SOC 165                                                                                             Prof. Akos Rona-Tas

TuTh  11:00-12:20

CENTR

224C

                                                                                   

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. (To read the linked ones, you may need to sign in with the UCSD Virtual Private Network. https://blink.ucsd.edu/technology/network/connections/off-campus/VPN/index.html .) 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). Both you can stream through e-reserves. 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 four simple tasks spread through the quarter:

Task 1. Make some predictions (see list)

Task 2. Find your horoscope read it and bring it to class

Task 3. To apply “Magic Sauce” to see what your Facebook of Twitter activities predict about you

Task 4. To retrieve your free credit bureau report

The Tasks will be listed under the Syllabus on TritonEd.

 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.

You can sign up for a Debate on TritonEd under Tools --> Groups.

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 TritonEd 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 TritonEd. The whole debate (with transitions) will take about 45 minutes and will happen in the second half of the class.

           There is a final paper that should be 6-10 pages. 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:

  1. Compare and contrast two types of predictions (e.g., predicting earthquakes vs. the stock market, outcomes of sport events vs. illnesses). What makes them different?  Which one is more likely to succeed and why?
  2. What is self-fulfilling and self-frustrating prophecy? How do they work? What would be good examples of each? Why do they end up with opposite results? Give examples and explain the mechanisms through which they work. Use examples from the scholarly literature.
  3. Sometimes wrong or unfounded beliefs about the future and prediction can be beneficial. How so? This can about excessive optimism/pessimism or about card, tea leaf, coffee grind reading, necromancy, astrology etc. (or both).
  4. Or you can propose a paper topic related to prediction.

The paper should present a clear argument supported by facts and scholarly literature on the topic. The paper must start with an Abstract, a short summary of the main argument in your paper (about 150 words). You need at least scholarly 5 references (academic articles or books) listed at the end of the paper (called Reference section). Use the MLA format. You submit the final paper through Turnitin on TritonEd. The paper must be entirely your own work. Plagiarism is a serious violation of university rules. You must see me at least once about your paper at my office hour.

The final paper is due on the Friday, 9 am (morning) of finals week (March 23). You may pre-submit your paper by Saturday noon, March 17. I will read it and either send it back with comments or offer you a grade with comments. If you got a grade and accept it, you are done. If you did not get a grade or you don’t like the grade you received, you can improve on the paper and turn it in by the original due date.

 There will be three pop quizzes on the readings up to that point. Simple questions to check if you did the readings or watch 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% each)                                  12%                 (you get full credit for doing them on time)

Debate                                                 30%                 (you can get full credit even if your team

loses the debate)

Pop quizzes (best 2 of 3, 4% each)       8%

Final paper                                          30%                

Class participation                               20%                

 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.  

SCHEDULE

The Big Questions

 

January 9       Introduction

 

TASK 1: Make Predictions in TritonEd.

            A). If Bitcoin will be over $20,000 on January 31.

B). The movie that will win Best Picture at the Oscars on March 4, 2018.

            C). The number of people indicted by Robert Mueller by March 15, 2018 through his investigation.

            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 February.

 

January 11     Time, Knowledge and Freedom

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

           

Required Reading:

Adam, Barbara, 2010, History of the future: Paradoxes and challenges, Rethinking History, 14:3, 361-378

Watts, Duncan J. 2011. Everything is Obvious. Once You Know the Answer. Crown Press. Chapters 5-7.

Further Reading:

Jens Beckert, 2016. Imagined Futures. Fictional Expectations and Capitalist Dynamics. Princeton University Press

 

The Curse and Use of Randomness

January 16     Randomness, Superstition and Control

 

TASK 2: Find your horoscope and bring it to class. Answer the questions on TritonEd.

 

            What is randomness?

            Cognitive control

Tarot cards, Tea Leaves, Astrology, Dreams

Required Reading:

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/

 

January 18     Prophets and prophecy

 

Tiresias in Homer’s Odyssey

Augurs of Delphi

Religious prophets

Secular prophets

           

Required Reading:

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

 

Same as It Ever Was: Predicting the Natural World

January 23         Laws of Nature

Forecasting Earthquakes, Weather and Climate Change

 

Required Reading:

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

Orrell, David. The Future of Everything. Chapter 4. Red Sky at Night. Pp.123-173.

 

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.    

 

January 25     No Class

Additional office hours are scheduled for January 22 and January 29 to discuss DEBATE 1-3.

January 30          Medical predictions: Genes and Diseases

            How doctors make prognoses

 

DEBATE 1: Peoples should never be held criminally liable for predictions.

 

Required Reading:

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.

 

Predicting the Social World

February 1     Imagining the World Many Years from Now

Film: Blade Runner

Required Reading:

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

 

February 6     Path Dependence: The Long Hand of History

            When things don’t change much

 

Required Reading:

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 8     Predicting Aggregate Behavior

Predicting the outcome of a large number of people’s actions

           

Traffic

            Demography

Economy (prophets and profits)

            Elections

 

Required Reading:

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

 

February 13       Sorting People: Personality and Intelligence Tests

            Sorting people by future potential

 

TASK 3. Apply Magic Sauce and answer the questions on TritonEd.

https://applymagicsauce.com/demo.html#_=_

 

Required listening:

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

 

Predicting What You Do

February 15        College Admission

            Estimating future academic performance

 

February 20     Applying for Credit

Guessing who will default and who will pay up

 

TASK 4. Retrieve your free credit record from one of the three credit agencies. Answer the questions on TritonEd.

https://www.annualcreditreport.com/cra/index.jsp

 

Required Reading:

Rona-Tas, Akos. 2017. “Off-label Use of Consumer Credit Rating’s”, Historical Social Research,

 

February 22       Predicting Future Crime

            Preventing crime: policing, sentencing and parole

 

Required Reading:

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

 

February 27 Film Minority Report

 

DEBATE 2: We should do predictive policing.

 

March 1          Expert Predictions

                How good are experts at predicting in their area expertise?

            Expert judgment vs. statistical calculation

            Heuristics vs. algorithms

Required Readings:

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

 

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

 

Sociology of the Future

March 6         The World of Big Data

            Privacy and prediction

            Does Google and Facebook know you better than you know yourself?

Required Reading:

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/

 

March 8          The Rule of Algorithms

How predictable are humans?

 

Required Reading:

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.

March 13     Predicting or Making It Happen?

                       

DEBATE 3: We should make important decisions always using algorithms rather than human judgment whenever that is possible.

 

Required Reading:

Robert Merton. 1948. “The Self-Fulfilling Prophecy.” Antioch Review, 8/2 http://www.jstor.org/stable/40607393

 

March 15    Review