Sense and Sensibility and Science (L&S 22)

Update

The course listing can now be found here!

Requirements Class Fulfills

• Meets L&S Breadth Requirement, Physical Science
• Meets L&S Breadth Requirement, Philosophy & Values
• Meets L&S Breadth Requirement, Social & Behavioral Sciences
• Meets CDSS Essential Skills Requirement, Human and Social Dynamics of Data and Technology Requirement
• Meets Data Science Major Requirement, Philosophical Foundations: Evidence and Inference

Class time

Each week, there will be one lecture period on Wednesdays from 2:00–4:00 pm, covering the topics from the two 90-minute labs/sections which are taught Tuesday and Thursday. On most Wednesdays, only the first 90 minutes of the period will be used for lecture, followed by 30 minutes of optional office hours. In addition, Friday 2:00–4:00 pm is reserved only for 2 midterms, 2 course events, and optional office hours. There are no lectures on Fridays.

Student quote

“Every single person, student or not, can benefit from taking this class. It has the potential to give amazing insight into our world and ourselves and gives practical tools for navigating the world.” —S&S&S student

Student quote

“It taught me things I would never have realized but never have known I needed. It most certainly was one of the most insightful courses I've taken.” —S&S&S student

About the Course

Every day we make decisions that can and should be informed by science. We make decisions as individuals, as voters, and as members of our various communities. The problem is, we don't do it so well—a fact sadly apparent in political debates. This course aims to equip students with basic tools to be better thinkers. We will explore key aspects of scientific thinking that everyone should know, especially the many ways that we humans tend to fool ourselves, and how to avoid them—including how to differentiate signal from noise, evaluate causal claims, and avoid reasoning biases. We'll then look at the best models for using science to guide decisions, combining both evidence and values, with the ultimate goal of bettering the world. We're facing a world that seems to struggle with rational collective decision making, especially in the face of conflict. How can we take into account our ostensibly differing values, fears, and aspirations while also grappling with and evaluating facts and evidence? As individuals, as groups, and as an often polarized society, we find this challenge everywhere we turn. This year, the challenge of making good decisions as a society seems both more difficult and more important than ever. Over the centuries, scientists, psychologists, and philosophers have developed rigorous, open-minded ways of thinking about the world that can help us address these universal and pressing concerns. This course explores and directly engages with some of the most useful tools of scientific-style critical thinking, taking into account both psychological biases and philosophical underpinnings.

About the Professors

Sense and Sensibility and Science is co-taught by faculty from Physics, Philosophy, and the Haas School of Business School. The course satisfies the Philosophy and Values, Physical Science, or Social and Behavioral Sciences breadth requirement in the College of Letters & Science.

Prof. Saul Perlmutter

Physicist

Saul Perlmutter is a 2011 Nobel Laureate, sharing the prize in Physics for the discovery of the accelerating expansion of the Universe. He is a professor of physics at the University of California, Berkeley, where he holds the Franklin W. and Karen Weber Dabby Chair, and a senior scientist at Lawrence Berkeley National Laboratory.

Prof. Ellen Evers

Social Psychologist

Ellen Evers is an Associate Professor of Marketing at the Haas School of Business. Her research focuses on judgment, decision-making, moral psychology, and pattern perception.

Prof. John Campbell

Philosopher

John's main interests are in theory of meaning, metaphysics, and philosophy of psychology. He is currently working on the question whether consciousness, and in particular sensory awareness, plays any key role in our knowledge of our surroundings. He is also working more generally on causation in psychology. He is the author of Past, Space and Self (1994) and Reference and Consciousness (2002).

Course Topics

	1.1 Introduction and When Is Science Relevant	When is science relevant? The many uses of a scientific approach.
	1.2 Shared Reality and Modeling	Science is grounded in belief in a common, shared reality with some degree of regularity.
	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.
	2.2 Systematic and Statistical Uncertainty	This topic explores the sources of error and uncertainty in data.
	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.
	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.
	4.1 Signal and Noise	The challenges of finding the information we want amidst messy data.
	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?
	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.
	5.2 Scientific Optimism	The psychological trick of believing one will make progress long enough to enable solving difficult problems.
	6.1 Correlation and Causation	An introduction to the scientific approach to determining causal relationships.
	6.2 Hill's Criteria	Building on Correlation and Causation, we examine how to collect evidence for causality in more difficult cases.
	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]).
	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.
	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.
	8.2 Fermi Problems	Estimating quantities based on what we know.
	9.1 Heuristics	Some of the heuristics biases that make our probability judgments go awry.
	9.2 Biases	Some of the psychological biases that make our probability judgments go awry.
	10.1 Confirmation Bias	Our tendency to preserve our existing or preferred beliefs, even against the evidence.
	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.
	11.1 Pathological Science	How to catch bad science.
	11.2 When Is Science Suspect	The capacity for science to be misused to reinforce existing power structures.
	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.
	12.2 Grill the Guest	Confront a working scientist about their work using course concepts.
	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.
	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.
	14.1 Scenario Planning	A third approach to integrating facts and values under conditions of uncertainty about what the future will be like.
	14.2 Wrap Up	An overview and conclusion of the course.