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9 Networked Minds
Today, we have a much more nuanced understanding of crowds and swarm intelligence.
3 We can explain why crowds are sometimes benign, but cause trouble in other
circumstances.
4 For the wisdom of crowds to work, first, independent information
gathering is crucial. Second, opinion formation should be decentralized, drawing
on local knowledge and specialization. Third, a larger diversity of opinions tends to
increase the quality of the outcome. The same applies to the diversity of in communication patterns.
5 Too much communication, however, can make the group as a whole
less intelligent.
In fact, if people collect information and evaluate it independently from each other,
and if these diverse streams of information are suitably aggregated afterwards, this
often creates better results than even the best experts can produce. This is also more
or less the way in which prediction markets work. These markets have been surprisingly successful in anticipating election outcomes or the success of new movies,
for example.
6 Interestingly, prediction markets were inspired by the principles that
ants and bees use to find the most promising sources of food.
7 Such complex selforganizing animal societies have always amazed people, especially because they are
based on surprisingly simple rules of interaction.
In contrast, the “wisdom of the crowd” is undermined, if people are influenced
by others while searching for information or making up their minds. This can sometimes create very bad outcomes, as misjudgments can easily spread if individuals
copy each others’ opinions. For example, in Asch’s conformity experiments, people
had to publicly state which one of three lines was equal in length to another line
presented to them.
8 Before the participant answered the question, other people gave
incorrect answers (as they were instructed). As a consequence, the participant typically answered incorrectly, too, even though the recognition task was simple. Recent
experiments that Jan Lorenz, Heiko Rauhut, Frank Schweitzer and I performed, show
that people are even influenced by the opinions of others when they are not exposed to
social pressure.
9 This demonstrates that the wisdom of crowds is sensitive to manipulation attempts and social influence, and that’s why one shouldn’t try to influence
how people search for information and make decisions, as nudging does.
But why are our opinions influenced by others at all? This is mainly, because
imitation, which builds on the experience of others, is often a successful and efficient
strategy. In the following, I will discuss, how we decide, why we behave in a social
way, and how information systems may change our behavior. If we want to understand
how the digital revolution might change our society, we must identify the various
factors that influence our decision-making. In particular, we need to find out how
growing amounts of information and the increased interconnectedness of people
3 Page [3].
4 See https://en.wikipedia.org/wiki/The_Wisdom_of_Crowds.
5 Woolley et al. [4].
6 Thompson [5]; for further recent prediction approaches see Siegel [6], Silver [7].
7 Bonabeau and Theraulaz [8].
8 Asch [9].
9 Lorenz et al. [10].
9 Networked Minds
Today, we have a much more nuanced understanding of crowds and swarm intelligence.
3 We can explain why crowds are sometimes benign, but cause trouble in other
circumstances.
4 For the wisdom of crowds to work, first, independent information
gathering is crucial. Second, opinion formation should be decentralized, drawing
on local knowledge and specialization. Third, a larger diversity of opinions tends to
increase the quality of the outcome. The same applies to the diversity of in communication patterns.
5 Too much communication, however, can make the group as a whole
less intelligent.
In fact, if people collect information and evaluate it independently from each other,
and if these diverse streams of information are suitably aggregated afterwards, this
often creates better results than even the best experts can produce. This is also more
or less the way in which prediction markets work. These markets have been surprisingly successful in anticipating election outcomes or the success of new movies,
for example.
6 Interestingly, prediction markets were inspired by the principles that
ants and bees use to find the most promising sources of food.
7 Such complex selforganizing animal societies have always amazed people, especially because they are
based on surprisingly simple rules of interaction.
In contrast, the “wisdom of the crowd” is undermined, if people are influenced
by others while searching for information or making up their minds. This can sometimes create very bad outcomes, as misjudgments can easily spread if individuals
copy each others’ opinions. For example, in Asch’s conformity experiments, people
had to publicly state which one of three lines was equal in length to another line
presented to them.
8 Before the participant answered the question, other people gave
incorrect answers (as they were instructed). As a consequence, the participant typically answered incorrectly, too, even though the recognition task was simple. Recent
experiments that Jan Lorenz, Heiko Rauhut, Frank Schweitzer and I performed, show
that people are even influenced by the opinions of others when they are not exposed to
social pressure.
9 This demonstrates that the wisdom of crowds is sensitive to manipulation attempts and social influence, and that’s why one shouldn’t try to influence
how people search for information and make decisions, as nudging does.
But why are our opinions influenced by others at all? This is mainly, because
imitation, which builds on the experience of others, is often a successful and efficient
strategy. In the following, I will discuss, how we decide, why we behave in a social
way, and how information systems may change our behavior. If we want to understand
how the digital revolution might change our society, we must identify the various
factors that influence our decision-making. In particular, we need to find out how
growing amounts of information and the increased interconnectedness of people
3 Page [3].
4 See https://en.wikipedia.org/wiki/The_Wisdom_of_Crowds.
5 Woolley et al. [4].
6 Thompson [5]; for further recent prediction approaches see Siegel [6], Silver [7].
7 Bonabeau and Theraulaz [8].
8 Asch [9].
9 Lorenz et al. [10].