New technologies to service SSR: The power of Collective Intelligence

by Etienne Sompairac · December 19th, 2018.

Engaging in Security sector Reform (SSR) is an intricate process which heavily relies on the thought process leading to the design of reform. To be sustainable, SSR programs require a broad scope of analysis with a wide range of actors. As such, online platforms harnessing the power of Collective Intelligence (CI) could facilitate the consultative phase and improve the quality of its outputs. Firstly, this blog will introduce the concept of Collective Intelligence. Then, it will focus on how CI could become an innovative tool for SSR regarding consultations preceding the design of reforms. Finally, it will briefly present Collective Intelligence’s limitations.

Although the term Collective Intelligence was coined quite recently, the premises of the concept were theorised by Nicolas de Condorcet in 1785 in his “jury’s theorem” which established that a group of individuals has a good probability of chances to collectively take a fair decision. 121 years later, Francis Galton witnessed a contest whereby 800 participants to a livestock fair were invited to guess the weight of an ox. To his surprise, the mean of the crowd’s estimates proved to be the exact weight of the animal. From then on, he put forward the concept of the “Wisdom of Crowds” which could be considered one of the epistemological ancestors of Collective Intelligence.  Collective Intelligence could be defined as the group intelligence that emerges from the collaboration and collective efforts of multiple individuals that leads to a form of consensus-based decision-making. Applying Collective Intelligence would consist of gathering predetermined actors on an online platform, engage them on a specific topic and collect the data derived from the process. Harnessing such collective brain power and engaging in a debate on an extensive scale can contribute to making better-informed and more sustainable decisions. However, CI requires a form of piloting by experts which will manifest through the consultation’s design and through the identification of valuable outputs. Stimulating participants’ interest in the consultation is also key; involved actors should understand that participating in the consultation process is in their own interest. CI is comparable to an orchestra. Every musician enjoys and knows how to play his instrument and can contribute to the group effort. Yet, the band needs a conductor to transform the din into a harmonious symphony. 

The political use of the Internet remains underdeveloped in light of the opportunities it presents. Collective Intelligence is one of these facets that still needs to be explored. CI’s potential is tremendous in light of its greater cost and time efficiency and the improved context-understanding that would result from engaging a broader audience with a greater diversity in views. Harnessing Collective Intelligence has the potential to reinforce the consultative phase preceding the design of reforms, to support the local ownership’s process and to result in enhanced knowledge. All these aspects could entrench sustainability thanks to the reforms’ increased legitimacy.  Yet, CI processes require significant mitigation strategies because structural and material constraints such as poor literacy rates or the absence of Internet could impede the procedure.

A good example of Collective Intelligence being used to source public strategies is the platform where experts write blog posts to generate a debate that then in turn influences the German government’s approaches. Other, more evolved platforms to harness Collective Intelligence are Assembl, Crowdoscope and Kiola. For instance, Assembl hosted a debate on the Civic Governance of Artificial Intelligence which also led to the production of a report which brought together a collection of the most interesting suggestions that stemmed from the process. This is a concrete example on how new technologies could support and improve the efficiency of consultative phases, a key step in designing effective and long-lasting reform processes.  

The consultative phase preceding the design of reforms is time-consuming and limited in reach due to resource constraints. Despite issues of representation and accessibility, using online collaborative platforms could help overcome these challenges, thereby increasing the efficiency of the consultative phase and asserting CI’s role as an innovative tool for SSR. While conducting their assessment of the Security Sector, experts have to go through a lengthy interviewing process that will only be partially satisfying because they rarely have the time to engage with all actors that could potentially have a say in the issue and who could share a unique stance on a topic. Ultimately, using Collective Intelligence would allow SSR practitioners to encompass much more actors in the deliberation process, leading to better adapted and more sustainable programs.

Yet, involving more actors means producing more ideas and more debates which would only burden experts with more work hence the importance to follow the principles of “Idea-filtering with the bag of lemons”. This approach is based on the assumption that it is easier for human brains to perceive what could be a bad idea rather than to perceive what could be a good one. Therefore, users could filter ideas by flagging the ones they believe to be irrelevant meaning that the relevant ones needing further studying would be easily identified. Collective Intelligence could become a worthwhile fact-finding technique as it is a way of optimizing and modernising the concept of “satisficing”, a practice which entails searching through the available alternatives until an acceptability threshold is met. Using online collaborative platforms would be an efficient way to do so by expanding the scope of analysis and reinforcing the inclusive character of the consultative process without necessarily adding more tasks to the experts’ workloads.

Collective Intelligence enables experts engaged in SSR to directly connect with local populations. In turn, the collective thought process could lead to improved contextual understanding and better consideration of local perspectives which would reinforce SSR practitioner’s expertise and lead to better-informed decisions.  While experts can guide the debate by asking the right questions and suggesting key themes, local populations can directly influence the design process of SRR by feeding in their understanding of issues at stakes. Harnessing local Collective Intelligence would not only shape SSR through a culture-sensitive lens, it would also instill a greater sense of local ownership. These two aspects are crucial to guarantee the long-lasting character of SSR and would provide enhanced legitimacy. This might as well assist in a potential local appropriation of the process. Through Collective Intelligence, locals could continually build upon the SSR process as an existing institutional basis to incrementally improve policies. This would foster a greater symbiosis, driven by democratic values, which could translate to a more cohesive society.

The following steps could guide the implementation of Collective Intelligence to SSR:

1-     Establish the issues at stakes and questions to be answered.

2-     Identify actors that should be involved in the collective thought-process.

3-     Choose the most adapted online platform to conduct the consultation.

4-     Invite actors to take part in the process and, if necessary, provide them the means to do so.

5-      Launch the consultation on a determined time-scale.

6-     Collect and analyse data and then compile a report as a guide to SSR implementation.

Nonetheless, Collective Intelligence cannot replace individual expertise and should be seen as a complementary process that would support the design of reform processes and reinforce their legitimacy. Defining clearly the inputs and what the consultation should revolve around is key to Collective Intelligence to ensure that intended goals are met. Moreover, the choice of participating actors and the sense of what constitutes a good idea are also inherently biased. As such, experts could potentially overlook some options that would not seem interesting to them but that could be better adapted to the ground’s reality. In accordance with typical consultative procedure, implementing Collective Intelligence requires a solid mitigation strategy taking into account a multiplicity of factors such as the neutrality of the platform, the nature of internet access, identity-related issues and the risk of actors hijacking the process.

To conclude, Collective Intelligence is simple in principle but conceptually complex. From an SSR perspective, it is the duty of SSR practitioners to broaden as much as possible the scope of consultations and Collective Intelligence can help fulfill this goal. This innovative approach to SSR can significantly contribute to implement sustainable Security Sector Reforms as it would facilitate the consultative phase preceding the reforms’ design and enhance the process’s legitimacy and sustainability through its inclusive character. SSR experts could shape their policies according to locals’ expertise and understandings which should enhance SSR programs’ efficiency and relevance. Thus, Collective Intelligence could become a valuable tool to entrench sustainable reforms and maximise the impact of programs designed by national, multilateral and bilateral actors. The combination of social theory to today’s technologies promises to disrupt our current modes of thinking and operating. The practical applicability and the power of Collective Intelligence could signal the dawn of a fascinating and auspicious future for Security Sector Reform. The digitalization of political interactions is approaching and there is no reason why SSR should not benefit from the promising opportunities it provides.  

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