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12.1 Wisdom of Crowds and Herd Thinking: Difference between revisions

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{{Cover|12.1 Wisdom of Crowds and Herd Thinking}}


== Useful Links ==
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.


* Jury Bias and Composition Papers
== The Lesson in Context ==
** [[:File:Kaplan and Miller - Reducing the Effects of Juror Bias.pdf|Reducing the Effects of Juror Bias (Kaplan and Miller, 1978)]]
** [[:File:Kerr et al. - 1985 - Effects of victim attractiveness, care and disfigu.pdf|Effects of Victim Attractiveness, Care and Disfigurement on the Judgements of American and British Mock Jurors (Kerr, Bull, MacCoun and Rathborn, 1985)]]
** [[:File:MacCoun - 1990 - The Emergence of Extralegal Bias During Jury Delib.pdf|The Emergence of Extralegal Bias During Jury Deliberation (MacCoun, 1990)]]
** [[:File:Kerr et al. - 1999 - Bias in Jurors vs Bias in Juries New Evidence fro.pdf|Bias in Jurors vs Bias in Juries: New Evidence from the SDS Perspective (Kerr, Niedermeier and Kaplan, 1999)]]
* [https://docs.google.com/spreadsheets/d/14NN0E_giywARzNf3o_cr-vG6sLbEMym9RzduUzQ0tZg/edit?usp=sharing Spreadsheet of Estimate Responses]
* [https://docs.google.com/forms/d/1KLslmn5o1zmYJtp_VSQoMED9JARief-Wrv0QGau7iW0/edit?usp=sharing Estimates Survey Template]
* [https://docs.google.com/document/d/1Vu588U1L04MpXg876tEzTofN7NSKGnTYHhrsbkdkGTk/edit?usp=sharing Three Column Overview of the Week]
* [https://docs.google.com/presentation/d/1bjUn2Pe7h3h2x9tBlFuH6hDY3KA4s5wyYcNr4XD7q-4/edit?usp=drivesdk Lesson Slides (2023 Master)]
* [https://sensesensibilityscience.berkeley.edu/topic/21 Website Page]


=== Readings and Assignments ===
<!-- Always begin section with a description of this lesson in relation to the course as a whole. -->
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.


* [https://app.playpos.it/player_v2?type=share&bulb_id=1186496&lms_launch=false PlayPosit Video]
<!-- Expandable section relating this lesson to other lessons. -->
* [[:File:The Social Psychology of the Wisdom of Crowds - Larrick.pdf|The Social Psychology of the Wisdom of Crowds]]
{{Expand|Relation to Other Lessons|
'''Earlier Lessons'''
{{ContextLesson|2.2 Systematic and Statistical Uncertainty}}
{{ContextRelation|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.}}
{{ContextLesson|9.2 Biases}}
{{ContextRelation|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.}}
{{ContextLesson|10.1 Confirmation Bias}}
{{ContextRelation|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.}}
{{Line}}
'''Later Lessons'''
{{ContextLesson|13.1 Denver Bullet Study}}
{{ContextRelation|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.}}
{{ContextLesson|13.2 Deliberative Polling}}
{{ContextRelation|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 ==


== Learning Goals ==
<tabber>
 
|-|Learning Goals=


After this lesson, students should
After this lesson, students should
<!-- Learning goals are written as a numbered list. -->
# Not take for granted that consensus offers the best conclusions.
# 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 consensus of a group which has reasoned about a question in a careful, appropriate way.
Line 27: Line 37:
# Identify shared biases in a given group which may increase the odds of problematic herd thinking rather than helpful wisdom of crowds.
# Identify shared biases in a given group which may increase the odds of problematic herd thinking rather than helpful wisdom of crowds.


=== Definitions ===
|-|Definitions=


* '''Wisdom of Crowds'''
<!-- Definitions must be written with the Definition and Subdefinition templates. The first Definition should have the "first=yes" flag at the end. -->
*: Sometimes groups make better judgments than individuals. This happens when:
{{Definition|Wisdom of Crowds|Sometimes groups make better judgments than individuals. This happens when:
*:* Judgments are genuinely independent, preventing herd thinking.  
:* Judgments are genuinely independent, preventing herd thinking.
*:* Members of the group do not share the same biases.  
:* 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).  
:* 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.  
:* Works especially well when estimating a quantity, where errors may be large but are not systematic.|first=yes}}
* '''Herd Thinking'''
{{Definition|Herd Thinking|Sometimes groups make worse judgments than individuals. This happens when:
*: 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.
*:* 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.}}
*:* Members of the group share biases, which can be exaggerated by discussion and cannot be decreased by averaging judgments.
{{Definition|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.}}
* '''Meta-analysis'''
<br />
*: 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.


=== Examples ===
|-|Examples=


* 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.
{{Example
* 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.
|Family Dynamics
* 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.
|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.}}
** 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.
{{Example
|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.}}
{{Example
|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.<br /><br />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.}}
{{Exemplary
|{{Blockquote|We can get a pretty good estimate of the weight of this turkey by asking everyone in the family to write their guess privately on a piece of paper, and then averaging the answers.}}
}}


=== Common Misconceptions ===
|-|Common Misconceptions=


* "Everyone agrees, so it must be true."
<!-- Misconceptions must be written with the Misconception template. The first Misconception should have the "first=yes" flag at the end. -->
*: 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.
{{Misconception|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.|first=yes}}
* "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."
{{Misconception|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.}}
*: 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.


== Context ==
|-|Expanded Learning Goals=


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.
After this lesson, students should
 
# Attitudes
=== Before ===
## 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.
: '''[[2.2 Systematic and Statistical Uncertainty]]'''
## Take seriously (but not as absolute!) the average of a large group's independent estimates of a number, under appropriate conditions.
:: 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.
# Concept Acquisition
: '''[[9.2 Biases]]'''
## '''Wisdom of Crowds:''' Sometimes groups make better judgments than individuals. This happens when:
:: 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.
### Judgments are genuinely independent, preventing herd thinking.
: '''[[10.1 Confirmation Bias]]'''
### Members of the group do not share the same biases.
:: 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.
### 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.
=== After ===
## '''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.
: '''[[13.1 Denver Bullet Study]]'''
### Members of the group share biases, which can be exaggerated by discussion and cannot be decreased by averaging judgments.
:: 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.
# Concept Application
: '''[[13.2 Deliberative Polling]]'''
## Recognize when groups are likely to make good decisions.
:: 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.
## Recognize when groups are likely to make poor decisions.
 
## Structure group decision-making processes so as to maximize the benefits and minimize the dangers.
== Recommended Outline ==
## Identify features of existing group decision-making practices which we could improve.
 
=== Before Class ===
 
* Review PlayPosit and lesson plans. If you have any questions, please ask!
* Update the Google Form in the [[#Warm-up Questionnaire|warm-up questionnaire]].
 
=== During Class ===
 
* (5 min) Come up with some fun way to assign the roles of spokesperson and notetaker (e.g. earliest birthday in the year, lives furthest from campus). Remind them of the responsibilities of these roles.
* (25 min) Questionnaire and presentation/slides.
* (30 min) Jury discussion and activity.
* (15 min) Optional: The Fermi problem if sufficient time remains.
 
=== After Class ===
 
* Go through the results from the [[#Warm-up Questionnaire|warm-up questionnaire]] and make visualizations to show in plenary.
 
== Lesson Content ==
 
=== Warm-up Questionnaire ===
 
For this discussion section, students will start by filling out a [https://docs.google.com/forms/d/1KLslmn5o1zmYJtp_VSQoMED9JARief-Wrv0QGau7iW0/edit?usp=sharing Google form] which asks for their best estimate of four quantities (should take 3-5 mins). While the UGSI pulls up the responses to this poll, the GSI will continue on to a poll which demonstrates the concept of '''herd thinking'''. After the poll, the UGSI will take over screen sharing to show the summary of Google poll responses, while the GSI gives the correct answer for each question. The aggregate of the Google poll responses should demonstrate the '''wisdom of crowds'''.
 
==== Instructions ====
 
# Google poll & Zoom/in-person poll with concept review.
## (4 min) '''Google poll''': Prepare Google Forms (either one per section or one for the whole class) with questions from [https://forms.gle/jAycmZD74s3xH2V96 here]. Provide the link to students (e.g. QR code) and tell them to just give their best guesses for each question ''without'' discussing with any classmates. Don't reveal the answers until after the next question.{{Answer|
##* What is the heaviest recorded weight for a cat as of 2013 (in pounds)? → 922 lbs
##* What was the average weight for American men in 1960 (in pounds)? → 166 lbs
##* What is the heaviest recorded weight for a rabbit as of 2013 (in pounds)? → 55 lbs
##* What was the average weight for American women in 2010 (in pounds)? → 163 lbs
##* These questions are an example of the wisdom of crowds, where a large collection of everyone's best-guess answers get us closer to the real answer than one may be able to figure out on their own. This applies to situations where the group does not all share the same prior bias.}}
## (5 min) '''Zoom/in-person poll''': students select which painter they think made the painting shown in [https://docs.google.com/presentation/d/1ewzuWCBtkGGZ40shJzPVhLX2PC-ck1jf/edit?usp=sharing&ouid=115828648209024194066&rtpof=true&sd=true slides] (A, B, or C).
### First have the students raise their hands for the answers. It's likely that students that don't know the answer just won't guess at all. But, they should be able to see how many people are voting for which options.
### Second, ''force'' the students to answer. Tell the students that ''every'' student needs to raise their hand for ''some'' choice even if they don't know the answer. Have them all go through it again. {{Answer|Armand Guillamin. It's likely the case that most people will pick Cezanne, because Cezanne is more widely known than the two other options. This is an example of the negative outcomes of herd thinking, where a group of people independently & collectively select the wrong answer because they all share the same prior bias (picking the famous painter).}}
# Collect the Google Form responses as a Google Sheet. Produce an average value and standard deviation for each of the questions. Write the correct answers next to the average values and reveal these results to the students.
# (8 min) Explain '''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.
# (8 min) Explain '''herd thinking'''—Sometimes groups make worse judgments than individuals. This happens when:
## Judgments of individuals are influenced by the judgments of others, leading to group-think and sometimes polarization.  
## Members of the group share biases, which can be exaggerated by discussion and cannot be decreased by averaging judgments.
 
=== Jury Composition and Deliberation ===
 
We use the composition and decision making process of juries as an example of a case where wisdom of crowds can be applied and misapplied.
 
==== Discussion Questions ====
 
See [https://docs.google.com/presentation/d/1ewzuWCBtkGGZ40shJzPVhLX2PC-ck1jf/edit?usp=sharing&ouid=115828648209024194066&rtpof=true&sd=true slides] for graphs and more detailed discussion.
# (5 min) How do the nuances of jury composition affect a jury's likelihood of coming to a verdict?{{Answer|Individual differences in jurors introduce variance (statistical uncertainty) in their judgment, while shared bias (e.g. due to racial prejudice) can lead jurors astray (systematic uncertainty).}}
# (5 min) Would a 6 person jury where 1 person believes not guilty come to the same conclusion as a 12 person jury where 2 people believe not guilty?{{Answer|Recall the Asch conformity experiment. It is easier for the 1 dissenter to be converted to the group opinion than for 2 dissenters to.}}
# (5 min) How might deliberation lead to fairer results or polarize group decision making? Refer to the conditions for wisdom of crowds or herd thinking. {{Answer|'''Optimistic Answer:''' Deliberation averages out individual biases in the group, leading to a fairer result, especially when the evidence is emphasised.}} {{Answer|'''Pessimistic Answer:''' Deliberation magnifies pre-existing group biases and creates polarization, especially when the evidence is weak.}} {{Answer|'''Compromise Answer:''' Groups magnify biases when the evidence is weak.}}
 
==== Redesigning the System ====
 
# (4 min) Have a brief whole class discussion where you ask the students to consider what the flaws with the current jury system are and how it diverges from wisdom of crowds.
# (6 min) In small groups, ask the think through the following question.
## Considering mainly wisdom of crowds, how would you design a better jury system? Consider the whole process from selection of people (if you even have this?) to the final decision that's made.
# (5 min) Bring the whole class back together to share their solutions.
 
=== Fermi Problem ===
 
(Optional) As a final point, give the students an especially challenging Fermi problem to solve collectively. This is to emphasize that some problems ''do'' benefit from having deliberation at certain stages.
 
==== Instructions ====
 
# (11 min) Have the students work out step 1 as groups.
# (4 min) Have the students make their individual estimates and then average them together.
 
==== Step 1: The Tree ====
 
IKEA mainly produces two types of industrial bags. There are the blue bags that people can purchase and the yellow bags that are only used in the store. Besides the colors, these two types of bags are identical. As a group, figure out the quantities you need to estimate in order to determine the following:
 
# How many blue (purchasable) bags does IKEA produce per year?
# How many yellow (only for use in store) bags does IKEA produce per year?
# Are there more blue or yellow IKEA bags?
 
==== Step 2: Estimates ====
 
Now, using wisdom of crowds, have every person in the group estimate each quantity independently without discussion. Then, average the final values together to get a result that's (hopefully) better than if the estimates were just determined individually.
 
==== Discussion Question ====
 
# In terms of wisdom of crowds and herd thinking, why should the first step be collaborative, while the second step is individual?{{Answer|The first step involves detailed logical reasoning, and each person can contribute a small step in that process with little chance of bias. The second step involves the estimation of numbers, where an average of independent guesses is more accurate than a deliberated group consensus.}}
 
=== Changemaker ===
 
{{Changemaker|"Members of a homogeneous group rest somewhat assured that they will agree with one another; that they will understand one another's perspectives and beliefs; that they will be able to easily come to a consensus. But when members of a group notice that they are socially different from one another, they change their expectations. They anticipate differences of opinion and perspective. They assume they will need to work harder to come to a consensus. This logic helps to explain both the upside and the downside of social diversity: people work harder in diverse environments both cognitively and socially. They might not like it, but the hard work can lead to better outcomes."}}


{{Changemaker|How does homogeneity in groups contribute to herd thinking? What benefit does diversity therefore provide?}}
</tabber>


{{#restricted:{{Private:12.1 Wisdom of Crowds and Herd Thinking}}}}
{{NavCard|chapter=Lesson plans|text=All lesson plans|prev=11.2 When Is Science Suspect|next=12.2 Grill the Guest}}
[[Category:Lesson plans]]
[[Category:Lesson plans]]

Latest revision as of 23:51, 11 June 2026

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

  1. Not take for granted that consensus offers the best conclusions.
  2. Take seriously (but not as absolute!) the consensus of a group which has reasoned about a question in a careful, appropriate way.
  3. Take seriously (but not as absolute!) the average of a large group's independent estimates of a number, under appropriate conditions.
  4. 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.

Exemplary Quotes

We can get a pretty good estimate of the weight of this turkey by asking everyone in the family to write their guess privately on a piece of paper, and then averaging the answers.

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.

After this lesson, students should

  1. Attitudes
    1. Not take for granted that consensus offers the best conclusions.
    2. Take seriously (but not as absolute!) the consensus of a group which has reasoned about a question in a careful, appropriate way.
    3. Take seriously (but not as absolute!) the average of a large group's independent estimates of a number, under appropriate conditions.
  2. Concept Acquisition
    1. Wisdom of Crowds: Sometimes groups make better judgments than individuals. This happens when:
      1. Judgments are genuinely independent, preventing herd thinking.
      2. Members of the group do not share the same biases.
      3. There are enough people in the group to balance out random biases or fluctuations (analogous to the need for an adequate sample size).
      4. Works especially well when estimating a quantity, where errors may be large but are not systematic.
    2. Herd Thinking: Sometimes groups make worse judgments than individuals. This happens when:
      1. Judgments of individuals are influenced by the judgments of others, leading to groupthink and sometimes polarization.
      2. Members of the group share biases, which can be exaggerated by discussion and cannot be decreased by averaging judgments.
  3. Concept Application
    1. Recognize when groups are likely to make good decisions.
    2. Recognize when groups are likely to make poor decisions.
    3. Structure group decision-making processes so as to maximize the benefits and minimize the dangers.
    4. Identify features of existing group decision-making practices which we could improve.

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