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[[File: | The concepts of the SSS curriculum can be broadly grouped into six main categories. | ||
== Philosophical Underpinnings == | |||
[[File:Watercolor Cover - Philosophical Underpinnings.jpg|thumb]] | |||
''What makes science an effective way of learning about the world?'' | |||
: We begin the course by exploring how the ideals and practices of science allow us to approach increasingly accurate and complete representations of our shared material reality. The scientific community does this through empirical investigation of the world, sharing observations and ideas with each other, and continued openness to revision as new evidence emerges. Science offers particularly powerful tools for investigating causal relationships, helping us decide on courses of action that accomplish our goals. | |||
'''Relevant Lessons''' | |||
{{ConceptListItem|1.1 Introduction and When Is Science Relevant}} | |||
{{ConceptListItem|1.2 Shared Reality and Modeling}} | |||
{{ConceptListItem|2.1 Senses and Instrumentation}} | |||
{{ConceptListItem|3.1 Probabilistic Reasoning}} | |||
{{ConceptListItem|6.1 Correlation and Causation}} | |||
== Probabilistic Thinking == | == Probabilistic Thinking == | ||
[[File: | [[File:Watercolor Cover - Probabilistic Thinking.jpg|thumb]] | ||
== Science's | |||
''How can we make informed decisions using noisy and uncertain data?'' | |||
: There are many sources of uncertainty, both in the accuracy and precision of data and in the inferences drawn from data. Scientists have developed strategies for tracking, reducing, and coping with this uncertainty, enabling us to make clearer judgments and more effective decisions even when we cannot know for sure what the outcomes will be. | |||
'''Relevant Lessons''' | |||
{{ConceptListItem|2.2 Systematic and Statistical Uncertainty}} | |||
{{ConceptListItem|3.1 Probabilistic Reasoning}} | |||
{{ConceptListItem|3.2 Calibration of Credence Levels}} | |||
{{ConceptListItem|4.1 Signal and Noise}} | |||
{{ConceptListItem|4.2 Finding Patterns in Random Noise}} | |||
{{ConceptListItem|5.1 False Positives and Negatives}} | |||
== Causal Reasoning == | |||
[[File:Watercolor Cover - Causal Reasoning.jpg|thumb]] | |||
''What causes what, and how can we find out?'' | |||
: To make a decision, one has to know its consequences. Much of science is dedicated to finding out about "what causes what." How does science do this through direct experimentation or indirect inference? What are the different types of causation and their implications on policymaking and criminal justice? | |||
'''Relevant Lessons''' | |||
{{ConceptListItem|6.1 Correlation and Causation}} | |||
{{ConceptListItem|6.2 Hill's Criteria}} | |||
{{ConceptListItem|7.1 Causation, Blame, and Policy}} | |||
{{ConceptListItem|7.2 Emergent Phenomena}} | |||
== Science's Can-do Aspect == | |||
[[File:Watercolor Cover - Can-do Aspect.jpg|thumb]] | |||
''How can we gain insights despite immense unknowns and conceptual and practical obstacles?'' | |||
: Science is balanced by, on the one hand, awareness that we might at any point be mistaken, and on the other hand, optimism that if we continue iteratively investigating, we will eventually gain understanding. This can-do spirit is bolstered by strategies that help us use what we know to handle what we don't know. | |||
'''Relevant Lessons''' | |||
{{ConceptListItem|5.2 Scientific Optimism}} | |||
{{ConceptListItem|8.1 Orders of Understanding}} | |||
{{ConceptListItem|8.2 Fermi Problems}} | |||
{{ConceptListItem|12.2 Grill the Guest}} | |||
== Human Cognition == | == Human Cognition == | ||
[[File: | [[File:Watercolor Cover - Human Cognition.jpg|thumb]] | ||
''What are cognitive traps that cause people to fool themselves?'' | |||
: Humans are prone to errors that arise from overapplied heuristics, cognitive biases, and limited processing power. Being mindful of these vulnerabilities can help us to moderate our own judgments, using cognitive and social strategies to reduce mistakes and biases. | |||
'''Relevant Lessons''' | |||
{{ConceptListItem|7.1 Causation, Blame, and Policy}} | |||
{{ConceptListItem|9.1 Heuristics}} | |||
{{ConceptListItem|9.2 Biases}} | |||
{{ConceptListItem|10.1 Confirmation Bias}} | |||
{{ConceptListItem|10.2 Blinding}} | |||
{{ConceptListItem|11.1 Pathological Science}} | |||
== Group Decision Making == | == Group Decision Making == | ||
[[File: | [[File:Watercolor Cover - Group Decision Making.jpg|thumb]] | ||
''How can groups make better decisions together?'' | |||
: Group decision-making can be challenging when people disagree. However, distinguishing between facts and values, accounting for values from a variety of stakeholders, and incorporating expert judgments of fact can produce decisions based on more accurate and complete information, greater community buy-in, and more widely desirable outcomes. | |||
'''Relevant Lessons''' | |||
{{ | {{ConceptListItem|1.1 Introduction and When Is Science Relevant}} | ||
{{ConceptListItem|11.2 When Is Science Suspect}} | |||
{{ConceptListItem|12.1 Wisdom of Crowds and Herd Thinking}} | |||
{{ConceptListItem|13.1 Denver Bullet Study}} | |||
{{ConceptListItem|13.2 Deliberative Polling}} | |||
{{ConceptListItem|14.1 Scenario Planning}} | |||
{{ConceptListItem|14.2 Wrap Up}} | |||
{{NavCard|prev=Course introduction|next=Parts of the course}} | {{NavCard|prev=Course introduction|next=Parts of the course}} | ||
[[Category:Introduction]] | [[Category:Introduction]] | ||
Latest revision as of 16:06, 17 December 2025
The concepts of the SSS curriculum can be broadly grouped into six main categories.
Philosophical Underpinnings
What makes science an effective way of learning about the world?
- We begin the course by exploring how the ideals and practices of science allow us to approach increasingly accurate and complete representations of our shared material reality. The scientific community does this through empirical investigation of the world, sharing observations and ideas with each other, and continued openness to revision as new evidence emerges. Science offers particularly powerful tools for investigating causal relationships, helping us decide on courses of action that accomplish our goals.
Relevant Lessons
Probabilistic Thinking
How can we make informed decisions using noisy and uncertain data?
- There are many sources of uncertainty, both in the accuracy and precision of data and in the inferences drawn from data. Scientists have developed strategies for tracking, reducing, and coping with this uncertainty, enabling us to make clearer judgments and more effective decisions even when we cannot know for sure what the outcomes will be.
Relevant Lessons
Causal Reasoning
What causes what, and how can we find out?
- To make a decision, one has to know its consequences. Much of science is dedicated to finding out about "what causes what." How does science do this through direct experimentation or indirect inference? What are the different types of causation and their implications on policymaking and criminal justice?
Relevant Lessons
Science's Can-do Aspect
How can we gain insights despite immense unknowns and conceptual and practical obstacles?
- Science is balanced by, on the one hand, awareness that we might at any point be mistaken, and on the other hand, optimism that if we continue iteratively investigating, we will eventually gain understanding. This can-do spirit is bolstered by strategies that help us use what we know to handle what we don't know.
Relevant Lessons
Human Cognition
What are cognitive traps that cause people to fool themselves?
- Humans are prone to errors that arise from overapplied heuristics, cognitive biases, and limited processing power. Being mindful of these vulnerabilities can help us to moderate our own judgments, using cognitive and social strategies to reduce mistakes and biases.
Relevant Lessons
Group Decision Making
How can groups make better decisions together?
- Group decision-making can be challenging when people disagree. However, distinguishing between facts and values, accounting for values from a variety of stakeholders, and incorporating expert judgments of fact can produce decisions based on more accurate and complete information, greater community buy-in, and more widely desirable outcomes.
Relevant Lessons
