7.2 Emergent Phenomena: Difference between revisions

Latest revision as of 23:05, 11 June 2026

From ants to galaxies, studies of complex physical systems have revealed that surprising phenomena can often arise on the whole when a large number of components interact according to very simple rules. In the context of causation, we encourage students to consider emergence, rather than purposeful orchestration, as a possible causal explanation of certain societal phenomena, such as sudden market crashes and the virality of misinformation on social media.

The Lesson in Context

After discussing more concrete forms of causation, we now introduce a type of causation whose outcome is not measured on an individual level, nor on a statistical level (e.g. averaging over individuals). In emergent phenomena, the outcome cannot be found by measuring any number of individuals, but is purely a property of the entire system. We tie this concept of causation to society by recognizing that many sociological phenomena may be of this type.

Earlier Lessons

1.2 Shared Reality and Modeling

The idea of emergent phenomena calls back to the "raft vs. pyramid" descriptions of science. From a reductionist viewpoint, all our understanding breaks down when we end up being wrong on a smaller scale. However, scientists may work on problems at different scales of explanation and still have meaningful results. Harkening back to the raft viewpoint, the areas where these explanations overlap should be consistent. If the explanation at any scale turns out to be wrong, it does not automatically invalidate the other scales.

7.1 Causation, Blame, and Policy

Singular causation is individual intervention leading to an individual result. General causation is the same intervention on many individuals leading to results on these individuals that can be seen only statistically. Neither cover the case where the result is purely a property of the whole system, rather than any number of individuals.
When something goes wrong in society, we may blame a particular leader or policy. This is can be helpful in determining how to intervene for future prevention. However, one shouldn't overlook the possibility that the cause is emergent, and therefore the blame may be misplaced.

Later Lessons

8.1 Orders of Understanding

When deciding what simple objects and rules to include in a model of an emergent phenomenon, it is helpful to separate the first-order causes from the higher-order ones. For example, in modelling the persistent traffic jams on highways as an emergent phenomenon, we do not include honking.

Takeaways

After this lesson, students should

Understand that simple things governed by simple rules can, in aggregate, result in surprisingly complex behaviors, which can be studied in and of themselves.
Be aware of when complex behaviors in some physical and sociological systems may be the consequence of relatively simple rules on the constituents, and therefore not fully explicable by either reductionism or deliberate agents.
Be aware of humans' tendency to over-perceive agency in external phenomena in general (e.g. anthropomorphizing), making us prone to mistaking emergent phenomena as intentional.
Understand that there is value at larger and intermediate scales of explanation despite the fact that larger scales may be reducible to smaller ones.

Scale of Explanation

The scale of the objects we're describing in a system and of the phenomena that emerges from their interaction. This is also called a "level" of explanation. For example, human interactions can be explained at various scales: On the scale of genetics and neurochemistry, on the scale of cognition and behavior, or on the scale of society and culture.

Emergent Phenomenon

A (sometimes surprising) phenomenon that's observed on a large scale due to the interaction of a large number of small constituents (often referred to as "agents") interacting with simple rules. (Note that these objects and rules may also be emergent due to interactions on an even smaller scale.)

Phase Transition

A point where a slight change in the small constituents or simple rules in a system cause a dramatic change in the behavior of the system as a whole.

Scientific Reductionism

A viewpoint that says the purpose of science is to look for the smallest possible (most "fundamental") components of a system that everything else is made of. This viewpoint overlooks that knowledge can be gained from considering objects at larger scales without referencing their smaller constituents. For example, we want to be able to program computers without having to reference the states of their constituent transistors, and treating depression at the level of relationships, environment, and cognitive habits can be more effective than considering the level of neurochemistry, although both are relevant.

Social media

When people are highly connected to each other in social networks with simple rules of interaction (likes, friending, retweeting, etc.), unintended emergent phenomena, such as widespread misinformation, are likely to arise.

Water

Water is wet, but water molecules are not. The property of "wetness" must emerge from the relatively simple rules that govern the interactions between water molecules.

Conway's Game of Life

A classic demonstration of cellular automata, in which simple local rules result in complex patterns arising on a larger scale.

Schelling Model of Segregation

A model wherein large scale racial segregation can emerge even when individual people have no explicit desire to segregate. When the agents are fine being in the minority as long as at least some fraction of people that live around them are of the same group, even this mild preference can lead to segregation.

Consciousness

Consciousness as a result of local interactions between neurons.

YouTube is promoting late night talk show hosts over smaller individual creators. It must mean that the YouTube executives are deliberately stifling small content creators.

While such a conspiracy is still possible, it is also likely that the rules that govern the recommendation algorithm result in this emergent phenomenon, when it was not the executives' explicit intention.

An arrogant physicist would say that all your thoughts and emotions are nothing more than complex interactions between subatomic particles.

Sure, this may be true in principle. But, describing thoughts and emotions purely in terms of subatomic particles skips so many scales of explanation so as to be fairly useless for understanding how to get about in the world as a person.

"Let's say chess is the rules of the universe. After two thousand years, we finally figured out how the pawns move. And then I suppose one day we'll have the God equation and that'll tell us how the whole chess board moves and then we'll become grand masters." -Michio Kaku

Just as knowing the rules of chess doesn't make one a grand master, simply knowing the fundamental laws of physics doesn't give one a full understanding of all things. One needs explanations at every scale, especially if one wants to be able to intervene at the scale we perceive (which is not the scale of atoms).

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-{{Navbox}}
+{{Cover|7.2 Emergent Phenomena}}
-== Useful Links ==
+From ants to galaxies, studies of complex physical systems have revealed that surprising phenomena can often arise on the whole when a large number of components interact according to very simple rules. In the context of causation, we encourage students to consider emergence, rather than purposeful orchestration, as a possible causal explanation of certain societal phenomena, such as sudden market crashes and the virality of misinformation on social media.
-* [http://nifty.stanford.edu/2014/mccown-schelling-model-segregation/ Simulator for the Shelling Model]
+== The Lesson in Context ==
-* [https://docs.google.com/document/d/1e3FfImFu0m2o1xFbPGgeD3RXkySiyBxAZjjuKn4Px9A/edit?usp=sharing Three Column Overview of the Week]
-* [https://docs.google.com/presentation/d/1_xF4kYKuGTW28ppQiQWzD1SbpkCC9G1YcaynCaqJxfA/edit?usp=drivesdk Lesson Slides (2023 Master)]
-* [https://sensesensibilityscience.berkeley.edu/topic/22 Website Page]
-=== Readings and Assignments ===
+<!-- Always begin section with a description of this lesson in relation to the course as a whole. -->
+After discussing more concrete forms of causation, we now introduce a type of causation whose outcome is not measured on an individual level, nor on a statistical level (e.g. averaging over individuals). In emergent phenomena, the outcome cannot be found by measuring any number of individuals, but is purely a property of the entire system. We tie this concept of causation to society by recognizing that many sociological phenomena may be of this type.
+<!-- Expandable section relating this lesson to other lessons. -->
+{{Expand|Relation to Other Lessons|
+'''Earlier Lessons'''
+{{ContextLesson|1.2 Shared Reality and Modeling}}
+{{ContextRelation|The idea of emergent phenomena calls back to the "raft vs. pyramid" descriptions of science. From a reductionist viewpoint, all our understanding breaks down when we end up being wrong on a smaller scale. However, scientists may work on problems at different scales of explanation and still have meaningful results. Harkening back to the raft viewpoint, the areas where these explanations overlap should be consistent. If the explanation at any scale turns out to be wrong, it does not automatically invalidate the other scales.}}
+<!-- {{ContextLesson|1.3 Plenary}}
+{{ContextRelation|The popularization of conspiracy theories can themselves be an emergent phenomenon, resulting from the simple rules by which humans hold and share beliefs.}}
+{{ContextRelation|Conspiratorial beliefs are likely to arise because people are prone to mistaking emergent phenomena as intentional.}} -->
+{{ContextLesson|7.1 Causation, Blame, and Policy}}
+{{ContextRelation|Singular causation is individual intervention leading to an individual result. General causation is the same intervention on many individuals leading to results on these individuals that can be seen only statistically. Neither cover the case where the result is purely a property of the whole system, rather than any number of individuals.}}
+{{ContextRelation|When something goes wrong in society, we may blame a particular leader or policy. This is can be helpful in determining how to intervene for future prevention. However, one shouldn't overlook the possibility that the cause is emergent, and therefore the blame may be misplaced.}}
+{{Line}}
+'''Later Lessons'''
+{{ContextLesson|8.1 Orders of Understanding}}
+{{ContextRelation|When deciding what simple objects and rules to include in a model of an emergent phenomenon, it is helpful to separate the first-order causes from the higher-order ones. For example, in modelling the persistent traffic jams on highways as an emergent phenomenon, we do not include honking.}}
+}}
+== Takeaways ==
-* [https://app.playpos.it/player_v2?type=share&bulb_id=1246900&lms_launch=false PlayPosit Video]
+<tabber>
-* [[:File:The Architecture of Complexity - Simon.pdf|The Architecture of Complexity]]
-* [https://youtu.be/16W7c0mb-rE Emergence: How Stupid Things Become Smart Together]
-== Learning Goals ==
+|-|Learning Goals=
 After this lesson, students should
+<!-- Learning goals are written as a numbered list. -->
 # Understand that simple things governed by simple rules can, in aggregate, result in surprisingly complex behaviors, which can be studied in and of themselves.
 # Be aware of when complex behaviors in some physical and sociological systems may be the consequence of relatively simple rules on the constituents, and therefore not fully explicable by either reductionism or deliberate agents.
-# Be aware of humans' tendency to overperceive agency in external phenomena in general (e.g. anthropomorphizing), making us prone to mistaking emergent phenomena as intentional.
+# Be aware of humans' tendency to over-perceive agency in external phenomena in general (e.g. anthropomorphizing), making us prone to mistaking emergent phenomena as intentional.
 # Understand that there is value at larger and intermediate scales of explanation despite the fact that larger scales may be reducible to smaller ones.
-=== Definitions ===
+|-|Definitions=
-* '''Scale of Explanation'''
-*: The scale of the objects we're describing in a system and of the phenomena that emerges from their interaction. This is also called a "level" of explanation. For example, human interactions can be explained at various scales: On the scale of genetics and neurochemistry, on the scale of cognition and behavior, or on the scale of society and culture.
-* '''Emergent Phenomenon'''
-*: A (sometimes surprising) phenomenon that's observed on a large scale due to the interaction of a large number of small constituents interacting with simple rules. (Note that these objects and rules may also be emergent due to interactions on an even smaller scale.)
-* '''Scientific Reductionism'''
-*: A viewpoint that says the purpose of science is to look for the smallest possible (most "fundamental") components of a system that everything else is made of. This viewpoint overlooks that knowledge can be gained from considering objects at larger scales without referencing their smaller constituents. For example, we want to be able to program computers without having to reference the states of their constituent transistors, and treating depression at the level of relationships, environment, and cognitive habits can be more effective than considering the level of neurochemistry, although both are relevant.
-=== Examples ===
-* '''Social media'''
-*: When people are highly connected to each other in social networks with simple rules of interaction (likes, friending, retweeting, etc.), unintended emergent phenomena, such as widespread misinformation, are likely to arise.
-* '''Water'''
-*: Water is wet, but water molecules are not. The property of "wetness" must emerge from the relatively simple rules that govern the interactions between water molecules.
-* '''Conway's Game of Life'''
-*: A classic demonstration of cellular automata, in which simple local rules result in complex patterns arising on a larger scale.
-* '''Shelling Model of Segregation'''
-*: A model wherein large scale racial segregation can emerge even when individual people have no explicit desire to segregate. When the agents are fine being in the minority as long as at least some fraction of people that live around them are of the same group, even this mild preference can lead to segregation.
-* Consciousness as a result of local interactions between neurons.
-=== Common Misconceptions ===
-* ''YouTube is promoting late night talk show hosts over smaller individual creators. It must mean that the YouTube executives are deliberately stifling small content creators.''
-*: While such a conspiracy is still possible, it is also likely that the rules that govern the recommendation algorithm result in this emergent phenomenon, when it was not the executives' explicit intention.
-* ''An [https://imgs.xkcd.com/comics/purity.png arrogant physicist] would say that all your thoughts and emotions are nothing more than complex interactions between subatomic particles.''
-*: Sure, this may be true in principle. But, describing thoughts and emotions purely in terms of subatomic particles skips so many scales of explanation so as to be fairly useless for understanding how to get about in the world as a person.
-* ''"Let's say chess is the rules of the universe. After two thousand years, we finally figured out how the pawns move. And then I suppose one day we'll have the God equation and that'll tell us how the whole chess board moves and then we'll become grand masters." -Michio Kaku''
-*: Just as knowing the rules of chess doesn't make one a grand master, simply knowing the fundamental laws of physics doesn't give one a full understanding of all things. One needs explanations at every scale, especially if one wants to be able to intervene at the scale we perceive (which is not the scale of atoms).
-== Context ==
-After discussing more concrete forms of causation, we now introduce a type of causation whose outcome is not measured on an individual level, nor on a statistical level (e.g. averaging over individuals). In emergent phenomena, the outcome cannot be found by measuring any number of individuals, but is purely a property of the entire system. We tie this concept of causation to society by recognizing that many sociological phenomena may be of this type.
-=== Before ===
-: '''[[1.2 Shared Reality and Modeling]]'''
-:* The idea of emergent phenomena calls back to the "raft vs. pyramid" descriptions of science. From a reductionist viewpoint, all our understanding breaks down when we end up being wrong on a smaller scale. However, scientists may work on problems at different scales of explanation and still have meaningful results. Harkening back to the raft viewpoint, the areas where these explanations overlap should be consistent. If the explanation at any scale turns out to be wrong, it does not automatically invalidate the other scales.
-: '''[[1.3 Plenary]]'''
-:* The popularization of conspiracy theories can themselves be an emergent phenomenon, resulting from the simple rules by which humans hold and share beliefs.
-:* Conspiratorial beliefs are likely to arise because people are prone to mistaking emergent phenomena as intentional.
-: '''[[7.1 Causation, Blame, and Policy]]'''
-:* Singular causation is individual intervention leading to an individual result. General causation is the same intervention on many individuals leading to results on these individuals that can be seen only statistically. Neither cover the case where the result is purely a property of the whole system, rather than any number of individuals.
-:* When something goes wrong in society, we may blame a particular leader or policy. This is can be helpful in determining how to intervene for future prevention. However, one shouldn't overlook the possibility that the cause is emergent, and therefore the blame may be misplaced.
-=== After ===
-: '''[[8.1 Orders of Understanding]]'''
-:: When deciding what simple objects and rules to include in a model of an emergent phenomenon, it is helpful to separate the first-order causes from the higher-order ones. For example, in modelling the persistent traffic jams on highways as an emergent phenomenon, we do not include honking.
-== Recommended Outline ==
-=== Before Class ===
-* [Any essential logistical things that need to be done for this class]
-* Prepare a seating chart.
-* Review PlayPosit and discussion questions and ask faculty, Gabriel, or Emlen any questions you have.
-* (Optional) Prepare a presentation.
-=== During Class ===
-* (15 min) Have the students walk through the [[#Conway Discussion|introductory discussion on Conway's game of life]].
-* (25 min) Guide the students through the [[#Shelling Neighborhood Segregation Model|Shelling neighborhood segregation example]].
-* (40 min) Guide the students through the [[#Conspiracy Theories|conspiracy theories discussion and modelling activity]].
-=== After Class ===
-* [Any essential logistical things that need to be done as followup for this class]
-* Collect answers from notetakers for the forum / plenary.
-== Lesson Content ==
-=== Conway Discussion ===
-The purpose of this discussion is to demonstrate that the reductionist view of science is incomplete. There's value at looking at phenomena at "higher" levels of understanding without reference to their constituents.
-==== Instructions ====
-# Show [https://youtu.be/YsqUzRMD0LM this] video, stopping every so often to ask the following questions. {{Caution|The slides will have this video ready to go with pre-designated pause intervals.}}
-## What are the pieces?
-## What are they doing?
-# Have the students discuss the questions below in small groups and then share with the whole class.
-==== Discussion Question ====
-# Suppose you're looking at the largest scale when your arrogant friend comes to you and says "I know what's going on here. There's tiny square pixels that turn on and off based on their neighbors. I can run an exact simulation of this and get everything you see on the larger scales. All your descriptions of intermediate pieces and interactions are superfluous."
-#: As a scientist studying this system, do you feel that your friend's explanation fully captures all there is to know about the system? Why or why not?
-# Let's say you're a physicist that knows all about electrons in solids and how transistors work. Your grandma comes to you and says that she's having trouble getting a game to open on her phone. She assumes that since you understand the technology that makes her phone function, you should be able to fix her issue.
-#: Is this correct? What are the assumptions she's making about scientific understanding?
-=== Shelling Neighborhood Segregation Model ===
-[[File:Shelling Simulator.png|thumb]]
-Students will play around with [http://nifty.stanford.edu/2014/mccown-schelling-model-segregation/ this] simulated model of neighborhood segregation. Have them mess around with it in small groups and answer the following discussion questions as they do so. Then call the class back together for a larger discussion.
-==== Discussion Questions ====
-# What are the components of this model/simulation?
+<!-- Definitions must be written with the Definition and Subdefinition templates. The first Definition should have the "first=yes" flag at the end. -->
-## What is the overall system, and what does it represent? {{Answer|Some grid of pixels representing a city.}}
+{{Definition|Scale of Explanation|The scale of the objects we're describing in a system and of the phenomena that emerges from their interaction. This is also called a "level" of explanation. For example, human interactions can be explained at various scales: On the scale of genetics and neurochemistry, on the scale of cognition and behavior, or on the scale of society and culture.|first=yes}}
-## What are the simple objects, and what do they represent? {{Answer|Pixels that can be either red or blue corresponding to some binary feature of a person, e.g. ethnicity.}}
+{{Definition|Emergent Phenomenon|A (sometimes surprising) phenomenon that's observed on a large scale due to the interaction of a large number of small constituents (often referred to as "agents") interacting with simple rules. (Note that these objects and rules may also be emergent due to interactions on an even smaller scale.)}}
-## What are the simple rules? {{Answer|A pixel moves to the nearest unoccupied space if an insufficient fraction of its immediate neighbors are the same color as it. This corresponds to some preference that people have to be near those that are similar to them.}}
+{{Definition|Phase Transition|A point where a slight change in the small constituents or simple rules in a system cause a dramatic change in the behavior of the system as a whole.}}
-# What is the phenomenon that emerges? (What complex pattern emerges as a result of this simple rule?) {{Answer|Pixels segregate into neighborhood clusters of the same color.}}
+{{Definition|Scientific Reductionism|A viewpoint that says the purpose of science is to look for the smallest possible (most "fundamental") components of a system that everything else is made of. This viewpoint overlooks that knowledge can be gained from considering objects at larger scales without referencing their smaller constituents. For example, we want to be able to program computers without having to reference the states of their constituent transistors, and treating depression at the level of relationships, environment, and cognitive habits can be more effective than considering the level of neurochemistry, although both are relevant.}}
-# Try tweaking the model and see how the emergent behavior changes. What parameters have the biggest impact? Under what conditions does the emergent phenomenon collapse/vanish?
+<br />
-# What features are missing from this model? Do those features matter with regards to the phenomenon that emerges?
-# How well do you think the agents in this simulation model real people picking their neighborhoods? Does this model tell us anything about how people behave and what sorts of interventions it might take to reduce neighborhood segregation?
-=== Conspiracy Theories ===
+|-|Examples=
-From the example of the Schelling Model above, we have learned that a model of causation by emergence involves many actors following simple rules of interaction. When we observe a phenomenon we suspect to be emergent, we can build an emergent model by first hypothesizing simple rules on individuals, and then simulating the outcome of the interactions of many such individuals.
+<!-- Example formatting is still experimental. -->
+{{Example
+|Social media
+|When people are highly connected to each other in social networks with simple rules of interaction (likes, friending, retweeting, etc.), unintended emergent phenomena, such as widespread misinformation, are likely to arise.
+}}
+{{Example
+|Water
+|Water is wet, but water molecules are not. The property of "wetness" must emerge from the relatively simple rules that govern the interactions between water molecules.
+}}
+{{Example
+|Conway's Game of Life
+|A classic demonstration of cellular automata, in which simple local rules result in complex patterns arising on a larger scale.
+}}
+{{Example
+|Schelling Model of Segregation
+|A model wherein large scale racial segregation can emerge even when individual people have no explicit desire to segregate. When the agents are fine being in the minority as long as at least some fraction of people that live around them are of the same group, even this mild preference can lead to segregation.
+}}
+{{Example
+|Consciousness
+|Consciousness as a result of local interactions between neurons.
+}}
-Consider a widespread conspiracy theory. (For example, 36% of Americans polled in 2006 believed that it was somewhat or very likely that federal officials assisted in the 9/11 attacks or knowingly let them happen. [https://web.archive.org/web/20060805052538/http://www.scrippsnews.com/911poll source]) We would like to model the popularization of this belief among Americans as an emergent phenomenon.
+|-|Common Misconceptions=
-In small groups, try to build such a model. (Think about the way the Schelling model works.)
+<!-- Misconceptions must be written with the Misconception template. The first Misconception should have the "first=yes" flag at the end. -->
-# What is the overall system that you are trying to model? What features do you want to include in your model?
+{{Misconception|YouTube is promoting late night talk show hosts over smaller individual creators. It must mean that the YouTube executives are deliberately stifling small content creators.|While such a conspiracy is still possible, it is also likely that the rules that govern the recommendation algorithm result in this emergent phenomenon, when it was not the executives' explicit intention.|first=yes}}
-# What are the simple objects (actors) that make up this system?
+{{Misconception|An [https://imgs.xkcd.com/comics/purity.png arrogant physicist] would say that all your thoughts and emotions are nothing more than complex interactions between subatomic particles.|Sure, this may be true in principle. But, describing thoughts and emotions purely in terms of subatomic particles skips so many scales of explanation so as to be fairly useless for understanding how to get about in the world as a person.}}
-# What are the simple rules that each of these objects follows (regarding the forming and sharing of beliefs)?
+{{Misconception|"Let's say chess is the rules of the universe. After two thousand years, we finally figured out how the pawns move. And then I suppose one day we'll have the God equation and that'll tell us how the whole chess board moves and then we'll become grand masters." -Michio Kaku|Just as knowing the rules of chess doesn't make one a grand master, simply knowing the fundamental laws of physics doesn't give one a full understanding of all things. One needs explanations at every scale, especially if one wants to be able to intervene at the scale we perceive (which is not the scale of atoms).}}
-# What are some parameters you could change in your model that might affect how beliefs spread through the system (i.e. society)? What do these represent in the real world sharing of beliefs?
-# How do you think the patterns of forming and sharing beliefs are likely to change as you move from smaller to larger scales? (i.e. consider how belief spread is different in a hunter-gatherer society of small nomadic bands vs. the contemporary globalized, internet-connected world.)
-Bring the whole class together to share their models with each other.
+</tabber>
+{{#restricted:{{Private:7.2 Emergent Phenomena}}}}
+{{NavCard|chapter=Lesson plans|text=All lesson plans|prev=7.1 Causation, Blame, and Policy|next=8.1 Orders of Understanding}}
 [[Category:Lesson plans]]