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| {{#restricted: | | {{#restricted: |
| | | {{7.2 Emergent Phenomena/restricted}} |
| == Useful Resources ==
| | }}{{NavCard|prev=7.1 Causation, Blame, and Policy|next=8.1 Orders of Understanding}} |
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| <tabber>
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| |-|Lecture Video=
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| <br /><center><youtube>LMZH1wBaZOI</youtube></center><br />
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| |-|Discussion Slides=
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| {{LinkCard
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| |url=https://docs.google.com/presentation/d/1_xF4kYKuGTW28ppQiQWzD1SbpkCC9G1YcaynCaqJxfA/
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| |title=Discussion Slides Template
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| |description=The discussion slides for this lesson.
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| }}
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| <br />
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| |-|Handouts and Activities=
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| {{LinkCard
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| |url=http://nifty.stanford.edu/2014/mccown-schelling-model-segregation/
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| |title=Shelling's Model of Segregation
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| |description=Simulator for the Shelling model.}}
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| <br />
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| |-|Readings and Assignments=
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| {{LinkCardInternal
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| |url=:File:The Architecture of Complexity - Simon.pdf
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| |title=The Architecture of Complexity
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| |description=Reading on how large systems tend to be organized.}}
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| {{LinkCard
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| |url=https://youtu.be/16W7c0mb-rE
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| |title=Emergence: How Stupid Things Become Smart Together
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| |description=Short video on the subject of emergence.}}
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| <br />
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| </tabber>
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| == Recommended Outline ==
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| === During Class ===
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| {{Agenda}}
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| === Conway Discussion ===
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| ==== Instructions ====
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| Show your students the following video. Pause the video whenever it stops and some text that says "Paused" appears in the top left corner.
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| <center><youtube>WwR4R1iE1ck</youtube></center>
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| Every time the video pauses, have your students spend one minute in small groups answering the following questions about the current state of the video.
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| # What are the pieces?
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| # What are they doing?
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| {{BoxTip|"Pieces" is asking what the objects of interest at the current scale are.}}
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| Once the video is done, ask your students [[#Conway Discussion Questions|the following discussion questions]].
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| ==== Conway Discussion Questions ====
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| ===== Arrogant Friend =====
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| 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."
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| 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?
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| {{BoxAnswer|There's a sense in which your friend is right, but they're being overly reductionist. There's a tendency to think only about the most basic rules and think that all the work is done. While that may in principle give you everything you need to know to simulate other scales, it doesn't tell you anything useful about how phenomena at those scales actually happen. If you're trying to intervene on a scale other than the smallest one, then just knowing the simplest rules may not be helpful.}}
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| ===== Solids and Transistors =====
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| 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.
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| Is this correct? What are the assumptions she's making about scientific understanding?
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| {{BoxAnswer|She's falling for [[#Arrogant Friend|the same trap that your friend was]] (though in a more innocent way). She's assuming since you understand electrons you understand ''everything'' that results from their interactions as well.}}
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| {{Line}}
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| What are some intermediate levels of understanding between your understanding of electrons/transistors and her understanding of user interface?
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| {{BoxAnswer|There's lots of levels that can broken up different ways. Here's one possible breakdown.
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| # Quantum Mechanics
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| # Electrons and Individual Transistors
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| # Logic Circuits
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| # Hardware Architecture
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| # Machine Languages
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| # Assembly Languages
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| # High Level Programming Languages
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| # Software and User Interfaces
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| # Your Grandma's Game Not Opening}}
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| === Shelling Neighborhood Segregation Model ===
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| [[File:Shelling Simulator.png|thumb|The interface your students see.]]
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| Students will play around with a 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.
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| {{LinkCard
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| |url=http://nifty.stanford.edu/2014/mccown-schelling-model-segregation/
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| |title=Shelling's Model of Segregation
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| |description=Simulator for the Shelling model.}}
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| ==== Shelling Discussion Questions ====
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| ===== Question 1 =====
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| What are the components of this model/simulation?
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| <ol style="list-style-type:lower-alpha" start=1>
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| <li>What is the overall system, and what does it represent?</li></ol>
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| {{BoxAnswer|Some grid of pixels representing a city.}} | |
| <ol style="list-style-type:lower-alpha" start=2>
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| <li>What are the simple objects, and what do they represent?</li></ol>
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| {{BoxAnswer|Pixels that can be either red or blue corresponding to some binary feature of a person, e.g. ethnicity.}}
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| <ol style="list-style-type:lower-alpha" start=3>
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| <li>What are the simple rules?</li></ol>
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| {{BoxAnswer|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 agents have to be near those that are similar to them.}}
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| ===== Question 2 =====
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| What is the phenomenon that emerges? (What complex pattern emerges as a result of this simple rule?)
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| {{BoxAnswer|Pixels segregate into neighborhood clusters of the same color.}}
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| ===== Question 3 =====
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| Set the model to the following values:
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| <ul>
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| <li>Similar: 75%</li>
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| <li>Red/Blue: 50/50%</li>
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| <li>Empty: 10%</li>
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| <li>Size: Any Value</li>
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| </ul>
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| And then also try setting it to these values (changing only the "Similar" item):
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| <ul>
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| <li>Similar: 76%</li>
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| <li>Red/Blue: 50/50%</li>
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| <li>Empty: 10%</li>
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| <li>Size: Any Value</li>
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| </ul>
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| Is the phenomena that we see different? If so what's the difference? How did we get such a drastic change just be tweaking one value by one percent? Do we think this would apply to the real world? Why or why not?
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| {{BoxAnswer|In the first set of values, you eventually reach a steady state of maximized segregation. In the second set, agents keep moving forever and are never satisfied. They would ''like'' to have similar neighbors, but it's too hard to find enough similar agents to make this happen. So the city stays diverse (but in motion) forever. We have observed a "phase transition." This is a point where a tiny change in values can cause a huge change in the behavior of the system. The change from the first set of values to the second is analogous to the change from frozen ice to liquid water.}}
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| ===== Question 4 =====
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| Continue playing with the model and see how the emergent behavior changes. What parameters have the biggest impact? Under what conditions does the emergent phenomenon collapse/vanish?
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| {{BoxAnswer|One thing students may observe is that the phase transition is shockingly robust with regards to changes in the red/blue ratio. There's other conditions where the model has interesting behavior as well. For example, if you have a low similar percent threshold and really imbalanced red/blue percents then the the city might not reach a steady state.}}
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| ===== Question 5 =====
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| What features are missing from this model? Do those features matter with regards to the phenomenon that emerges?
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| {{BoxAnswer|There's ''lots'' of missing features. For example, there's no terrain to create natural neighborhood boundaries. There's also no schools, work, stores, or other things that would cause agents to leave their neighborhoods. Other oversimplifications are that there's only two types of agents, everyone has the same threshold, the agents opinion of each other doesn't change, etc. The list goes on.}}
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| ===== Question 6 =====
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| How well do you think the agents in this simulation model real agents picking their neighborhoods? Does this model tell us anything about how agents behave and what sorts of interventions it might take to reduce neighborhood segregation?
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| {{BoxAnswer|The model suggests several possible interventions. One option is to enforce rules around whether or not agents live in diverse environments. Given the simplifications of the model, this could deal with neighborhood segregation, but would leave many of the agents unsatisfied. An alternative option would be to intervene on the ''agents'' and see if it's possible to change their similarity thresholds. In this model, that would reduce neighborhood segregation while also leaving agents satisfied.}}
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| {{BoxCaution|Note that we don't claim that agents's local preferences is the only (or even dominant) cause of neighborhood segregation. You could also enforce segregation by enforcing neighborhoods on a "global" level (such as with [https://en.wikipedia.org/wiki/Redlining red lining]).}}
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| === Conspiracy Theories ===
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| 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.
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| 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.
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| In small groups, try to build such a model. (Think about the way the Schelling model works.)
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| # What is the overall system that you are trying to model? What features do you want to include in your model?
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| # What are the simple objects (actors) that make up this system?
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| # What are the simple rules that each of these objects follows (regarding the forming and sharing of beliefs)?
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| # 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?
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| # 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.)
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| Bring the whole class together to share their models with each other.}}{{NavCard|prev=7.1 Causation, Blame, and Policy|next=8.1 Orders of Understanding}}
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| [[Category:Lesson plans]] | | [[Category:Lesson plans]] |