The Collective Intelligence Blog

To complete the trilogy of posts that I am writing in this blog to discuss the possibilities that Design offers to conceive participatory spaces that reinforce the democracy (I recommend first read the two previous releases: post I and post II), I will share as advance of the research I am doing for my book, a decalogue of principles that, in my own experience as a designer of participatory architectures, are critical for collective intelligence to be genuinely democratic

1. SIMPLICITY:

Simple rules allow for complex behaviors. Design guidelines must be minimal. The objective is to define basic principles for structuring the conversation and the aggregation. They should be a few but powerful. Be careful about over-designing because that, paradoxically, encourages simplistic behavior. Read more ›

In the previous post, I argued my thesis of why collective intelligence for democracy can be understood, and improved, from the point of view of Design. In this second post of the series, I will propose an equation (now in beta) that intends to summarize the factors that determine, and enable evaluation of, the effectiveness of a collective intelligence mechanism for democracy.

Going to the point, I propose to work with the following equation that can serve, in principle, as a frame of reference for building participatory design that can work well for the purpose:

Equation (Beta) of Collective Intelligence for Democracy:

CIforD = Effectiveness + Efficiency + Autotelic Process + Legitimacy

I will now describe each of these variables separately: Read more ›

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.- vnp 加速: 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 ›

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 小时候看不懂的片段，真的是太污了，你看懂了吗_腾讯视频:2021-8-23 · 小时候看不懂的片段，真的是太污了，你看懂了吗, 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 ›

I have finished reading “Wiser”, the latest book by the North American jurist and academic Cass Sunstein, co-authored by the Chicago University professor 搜罗vnp. 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 ›

Nowadays 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, “搜罗vnp”, 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. 搜罗vnp

Collective 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, vnp怎么搞 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 ›