The evolution of regulation of, on and even by the Internet clearly demonstrates the influence of ‘cultures of regulation’ on interventions and the ‘fitness’ of technological and behavioural innovations. These cultures – and the associated stovepipes - complement the formation of conventions of service provision, investment, business models and enterprise coordination, individual (customer or end-user) behaviour and technology development. This leads to punctuated equilibrium; each period’s gaps and slack create the conditions for the next phase. These phases are not simply defined by adoption of new models or regulatory tools; instead they are marked by often dramatic changes in: the allocation of power and flow of information among government, business and civil society; the participants in each domain and the objectives or challenges to which they pay attention; and the effects of laisser-faire policies. This suggests at least two reasons why it is no longer sufficient to respond to new challenges as they come along. At crucial moments, change may be too fast or complex for effective response. More importantly, the information needed to identify governance challenges and to formulate, assess and implement interventions (or decide that no response is possible) may be unobtainable, impossible to interpret or unreliable. Especially on the Internet, where almost everything can be observed but very little may be worth the effort of collection and analysis, these twin problems of informational complexity and endogeneity may call for approximate (rather than light-touch) forms of intervention, principles-based and reliant on self-organisation to a much greater extent than even today’s ‘smart regulation.’This paper combines evidence from the coevolution of advanced telecom-based services and new forms of regulation with a simple model of strategy choice in a complex adaptive network to develop a framework for adapting regulation to an environment in which networked information is faster and more extensive, by taking into account the persistence of regulatory cultures and their influence on the way new problems are recognised and dealt with.For instance, a formerly dominant model of telecom regulation combined a technological focus (e.g. efficient use of spectrum and network capacity) and an economic perspective based on natural monopoly regulation (e.g. of network infrastructures) and the ex-ante economic efficiency of competition (e.g. regulatory approximations to Ramsey pricing and facilitated entry) with limited societal regulatory objectives (e.g. Universal access/service and discrimination in favour of local call access). This was reasonably well-adapted to telephony and analogous binary content exchange services (e.g. Fax). Indeed, the forms of ‘slack’ it created facilitated the emergence of new services, technologies and business models, especially Internet-based services focused on content access and distribution. This gave rise to the period of ‘converged regulation’ either around content and communication (UK’s OfCom, with its additional heritage of societal content regulation and extended vertical market power concerns) or network industries (Germany’s BNetzA, with its additional attention to network and cross-network externalities and to system resilience). These in turn led to different architectures and models for e.g. network provisioning, QoS and access pricing and to different ways of tackling new issues associated with this change e.g. privacy, DRM and net neutrality. At the same time, existing regulatory tools (e.g. spectrum allocation processes and licence forms) began to change. Further changes now in train (linked to e.g. the Internet of (sensor and actuator) Things and computer-based financial trading) are forcing redefinition of terms like QoS and privacy, and causing fundamental metaphors to shift from content to interaction, from informed consent to emergent or herd behaviour and from ‘prudential’ (entity-based) to ‘macroprudential’ (structure-based) market surveillance and intervention. The paper defines a modelling and evidence framework for policy formulation and assessment.
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Sep 30, 2016
Konstantinos Blazakis + 3
Open Access
