A syllabus update is coming soon– in January 2023 (this is a 2021 sample!)

PREDICTION: THE PAST & PRESENT OF THE FUTURE

Harvard GenEd 1112, Spring 2021, Zoom, Tuesdays & Thursdays 1:30-2:45 PM

COURSE CANVAS SITE (with Zoom links) • PREDICTION PROJECT WEB SITE

INSTRUCTOR

Prof. Alyssa GOODMAN, Robert Wheeler Willson Professor of Applied Astronomy and co-Director for Science, Radcliffe Institute for Advanced Study   

Office Hours: Friday, 3:30 PM Boston time, on zoom (links).  
Contact: agoodman@cfa.harvard.edu

INSTRUCTIONAL STAFF

Teaching Fellows in this course will lead discussion sections once per week, at times to be arranged.  Each will have a one-hour office hour, on zoom.

Andrew Deloucas, Ph.D. candidate in Assyriology, Graduate School of Arts and Sciences
Office Hours: TBA
Contact: adeloucas@g.harvard.edu

Drew Lichtenstein, Instructional Designer

Office Hours: 10:00am

Contact at: drewlich217@gmail.com

In addition to the Teaching Fellows, two undergraduate PredictionX project team members, who are also GenEd 1112 alumni, will join us during class to facilitate discussion.  Feel free to also contact them with questions as-needed.

London Vallery, History of Science concentrator (Technology, Information, and Society Track - Astrophysics), Harvard College

Contact at: londonvallery@college.harvard.edu

Elliott Hyman, Social Studies concentrator with a secondary in Environmental Science and Public Policy (Climate Change Policy focus field), Harvard College

Contact at: elliotthyman@college.harvard.edu

STUDENTS

Enrollment for GenEd 1112 is limited, so that the discussion on zoom will remain manageable.  We will value contributions from each student, and we hope to get to know you.  Please fill out your biographical profiles on Canvas to help us learn more about you!

COURSE CATALOG DESCRIPTION

Human beings are the only creatures in the animal kingdom properly defined as worriers. We are the only ones who expend tremendous amounts of time, energy, and resources trying (sometimes obsessively) to understand our futures before they happen. While the innate ability of individual people to predict has not changed much in the past few millennia, developments in mathematical and conceptual models have inordinately improved predictive systems. These systems have integrated comparisons to past results and quantified how “certain” we can be about various aspects of the future -- processes that were, in many cases, inconceivable at one point in the past. This course is a coordinated investigation of the history and future of prediction, beginning with Ancient Mesopotamians reading signs in sheep entrails and ending with modern computer simulations for climate, health, wealth, and the fate of our Universe. In this class, you will design your own predictive systems to critically engage with assumptions about how the world works and situate your explorations in a study of how motivations and techniques for divining the future have changed–and not changed–throughout human history.

COURSE OBJECTIVES &  EXPECTATIONS

The Framework for Predictive Systems shown here captures much of the fundamental content of our curriculum.   By the end of GenEd 1112, all students should be able to apply this Framework to the analysis of any predictive system.  

Students will become familiar with various PREDICTIVE SYSTEMS (shown as a grey box in the Framework).  Over the course of the term, each student will choose to analyze particular extant systems, as well as  invent their own, so not all students will be expert on the same systems.  Instead, the goal is to gain and appreciate expertise on just a few systems, or types of systems, while using the Framework to understand how many systems fall into general groupings, appreciating the general features of those groupings.  By way of a simple example: predictive systems with a great deal of #HUMAN input can all be very subjective.

The bubble in the Framework labeled EVALUATE ACCURACY is also key to GenEd 1112, as it encompasses the concept of Uncertainty.  There are vast differences in how uncertainty is and has been evaluated (if at all) and  valued in predictive systems throughout history.  By the end of GenEd 1112, students will have a deep appreciation for how, for example, Ancient Greeks may have thought about the Oracle of Delphi’s accuracy, while also appreciating how to understand the uncertainty associated with weather forecasts, or Bayesian analyses of jury trials’ likely outcomes.

To attain this deep understanding of Predictive Systems and the inherent uncertainty associated with them, students will:

1. Attend two 1.25-hour sessions led by Prof. Goodman per week.  These sessions will take place on zoom, and will make use of breakout groups to facilitate small group activities and discussions.^[1]  These activities will be interwoven with presentations and demonstrations by Prof. Goodman and guests.
2. Carry out the readings, preparation, and assignments summarized below, and explained on the Canvas Assignments page.  Please note that in order to adapt well to student interests as the course proceeds, assignment details will only be finalized on Canvas a week or two before they are relevant, so do check back as the semester proceeds.  In other words, assignments listed  below are estimates about the future, with some “uncertainty”!  Please consider Canvas the definitive source of your assignments.
3. Post to the “Forum” page at PredictionX.org.  Most weeks, a new discussion thread will be created corresponding to a topic we discussed in class. The discussion thread will have a short reflective prompt for you to answer in a minimum of 100 words. In addition to posting your own response, you will also reply to one of your classmates' posts. This will count towards your participation grade for the class and is meant to be a low-stress way for you to think about how prediction impacts your everyday life or academic field. Please remember that this forum is open to the general public, so don't post anything you would not want the world to see. If you have any concerns about participating in the forum, please reach out to your TF to discuss alternative arrangements.
4. Create two substantial projects: a Prediction Journal (added to periodically over the course of the semester) and an online final project presenting a specific Predictive System.  GenEd 1112 has no midterm or final, and instead relies on evaluation of each student’s Prediction Journal and Final Project.  Detailed instructions for the Journals and Final Project will be provided in class, in section, and on Canvas.  A short summary of the Final Project is below. Teaching Fellows will provide personalized  support for students on these projects, in person during office hours, in section.
5. Attend sections, which will often offer enriching material not available in class or elsewhere online, and TFs will customize sessions based on their own expertise.  Attendance in section will be recorded, and it is strongly suggested that you attend.

Students should bring laptops or tablets to class, as much class time will involve realtime research and the creation of collaborative (Google) documents.   Please do not be distracted by the internet when other people are lecturing or presenting.

There are no prerequisites for GenEd 1112.

MATERIALS AND ACCESS

Books for GenEd 1112

Amazon links are below, but all books should also be at the Harvard Coop, using this convenient link.

Required

1--The Signal and the Noise: Why So Many Predictions Fail-but Some Don't, by Nate Silver  [read online]

2--To Explain the World, the Discovery of Modern Science, by Stephen Weinberg [read online]

Recommended

1-Climate of Hope: How Cities, Businesses, and Citizens Can Save the Planet, by Michael Bloomberg & Carl Pope [read online]

2- The House of Wisdom: How Arabic Science Saved Ancient Knowledge and Gave Us the Renaissance, by Jim Al-Khalili [not yet available online]

3--Prediction Machines, by Ajay Agrawal, Joshua Gans, & Avi Goldfarb [read online]

4--The Knowledge Machine, by Michael Strevens [not yet available online]

5--On The Future, by Martin Rees [read online]

6--Thinking Fast, and Slow, by Daniel Kahneman [read online]

Also, copies of “The Pursuit of Destiny,” by Halpern--a very useful reference, can be downloaded from this Scribd PDF link. (The book is out-of-print.)

Information on additional library materials, study group options, etc., will appear here during the course.

Much of the material you’ll be asked to read/watch is online, via edX, LabXchange, and the PredictionX.org website.  Specific links will be provided as we go along.   Curious students can see sample material for edX (as featured on Mashable) here, on LabXchange here, and/or at at the PredictionX website.

ASSIGNMENTS AND GRADING PROCEDURES

Grading will use an unconventional system of “units” (converted to “points” on Canvas).  The ~ signs below indicate that the listed point values are approximate, in that certain assignments will be worth slightly more/less than average. The total number of units possible will be ~2500. (We use large numbers to ensure that “a few points off” never unintentionally has too large an impact.)

Here’s the approximate breakdown: Weekly homework requests, including incremental additions to Journals: ~100 units.  Prediction Journal and Final Predictive System project: 500 units each (total).  Class/section participation (including Forum posts): ~250 units total.  Movie watching (with written response)  “extra credit” 50 units/movie (2 movies for credit max).   Thus, credit awarded is proportional to the difficulty of assignments.  Please take note that a grade such as “140 out 150,” while 87%,  is not an "87” or a B+, it’s just 140 points toward your total in the class when you could have had 150.  Your grade for the full course  will be calculated “on a curve” using point totals.  Students who do very well will receive a flavor of A, and if the class does very well overall, there will (should!) be many As.  If you put full effort into the class and complete all assignments effectively, you can expect a B or better.  So, in summary, all students who attend class, participate fully, make good use of section time and office hours, and create a meaningful Prediction Journal and Final Predictive System Project should be able to receive a good grade.  

Details on grading policies

Harmonizing grades across sections/TFs:  When this class concludes, we will adjust scores issued  by  TFs to make the average (mean) and spread (dispersion) of grades given by each TF as similar as possible.  Even though students and TFs are given instructions on what each assignment requires, grading of anything other than multiple-choice exams always has a subjective component.  The end-of-term re-calibration should remove effects of small variations caused by multiple graders.

Late assignments: Deadlines are clearly specified on Canvas, and students should work to those deadlines.  In the unlikely event that a deadline is changed for everyone, a notification will be sent out. Barring changes, we will allow a 1-hour grace period past the deadline (with the caveat that no assignments can be turned in during class time unless explicitly requested for then), but beyond that, 10 units will be subtracted per day of lateness.  Requests for extensions may be granted at the discretion of your TF, as long as they are requested a day or more in advance.  Tardiness due to illness or other personal crises can be excused, with appropriate documentation, upon request to your TF.

Disputing a grade: Requests for re-grading should be made sparingly. We warn that a request for re-grading can cause grades to rise, or fall, so do not make such requests lightly.  TFs will need to seek permission from Prof. Goodman for re-grading if any student makes more than one such request.

Extra Credit: To reiterate, writing up comments on a prediction-relevant movie can earn you up to 50 units at any time.  Just submit your writeup on Canvas (see “Movie Response #1” and “Movie Response #2”).   You can do this up to twice during the course, for a total of 100 extra credit units. (But, of course, you may watch as many movies as you like!)  Suggested movie match-ups are listed on the schedule below, but feel free to choose any movie on this list, or suggest another film to any member of the staff for addition to the list.

ACADEMIC INTEGRITY

Collaboration is encouraged in this course.  That said, work you add to your Prediction Journals and Predictive System should be your own.   When you are explicitly asked to record work done in groups, as you will frequently be in class and in section, please remember to include the names of all group members (e.g. in a Google Doc or video you create).  As a reminder, the Harvard Honor Code is online for your reference.

In all formal assignments, including your Prediction Journals, Predictive Systems, as well as week-to-week requests, please CITE your sources according to these examples:

Traditional materials--The Modern Language Association citation format, or some similar variant of it, is fine. Here’s a page of examples.

Online material--as much like the following example as is feasible (allowing for the possibility that author names or publication dates may be missing)

Sample, Ian. “Astronomers discover huge gaseous wave holding Milky Way's newest stars,” TheGuardian.com,  The Guardian. Published 07 January  2020, online. Retrieved 24 January, 2020, from: <https://www.theguardian.com/science/2020/jan/07/astronomers-discover-huge-gaseous-wave-holding-milky-ways-newest-stars>. Format: text and graphics-based web page [or use instead, video, audio file, other media designation as-needed]

ACCOMMODATIONS FOR STUDENTS WITH DISABILITIES

Students needing academic adjustments or accommodations because of a documented disability must present their Faculty Letter from the Accessible Education Office (AEO) and speak with Prof. Goodman by the end of the second week of the term. All discussions will remain confidential.

Reading, media assignments, and journaling activities are to be done in advance of class for the week listed.

This “live” (evolving)  syllabus is meant as a guide to course content,  
while the GenEd 1112 Canvas site gives links to slides, handouts, and definitive details on assignments.
Anything in light  type is based on a prior version of the course, and will be updated as the semester proceeds.

Week 1  (1-26 and 1-28-21)

 TOPIC   What is Prediction? Why Predict?          CASE  Student Conceptions of Prediction

In class this first week, Prof. Goodman will tell the story of how she became interested in the past, present, and future of prediction.  Then, she will offer a presentation that introduces the course material, inspiring students to think about why, when, and how predictions are made. After these introductory remarks, we will collect and discuss student views on prediction, and discuss them in small groups and as a class. It’s likely that a range of opinion will emerge, guiding us toward an initial appreciation of one of this class’ core precepts: “Prediction” as a subject, is part art, part science, and as-such, there are often no purely “right” answers to questions about it.

Some sample motivating ideas and questions that will be covered in Week 1...
“Prediction” is a very common word in English, but what does it mean? Sure, most people will say “prediction” has something to do with the future-–but questions linger.  How far is this “future”?  Is testability required?  Is a prediction always part of a decision?  How is a decision different from a prediction?  Who really knows and doesn’t know the future? Why do we want to know? How can we know? How does prediction manifest in your everyday life? In society? Today? In the past? In the future?

We will also have a preliminary discussion of weather prediction, using takeasweater.com,  and we will take a look at some of the “Essentials” from PredictionX to be used in GenEd 1112, most importantly the “Framework” diagram. And, of course, we will have an overview of course logistics.

Week 2 (2-2 and 2-4-21)

 TOPIC   Conceptions of Time and Space          CASE  Ancient Predictive Systems

As we introduce some of the ancient predictive systems highlighted in PredictionX “Omens & Oracles,” we will contextualize them using the “Framework for Predictive Systems” developed as part of the PredictionX project.  (Small groups of students will apply the Framework to selected systems.)

We can think about our yearning to know what comes next in time as analogous to our wishes to see further in space. In Week 2, we will ponder this time-space parallel, and ask which aspects of predictive systems are common, uncommon, ancient, or modern, and which seem constant across cultures.  We will also consider what assumptions justify or underpin “non-scientific” systems.

We’ll also introduce the “free will vs. determinism” dichotomy--asking why some cultures believe(d) fate is written in advance, and others do not.   Students will begin to discuss how ideas around free will interact with predictive traditions.

By the end of the week, each student will choose one non-scientific predictive system, from the Diviner’s Guide, or other (e.g. see long Wikipedia list of “Methods of Divination,”) to research and present at our first “Fair,” in-class, during Week 3.

Week 3 section: Discuss student prediction journals, substance and OneNote issues, also look into astrology & tarot.

Week 3 (2-9 and 2-11-21)

 TOPIC   Free Will & Determinism                   CASE  Ancient Predictive Systems Fair

SPECIAL EVENT: PREDICTIVE SYSTEMS FAIR on February 11, 2021

Drawing upon some of the material in both Cross-Cultural Conversations material on edX in the “Lathe of Laplace” reading, we will  discuss the dichotomy of  “free will & determinism” as it relates to predictive systems. For most of the class time, we will hold a Predictive Systems Fair, as described under the Week 3 Assignments on Canvas. 

Week 4 Section notes: Learn the Physics behind Newton’s Laws of Gravity, and several of the other ideas that prove critical to the Path to Newton.

Especially for Week 4 and beyond, please consider materials posted to Canvas as the up-to-date version of this Syllabus.  All slides and handouts are in the “Files” tab, and all readings and assignments are under “Assignments.” Also, “Modules” organize materials week-by-week.
We also update this Google Doc version as time permits, but do refer to Canvas for the active syllabus .

Week 4 (2-16 and 2-18-21)

 TOPIC   From Phenomenon to Theory         CASE  The Path to Newton, Darwin & AI

Bridge between Ancient and Rise of Theory

Big picture:

- Assumptions about the world changed with ways of measuring/thinking about the world

- Different assumptions evolved with different predictive systems

- This happened slowly! (against idea of sudden revolution)

Movies: Cosmos Newton/Halley Episode; maybe also Galileo video? (optional on Evolution, this NOVA episode on how Darwinian Evolution works,

Books: The House of Wisdom by Jim Al Khalili, To Explain the World by Steven Weinberg, The Gene: An Intimate History by Mukherjee

Week 5 (2-23 and 2-25-21)

 TOPIC  Origins of Scientific Prediction         CASE  The Path to Newton Fair

SPECIAL EVENT: PATH TO DARWIN FAIR on February 23 & 25, and March 2, 2021

Smaller picture:

- Truly predictive system (opposed to empirically derived)

- Individual contributions to history of ideas

- Importance of specific ideas and theories along Path

- Importance of specific instruments to progress along the Path and correlations to ideas and theories

- Extrapolation to future (eg genome sequences)

Books: To Explain the World: The History of Modern Science by Steven Weinberg; The Pursuit of Destiny, Paul Halpern

Week 6 (3-2 and 3-4-21)

 TOPIC  Navigation as Prediction                 CASE  Lost without Longitude

SPECIAL EVENT: OUTDOOR NAVIGATION EXERCISE as an ASSIGNMENT

- Particular instance of predictive theory (idea of lunars) but not enough data + precision in instruments

- UNCERTAINTY

- Interaction between development of technology and uncertainty

- How models (e.g. celestial sphere) can be 'true enough' to make meaningful predictions

Week 7 (3-9 and 3-11-21)

 TOPIC   Health                                 CASE  John Snow & Cholera

Bridge between Rise of Theory and Modern Simulation

- Advent of modern epidemiology

- Use of visualization to make predictions about health/disease

- Visualization as representation/ exemplification

Week 8 (3-18 and 3-23-21)

 TOPIC    Earth                                 CASE  Weather and Climate

- What does uncertainty in weather forecasting show about climate change?

- What contributes to people's/ organizations' decisions regarding long term predictions like climate change?

- How are climate simulations created and what do they show?

- What does uncertainty in weather forecasting show about climate change?

- What contributes to people's/ organizations' decisions regarding long term predictions like climate change?

- How are climate simulations created and what do they show?

Week 9 (3-25 and 3-30-21)

 TOPIC   Modern Data Science                  CASE  Personal Health and Behavior

Movie: Minority Report

Week 10 (4-1 and 4-6-21) --NOTE: Special Event on 4/1--Health & AI “at” Radcliffe--Details to come

 TOPIC   Wealth                           CASE  Personal & Global Finance

- Connection between climate and finance

- Complexity of social systems/ complexity theory

- Can economics be considered science?

Movie: The Big Short

Week 11 (4-8 and 4-13-21)

 TOPIC  Space                                 CASE  Astrophysical Simulation & SETI

- Simulation on timescales we can't observe

- Are we alone? Drake Equation (astronomy => astrophysics => exoplanets as example of technologies influencing uncertainty influencing prediction parameters)

- Cosmic Evolution

Week 12 (4-20 and 4-22-21)

 TOPIC  Hypothesis-free Prediction?         CASE  AI/Machine Learning

- How are computers used to make predictions?

- What is machine learning?

- What is intelligence and can computers have it?

(highlight  Brendan Meade interview)

Concluding Meetings (4-27 and 4-29-21)

 TOPIC   The Future of the Future           CASE  Integration: Health, Wealth, Earth, Space

- Student conceptions about future, esp. in relation to beginning of class

- What is Prediction?

- How do modern predictive systems interact?

About the final “Predictive System” project

In short, your instructions will be: Carry out a study of a particular type of predictive system, with special attention to how accurate it should be, how uncertainty is measured, and how uncertainty about it is communicated.  In particular, find a way to study its accuracy on your own, either with new analysis, or from the literature.  In the end, you will create an online interactive and/or video summary of your findings, with accompanying text and graphics.  A list of suggested systems to study will be provided--but, alternatively,  you will be allowed to suggest a system for study on your own, or even invent your own predictive system.  In all cases, the system you choose will need to be approved by the Teaching Staff before you begin work.  A more detailed version of these project instructions will be posted to Canvas in March, 2021.