We Think Therefore We Are: The Study of Collective Intelligence

Endless studies have been made regarding analyzing the nature of human intelligence as individuals, but now with the growth of the Internet and social media (Facebook, LinkedIn, Twitter, etc.), new models and approaches are being called upon as the new field of ‘Collective Intelligence‘ comes to the fore.

Collective intelligence is simply what its name implies: studying the nature of intelligence as a series of groups or collectives. And the man who’s leading the development of this new field is Thomas Malone of MIT (http://io9.com/5962914/the-emerging-science-of-collective-intelligence–and-the-rise-of-the-global-brain). As Dr. Malone put it:

I’d define collective intelligence as groups of individuals acting collectively in ways that seem intelligent. By that definition, of course, collective intelligence has been around for a very long time. Families, companies, countries, and armies: those are all examples of groups of people working together in ways that at least sometimes seem intelligent.

Well, at this point, one has to point out that groups of people don’t always act intelligently – at least not in ways that we may regard as being smart – as Dr. Malone also pointed out:

It’s also possible for groups of people to work together in ways that seem pretty stupid, and I think collective stupidity is just as possible as collective intelligence. Part of what I want to understand and part of what the people I’m working with want to understand is what are the conditions that lead to collective intelligence rather than collective stupidity. But in whatever form, either intelligence or stupidity, this collective behavior has existed for a long time.

So what does any of this have to do with the price of beans in China, you may ask? After all, it all seems kind of obvious when you think about it (as the old saying goes, ‘a person is smart; a group of people aren’t’).

Think again:

What’s new, though, is a new kind of collective intelligence enabled by the Internet. Think of Google, for instance, where millions of people all over the world create web pages, and link those web pages to each other. Then all that knowledge is harvested by the Google technology so that when you type a question in the Google search bar the answers you get often seem amazingly intelligent, at least by some definition of the word “intelligence.”

Or think of Wikipedia, where thousands of people all over the world have collectively created a very large and amazingly high quality intellectual product with almost no centralized control. And by the way, without even being paid. I think these examples of things like Google and Wikipedia are not the end of the story. I think they’re just barely the beginning of the story. We’re likely to see lots more examples of Internet-enabled collective intelligence—and other kinds of collective intelligence as well—over the coming decades.

If we want to predict what’s going to happen, especially if we want to be able to take advantage of what’s going to happen, we need to understand those possibilities at a much deeper level than we do so far. That’s really our goal in the MIT Center for Collective Intelligence, which I direct. In fact, one way we frame our core research question there is: How can people and computers be connected so that—collectively—they act more intelligently than any person, group or computer has ever done before? If you take that question seriously, the answers you get are often very different from the kinds of organizations and groups we know today.

Collective intelligence analysis is a field which reviews how people think on a collective basis (which brings to mind Isaac Asimov’s famous “Foundation” series in which a futuristic galactic Empire’s eventual collapse and fall is predicted by a so-called “psycho-historian” who creates his magnum opus involving a detailed plan of the galaxy’s future foretelling the fall of The Empire – and then developing a detailed plan for establishment of a replacement Empire by predicting how people will behave in terms of groupings – ala presumably collective intelligence analysis – and all of this 1,000 years after the fall!).

All sounds far-fetched? Perhaps. But as many stock market programs and financial market computer services functions following the 1987 stock market crash, systems have been put in place to prevent ‘panics’ or other group / market scenes in anticipation of how the herd acts (as the old saying goes, ‘it’s fear and greed which largely motivates Wall Street’) – and understanding how the herd thinks (depending, of course, which herd you’re looking at) is now, more than ever before, important.

We’re talking about big money here – and much, much more than just about money.

We live in a crowded world with diminishing resources: the ice caps are melting, population groupings becoming restless (witness the recent study regarding the so-called Arab Spring riots collating directly to rising food prices – http://www.mindfulmoney.co.uk/13103/sector-watch-/the-economic-consequences-of-rising-commodity-prices.html). With all of this, it’s now – more than ever before – a matter of our survival to know and understand how people think, especially in terms of groupings as there are as few things as dangerous as when groups of people come together (anything can happen: an impromptu football game, a sudden Shriner’s parade – or worse!).

It’s also worth noting that understanding how groups of people work is also fundamental to the success of any political / electoral undertaking.

So what; old news. We’ve all come to expect and realize how people behave badly (or otherwise) in large groupings.

Not really.

All of this also underscores a subtle – but very significant development – which Dr. Malone points out: where do we draw the line between collective intelligence and cognitive intelligence inherent within our computer networks? It’s becoming more and more like the ‘push / pull’ scenario: who or what is doing which? Or can we ever really tell?

This distinction is one that’s becoming more and more blurred – and only promises to continue doing so as we become more and more intermeshed with our social media / computer networks. Who we are is increasingly being defined as part of a greater electronic vision of ourselves: at what point does the mirror reflect upon itself and its electronic image – and not just directly on us?

No matter how you look at it, there is tremendous potential within this field of study. Perhaps with a little luck, we can not only understand how and why groups of people behave as they do, perhaps we could eventually figure out how to keep them from doing stupid things.


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