The following astract was submitted to CCS16 by Kunbei Zhang and Aernout Schmidt:
Blending Complexity Research
Disruptive complex adaptive systems (CASs, e.g. the profiling/social-media complex) put more and more pressures on individual agents’ capacities to act autonomously and responsible. As legal theorists we have some questions here. The foundation of our trade is a conception of individual freedom that supports liability for deliberate behaviors. Thus: pressures on individual agents’ capacities to act autonomously disrupt the basic paradigm of our discipline. This is worth investigating. Yet, investigating the potential of CASs to disrupt the law as a cultural survival vehicle requires “blended research,” by a whole gamut of disciplines, including legal theory.
Blending different disciplinary efforts is notoriously difficult, as each discipline tends to develop its own technical language for its own specific specializations. `Tort’ is a different concept for legal and for non-legal specialists, as `rational choice’ is for economic and non-economic specialists, as `culture’ is for anthropologists and non-anthropologists and as `inflation’ is for cosmologists and non-cosmologists. These differences are sticky, as they tend to nurse specialist identity. In order to support diverse specialists to work together on complex problems in cross-disciplinary teams we need a lingua franca that allows for discussing and deciding on the merits of the models involved while leaving relevant parts of the domain of discourse to specialists. How can we do that?
That is what this contribution is about. We distill an instance of the lingua franca required from the requirements-engineering literature that has emerged in the computing sciences around 2000. We introduce simple techniques to support cross-disciplinary discussion, using Acemoglu and Robinson (2001)’s formal econometric model of democratic/non-democratic regime change as a vehicle. And we show how the approach helps improve access to comprehension of complex situations by blending cross-disciplinary contributions.