendly critic) for the team. One member from each team is elected to be part of a coordination team to ensure good interteam communications.
Along the way to arriving at their optimal design, the students learn valuable lessons regarding critical, transdisciplinary thinking, the challenges and rewards of working in teams both large and small, the importance of organizing and synthesizing data from many sources, and the need to justify assumptions and decisions. Early in the development of the class, we learned that a grading scheme was necessary that recognized individual accomplishment but rewarded collaborative problem solving. We allow students to critique their own work, the work of others on their thematic teams, and the class as a whole. But the final grade for the semester depends disproportionately on the quality and sophistication of the overall design as judged by the teaching staff with input from the expert panelists.