The challenge of developing a governance models for collective intelligence

A blogpost for The MacArtur Foundation Research network on Opening Governance

Collective intelligence often refers to the process by which large groups of individuals pool their knowledge, data and skills to contribute in solving societal issues. By inputting environmental or clinical data, mapping territories, discussing and voting, coding and writing, citizens can contribute their knowledge and ideas to data collection tasks, analysis, decision making and public debates.

Two converging phenomena have brought to the forefront the idea of leveraging collective intelligence to address problems of public policy. One is the pressing demand for innovation in models of public governance. The combined effect of loss of trust in elected officials and government institutions, coupled with the increased complexity of social and political issues, is pushing traditional public services to incorporate more participatory models of governance. The other is the increasing ease with which networked publics can carry out participatory activities online. The simplification of  digital tools and platforms, combined with growing digital literacy and an ever increasing sophistication of computational systems, has expanded the range and complexity of activities in which citizens can now be involved.

The most spectacular examples of collective online action, such as Wikipedia, the Linux operating system, or numerous other results from the Open Source dvelopment movement, have shown the potential of digital tools and a distributed networked public to generate forms of collective intelligence. These forms of collaboration and joint action seem to be qualitatively different from other and more traditional forms of social action, in that they are essentially epistemic. They also have characteristics which depart from more classical forms of division of labour which have underpinned industrial production and are still present in some forms of digital labour (Scholz 2013).[1] The number and distribution of people, the presence of digital platforms and specific structures of coordination, as well as unprecedented modes of participation and governance, are constitutive elements of tthe production of new forms of knowledge.  However, we know by now, that it is exceptionally difficult to replicate these cases and that there are a complex set of requirements for such forms of intelligence and collaboration to emerge.

In our work we are trying to understand how to support groups of distributed citizens, with a loose organisation, to coordinate and produce complex solutions to major societal problems, be they in healthcare, sustainability or economic development. The processes we are attempting to enable seem to have an emergent property that in our view are evocative of the mechanisms underlying cultural transmission. When looking at the cognitive, cultural and organisational dimensions of collaboration, the conditions for the emergence of a certain form of cognitive coordination seems to be best explained in analogy with cultural development.

There is ample evidence showing that humans have a cognitive predisposition for collaboration which is manifested in the capacity to elaborate we-intentions and joint objectives (Tomasello 2011, 2008, Tomasello et al. 2005).[2] This process is sustained by the production of  public representations such as utterances, writing, tools or other artifacts which not only make manifest individual mental states but become material forms that can be revisited, modified, reflected upon, transmitted by multiple people. Digital networks are obviously greatly extending and accelerating the distribution of such public productions and computational systems are allowing for an infinitely greater potential of transformation. Collectives are not only producing content but are actively working on the tools, notations and organisational models to bring these about.  If we take any open source development project, the intelligence of the collective is being expressed not only in the production of the code, but also the legal framework, the notation, the labeling, the usage modes, the organisation and learning processes. The full visibility, access and modifiability of the system are a source of motivation for the participants and the basis for learning and improving. The collective learning is materialised in the tools themselves which in turn give rise to improved contents which then require the tools to be improved. This process of learning and refashioning is in our view the most compelling description of collective intelligence. Chris Kelty (2008) calls this a “recursive public” a concept to describe the unique phenomenon of a public which builds and modifies the tools and conditions that enable its existence. The constant refashioning of tools and representations is an integral part of the collective intelligence of the project as it serves as a constant rekindling and redefinition of the joint objectives.

Not all internet systems however, have the capacity to support collective intelligence. We have witnessed numerous failed attempts to generate “collective wisdom” by bringing together citizens on loosely designed discussion platforms. Public forums to discuss policies, budgets, health or other crucial topics often fail to generate the collective creative output that we witness in Openstreetmaps or Wikipedia. Often these platforms simply offer text boxes where individuals can write opinions and reply to others. In practice they offer an open environment for debate with limited functions for storing and grouping the discussions. In these systems the burden of coordination and synthesis is on the participants and it comes as no surprise that participation is low, discusssions repetitious and conversations dwindle after few interactions.

These types of environments do not offer objects on which to jointly operate, they do not provide visualisations of the common results, they do not make tangible the “whole” emergent results. What they offer on the contrary is exactly the contrary, elements which display the individual contributions, the parts or fragments. By not providing a sense of the emerging collective output they inhibit the creation of the collective itself.  From these experiences what we can learn is that for digital systems to become components of the collective extended mind and foster collective intelligence, they have to have some characteristics. These characteristics include the possibility to modify the tools, aggregate the contents and contributions, retrace the history, visualise the aggregations and the single elements, include analytic tools and allow the negotiation of terms. In other words, systems should support learning and metacognition through synthesis and modification, mimicking the process of cultural transmission.

Collective intelligence also emerges in social contexts which are never isolated but operate in interaction or opposition to existing institutions that want to leverage collective action for an objective. When thinking about the prerequisites for collective intelligence it seems therefore essential to stress the inter-dependance of the technology with a certain governance model in order to enable cognitive predispositions for cultural transmission to fully emerge. The challenge for collective intelligence in social groups, is not only to create settings for sharing and communication, but also to provide the means for knowledge to be assembled, sedimented and above everything, modified. There is a fine balance between preservation and modification : ensuring the continuity of  the knowledge produced, while allowing constant refashioning and appropriation.

Any reflection on the governance models to sustain processes of collective intelligence, should therefore consider what are the legal, economic and administrative requirements for an open and reusable system of knowledge creation and sharing which recognises the multiple entanglements of knowledge systems (Coombe 2008, and Cohen 2006, 2012).[3]  Culture and science develop through a constant process of imitation, pastiche, copying, recombination and gradual modification. It is a collective process of appropriation and transformation and open source development have showm us how this happens in an accelerated mode. The opposition between a model of individual authorship and one of collective social construction of cultural content, has been discussed before in relation to copyright law (Coombe 2011) but it seems relevant once again when thinking of collective intelligence. The ongoing battles around intellectual property law are therefore a good example of why governance models are a crucial condition to ensure that collective intelligence can in fact emerge.

[1] Scholz,T. 2013. Digital labor: The Internet as playground and factory. New York: Routledge

[2] Tomasello, M. 2008 Origins of Human Communication, Cambridge, Mass., MIT Press

Tomasello, M. 2011 Human culture in evolutionary perspective, in M. Gelfand, Chi-Yue Chiu, Ying-Yi Hong (eds), Advances in Culture and Psychology, Oxford, Oxford University Press.

Tomasello, M., Carpenter, M., Call, J., Behne, T. & Moll, H. 2005 Understanding and sharing intentions: The origins of cultural cognition, in «Behavioral and Brain Sciences», 28, pp. 675-691.

[3] Cohen, J. E. 2012 Configuring the Networked Self: Law, Code, and the Play of Everyday Practice . New Haven, Conn.: Yale University Press

Cohen, J.E. 2006 Copyright, Commodification, and Culture: Locating the Public Domain,” in P.B. Hugenholtz & L. Guibault, eds., The Future of the Public Domain 121-66, The Hague: Kluwer Law International

Coombe, R.J. 1998 The cultural life of intellectual Properties: Authorship, Appropriation and the Law. Durham : Duke University Press reprinted 2008

Coombe, R. J. 2011 “What’s Feminist about Open Access? A Relational Approach to Copyright in the Academy”” feminists@law: an open access journal of feminist legal scholarship 1(1): (with Carys Craig and Joseph F. Turcotte).


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