7.1 Causation, Blame, and Policy: Difference between revisions
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{{Cover|7.1 Causation, Blame, and Policy}} | |||
Real-world decision making must consider more than whether a randomized controlled trial says one variable causes another. In some legal and policy settings, evidence for singular causation, rather than general causation, plays a bigger role. With the Trolley Problem, we illustrate the powerful omission bias. Students are encouraged to reflect on the interplay between blame and causation in decision making. | Real-world decision making must consider more than whether a randomized controlled trial says one variable causes another. In some legal and policy settings, evidence for singular causation, rather than general causation, plays a bigger role. With the Trolley Problem, we illustrate the powerful omission bias. Students are encouraged to reflect on the interplay between blame and causation in decision making. | ||
== The Lesson in Context == | == The Lesson in Context == | ||
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{{ContextRelation|The omission bias is one explanation for the status quo bias, in that humans tend to prefer not actively changing the current situation or trend, even when it may be worse than the potential pitfalls of the new outcome.}} | {{ContextRelation|The omission bias is one explanation for the status quo bias, in that humans tend to prefer not actively changing the current situation or trend, even when it may be worse than the potential pitfalls of the new outcome.}} | ||
}} | }} | ||
== Takeaways == | == Takeaways == | ||
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|-|Examples= | |-|Examples= | ||
{{Example | |||
|Drug Trials | |||
|A randomized controlled trial for a drug may demonstrate its general therapeutic effect (general causation), e.g. taking this drug reduces the risks of this disease, but it cannot conclusively demonstrate a causal connection in any particular instance of a patient taking this drug (singular causation).}} | |||
{{ | {{Example | ||
|Weather and Climate Change | |||
|One can claim that climate change causes extreme weather events (general causation), but not that any particular instance of wildfire was caused by climate change (singular causation).}} | |||
{{Exemplary | |||
|{{Blockquote|Just because the drug didn't cure me doesn't mean it can't cure you. RCTs show that it does help most people with our condition.}} | |||
{{Blockquote|I know penicillin saves lives. But I shouldn't take it no matter how sick I feel, because I'm allergic to penicillin. For me, that cure is worse than the disease.}} | |||
{{Blockquote|Susan Wenszell didn't know who shoved her off a passenger platform at an Atlanta subway station. And unconscious after she fell onto the tracks, she was unaware that a train was rolling right at her. But her 28-year-old daughter, Katie, leaped down to rescue her. 'She pulled me in between the two rails, and the train rolled over me'|[https://www.cnn.com/2018/08/28/us/iyw-woman-saves-mom-from-oncoming-train-trnd/index.html Source]}} | |||
}} | |||
|-|Common Misconceptions= | |-|Common Misconceptions= | ||
<!-- Misconceptions must be written with the Misconception template. The first Misconception should have the "first=yes" flag at the end. --> | <!-- Misconceptions must be written with the Misconception template. The first Misconception should have the "first=yes" flag at the end. --> | ||
{{Misconception|This drug will absolutely cure you, because there was a really big RCT that showed it works for your exact disease!|RCTs can only | {{Misconception|This drug will absolutely cure you, because there was a really big RCT that showed it works for your exact disease!|This quote is incorrect because RCTs can only general singular causation.|first=yes}} | ||
|-|Expanded Learning Goals= | |||
After this lesson, students should | |||
# Concept Acquisition | |||
## '''Multiple Causation:''' Any given effect may be brought about by a complex combination of many causes (which may interact with each other), with varying degrees of influence on the outcome. | |||
## '''Singular causation:''' A relation between specific events — i.e., Event <math>A</math> caused Event <math>B</math>. | |||
## '''General causation:''' A relation between variables — i.e., <math>X</math> causes <math>Y</math>. | |||
## '''Causation as production:''' There is a spatiotemporally connected series of causal connections between two events or event types (i.e., the kind of causation people have in mind when they say there is no action at a distance; e.g., commission). | |||
## '''Causation as dependence:''' If <math>X</math> hadn't happened, <math>Y</math> would not have happened (counterfactual dependence, e.g. omission, double prevention [prevention of a prevention]). | |||
## Decision-making involves not only assessment of the outcome, but also the agent's causal role in the production of the outcome (i.e., omission vs. commission, e.g. trolley dilemma). | |||
# Concept Application | |||
## Distinguish between cases of singular and general causation. | |||
## Distinguish between cases of production and dependence. | |||
## Distinguish between the evidence needed to establish singular causation and the evidence needed to establish general causation. | |||
## Identify different policy implications of singular vs. general causation (e.g., for policy and legal decision-making). | |||
## Identify different policy implications of production vs. dependence (e.g., for policy and legal decision-making). | |||
</tabber> | </tabber> | ||
Latest revision as of 23:03, 11 June 2026
Real-world decision making must consider more than whether a randomized controlled trial says one variable causes another. In some legal and policy settings, evidence for singular causation, rather than general causation, plays a bigger role. With the Trolley Problem, we illustrate the powerful omission bias. Students are encouraged to reflect on the interplay between blame and causation in decision making.
The Lesson in Context
This course has so far only discussed general causation, which can be demonstrated through randomized controlled trials and to a weaker extent Hill's criteria. But personal, policy, and legal decisions often depend on singular causation as well. It also sometimes matters whether the causation is by commission or by omission. The famous Trolley dilemma is discussed.
Takeaways
After this lesson, students should
- Distinguish between singular and general causation.
- Distinguish between the evidence needed to establish singular or general causation.
- Identify different policy implications of singular or general causation.
- Recognize cases where omission bias and status quo bias can influence decision making, even when this results in a worse outcome.
Singular Causation
General Causation
Omission Bias
Status Quo Bias
Drug Trials
Weather and Climate Change
Exemplary Quotes
“Just because the drug didn't cure me doesn't mean it can't cure you. RCTs show that it does help most people with our condition.”
“I know penicillin saves lives. But I shouldn't take it no matter how sick I feel, because I'm allergic to penicillin. For me, that cure is worse than the disease.”
“Susan Wenszell didn't know who shoved her off a passenger platform at an Atlanta subway station. And unconscious after she fell onto the tracks, she was unaware that a train was rolling right at her. But her 28-year-old daughter, Katie, leaped down to rescue her. 'She pulled me in between the two rails, and the train rolled over me'”
This drug will absolutely cure you, because there was a really big RCT that showed it works for your exact disease!
After this lesson, students should
- Concept Acquisition
- Multiple Causation: Any given effect may be brought about by a complex combination of many causes (which may interact with each other), with varying degrees of influence on the outcome.
- Singular causation: A relation between specific events — i.e., Event [math]\displaystyle{ A }[/math] caused Event [math]\displaystyle{ B }[/math].
- General causation: A relation between variables — i.e., [math]\displaystyle{ X }[/math] causes [math]\displaystyle{ Y }[/math].
- Causation as production: There is a spatiotemporally connected series of causal connections between two events or event types (i.e., the kind of causation people have in mind when they say there is no action at a distance; e.g., commission).
- Causation as dependence: If [math]\displaystyle{ X }[/math] hadn't happened, [math]\displaystyle{ Y }[/math] would not have happened (counterfactual dependence, e.g. omission, double prevention [prevention of a prevention]).
- Decision-making involves not only assessment of the outcome, but also the agent's causal role in the production of the outcome (i.e., omission vs. commission, e.g. trolley dilemma).
- Concept Application
- Distinguish between cases of singular and general causation.
- Distinguish between cases of production and dependence.
- Distinguish between the evidence needed to establish singular causation and the evidence needed to establish general causation.
- Identify different policy implications of singular vs. general causation (e.g., for policy and legal decision-making).
- Identify different policy implications of production vs. dependence (e.g., for policy and legal decision-making).
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