1. Tales of Competing Altruists As told by… Ted Bergstrom, Rod Garrett, and Greg Leo UC Santa Barbara

2. A Dark Tale from the Big Apple

3. The Kitty Genovese Case In 1964, as she returned home from work late at night, Kitty Genovese was assaulted and murdered, near her apartment in Queens, New York City. According to a story in the New York Times – For more than half an hour, 38 respectable, law- abiding citzens in Queens watched a killer stalk and stab a woman in three separate attacks.... Not one person telephoned the police during the assault”

4. Pundits’ Reactions Pundits found this “emblematic of the callousness or apathy of life in big cities, particularly New York.” The incident was taken as evidence of ``moral decay’’ and of “dehumanization caused by the urban environment.”

5. In Defense of New Yorkers? Sociologists, John Darley and Bibb Latane suggested an alternative theory – City dwellers might not be “callous” or “dehumanized.” They know many are present and believe that it is likely that someone else will act. Darley and Latane called this the “bystander-effect.” They found this effect in lab experiments: Someone pretended to be in trouble, – When subjects believed nobody else could help, they did so with probability.8. – When they believed that 4 others observed the same events, they helped with probability.34.

6. Volunteer’s Dilemma Game Andreas Diekmann, a sociologist, created a game theoretic model, the “Volunteer’s Dilemma” N-player simultaneous move game: Strategies Act or Not. – All who act pay C. If at least one acts, those who acted get B-C.. Those who didn’t act get B. If nobody acts, all get 0. In symmetric mixed strategy Nash equilibrium, as N increases, it less likely that any one person calls. In fact, it is more likely that nobody calls.

7. Further defense of New Yorkers Less interesting for theory, but facts deserve respect. Fact-checkers later found the journalists’ story partly fabricated (albeit by NYC-based journalists). – No evidence that 38 people knew what was going on. It was 3 am on a cold night. Windows were closed. One person tried to help.

8. A larger question In Volunteer’s Dilemma game, despite technical increasing returns to scale, people are worse off belonging to larger groups than to smaller groups. Is this generally true? If so, this seems a serious disadvantage of urban life and large group formation in general.

9. The Volunteer’s Paradox In the volunteer’s dilemma, no matter how many people benefit from the helpful act, one person’s effort is sufficient. Thus we have very strong technical increasing returns to group size. Despite there returns to scale, the larger the group the worse off everyone is in Nash equilibrium.

10. Is the Volunteer’s Paradox robust to changes in these assumption? Simultaneous moves, no coordination Identical players

11. Coordinated Volunteers’ Dilemma Sometimes it is possible to organize volunteer work by asking for volunteers, then randomly select one volunteer to do the job. Probability that help arrives is higher than in uncoordinated Volunteers’ Dilemma But the probability that nobody takes action still increases with size of group. – Weesie and Franzen 1998 – Bergstrom 2012

12. First to offer does the job No problem of oversupply since players see if someone else has done it—but delay may be costly. Subway passenger offers a seat to old person. Rescuing a drowning swimmer. Audience member opens a window in a stuffy auditorium. Being first (shy) couple on the dance floor.

13. A traveler from Jerusalem to Jericho was robbed, beaten and left by the roadside, half dead. A priest came along and when he saw the victim, he passed by on the other side of the road. Another big shot came by and did the same thing. Then a Samaritan (a low status guy) arrived. He bound the victim’s wounds, brought him to an inn, and took care of him. Parable of the Good Samaritan (Short Version)

14. Updated Story You are Driving down a lonely road, you see a stalled car and a motorist who has run out of gas. You consider stopping to help, but realize this may cost you a good deal of time and some extra driving.

15. Two questions Might your decision be different if the road were more heavily travelled? If you were to run out of gas, would you prefer that it be on a busy highway, or a lonely road?

16. Road to Jericho (Model 1) Drivers pass stranded motorist at Poisson rate λ Passers-by sympathetic but stopping is costly (costs c). If you don’t stop, expected wait for motorist until next car comes is w=1/λ. Your psychic cost of having him wait this long is vw. You will stop if c<vw.

17. Will they stop? On sparsely traveled roads where λ c. But if λ>c/v, then there can not be a pure strategy equilibrium. – If everybody else stops, nobody would stop. If nobody else stops, everybody would stop. For λ>c/v, there is a mixed strategy equilibrium where drivers stop with probability p. Then expected waiting time is 1/pλ =v/c.

18. When is stranded traveler better off? (with identical motorists) On sparsely traveled roads, more traffic is better (because everyone will stop) On well-traveled roads, as traffic becomes denser, each motorist is less likely to stop, but expected waiting time for help diminishes with denser traffic.

19. What if sympathies or costs differ? In Good Samaritan story, maybe the priest and the Levite have important things to do and suspect that someone whose time is less valuable will come along.

20. Differing Sympathies and Incomplete information Suppose that stopping costs c and sympathies v vary in the population. Each motorist knows his/her own v and c, but only knows the probability distribution of these values for the motorists who follow. Then in equilibrium, it is always the case that with denser traffic, the stranded motorist has a shorter expected waiting time.

21. Differing Costs and Sympathies Volunteers’ Dilemma played by strangers Players know their own costs and benefits, but only know the distribution function of cost- benefit ratios of others. There is a symmetric equilibrium in pure strategies. Act if cost/benefit ratio is below some threshold.

22. Dragon-Slaying and Ballroom Dancing Bliss and Nalebuff (1984). Many couples want to dance. Nobody wants to be first. Some are more eager to get started than others. Game of attrition. As number get larger, expected waiting time to first dance could increase or decrease. But all have higher expected utility with larger numbers.

23. Maybe cities aren’t so bad. Volunteer’s paradox is not in general robust to – Information Structure (Road to Jericho) – Allowing for differences in costs and sympathies. (Road to Jericho, Dragon-Slaying and Ballroom Dancing)

24. A Brighter Tale

25. Stem cell donations Bone marrow or stem cell transplants dramatically improve survival prospects of people with leukemia and other blood diseases. For transplants to work, donor must be a genetic match for recipient. Only 30% of patients have matching sibling. Others must seek match in population at large.

26. The Bone Marrow Registry Six million Americans and 20 million people worldwide have offered to donate stem cells or bone marrow to save the life of a complete stranger. Bone marrow extraction is traditional method. Requires anesthesia and big needles. Newer method is stem cell extraction. Requires prior steroid injections, blood aphoresis. About as unpleasant as a case of the flu.

27. Bone Marrow registry Registrants promise to donate bone marrow or stem cells to any needy person if called upon to do so. (not a binding contract) Registry collects saliva sample, does a DNA test for HLA type and records registrant’s contact information.

28. Why such a large registry? There are about 20 million distinct types. Probability that two Americans of European descent are a match is 1/11,000. About half the Caucasian population are in types of frequency smaller than 1/100,000. About 20 per cent are in types of frequency smaller than 1/1,000,000. African-American types are even more diffuse.

29. Competing altruists? Only about 1% of those who join registry will ever be asked to donate. Most people are of relatively common types. If you are asked, the probability is about.9 that there was someone else in the registry of the same type who also could have been asked.

30. Registry appeal: They do not highlight probability that you may be the only one in the registry who can save a life. They say: If you register, you have a chance to “Be the Match that saves a life.”

32. Detecting Altruists’ Motivations by Experiment Usual game theoretic experiments – Try to induce known payoffs for subjects – Then see if subjects find their way to Nash Equilibrium assuming their motivations are the induced ones Not us. We want to find out motivations. We believe subjects bring to the lab the rules of behavior that they normally use in life and try to apply them in the proposed situation. We want to find out what motivations they bring to the lab.

33. Possible motivations Egoist Sympathetic consequentialist. “Do the right thing” ethic (deontologist) Impact philanthropist (wants to “Be the one.”)

34. First-to-help experiment A group of $N$ people. All but one are given $10, the other gets $0. All are told what happened and that anyone can give up $1 so that the unlucky person will get $9 instead of $0. The $1 will be taken from the first person to offer help. In separate treatments, $N$ ranges from 2 to 7. Donors and recipients are anonymous to each other.

35. Implementation Subjects sit at a computer screen and the game is explained. A time clock is shown and they can offer to help at any time during a 30 second interval. They can also press buttons – First Possible Moment – Last Possible Moment – Not at all

36. 123456 7 Number of Potential Donors 100% 80% 60% 40% 20% When they volunteer First Last Other No

37. Exploring Intentions After the experiment was run we interviewed participants. We asked those who volunteered at some time – ``If someone else is willing to give would you rather we take from you or from someone else?” We asked those who did not volunteer: – If nobody else will give, would you prefer to give?

38. Classifying Players Be-the-one types--First possible moment and “take it from me.” Deontologists--First possible moment and “take it from somebody else.” Consequentialist altruists—Last possible moment or Not at all but “if nobody else will give, I will give. Egoist Not at all and “if nobody else will give, I won’t give.

39. What we expect Egoists will not give. Sympathetic consequentialists if they do give will give at last possible moment. (They want person to be helped, but would rather someone else did it.) Impact philanthropists and some deontologists would choose first possible moment.

40. 123456 7 Number of Potential Donors 100% 80% 60% 40% 20% Classifying types Egoists Sympathetic Consequentialists Impact philanthropists

41. 1 23456 7 First Yes First No 5-25 25-30 30+Yes Last No No+No *To Volunteers, we ask “In case of tie would you prefer we take it from you?” To Non-Volunteers, we ask “If no one volunteers, would you prefer to switch?” Exploring intentions* Number of Potential Donors 100% 80% 60% 40% 20%

42. 1 23456 7 5-25 25-30 30+Yes *To Volunteers, we ask “In case of tie would you prefer we take it from you?” To Non-Volunteers, we ask “If no one volunteers, would you prefer to switch?” Exploring intentions* Number of Potential Donors 100% 80% 60% 40% 20% Egoists Sympathetic Consequentialists Impact Philanthropists Deontologists

43. Rough proportions of types Egoists 25% Sympathetic Consequentialists 40% Impact philanthropists (Be the one) 10% Deontologists (Do the right thing) 10% Unclassified 15%

44. Brighter news for urbanites The unhappy conclusion of the Volunteer’s dilemma does not generalize to cases where players preferences differ. The case of the world bone marrow registry is a spectacular instance of generous actions taken despite very high probabilities that one’s own sacrifices are not necessary because of the availability of other donors. In populations that have some “impact philanthropists” (be-the-one types) and deontologists (do-the-right-thing types), larger groups will do better than smaller groups in volunteers’ dilemma situations.

45. More Questions?