Emergence/Self-organization

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

Aggregation mechanisms, Collaboration Culture, Crowdsourcing/Co-creation, Decision Making/Problem Solving, Emergence/Self-organization, Governance/Leadership, Participation, Politics/Democracy

10+1 attributes of ideal challenges for Collective Intelligence

Desafios-1

Not all problems are equally suited to a collective approach. In this post I propose a way of typifying problems most likely to be successfully treated with CI. Here is a list of 11 attributes of a task or challenge that give reason to believe it is particularly suited for the use of Collective Intelligence. The greater the number of these attributes presents in a certain problem, the greater the chance it is wise to go for a collective stand:

1.- Geographically highly disperse data that is costly to collect: Situations in which collecting and aggregating large amounts of data can significantly improve our analysis but in which this data is so highly dispersed that it is expensive and cannot viably be gathered by a small group of agents.

2.- Vastly varying views when interpreting the problem: When a problem, or its interpretation, can be seen in different lights, depending on the interests, roles and experience of different agents in relation to the challenge, it would seem a good idea to create a collective space in which these differing perspectives can meet. CI is favorable if diversity is a factor that affects the quality of the final results.

3.- Multidisciplinary nature: Situations that may coincide with previous attribute, but in this case refer to cognitive diversity (neither roles nor interests, differing paradigms) that requires the solution of a complex problem with inputs from different fields of knowledge. As we shall see, the greater the mutidisciplinarity of a problem, the more can be gained with CI because participating agents will self-select and no point of view, that can add value to the analysis, will be lost. Read more ›

by × May 31, 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 × 1 comment

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 × 8 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, Emergence/Self-organization, Group Performance, Participation, Reputation mechanisms

Open Participation vs. Expert Groups: Biases and filters

MultitudesDuring the training workshops I give, the participants often ask me the following question: what are the advantages and disadvantages of the open participatory models vs. expert groups?

This issue appears at almost every debate on collective intelligence. I could use Manichaean way of saying it: “collective intelligence ALWAYS works better than the experts“, but it is not true. There are circumstances that give advantage to one option over the other, and even though both of them have their drawbacks.

I used to think that the answer has laid in the level of the “technical” complexity of the problem. I thought if it was a very complex problem, with specific expert skills requirements, then the experts solution could work better. But then I´ve realized that it is not so relevant, and that the key to succeed is how you design the spaces for participation.

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by × August 30, 2013 × 2 comments

Collaboration Culture, Complexity, Decision Making/Problem Solving, Emergence/Self-organization, Group Performance, Network Design

Networks, enterprises and transaction costs

1_Colaboracion grupos_Eric Constantineau FlickrIn this post I would like to share an idea that seems to me quite complex: Are networks better than companies? Is it true that the “transaction costs” have collapsed so much to make the “network” a superior alternative to the “enterprise”?

Well, once again, let me say “that depends”: The networks are not always more agile than firms. It is rather the opposite: usually it happens that they involve a great complexity of relationship management. Yes, a robust and well-oiled network can be more agile than a versatile firm; okay … but to achieve this is not easy at all.

It hurts me to recognize that networks that work well and are agile, are still an exception rather than a rule. They serve to share ideas and to promote the exchange of knowledge, but when it comes to make a joint effort and carry out the distributed work, a lot of inefficiencies jump out.

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by × August 11, 2013 × 0 comments