TuTh 5:00-6:20 |
WARREN Lecture Hall |
2113 |
Office Hours: T 11:00-12:00
Th 2:00- 3:00 or by appointment
SSB 488
Email: aronatas@ucsd.edu
Predicting the Future: From Tarot Cards to Algorithms
A Sociological Introduction
No one can see the future, but everyone must try. We must predict the future every day. We brush teeth predicting fewer cavities, buy ice cream expecting to eat it, choose spouse anticipating happiness. College students choose majors and take classes with an eye on their future career. Loan clerks, college admission officers, stockbrokers, and parole boards and many others predict for a living, betting on future outcomes. Most classes are about the past or the present. In this class, we look at ways people try to peek into the future.
For most classes there will be required readings, all are on ereserves or linked in the syllabus, except the only book you need to read: Yuval Harari’s Homo Deus that you can buy on Amazon. It is a fun book but a long one, so start reading it well in advance of December when we discuss it. Be prepared to discuss the readings in class. You will also need two chapters of Orrell’s book, The Future of Everything. I recommend you buy it. It is a great book.
There are also two movies you have to watch: The Minority Report (2002) by Steven Spielberg (2 hours and 26 minutes), and Blade Runner (1982) by Ridley Scott (1 hour 57 min). This is the original version not the sequel. Both you can stream through e-reserves.
To access the articles off campus or the movies, you need to use a VPN. Here is
the necessary info:
https://blink.ucsd.edu/technology/network/connections/off-campus/VPN/
Finally, there is one podcast you must listen to, The Sorting Hat, an episode of Hidden Brain by Shankar Vedantam (51 min). You must do the readings, the listening and watch the films before the date they appear on the syllabus. (Further readings or listenings are optional.)
This is a small class, and I expect you to attend all classes and to participate actively. You can miss one class without excuse.
You will have three simple tasks spread through the quarter:
Task 1. Make predictions (see list)
Task 2. Find your horoscope read it and bring it to class
Task 3. Retrieve your free credit bureau report
You will participate in one of three debates with two or three other students as a team. (In the other two debates you will be a member of the audience, and will have lighter duties.) You can divide the work on your team as you see fit, but I expect every member to be equally involved. Two teams will debate the following propositions:
Debate 1. People should never be held criminally liable for predictions.
Debate 2. We should do predictive policing.
Debate 3. We should make important decisions always using algorithms rather than human judgment whenever that is possible.
The rules of the debate will be as follows. One team will argue for (Affirmative Team or AT), the other against the proposition (Negative Team or NT) but which team gets which side will be determined by a coin toss moments before the debate, so you and your team must prepare to argue both for and against. Your team will have to do your own research.
Round 1. The debate will start with the statement of the AT, followed by a statement by the NT, five minutes each. (10 min)
Round 2. The two teams rebut the other’s points. Starting with NT, the two teams take turns. Each will have three turns and each turn will be 2 minutes. Up to 1 minute for the question and the rest for the answer. (2x3x2=12 min)
Round 3. Questions from the audience and me to each team. (18 min)
Everyone (team members and audience members) vote on the proposition through Canvas before the class where the proposition is debated. At the end of the debate, the audience votes again on the proposition and on who won the debate again, using Canvas. The whole debate (with transitions) will take about 45 minutes.
You will have to sign up for a debate by October 3.
There is a short midterm. You will be given 4 questions about the readings from which you choose three to answer. (If you answer all four, I will count the best three.) You will need a blue book.
There is a final paper that should be 6-10 pages long. You can use 1.5 lines paragraphs and 12 point fonts. It should have a reference section that does not count towards the page count.
You can choose from the following topics:
The paper should present a clear argument supported by facts and scholarly literature on the topic. The paper must start with an Abstract, which is a short summary of the main argument in your paper (about 150 words). You need at least 5 scholarly references (academic articles or books) listed at the end of the paper (called Reference section). Use the MLA format. You will submit a first draft by November 26 11:59 pm and the final version by December 13, 9:59 pm through Turnitin on Canvas. The paper must be entirely your own work. Plagiarism is a serious violation of university rules so is purchasing papers, or getting someone to write your paper as a favor. You must see me to discuss the paper at a scheduled appointment during the week of November 11-15. Of course, you are welcome to see me at other times as well.
There will be three pop quizzes on the readings up to that point. Simple questions to check if you did the readings or watched the movies at all. The best two of the three will be counted in your grade.
Your grade will be determined as follows:
Tasks (3 @4% each) 12% (you get full credit for doing them on time)
Debate 20% (you can get full credit even if your team
loses the debate)
Pop quizzes (best 2 of 3, 4% each) 8%
Midterm 15%
Final paper 30%
Class participation 15%
I predict that anyone who takes the course seriously, engages with the material actively and plays by the rules will get a B or better.
A). The value of Tesla stock at market close on December 2, 2019.
B). The grade you will get in this class.
C). If there will be rain on campus on our last day of classes (December
5, 2019).
D). The probability that you will ever meet your perfect soulmate. [Give
a number between 0 and 100]
E). If something will happen that will have a major impact on the history
of the United States this November.
Past, present, future
Speed of time
Why the future is different from the past and present
Can we imagine a world with change but without a future?
Illusion of hindsight
Sam Woolfe. Presentism and Eternalism: Two Philosophical Theories About Time.
https://www.samwoolfe.com/2013/05/presentism-and-eternalism-two.html
Kristie Miller. 2013. Presentism, Eternalism and the Growing Block. In Heather Dyke and Adrian Bardon. A Companion to the Philosophy of Time.
https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118522097.ch21
Adam, Barbara, 2010, History of the future: Paradoxes and challenges, Rethinking
History, 14:3, 361-378
Further Reading:
Watts, Duncan J. 2011. Everything is Obvious. Once You Know the Answer. Crown
Press. Chapters 5-7.
What is randomness?
Cognitive control
Tarot cards, Tea Leaves, Astrology, Dreams
Whitson, Jennifer A. and Adam D. Galinsky. “Lacking Control Increases Illusory
Pattern Perception.” Science 322, 115 (2008) (online version at
http://www.sciencemag.org/content/322/5898/115.full.pdf
)
Damisch, Lysann, Barbara Stoberock and Thomas Mussweiler.
2010. ”Keep Your Fingers Crossed!: How Superstition Improves Performance.”
Psychological Science, 21(7) 1014
–1020 (online version at
http://pss.sagepub.com/content/21/7/1014
)
Further Reading:
Here is a nice blog by Ed Yong explaining these issues to a wider audience:
http://scienceblogs.com/notrocketscience/2008/12/27/lacking-control-drives-false-conclusions-conspiracy-theories/
Tiresias in Homer’s Odyssey
Augurs of Delphi
Religious prophets
Secular prophets
Schutz, Alfred,
1959, Tiresias or Our Knowledge of
the Future. Social Research, Vol.
26, No. 1 (SPRING 1959), pp. 71-89
Dawson, Lorne L.
1999. When Prophecy Fails and Faith Persists: A Theoretical Overview.
Nova Religio: The Journal of Alternative
and Emergent Religions, Vol. 3, No. 1, pp. 60-82
Balch, Robert W.
and David Taylor. 1977. Seekers and Saucers. The Role of the Cultic Milieu in
Joining a UFO cult. American Behavioral
Scientist
Forecasting Earthquakes, Weather and Climate Change
Cartlidge, Edwin. 2011. “Quake Experts to Be Tried for Manslaughter.”
Science 332 (6034) :1135–1136
http://brightmouse.org/AmericanLandscape/wp-content/uploads/2011/06/1135.full_.pdf
Further reading:
Orrell, David. 2007. The Future of
Everything. Thunder’s Mouth Press
International Commission on Earthquake Forecasting for Civil Protection. 2011.
Operational Earthquake Forecasting. State of Knowledge and Guidelines for
Utilization. Annals of Geophysics,
54, 4, pp. 319-391. https://www.annalsofgeophysics.eu/index.php/annals/article/viewFile/5350/5371
How doctors make prognoses
Kondziolka, Douglas et al. 2014.
The accuracy of predicting survival in individual patients with cancer.
Journal of
Neurosurgery,
120:24–30
Orrell, David. The Future of Everything. Chapter 5. It’s in the Genes. Pp.
174-217
Further reading:
Christakis, Nicholas A. 1999. Death Foretold. Prophecy and Prognosis in Medical
Care.
Film: Blade Runner
Scherker, Amanda. 2014. “11 Visions of the Future That Were Utterly Wrong.”
Huffington Post, January 3
http://www.huffingtonpost.com/2014/01/03/visions-of-the-future_n_4520597.html?ir=World
Davis, Lauren. How Our Predictions for the Year 2000 Changed Throughout the 20th
Century.”
http://io9.com/5908600/how-our-predictions-for-the-year-2000-changed-throughout-the-20th-century
When things don’t change much
David, Paul A. "Clio and the Economics of QWERTY." The
American economic review 75.2
(1985): 332-337. JSTOR
http://www.jstor.org/stable/1805621
Stan J. Liebowitz and Stephen E. Margolis. 1990.
Fable of the Keys. Journal of Law and Economics, 33/1:1-25.
Arthur, W. Brian. 1990. "Positive Feedbacks in the Economy." Scientific
American, February
https://www.jstor.org/stable/pdf/24996687.pdf
Predicting the outcome of a large number of people’s actions
Traffic
Demography
Economy (prophets and profits)
Elections
Congressional Budget Office. 2013.
CBO's Economic Forecasting Record: 2013 Update. January 17.
http://www.cbo.gov/publication/43846
Homa, Ken. Nums: Why’s the Fed so bad at forecasting?
http://kenhoma.wordpress.com/2013/06/24/nums-whys-the-fed-so-bad-at-forecasting/
Further Reading:
Tetlock, Philip. 2006. Expert Political Judgment. How Good Is It? How Can We
Know? Princeton University Press
Stabilizing who you are
Sorting people by future potential
Sorting Hat. Hidden Brain Podcast by Shankar Vedantam.
https://www.npr.org/templates/transcript/transcript.php?storyId=568418089
Further reading:
Fourcade, Marion and Kieran Healy. 2013. Classification situations: Life-chances
in the neoliberal era. Accounting,
Organizations and Society, 38, pp. 559-572
Estimating future academic performance
Guessing who will default and who will pay up
https://www.annualcreditreport.com/cra/index.jsp
Rona-Tas,
Akos. 2017. “Off-label
Use of Consumer Credit Ratings”, Historical Social Research,
Preventing crime: policing, sentencing and parole
ProPublica. Machine Bias.
https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
Further readings:
Harcourt, Bernard E. 2007. Against Prediction. Profiling, Policing and Punishing
in an Actuarial Age. University of Chicago Press
DURING THE WEEK OF NOVEMBER 11-15 YOU HAVE TO
SIGN UP FOR A MEETING WITH ME TO DISCUSS YOUR FINAL PAPER
How good are experts at predicting in their area expertise?
Expert judgment vs. statistical calculation
Heuristics vs. algorithms
Dawes, Robyn M., David Faust, and Paul E. Meehl.
1989, "Clinical versus actuarial judgment." Science 243.4899 :
1668-1674.
http://apsychoserver.psych.arizona.edu/JJBAReprints/PSYC621/Dawes_Faust_Meehl_Clinical_vs_actuarial_assessments_1989.pdf
Webb, Amy. 2017. The Flare and Focus of Successful Futurists. MIT Sloan Review
of Management
https://ilp.mit.edu/media/news_articles/smr/2017/58412.pdf
Further Reading:
Tetlock, Philip and Dan Gardener. 2015.
Superforecasting. The Art and Science of Prediction. Crown Publisher
Gigerenzer, Gerd. 2007. Gut Feelings: The Intelligence
of the Unconscious. Viking
Privacy and prediction
Does Google and Facebook know you better than you know yourself?
Kerr, Ian and Jessica Earle. 2013. Prediction, Preemption and Presumption. How
Big Data Threatens Big Picture Privacy. Stanford Law Review, September 3
http://www.stanfordlawreview.org/online/privacy-and-big-data/prediction-preemption-presumption
Further listening:
The Privacy Paradox. Note to Self podcast
https://project.wnyc.org/privacy-paradox/
THE FIRST DRAFT OF YOUR FINAL PAPER IS DUE
How predictable are humans?
Wakefield, Jane. 2011. When Algorithms Control the World.” BBC News, August 22,
http://www.bbc.co.uk/news/technology-14306146
Wang, Yilun and Michal Kosinski. 2017. Deep neural networks are more accurate than humans at detecting sexual orientation from facial image. Journal of Personality and Social Psychology. https://osf.io/hv28a/download/?format=pdf
November 28
Robert Merton. 1948. “The Self-Fulfilling Prophecy.” Antioch Review, 8/2
http://www.jstor.org/stable/40607393
Harari,Yuval. 2017. Homo Deus. A Brief History of Tomorrow. Harper 464 pages