12.1 Wisdom of Crowds and Herd Thinking

Social psychology has revealed that a group of people collectively can reach better conclusions in some situations and worse in others. With real-world examples, we explore how to avoid the pitfalls of group reasoning and to maximize the benefits.

The Lesson in Context

This lesson discusses when groups of people make better or worse judgments than individuals. It leads into the last part of the course, which revolves around group decision making, e.g. as a society.

Earlier Lessons

2.2 Systematic and Statistical Uncertainty

Individual judgments can deviate from the truth due to systematic bias and random fluctuation. Reducing shared bias and increasing sample size are ways to improve the effects of Wisdom of Crowds.

9.2 Biases

Conformity to the group consensus, illustrated by the Asch experiment, and obedience to a perceived authority in a group, illustrated by the Milgram experiment, are psychological tendencies that affect group decision making, tending to increase herd thinking.

10.1 Confirmation Bias

Confirmation bias can exacerbate other biases in group decision making, such as the motivation to make judgments that conform to the group consensus or agree with the opinion of the authority figure - again, increasing problematic herd thinking.

Later Lessons

13.1 Denver Bullet Study

When making group decisions using the Denver Bullet Study method, it is important to survey each expert (on matters of fact) and each stakeholder (on matters of value) individually and independently so as to reduce "herd thinking" effects.

13.2 Deliberative Polling

In a somewhat opposite approach, deliberative polling encourages moderated discussion between all participants punctuated by dialogue with the relevant experts, before participants answer a poll to make informed decisions in society. Conformity with other participants as well as "obedience" to (in the sense of taking advice from) the expert panelists are essential features. The result tends to be a convergence of opinions towards moderation on divisive issues.

Takeaways

After this lesson, students should

Not take for granted that consensus offers the best conclusions.
Take seriously (but not as absolute!) the consensus of a group which has reasoned about a question in a careful, appropriate way.
Take seriously (but not as absolute!) the average of a large group's independent estimates of a number, under appropriate conditions.
Identify shared biases in a given group which may increase the odds of problematic herd thinking rather than helpful wisdom of crowds.

Wisdom of Crowds

Sometimes groups make better judgments than individuals. This happens when:

Judgments are genuinely independent, preventing herd thinking.
Members of the group do not share the same biases.
There are enough people in the group to balance out random biases or fluctuations (analogous to the need for an adequate sample size).
Works especially well when estimating a quantity, where errors may be large but are not systematic.

Herd Thinking

Sometimes groups make worse judgments than individuals. This happens when:

Judgments of individuals are influenced by the judgments of others, leading to groupthink and sometimes polarization.
Members of the group share biases, which can be exaggerated by discussion and cannot be decreased by averaging judgments.

Meta-analysis

A statistical analysis that aggregates the results from many independent studies addressing the same question. Each individual study is expected to have some error independent of the other studies. By combining these results this aggregate statistical error can hopefully be eliminated.

Family Dynamics

Within a group like a family, the parents may have chosen each other partly due to shared opinions and beliefs, and taught these to their children. The experience of strong consensus and absence of dissent within the family can cause the members to become more confident and more extreme in their beliefs (herd thinking), even if these opinions are quite different from a broader consensus in society. Moreover, it can be difficult for members to break out, since disagreeing with the group can be seen as disloyal, unethical, defiant, and ungrateful.

Congressional Committees

In Congress, most committees include both Republicans and Democrats. Ideally, this leads to groups whose members have different biases, helping to prevent herd thinking and leading to more considered policy proposals.

Scientific Community

In science, the ideal is a large community of people with varied biases who pursue investigations independently, and share their findings and ideas periodically. These features help the enterprise of science take advantage of the virtues of wisdom of crowds.

Insofar as the members of the scientific community share the same biases - for example, that they are not demographically representative of humanity at large - this can reduce the efficacy. For this reason, representation in science is important not only for ethical reasons of equity, but also for epistemic reasons.

Everyone agrees, so it must be true.

Sometimes everyone in a group agrees due to shared biases, sometimes combined with a charismatic or dominating figure who has convinced everyone else. Consensus can be a good indicator of accuracy, especially when biases are distributed and independent judgments are included, but it isn't a guarantee, especially when the group is missing key information.

I trust my guess about how many pages are in this book more than the average of my guess with other people's guesses, because even if I don't have more information than other people, it's MY guess and you should stick with your own guess.

If the goal is accuracy, more information is generally better. When other people's guesses don't share biases, as is typical with numeric guesses, averages of many independent guesses tend to be more accurate than any given randomly selected guess. Of course, if one person is an expert in some way, it may be worth weighting their answer more highly or even trusting their expertise.

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