Class 3 – Social Psychology & Personality Heterogeneity

1. Social Networks, Social Norms, and Behavioral AnalysisLior Strahilevitz , University of Chicago Law School Class 3 – Social Psychology & Personality Heterogeneity

2. Course OVErview • Monday’s lecture: The Rational Actor Model and Its Complications – How does classical economics assume people will behave and how consistent are these assumptions with laboratory and real-world observations? • Yesterday’s lecture: Law & Social Norms – What role do informal social norms play in supplementing formal law? Are such norms efficient? How are they enforced? When should we expect to see more / less formality? • Today’s lecture: Social Psychology & Personality Heterogeneity – Do people have similar or dissimilar personalities and dispositions? Can variation be understood in a systematic way? How might law be tailored in light of personality heterogeneity? • Thursday’s lecture: Social Network Theory – How does information flow among people and within organizations? Is information transmission predictable? What are the economic consequences of particular pathways for information to flow? • Friday lecture: Legal applications – How might behavioral law & economics influence regulatory policy? How do social norms incentivize the creation of intellectual property? Can personality explain variation in the way judges think about criminal procedure? Can social network theory explain and rationalize information privacy law? Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

3. A clarification or two • My lists of other suggested readings are not meant to be exhaustive. There are many great scholars whose work you should read, and my goal is to give you a few places to start. Also, I am emphasizing legal scholarship whenever possible. If I omit something from my slides, that does not mean you should not read it. (And, of course, my domain is exclusively English language sources). • I have presented some conflicting work over the last few days and will present more of it today. We should try to be Bayesians -- take all the existing social science research into account and update our beliefs as new information comes to light. Some of the issues I am covering are ones about which there is no consensus. So you might see me present problems with a rational actor model on day one, and use a rational actor model (e.g., Eric Posner) on day two. • The Digman reading for today provides a nice overview of the Big Five / Five-Factor Model. It’s not path-breaking scholarship in its own right, so we won’t spend much time on it today in the lecture, but I’ll emphasize some core concepts covered in it. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

4. heterogeneity • People have not only different preferences but also different frameworks for sorting out those preferences. • Some care a great deal about their absolute wealth and others care a great deal about their relative wealth. • Some are very altruistic and others are not at all altruistic. • Some are very susceptible to biases like the availability heuristic or loss aversion and others are not. • Some are naturally talented at a particular task or take innate pleasure in doing a particular task and others are not and do not. • Today’s lecture will highlight one very important aspect of interpersonal heterogeneity: personality heterogeneity Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

5. Big Five / five factor analysis Systematizing personality heterogeneity • Five factors largely explain human psychological orientations Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

6. These factors operate in different dimensions Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

7. Each of the big five has component subfactors Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

8. How are individuals’ big five scores determined? Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

9. Survey instruments: have to rely on self reports (at least initially) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

10. Test your own personality • http://www.outofservice.com/bigfive/ (A free, anonymous Big-Five test administered by Professor John P. Oliver at the University of California Berkeley Psychology Department) • There are surely many online tests in other languages. If you care about your own privacy be cautious about using online tests that may ask for your identity or be able to determine it based on tracking your web activity. You can also use a library / Internet cafe computer (not your own) and provide inaccurate information to age and other demographic questions. • Once you know your personality (or someone else’s) what can you do with it? In other words, why is this a useful tool? • It is a useful tool because it predicts future behavior. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

11. The big five’s predictive abilities • SampoPaunonen, Big Five Factors of Personality and Replicated Predictions of Behavior, 84 J. Personality & Soc. Psych. 411 (2003). • Different tests (i.e., verbal versus non-verbal) tend to produce highly correlated results • Reviews the literature, but a host of different articles do the same, tying personality scores on Big Five tests to other sorts of behavior (e.g., success as managers within firms, propensity to become a politician or bureaucrat, penchant for sharing personal information on social networks, attrition rate for workers at firms, etc.) • Sometimes components of the Big Five (subfactors) predict a future behavior better than the aggregated Big Five metric. Extraversion combines different attributes like spontaneity, energy, talkativeness, indiscretion, etc. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

12. The big five’s predictive abilities (Continued) • Academic performance: Predicted by Conscientiousness • Intelligence: Predicted by Openness (positive) and neuroticism (negative) • Alcohol Consumption: Predicted by Extraversion (positive) and conscientiousness (negative) • Tobacco Consumption: Predicted by Agreeableness (negative) • Party Attendance: Strongly predicted by Extraversion (positive) • Plays Musical Instrument: Predicted by Openness (positive) • Regularly Exercises: Predicted by Extraversion (positive) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

13. But what if people are mischaracterizing their behavior? • Paunonen runs a series of tests where subject’s characterizations of their own behavior are tested against their peers’ characterizations of the subjects’ behavior • Ask Smith: “Do you smoke?” • Ask Smith’s university roommate: “Does Smith smoke?” • Correlation of Smith’s answer and Smith’s roommate’s answer = .92 • Ask Smith: “How popular are you?” • Ask Smith’s roommate: “How popular is Smith?” • Correlation of Smith’s answer and Smith’s roommate’s answer = .21 (still pretty good for social science, but self-assessment is much less reliable – and of course roommate responses do not represent “the truth” either) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

14. Selected correlation coeffecients between subject response and roommate’s response Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

15. Longitudinal studies of personality • Stephen Soldz & George E. Vaillant, The Big Five Personality Traits and the Life Course: A 45-Year Longitudinal Study, 33 J. Research in Personality 208 (1999). • Assess personalities of 163 Harvard University students, mostly at age of 21 (using metric developed prior to Big Five, but which could be subsequently coded into Big Five categories) and tracks them over the next 45 years. • Finds personality scores are consistent across these time periods, with the strongest correlations found in Neuroticism (.20 – significant), Extraversion (.19 – significant), and Openness (.38 – very highly significant). Correlations in Agreeableness (.07) and Conscientiousness (.12) are not significant. Study biased against result because Big Five tests not administered at beginning of study period. • Strong correlations between personality at age 21 and various life course variables, such as: High income & Extraversion (.22), Smoking & Neuroticism (.21) / Conscientiousness (-.16), Creativity & Openness (.40) / Agreeableness (-.27), Conservative Political Attitudes & Extraversion (.22) / Openness (-.39) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

16. More Longitudinal analysis, differing results • Sarah E. Hampson& Lewis R. Goldberg, A First Large Cohort Study of Personality Trait Stability over 40 Years Between Elementary School and Midlife, 91 J. Personality & Social Psych. 763 (2006). • Longitudinal study based on elementary school teacher assessments and self-reports 40 years later during midlife. Finds highest correlations for Extraversion (.29) and Conscientiousness (.25), then Openness (.16), Agreeableness (.08), and Neuroticism (.00). (Note contrast with previous study, especially on Agreeableness and Neuroticism – stability may differ between different parts of life cycle). • Johanna Rentanen et al., Long-Term Stability in the Big Five Personality Traits in Adulthood, 48 Scandanavian J. of Psychology 511 (2007). • Tracks personality stability in mid-adulthood from ages 33 to 42. Very high correlations across this time period: • Neuroticism (.81 for men; .65 for women) • Extraversion (.97 for men; .76 for women) • Openness (.90 for men; .95 for women) • Agreeableness (.83 for men; .85 for women) • Conscientiousness (.73 for men; .66 for women) • Over all Big Five (.85 for men; .78 for women) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

17. Are there national differences in personality? David P. Schmitt et al., The Geographic Distribution of Big Five Personality Traits: Patterns and Profiles of Human Self-Description Across 56 Nations, 38 J. Cross-Cultural Psychology 173 (2007) (means, based largely on college student surveys). Note that rates of college attendance differ dramatically in these countries. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

18. Big Data (Data mining + Analytics): The New Frontier in Assessing Personality Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

19. Using observed behavior & Big DatA to assess personality - smartphones • Gokul Chittaranjan et al., Mining Large-Scale Smartphone Data for Personality Studies, 15 Personal Ubiquitous Computing 1 (December 2011). • Analyze smartphone data to identify individuals’ personality traits • Extraverts receive more calls, spend more time on phone • Agreeable women receive more calls; Agreeable men communicate with more unique contacts • Conscientious people use email app more • Neurotic individuals received fewer incoming SMS messages • People with high Openness scores used non-standard ring tones and made greater use of video & music smartphone apps Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

20. Using observed behavior & Big DatA to assess personality – social networks • YoramBachrach et al., Personality and Patterns of Facebook Usage, WebSci 2012 Conference Paper. • Extraversion – lots of status updates, more interactions, more friends • Agreeableness – tagged more frequently in photos • Neuroticism, Openness – lots of “Likes” on Facebook • Predictive personality testing via Big Data: Model predicts Extraversion with r-squared of .33, Neuroticism with r-squared of .26 Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

21. Reasonable technological assumptions • Big Data is here (in the U.S) to stay and is likely coming to China; the trend has its own economic momentum. • There are partial psychological explanations for this: people who devalue own privacy (Extraverts) likely to vote & get involved in political process. Politicians in democracies tend to be Extraverts too. See Lior Jacob Strahilevitz, Toward a Positive Theory of Privacy Law, 126 Harvard Law Review 2010 (2013). • Early Big Data often identified stimuli that could predict future behavior (e.g., Target’s early warnings for pregnancy) • Transitional Big Data identified correlations that likely had personality as omitted variable (e.g., felt pad purchases and credit card delinquencies) • Mature Big Data identifies regularities in the personalities of individuals; personality in turn predicts future behavior. Big Data = administering personality tests to large numbers of people, possibly without their knowledge or consent. Tests use revealed preferences, so more reliable. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

22. Important caveats • Note that the Big Five is not the only personality scale; there are many others. But it is the one with the longest track record and the richest, best-developed academic literature. • Caution is always warranted about causal inferences. Salient life events (e.g., incarceration, death of spouse, child abuse, education) can permanently change personality. • Significant correlations between Big 5 personality measures and behavior are often in the .20 to .35 range (though sub-factors often do better). Accounting for 20-35% of the variation in behavior is a significant accomplishment, but one has to remember that much of human behavior remains unexplained by existing personality metrics. • The Big Five / Big Data nexus literature is very new, with just a handful of papers having appeared to date. Much of the research is secret / proprietary. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

23. Next UP: Porat & StrahilevitzNow: Questions on the Big Five ? Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

24. Applying Personality insights to legal problems : Personalization • Ariel Porat & Lior Jacob Strahilevitz, Personalizing Default Rules and Disclosure with Big Data, 112 Michigan Law Review ___ (forthcoming 2014). • In Progress (Comments & Criticism Welcome! – Lots of our arguments may be wrong.) • Default Rule = Term that the law reads into a contract or will if the document itself is silent or ambiguous. By definition, defaults can be waived by contract. Parties can always specify a different provision via the document itself. • Disclosure = Information disclosed by firm or government to enable third parties to make sensible decisions about products, services, risks, etc. • Propose an alternative to Majoritarian Default Rules and Ayres & Gertner’s Penalty Default Rules (99 Yale L.J. 87 (1989)). Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

25. Depersonalized law • Married fathers more likely than married mothers to bequeath all their property to their spouse (55 percent compared to 34 percent) • Men bequeath 80 percent of estates to widows but women bequeath 40 percent of estates to widowers • Nevertheless, the laws of intestacy (default rules for wills) does not differentiate between male and female testators; one-size-fits-all rule • Crude Personalization: Most people die without wills. The Law of Intestacy could treat men and women differently, with larger shares of estate given to widows than to widowers in cases where decedent has left no will. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

26. Fine-grained personalization • Gender is just one factor that influences preferences about one’s estate. There may be lots of others – size of estate, widow/er’s income, children from prior marriages, strength of bonds between widow/er and decedent • Some of these factors are discernible through public records; others via data mining private records • Law should identify regularities in preferences among decedents and provide individuals with will terms chosen by “people just like them” • Many trusts & estates lawyers do personalization of this sort already, albeit in a non-data-driven way • Substantial savings on transaction costs of drafting and executing wills Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

27. Broader proposal: personalized default rules • Compensate a subpopulation of “Guinea Pigs” (human research subjects) for permission to analyze their private information and preferences with respect to contractual provisions • Assign to every individual the default terms chosen by the Guinea Pigs most similar to them; make these available to consumer at the point of sale / contracting so consumer can modify them if s/he wishes • Test to see whether personality factors predict preferences for different default terms • Do groups with common personalities systematically value specific performance, rather than damages, highly? • Are particular types of people more likely to accede to arbitration for dispute resolution? • Should labor entities in which Extraverted & Neurotic workers are overrepresented be unionized by default? • Are there personality correlates with high- or low-levels of privacy concern, such that different people may be given different privacy settings by default? Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

28. Some objections to the personalization of default rules • Cross Subsidies • There are cross subsidies either way, with personalization or without it. • Strategic Behavior • Personalization & transparency are hard to combine • Uncertainty • Consumer already has lots of self-knowledge, helps predict content of personalized rules • Personalized Disclosures help • Subordination & Adaptive Preferences • Reject purely majoritarian default rules sometimes (e.g., marital name change default with gender as only variable) • Complex formulas may be less problematic than crude stereotypes • Control the Guinea Pigs, Control the World • Need independent government / academic presence to control manipulation • Privacy • Personalization of defaults wouldn’t drive Big Data • Approach permits sorting of population with pluralistic preferences with regard to privacy. • People Change • Defaults are waivable, Personalization is itself a default; and people tend not to change much over the course of a decade but change more over the course of a life-cycle (recall longitudinal studies) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

29. Impersonal disclosure Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

30. We propose personalized disclosure • Impersonal Disclosure -> Warnings Ignored. Too much disclosure is costly & self-defeating. Omri Ben-Shahar has written and lectured about this persuasively. • Personalized Disclosure based on what “People Like You” found salient can increase relevance of disclosure, cause people to pay attention • Checkout line warnings: Peanut-allergic shopper might be asked “Are You Sure?” about purchase of allergen-heavy product • Warning labels are twentieth century technology; smartphone shopping can facilitate personalized disclosure • Personalized disclosure can facilitate personalized default rules – disclose the defaults likely to be controversial • Specific proposal: We discuss whether FICO Adherence Scores should be used to define baseline requirements for informed consent. Patients with different likelihood of following doctor’s instructions will encounter different risks and therefore might receive different, personalized disclosures. May enhance health, especially with psychosomatic conditions Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

31. Personalized disclosure by the government • EPA air-quality warnings targeted only to vulnerable populations • Traffic hazard warnings only to people with particular commuting patterns, or whose personality profiles indicate likelihood of aggressive response to driving on highly congested roadways • Tailored warnings about military service at time of enlistment, based on personality • Personalized disclosure of risks associated with educational, mortgage & other types of borrowing • Information now available from the government (if at all) only if a consumer / citizen requests it; we propose that the government push this information to those consumers likely to find it relevant. Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

32. Synthesis – how does the big five relate to what we covered earlier in the week? • Recall the discussion of bounded self-interest. People are heterogeneous with respect to this attribute. Might Agreeableness predict differential responses in experiments? • Recall the discussion of cheating. It suggested that small-scale cheating was relatively common, but it’s not uniform. Might Conscientiousness help explain the extent of cheating? Are Extraverts more likely to cheat when the spoils are split? • Recall the problem of social norm enforcement. Some people are more willing than others to enforce these norms than others. Might Conscientiousness and Extraversion differentiate enforcers from non-enforcers? • Recall the problem of social norm change. Some people are very resistant to adopting new norms but others are relatively willing to do so. Openness to New Experiences could well predict this sort of behavior. • Scholars aren’t presently asking these kinds of questions. The literatures I’m presenting to you are not unified. Economists and Psychologists are using different methodologies. Personality isn’t the solution to all these questions, but it may be a way to make progress. • Almost no legal scholars are using personality in a sophisticated way to inform legal scholarship. There is a great deal of “low-hanging fruit.” Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

33. Problematic domains for profiling • Big Five Factors associated with criminal convictions and recidivism (repeat offenses) • See Coleta van Dam et al., PEN, Big Five, Juvenile Delinquency and Criminal Recidivism, 39 Personality and Individual Differences 7 (2005). • Comapares Dutch juvenile offenders, repeat-offenders, non-repeat offenders, and college students • Offenders relatively low on Agreeableness and Openness (highly significant) • Repeat offenders more Neurotic and Less Aggreeable than Non-repeat offenders (highly significant) • Application to criminal law & policy should be extremely controversial • Literature is tiny, differences are significant but often not enormous in magnitude, self-reports of offenders may be especially suspect, great potential for stigmatization and incorrect / offensive use (note that 50% of personality is genetically determined according to Digman at 432). But given what governments are doing with Big Data and surveillance, it wouldn’t shock me if these strategies are already being employed somewhere (e.g., early release decisions?) Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

34. Questions on personalization of default Rules and Disclosures ? Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics

35. The end Professor Lior Strahilevitz, University of Chicago Law School 2013 Summer School in Law & Economics