Humans make decisions every day. As individuals, voters, and citizens of the world, the choices we make have the power to shape the world around us. The problem is, we don't make choices very well.
SSS attempts to address this. Our curriculum uses the tools developed by science to help people better understand the world around them and make better decisions together in an increasingly uncertain world.
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1.1 Introduction and When Is Science Relevant | When is science relevant? The many uses of a scientific approach. |
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1.2 Shared Reality and Modeling | Science is grounded in belief in a common, shared reality with some degree of regularity. |
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2.1 Senses and Instrumentation | Science uses both our direct senses and a variety of instruments to extend our ability to observe phenomena. We trust our instruments for the same reasons we trust our senses; interactive exploration and comparison. |
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2.2 Systematic and Statistical Uncertainty | This topic explores the sources of error and uncertainty in data. |
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3.1 Probabilistic Reasoning | Using meta-judgments of the likelihood that your best judgment is right—how confident you are—enables decisions that take uncertainty into account. |
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3.2 Calibration of Credence Levels | It is important to check the calibration of credence levels; that is, how good one's judgments are about how likely each of one's claims is to be right. |
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4.1 Signal and Noise | The challenges of finding the information we want amidst messy data. |
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4.2 Finding Patterns in Random Noise | We often find mistake noise for signal; how do we minimize these mistakes, given that they are not always easy to tell apart? |
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5.1 False Positives and Negatives | Considering the relative costs of each possible mistake helps us make better decisions under conditions of uncertainty, when we cannot eliminate the possibility of a mistake either way. |
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5.2 Scientific Optimism | The psychological trick of believing one will make progress long enough to enable solving difficult problems. |
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6.1 Correlation and Causation | An introduction to the scientific approach to determining causal relationships. |
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6.2 Hill's Criteria | Building on Correlation and Causation, we examine how to collect evidence for causality in more difficult cases. |
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7.1 Causation, Blame, and Policy | Distinguishing singular causation ([math]\displaystyle{ A }[/math] caused [math]\displaystyle{ B }[/math]) from general causation ([math]\displaystyle{ X }[/math] tends to cause [math]\displaystyle{ Y }[/math]). |
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7.2 Emergent Phenomena | Many phenomena in science are emergent, i.e., visible only at higher levels of organization. This tends to occur when large numbers of elements interact, e.g. as in individuals on social media. |
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8.1 Orders of Understanding | Because each event and/or phenomenon has many causal factors, it is often important to distinguish which factors affect it the most and which factors play a smaller role. |
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8.2 Fermi Problems | Estimating quantities based on what we know. |
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9.1 Heuristics | Some of the heuristics biases that make our probability judgments go awry. |
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9.2 Biases | Some of the psychological biases that make our probability judgments go awry. |
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10.1 Confirmation Bias | Our tendency to preserve our existing or preferred beliefs, even against the evidence. |
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10.2 Blinding | Blind analysis, the practice of deciding how we will analyze data before finding out if the analysis we have chosen supports our hypothesis, counteracts confirmation bias. |
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11.1 Pathological Science | How to catch bad science. |
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11.2 When Is Science Suspect | The capacity for science to be misused to reinforce existing power structures. |
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12.1 Wisdom of Crowds and Herd Thinking | Explore ways that groups fall short of their optimal reasoning ability. There are better and worse ways to aggregate a group's knowledge. |
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12.2 Grill the Guest | Confront a working scientist about their work using course concepts. |
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13.1 Denver Bullet Study | The Denver Bullet Study offers one approach to integrating facts and values in a controversial real-world problem, drawing facts from a set of experts, gauging the values of different stakeholders, and bringing these together for a final decision. |
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13.2 Deliberative Polling | Another approach to getting groups of people to come together to make decisions, in a process where the integration of facts and values is scaffolded. |
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14.1 Scenario Planning | A third approach to integrating facts and values under conditions of uncertainty about what the future will be like. |
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14.2 Wrap Up | An overview and conclusion of the course. |