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Aggregation mechanisms, Collaboration Culture, Complexity, Decision Making/Problem Solving, Emergence/Self-organization, Examples/Cases, Governance/Leadership, Group Performance, Participation, Politics/Democracy

Scaling is a big challenge for Collective Intelligence

Crecimiento_escaladoIt seems quite clear that the new “collaborative economy” is a good example of how advances in Collective Intelligence can add a lot of value through mechanisms like “collective filtering” attenuating the impact of “the Paradox of Choice”. The Basque consultant Julen Iturbe explains it very well in a blog post: As collaborative products and services eliminate scarcity of professional services and can be provided by anyone with a resource (a room at home, a seat in the car…) to spare, we face a hitherto unknown problem: “the offer can overwhelm our capacity to deal with it”, and this is when we really have to talk about getting attention.

I don’t think that these initiatives will die being over bloated and hypertrophic as Julen suggests. This will not happen because abundance automatically tends to create its own selection mechanisms. New P2P intermediaries like Airbnb know this very well. Indeed their differentiation efforts are now centered on two aspects: 1) recruitment, 2) filtering.

However overwhelming the offer, there will always be a way to get on to the “front page” without being dragged down by Schwartz’s paradox. I am a frequent client of Airbnb and my choices are based on the comments of people that have stayed in the rooms I am checking. It may well be that this filtering mechanism is not optimal and doesn’t quite satisfy expectations, but the same is true of the offer of more traditional middlemen such as Booking or Trivago.

Obviously there is no easy solution. I believe that the challenge lies midst metadata and comment/reputation management. The problem of “attention distribution” that is created by abundance cannot be solved by shouting louder, we must improve the mechanisms that help separate the signal from the noise. But what is really interesting is that the problem of choosing a room with Airbnb in Paris is very similar to the problem of scaling as the number of members of a collective. The more people intervening in a dialogue, the greater the risk of it “overwhelming our capacity to deal with it”. Read more ›

by × June 2, 2015 × 0 comments

Complexity, Emergence/Self-organization, Group Performance, Network Design, Politics/Democracy

CoNNective vs. CoLLective Intelligence: the individual and the collective

Conexiones

There is an open debate on the Net about “CoNNective Intelligence” in contraposition to “CoLLective Intelligence”. It all starts with the sociologist Derrick de Kerckhove, and his Theory of Connected Intelligence, that tries to update Pierre Levy ideas which he considers too “collectivist”. Later George Siemens, in his article “Collective Intelligence? Nah. Connective Intelligence”, directly sets both types of intelligence against each other, stating that Collective Intelligence “favors the group” in search of a common identity whilst Connective Intelligence is based on the individual that, seeking self-satisfaction, contributes value to the group.

This is a timely debate as it considers the way individuality is perceived in these processes. Following the foresaid distinction Del.icio.us, the social bookmarking site, is a good example of Connective Intelligence. Users of this service are mainly seeking their own interests, trying to organize their bookmarks in the cloud and, as a consequence of their “selfish” motivation, are the spinning of a net of connection among links that improves collective knowledge. Wikipedia is the flagship of Collective Intelligence. The individual contributor sets out to create or edit an article of that is part of this collective effort.

I agree that different motivations give rise to both types of intelligence, but I would like to reconsider the term “Connective Intelligence” seeking a better, less confusing, definition. In the book I am writing, these posts are tidbits of what is underway, I intend to speak of connective intelligence as intelligence developed by individuals as they connect to collective networks of knowledge. That is improved individual intelligence as a result of participating in a group. Read more ›

by × May 28, 2015 × 0 comments

Aggregation mechanisms, Collaboration Culture, Examples/Cases

Lévy vs. Surowiecki: Collective Intelligence with no Collaboration?

Musical group_Stoney Lane

One of the things I have had trouble explaining when defining the concept of Collective Intelligence is the preceding headline. That is, there are situations that can lead to Collective Intelligence (CI) in which individuals do not interact directly or are even conscious of the fact they form part of the collective.

The MIT Centre for Collective Intelligence and many well-known authors in the field admit both the results of non-conscious aggregations and the consequences of active collaboration as manifestations of CI. In James Surowiecki’s “The Wisdom of Crowds”, the book that popularized CI, there are plenty of examples based on pure statistical aggregation, that is, without any direct interaction among participants.

To make the differences between modalities clearer I use the terms “Collected” and “Collaborative” Collective Intelligence. Let me explain both. Read more ›

by × May 26, 2015 × 2 comments

Aggregation mechanisms, Collaboration Culture, Decision Making/Problem Solving, Group Performance

Wiser, Groupthink and the Common Knowledge Effect

Wiser menI have finished reading “Wiser”, the latest book by the North American jurist and academic Cass Sunstein, co-authored by the Chicago University professor Reid Hastie. It was published in January 2015, so the print is still quite fresh. The book is mainly of interest because it covers factors that give rise to (and can inhibit) Groupthink.

As you may remember, “Groupthink” is a term coined in the seventies by the psychologist Irving Janis, naming those situations where individuals participating in a group adapt and submit to the collective opinion even if it differs from their own point of view. The more cohesive the group the stronger the bias, because the social (and informational) pressure that generate cohesion affect the individuals’ capacity to make good use of their private information sources, thus gravitating to the groups’ central opinion. The consequences of this behavior are negative. Groups end up making bad or irrational decisions because the diversity of opinions of the individual group members are not aggregated efficiently.

Wiser” addresses this issue in two parts. The first half of the book analyses the factors that lead to different cognitive biases when groups are at work as a collective. The second presents different palliative measures for the Groupthink effect.

This subject has been approached by many authors. James Surowiecki, in “The Wisdom of Crowds” analyses this phenomenon in some depth (with plenty of examples), reminding us once more that “as a group becomes more cohesive, the individual becomes more dependent“. Reducing the adverse effect of Groupthink is one the greatest challenges in the practice of Collective Intelligence. Read more ›

by × May 20, 2015 × 0 comments

Collaboration Culture, Complexity, Decision Making/Problem Solving, Emergence/Self-organization, Governance/Leadership, Group Performance, Participation, Politics/Democracy

The limits of diversity: how much is right?

celebrating diversityNowadays no one needs to prove that cognitive diversity is an important factor that enables groups to act intelligently as a collective. James Surowiecki took the trouble of explaining it in his “Wisdom of Crowds”; so today I am not going to talk about how good diversity is for collective intelligence but about a less covered aspect, that is, to question if there are degrees of diversity that, under certain circumstances, could end up being detrimental.

Some time ago I discovered that diversity is a factor that, at a certain level, creates noise punishing group intelligence. I have seen this in a few projects so I set out to find argumentation to help me confirm my observations. A book I finished this weekend has been handy, and it is well worth a blog post of its own, “Too big to know”, by David Weinberger.

Based on the experience of Beth Noveck (an academic that worked a few years on Obama’s Open Government initiative), Weinberger explains that in environments where there is pressure to get things done, where apart from cogitation action is needed, the point where diversity becomes a problem, rather than part of the solution, must be pinned down.

We enjoy diversity until we discover what it really means”, and this is completely valid when managing high impact projects, where there are clear expectations about results. So it seems that there is a “correct degree of diversity”, after which we start getting into trouble, because the cost of reaching consensus or aggregating opinions exceeds the benefits of having different points of view. At the tipping point feasibility begins to be more important than diversity. Read more ›

by × May 19, 2015 × 1 comment

Aggregation mechanisms, Emergence/Self-organization, Group Performance

Collective Intelligence as a process of aggregation

Collective artThe most referenced concept of “Collective Intelligence” is the one of the MIT Center of Collective Intelligence (CCI): “Groups of individuals acting collectively in ways that seem intelligent”. I already said that it seems to me a weak definition because it is too vague and because it has a limited operative value.

I understand the reasons of the CCI to define a conceptual framework as flexible as possible, especially considering that it is indeed an emerging area of ​​study and it is intended to highlight the inter-disciplinary nature of this field. But even so, I think that trying to fit all the possible definitions in a politically correct one leads to a decaffeinated definition, whose main weakness is that it is not useful to discern.

A good concept is not one that tries to adapt to all existing perspectives, but the one that helps to understand the limits of the identity of something, that is to say, what do we leave inside and outside of the subject we try to define. In fact, often the most effective way to test the reliability of a concept is to see how much it helps to leave things out, that is, it serves to discern. Read more ›

by × June 30, 2014 × 0 comments

Collaboration Culture, Decision Making/Problem Solving, Group Performance, Participation

Toward a more functional definition of Collective Intelligence

Collective Intelligence-2Collective Intelligence (CI) generates increasing interest as an emerging discipline, but it seems difficult to find a clear and intuitive definition of what it means. It is tried to partly alleviate that deficit by adopting the terminology used by the MIT Center of Collective Intelligence but in my opinion the CCI intends to encompass so many scopes that lead to us to a definition very little operative.

For example, Thomas Malone and his team often use this definition of CI: “Groups of Individuals acting collectively in ways that seems intelligent“. Quite frankly, I do not know if this clarifies anything or adds more confusion for people like me who are looking to put theory into action.

The ontological advances in the field of CI either do not seem to give great results. We do not have a conceptual framework that serves to agree on the narrative. The universe of disciplines that converges here is broad, and knowledge is very fragmented. The diversity is good, but there is an excess of cognitive dispersion that does not help to achieve consistent progress. In fact, I know that is difficult to categorize the issues or to have a taxonomy that contributes order when we want to accede to research results. So it seems necessary to review and to simplify the narrative we use to reach more people. Therefore I’ll try to explain what I mean by Collective Intelligence as intuitive as possible, although I do not know if I will be able to :-( Read more ›

by × June 9, 2014 × 2 comments

Crowdsourcing/Co-creation, Decision Making/Problem Solving, Participation

Types of problems that can be solved by Collective Intelligence

CollectivesPeople often ask me about what kind of problems best leverage the benefits of a collective intelligence (CI) approach. I always say it depends on several factors, but according to my experience I think I am able to advance here seven types of problems or challenges that that can be suitable for open and participatory project with good results:

  • Creativity: CI is quite effective at generating ideas. The more people thinking, the more likely they will find a creative solution.
  • Bias assessment: Activities those are highly susceptible to selection and assessment biases due to their inherent relativity or spurious interests. CI works well in data interpretation tasks subject to many different perspectives. Opening the analysis to a wide variety of points of view can help reduce the “expert bias” and achieve a more complete and balanced judgment.
  • Distributed Surveillance: Activities in which the cost of failure is high. Any errors are best detected if more people are reviewing (Remember Linus’s Law enunciated ​​by Eric Raymond: “Given enough eyeballs, all bugs are shallow“).

Read more ›

by × May 5, 2014 × 0 comments

Complexity, Decision Making/Problem Solving, Emergence/Self-organization, Governance/Leadership, Interdisciplinary approaches, Politics/Democracy, Social Networks

Biomimetics and Collective Intelligence

antsNature can inspire us to explore emerging models of interaction that will help to better understand patterns of collective intelligence in human groups. Steven Johnson, in his book “Emerging Systems” (2001), masterfully demonstrates how that connection (called Biomimicry or biomimetics) is full of metaphors. The Web Ask Nature, the Biomimicry Institute, brings together hundreds of examples of such associations.

In a previous post I mentioned that one of the things I liked about the Collective Intelligence Conference held at MIT in April 2012 was to listen to Deborah Gordon (Stanford) and Ian Couzin (Princeton), two behavioral biologists, who focused on the study of the patterns of behavior of animals in their natural habitats. They are not “biologists” in its classical sense but work as multidisciplinary groups that are making increasing use of mathematics and computer science as well as tracking and geolocation devices to investigate the collective behavior of swarms or “Swarm Intelligence“, a branch of artificial intelligence based on the collective behavior of decentralized and self-organized systems. Read more ›

by × May 5, 2014 × 1 comment

Collaboration Culture, Complexity, Group Performance, Network Design, Participation

7 forces that influence community building

CommunitiesIt’s hard to question the superiority of networks for activities such as collaborative learning (type “communities of practice“), experimentation with new cultural approaches, idea generation, or to mobilize in favor of some collective claim.

But what happens when the challenge is to put many people to work together to achieve certain results respecting deadlines and costs, and also do it by cultivating an ongoing relationship . I’m talking about “productive” and “stable” networks, that is, a reticulate model without organic links, which poses work for projects within deadlines and that the result can effectively overcome the company.

In my experience, these conditions can only be fulfilled if we conceive networks of higher order, more than “ordinary networks“, and therefore we would have to call them differently, to distinguish them from those based on weak ties structures, which are good to encourage creative and random connections, but not to serve goods and services, or manage complex projects. Read more ›

by × May 5, 2014 × 1 comment