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Professional Knowledge, Complexity and Interdisciplinary Teams Angus McMurtry, University of Alberta

Introduction

In this paper, I examine some of the issues involved in “crossing boundaries” in the sense of thinking across different professional disciplines, such as law, medicine, engineering, education, social work, and so on. More specifically, I begin by describing several surprising observations I made while working as an occupational researcher and interviewer. I then interpret these observations through the lens of complexity science, arguing that each major professional area can be seen as a complex, learning system—one that embodies a rich and dynamic web of knowledge that cannot be easily reduced or translated into other professional areas’ ways of knowing. Finally, I argue that this incommensurability between different disciplines or professions has important implications for interdisciplinary teams. Most controversially, it challenges the notion that such teams should aim for consensus. Professional Knowledge(s)

For most of the past ten years, I have been working as part of a team building an online career guide called Career Cruising (2005). One of my most important tasks was to research occupations and interview people within them. In total, I researched approximately 450 common professions (everything from accountant to zoologist) and interviewed almost 900 people, usually in their place of work. During this time, I observed a number of recurring themes. The first concerned the remarkable depth and diversity of the Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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concepts, practices, conventions and assumptions embedded in each major professional area: business, engineering, education, skilled trades, health care and so on. Each area had evolved over many years (even centuries) in relation to its specific contexts and through the dynamic interactions of its particular practitioners. As a result, each area had to be approached on its own terms; it could not be reduced to, or 36 |

understood in terms of, ideas originating in other areas. One relatively well-known example is the legal system, with its highly specialized vocabulary, formalities, adversarial orientation, analytic forms of argumentation, and grounding in historical precedent. These practices and ways of thinking are enacted and understood by lawyers and other long-time participants, and are well-suited (or at least adequate) to the very difficult problems and issues the legal system has to wrestle with every day, despite the fact that they might appear Byzantine—even nonsensical—to those who are new to the system. This observation applied to other areas of work as well. For example, I could not comprehend the grounded, practical—and yet very sophisticated—understandings of the skilled trades using the academic categories and assumptions I had developed at university. Even for my relatively superficial research purposes, it was necessary to get to know an area on its own terms and only then try to represent it. And, this process seemed to involve making incremental changes to my orientation within the world, rather than simply adding knowledge to my existing “stock,” or rationally and consciously amending my beliefs. As well-know workplace learning author Etienne Wenger (2000) writes, Learning from our interactions with other practices is not just an intellectual matter of translation. It is also a matter of opening up our identities to other ways of being in the world. (p. 173)

Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

Of course, long-time participants within each system usually recognized the depth and complexity of their area. In some cases, their recognition was explicit. For example, many well-educated businesspeople were quite adept at explaining how the “invisible hand” works within a freemarket economy and how even well-intentioned government regulations may have unintended, negative consequences. However, in many more cases, people’s recognition of the complexity of their area of work was more tacit. They would enact complex sensibilities without necessarily being able to articulate reasons for doing so. For instance, many of the most effective teachers I interviewed had a deep sensitivity to the social, cultural, and biological contexts of their students, and an ability to adapt rapidly to the unpredictable day-to-day dynamics of their classroom. If pressed to explicitly describe their teaching strategy, however, they often fell back on the more simplistic and mechanical concepts and strategies offered by official curricula and teacher evaluation materials. In more candid situations, many teachers admitted that they thought such simplistic curricula and evaluations were largely irrelevant to the complexity of their actual work and accomplishments in the classroom. But, most lacked a vocabulary with which to develop an alternative way of interpreting their experiences—in spite of their general success in meeting the day-to-day challenges of teaching. In any case, all of the people I interviewed seemed to have an understanding (albeit in many cases a tacit one) of the depth, complexity and contextuality of their area of work. And, this knowledge was something that could not easily (if at all) be grasped by someone who had not spent a significant amount of time immersed in its day-today practices. In other words, one area’s way of knowing could not simply be translated or reduced into the terms of another area. Not surprisingly, then, most people tended to resent and resist Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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what they perceived as overly simplistic, external attempts to control their activities. I cannot even begin to count the number of times those whom I interviewed protested rules imposed upon them by people who were unfamiliar with the day-to-day realities of their systems. I have already mentioned how businesspeople resisted such interference. Health care workers provide another example: Those in Canada often 38 |

resented one-size-fits-all bureaucratic regulations imposed on them by provincial governments, while those in the United States objected strongly to the profit-oriented rules of health management organizations because they interfered with giving patients appropriate care. What was even more interesting (if not exactly surprising) was that people were far less likely to recognize the complexity of other occupational areas. They tended to assume that other areas—unlike their own—could be externally controlled or subjected to universal, standardized, context-free rules. This led them to support the very kind of overly simplistic, inappropriate regulation that they would fight if it were applied to their own area. This tendency to harmfully oversimplify can be seen in neo-conservative, business-led reforms of education in North America during the past 25 years. Authors like Apple (1996) and Carlson (1996), for example, have written extensively on the ‘rationalization’ and ‘de-skilling’ of education. Closely related to this over-simplification of other occupational areas were two other beliefs. One was the assumption that rules or practices from one’s own area could be unproblematically exported to other areas; another was the conviction that any perceived problems within other occupation areas must be the result of the intellectual or moral shortcomings of its participants. Again, these tendencies are clearly shown in neo-conservative reforms of education. Giroux (1996), for instance, describes the “development of school policy based on… market logic” and the neo-con habit of looking for educational Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

“solutions” in the “realm of management and economics” (pp. 296297). And, Gitlin (1996) notes that structures within schools have been based on the “assumption that teachers are the major source of educational failure, and in need of guidance and strict control” (p. 116). One should not, however, conclude from the preceding that education is the only area that suffers from such reductive impositions or that businesspeople are the only ones doing the reducing—they are just the most powerful. As a former entrepreneur, for example, I am often taken aback by the reductive generalizations some otherwise wellinformed people make about small businesses and the motives of those who run them. And, many of us seem quite ready to blame lawyers for the difficulty in obtaining “just” results in all court cases, rather than the extraordinary difficulty of balancing the rights of plaintiffs, defendants, victims, and the accused in complex real life situations. In summary, over the course of my occupational interviews and research, I made a number of interesting observations. The first concerned the depth, complexity, and diversity of knowledge embedded in each occupational area; the explicit or implicit recognition of this by long-time practitioners; and the resistance within each area to overly simplistic, external attempts to control their activities. My second observation was of a strong tendency among people to assume that other occupational areas (unlike their own) could be directly controlled or subjected to universal, standardized rules—including rules imported from other areas. To put it another way, they recognized the depth, complexity and uniqueness of their own area, but often failed to respect these very same qualities in other occupational areas. Complexity Science

Complexity science, often called complex systems theory, is a Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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promising discourse that has emerged in the last few decades. Although it has roots in the physical and biological sciences, complexity’s explanatory framework and core concepts have been adopted by thinkers in a wide variety of disciplines, including mathematics, social science, business, and the humanities. The focus of complexity science is complex systems, that is, 40 |

phenomena that resist explanation in terms of traditional, analytic methods. As Paul Cilliers (1998) points out, A complex system is not constituted merely by the sum of its components, but also by the relationship between these components. In ‘cutting up’ a system, the analytical method destroys what it seeks to understand. (p. 2, emphasis original) Thus, a complex systems is often described as being ‘greater than the sum of its parts’ since its behaviour (unlike that of merely mechanical or ‘complicated’ systems) cannot be fully understood or predicted simply by analyzing it into its component parts. “Living” phenomena like brains, people, economies, social groups, and ecosystems are typically considered to be complex systems. Complexity offers a number of conceptual tools that I believe can help make sense of my observations of various occupations and the knowledge embedded within them. The first is an expanded definition of what counts as a living, learning entity. For complexivists, knowledge is not limited to individual brains; it is also enacted and embodied in the relational, networked activities of complex ‘learning’ systems that emerge at multiple biological and cultural levels—everything from amoebas and ecosystems to human beings, classrooms, and societies (Capra, 2002; Varela et al., 1991; Davis, 2004). This way of understanding social collectives as complex, learning systems dovetails well Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

with my characterization of professional fields as evolving in relation to their contexts and the problems they face. A second conceptual tool offered by complexity is that of selforganization. Complex learning systems emerge through the dynamic, non-linear interaction of their component parts. Since complex systems arise in this manner, rather than from the imposition of ‘top-down’ instructions, their form of organization is often described as being decentralized, or ‘bottom up,’ in nature. Although top-down processes can emerge within sufficiently complex systems, they always arise in and through the on-going, bottom-up activities of the system itself and never as a unidirectional, controlling cause (Juarrero, 1999). A crucial consequence of complex systems’ self-organization is that they cannot be reduced to, or understood in terms of, straightforward causal inputs and outputs. They “change their own operations through operating” (Davis & Simmt, 2003, p. 139) and thus resist direct, external control or accurate prediction—a quality that sets them apart from the mechanical systems studied by traditional analytic scientific methods. An illustrative example of the self-organizing quality of complex systems is provided by well-known philosopher and physicist, Fritjof Capra (2002): [W]hen you kick a stone, it will react to the kick according to a linear chain of cause and effect. Its behavior can be calculated by applying the basic laws of Newtonian mechanics. When you kick a dog, the situation is quite different. The dog will respond with structural changes according to its own nature and (nonlinear) pattern of organization. The resulting behavior is generally unpredictable. (p. 35) The third useful conceptual tool is adaptation. Complex systems are adaptive because they change their own structure in response to Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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internal or external pressures. A complex system’s structure—that is, the dynamic relations among its component parts—adapts to, or couples with, its environment (though in a self-organizing rather than deterministic fashion). It is this dynamic, adaptive quality that makes complex systems ‘learning systems.’ An important consequence of adaptation is the importance of 42 |

context and history. Complex systems are always open systems: they interact with and adapt to their specific environments (Cilliers, 1998). Indeed, most complex systems are so interwoven with their environments that it is difficult to define their borders. To understand a complex system, then, one must take into account its particular history and context. For example, one cannot understand animal species without understanding the nature and history of the ecosystem within which they evolved; giraffes’ extraordinarily long necks make little sense until one places them within the dynamic context of high trees and competition for scarce food sources. It is for this reason that complex systems are said to embody their history in their structure. The development of the legal system provides an illustrative example of how self-organization and adaptation play out when applied to occupational areas as complex systems. In terms of adaptation to specific historical contexts, Canada’s common law has its roots in medieval Anglo-Saxon society. Its orientation towards individual property rights (especially land) and its tendency to measure all harms in monetary or exchange terms (for example, two silver coins being considered appropriate compensation for a severed left hand) seem to have begun at that time. Since then, the law has had to adapt to innumerable new dilemmas, including corporate law (which involved literally inventing a fictional legal “person” for financial and liability reasons) and, more recently, intellectual property, environmental harms, and biomedical issues such as cloning. The legal system has also been Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

shaped by social conventions and government legislation that gives it near monopoly power to resolve all disputes. To a certain extent, it is embedded in the larger economic system and its disparities: wealthy people and large corporations can ‘tip the scales’ in their favour by hiring more and better lawyers than their less affluent opponents. However, it is important to stress that such adaptation to contexts is not entirely determined by such external influences. As in all complex systems, self-organization has played a role as well. For example, the legal system will often resist external pressures to change, or assimilate new dilemmas within its existing framework (for example, the way non-material ideas like patents were analogically equated with physical property—thus “intellectual property”). And, hard-fought cases can often help to bring significant change to the very social, economic and political structures in which legal system is embedded (recent same sex marriage rulings here in Canada, for instance, provide an example of how the legal system can bring about changes that a majority of people might not be ready to support). Similar but different self-organizing principles could be identified in other occupational areas as well. A fourth useful insight offered by complexity science concerns the incommensurability of differing systems. Because of their selforganizing and adaptive qualities, one complex system can never be collapsed into a mere instance, variation, or elaboration of another. Nor can two systems be entirely reduced to a common underlying phenomenon. As Davis and Simmt (2003) write, complex unities must be studied at the levels of their emergence… complexity science suggests that discourses concerned with different phenomena (such as radical or social constructivism—or neurology, ecology, or biological evolution) can be simultaneously incommensurate with Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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one another and appropriate to their particular research foci. (p. 143) A similar view regarding the irreducibility of disciplines concerned with different phenomena has been expressed by Nobel laureate Phillip Anderson. In his classic 1972 paper, “More is Different: Broken Symmetry and the Nature of the Hierarchical Structure of Science,” he 44 |

writes that no field of science is necessarily more fundamental than another. Disciplines concerned with larger scale phenomena, such as chemistry, molecular biology, and medical sciences, have unique “complications” and new types of behaviour that cannot be entirely reduced to particle physics or other rules originating at a more “fundamental” level (Anderson, 1972, p. 396). A similar point could be made about the social sciences and how they cannot be dismissed as merely vague extrapolations of the ‘hard’ sciences. These insights support my observation that each professional discipline enacts unique ways of knowing that cannot simply be translated or reduced into the terms of another area. Together, these four concepts—1) complexity’s expanded definition of what counts as a living, learning entity, 2) selforganization, 3) adaptation, and 4) the incommensurability of different complex systems—offer a very useful framework for understanding how occupational areas and the knowledge embedded within them can be so complex and diverse: Each occupational area can be seen as a self-organizing, learning system that has adapted over time and in relation to its own specific historical contexts or environments. Interdisciplinary Implications

Interdisciplinary teams are becoming more common in a wide range of Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

private and public sector areas. Everyone from Japanese automakers to Canadian health care providers are cultivating such teams in the belief that they can provide more effective and intelligent solutions to complex problems. Indeed, there is a significant body of literature available to support this belief (see, for example, Watts, 2003). If, as I have argued, we ought to understand professional disciplines as incommensurable complex systems, then this will likely have important implications for such interdisciplinary teams. For instance, it would seem to compel individuals working within such teams to continue defending the complexity of their own area and expertise, while at the same time (and this is the hard part!) respecting the complexity and expertise offered by other people’s areas. No doubt many other, subtler implications will be revealed as the conceptual tools of complexity are applied within the context of interdisciplinary teams. For present purposes, however, I would like to focus on one particular issue: the idea of consensus within such teams. Many people who have written on the subject of interdisciplinary teams stress the importance of consensus (see, for example, Ray, 1998, in the context of health care teams). Consensus is often defined as “general accord and agreement” (Dictionary.com, n.d.) or as “unanimity” in the sense of “being of one mind” (Merriam-Webster Online Dictionary, 2005). But, is such consensus or unanimity desirable or even possible in the context of interdisciplinary teams? Can people from different disciplines achieve consensus if, as I have argued, their professional systems and associated ways of knowing are truly incommensurable? The answer would seem to be “No.” Take, for instance, a doctor and a social worker who meet to develop a treatment program for a patient with a serious substance abuse problem. How can the doctor (whose knowledge is primarily concerned with an individual’s bodily systems and sub-systems) and a Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

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social worker (whose training is primarily concerned with family, social and economic systems) ‘be of one mind’ in developing a treatment program? Not only are they dealing with different complex systems (and the knowledge associated with that system), they also have different criteria for measuring success. The doctor will typically measure it at the bodily level (for instance, in terms of the functioning 46 |

of an organ), while the social worker will measure functionality in a more interpersonal or social sense. Does this mean that interdisciplinary teams are doomed to failure? Not at all! The problem is with the assumption that teams can and should reach a kind of mental consensus or unanimity. Interdisciplinary teams can and do achieve intelligent, effective action, I submit, even in the absence of such consensus. My own experience with web development—an activity that typically involves a wide range of disciplines—provides a useful illustration. When I was helping to develop Career Cruising’s website, I would meet regularly with programmers and graphic designers to plan the layout and organization of new webpages. I had a good understanding of our career-related content and how to write and do research, but I knew almost nothing about programming and visual design. The programmers and designers, on the other hand, knew a great deal about programming and visual design, but very little about our career-related content and the research and writing that went into it. When we met, one or more people would suggest an idea for a webpage and the others would offer feedback from the perspective of their particular expertise. For example, I might say that a particular page design would be suitable (or unsuitable) in terms of content issues, while a programmer might say that something would (or would not) work technically. Each of us would adapt our ideas in response to others’ feedback, even though we did not necessarily understand the Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

reason behind that feedback (I for example, might not understand why something was technically unfeasible). By the end of a meeting, a course of action was decided upon—though not necessarily unanimously—and we went our separate ways to work on our components of the new webpage. The crucial point here is that we had not reached a consensus; we were not thinking the same thing or “of one mind.” We each had a rough idea of what the new webpage might look like, but very little of the total knowledge that would go into developing the new webpage was shared. I did not learn much about the programming or design that went into the website, and the programmers and designers presumably still knew very little about career content, writing, and research. Instead, we each a rough idea of what we had to do to contribute to the new webpage and we thought and acted accordingly. A supporter of the consensus-based approach might object that a consensus existed not so much in our minds as in the realm of action, in the commonality of our work. Indeed, it is true that our actions were more or less complimentary and that they led towards the accomplishment of a collective goal. However, having a collective goal is not that same as achieving consensus among the individual members of that collective. Recall that social collectives, including interdisciplinary groups, are complex systems and that complex systems can be ‘greater than the sum their parts’; that is, they possess ‘emergent’ qualities that cannot be fully explained simply by analyzing them into their component parts. This means that a group can be said to have a collective behaviour or goal that is not necessarily ‘in’ any of the members of that group, considered individually.1 In the context of our Steven Johnson’s 2001 book, Emergence, offers many compelling examples of such collective-level intelligence, in realms as diverse as insect colonies, the Internet, and city growth. 1

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web development group, it meant that we could work together towards a common goal, in spite of the fact that our understandings of that goal, and our contributions to it, were quite limited and not entirely consistent. In any case, the preceding gives us good reason to believe that consensus is something that is quite difficult and perhaps unnecessary 48 |

to achieve in interdisciplinary teams. Furthermore, even if it could be achieved, consensus may actually be undesirable in interdisciplinary teams. A growing body of complexivist and complexity-compatible literature suggests that diversity and dissent are crucial to intelligent behaviour in complex systems, and that consensus-based approaches can lead to ‘information cascades’ and other forms of poor decisionmaking (see, for example, Davis, 2004; Watts, 2003; and Surowiecki, 2003). In The Wisdom of Crowds (2003), James Surowiecki, a leading business writer, expresses it thus: You do not need consensus in order… to tap into the wisdom of a crowd, and the search for consensus encourages tepid, lowest-common-denominator solutions which offend no one rather than exciting everyone. Instead of fostering the free exchange of conflicting views, consensus-driven groups—especially when the members are familiar with one another—tend to trade in the familiar and squelch provocative debate. (p. 203) Of course, there must be a way for such groups to aggregate or organize individual opinions in order to produce collective judgements and coordinate their actions (Surowiecki offers, as examples of successful group decision-making, certain forms of markets and voting systems that do not depend on consensus). But, assuming that some means of aggregating individual opinions is present, a group ought to protect and nurture the diversity and independence of its members, not Crossing Boundaries: An Interdisciplinary Journal NS 1.2 (2006) | © | ISSN 1711-053X | eISSN 1718-4487

seek consensus.2 With the right conditions in place—both diversity and some means for aggregating or coordinating individual activities—a group can produce collective solutions that are not only smart, but also “smarter than the smartest person’s solution” (Surowiecki, 2003, pp. 71, 75). Interdisciplinary teams should be well positioned to take advantage of such collective wisdom; by definition, they bring together people from a diverse range of professions. However, if we are to truly take advantage of this diversity, it seems we must dispense with the requirement for consensus and allow groups to self-organize in a less uniform manner. As we have seen, the consensus approach to interdisciplinary teams is problematic in several ways: 1) it is difficult, and perhaps impossible, to achieve due to the incommensurability of different professional disciplines; 2) it is probably unnecessary, since teams can act effectively even when they are not “of one mind”; and finally, 3) it may lead to poor decisions. In this paper, I have argued that professional disciplines can be seen as complex systems and that the different ways of knowing associated with them are largely incommensurable. I have also used this insight to examine interdisciplinary teams and, more specifically, to challenge the notion that such teams ought to be guided by consensus. Complexity science and related ideas such as network theory will no doubt offer many more insights into interdisciplinarity generally and interdisciplinary teams specifically in the future. What I have proposed here is just a small tip of what may turn out to be a very large iceberg— or, to use a metaphor better suited to complexivist sensibilities, just a

2 Surowiecki goes so far as to say that a differing opinion can make a group smarter even when it is wrong, since it forces other members of the group to interrogate their own positions more carefully (2003, p. 183-184)

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few threads in (a) much larger web(s) that I and many others are collectively weaving.

References

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