Along with machine learning (ML) and artificial intelligence (AI), collective intelligence (CI) is among the new tech vocabulary sneaking into business-speak. As a concept, ‘collective intelligence’ alludes to that two heads think better than one, that we are smarter together.
This is not a new idea. Since the dawn of man, people have worked together and found solutions collectively. Socrates used dialogue to come closer to the truth - challenging other peoples’ beliefs and his own. Is collective intelligence just a fancy way of saying we should work together and talk more together?
In truth, all the basics of people working and interacting together are important ingredients for collective intelligence. What is new is technology and how it allows us to interact in direct and indirect ways. The Internet and software systems allow groups of people to contribute to common problems that require our collective cognitive effort.
Another significant change is data and how it allows us to analyze and systemize knowledge about crowds' smartness. This has brought new insights about when groups of people are collectively intelligent and when they’re not. For example, group think – that individuals in a group choose to agree for harmony and consensus - is seldom conducive to creating smart crowds.
Market prices and stock exchanges are good examples of collective intelligence in action. When the coronavirus's news hit the press, markets immediately reacted and interpreted what this meant for industries and companies. By investing or disinvesting, agents all around the globe signaled their updated beliefs and market outlook.
All investment decisions – buying and selling of stocks - collectively translate into continuously updated stock prices (Hayek, 1945).
This is collective intelligence in action. It even has a name in finance – the efficient market hypothesis – which posits that it is impossible to consistently beat the market because all current information is reflected in market prices (Fama, 1970). Technology now allows us to use the same market mechanism to predict, for example, who is becoming the next president in the USA (Wolfers and Zitzewitz, 2004).
So, what specifically is this thing called collective intelligence? The answer to that question depends on the research context. Still, it implies that as a collective, we reach better solutions or make more accurate predictions than we normally would be able to as individuals (Page, 2008). This result builds on the idea that relevant information is fragmented and spread out. Just think about the complexities and ongoings in global markets—no single expert knows-it-all.
Another key component is diversity. A diverse group of people who can add different pieces of information, different perspectives are more likely to solve a difficult problem. Complex problems require the ability to approach a problem from different angles. With the right perspective, a complex problem becomes simpler.
And diversity does matter in a world where complexity is quickly rising. It is not desirable to have only investors in New York and London to interpret what is happening in global markets. We want investors in Valencia, Shanghai, Jakarta, and Cape Town to have their say as well.
Local knowledge can be key to understand local events that affect markets globally.
Which brings us over to organizations. Just as New York and London's financial communities are not almighty knowledgeable about global markets, neither are top management about their organizations and their markets. To think that a leader can step onto the podium with a ready-made solution, a silver bullet, to complex organizational challenges is far-fetched, to put it mildly.
In organizations, there is a wealth of knowledge held explicitly and tacitly by its employees.
Frontline employees are often the first to catch on to the latest developments affecting an organization. Internet-based technologies now allow organizations to engage a wide range of their employees to solve difficult problems.
If asked and engaged, employees will step up and provide highly relevant input. Specifically, the pool of employees can be engaged to make predictions about things that really matter for an organization or engaged in solving specific problems. New technology designed to tap into the collective intelligence now makes this feasible.
At Mindpool, we are on a mission to support proactive organizations to tap into the collective intelligence and tacit knowledge of their very own people. We believe the combination of human minds and technology will pave the way for entirely new business and bring out the best organizations and their people. Collective intelligence is truly a competitive resource in augmenting decisions with data-driven insights and at the same time engaging employees and democratizing knowledge.
Fama (1970), "Efficient Capital Markets: A Review of Theory and Empirical Work." Journal of Finance. 25 (2): 383-417.
Hayek FA. (1945), "The use of knowledge in society." American Economic Review, 35(4): 519–530.
Page (2008), "The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies-New Edition."
Wolfers and Zitzewitz (2004), "Prediction markets" Journal of Economic Perspectives, 18(2): 107–126.
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