UC Berkeley Act of Altruism Hamiltons Rule Discussion Questions 1. Find a news story from the last five years that involves an act of altruism (or what app

UC Berkeley Act of Altruism Hamiltons Rule Discussion Questions 1. Find a news story from the last five years that involves an act of altruism (or what appears to be an act of altruism). Then analyze the story, using one concept from the reading, and three concepts from the lecture. Each of your four points should get one good, solid paragraph. Make sure to include a link to the news story you’re using.

2. What do you think is the most successful song of all time? Please give me the title and the artist or composer, and briefly explain (1-3 sentences) why you think that song is the correct answer. Note that I am deliberately not defining “successful,” so that you can answer based on your own judgment of what that words means. This is worth 2 points, and is unrelated to this lecture.

Here are some concepts from lecture:

Types of interactions:

Interaction #1: Mutualistic- I win, you win

Interaction #2: Selfish- I win, you lose

Interaction #3: Spiteful- I lose, you lose

Interaction #4: Altruistic- I lose, you win

Explanation for Altruistic behavior: Hamilton’s Rule CHAPTER 3
UNBELIEVABLE STORIES ABOUT APATHY AND
ALTRUISM
In March 1964, late on a cold and damp Thursday night,
something terrible happened in New York City,
something suggesting that human beings are the most
brutally selfish animals to ever roam the planet.
A twenty-eight-year-old woman named Kitty
Genovese drove home from work and parked, as usual, in
the lot at the Long Island Rail Road station. She lived in
Kew Gardens, Queens, roughly twenty minutes by train
from Manhattan. It was a nice neighborhood, with tidy
homes on shaded lots, a handful of apartment buildings,
and a small commercial district.
Genovese lived above a row of shops that fronted
Austin Street. The entrance to her apartment was around
the rear. She got out of her car and locked it; almost
immediately, a man started chasing her and stabbed her in
the back. Genovese screamed. The assault took place on
the sidewalk in front of the Austin Street shops and across
the street from a ten-story apartment building called the
Mowbray.
The assailant, whose name was Winston Moseley,
retreated to his car, a white Corvair parked at the curb
some sixty yards away. He put the car in reverse and
backed it down the block, passing out of view.
Genovese, meanwhile, staggered to her feet and made
her way around to the back of her building. But in a short
time Moseley returned. He sexually assaulted her and
stabbed her again, leaving Genovese to die. Then he got
back in his car and drove home. Like Genovese, he was
young, twenty-nine years old, and he too lived in Queens.
His wife was a registered nurse; they had two children.
On the drive home, Moseley noticed another car stopped
at a red light, its driver asleep at the wheel. Moseley got
out and woke the man. He didn’t hurt or rob him. The
next morning, Moseley went to work as usual.
The crime soon became infamous. But not because
Moseley was a psychopath—a seemingly normal family
man who, although he had no criminal record, turned out
to have a history of grotesque sexual violence. And it
wasn’t because Genovese was a colorful character herself,
a tavern manager who happened to be a lesbian and had a
prior gambling arrest. Nor was it because Genovese was
white and Moseley was black.
The Kitty Genovese murder became infamous because
of an article published on the front page of The New York
Times. It began like this:
For more than half an hour 38 respectable, lawabiding citizens in Queens watched a killer stalk and
stab a woman in three separate attacks in Kew
Gardens…. Not one person telephoned the police
during the assault; one witness called after the
woman was dead.
The murder took about thirty-five minutes from start to
finish. “If we had been called when he first attacked,” said
a police inspector, “the woman might not be dead now.”
The police had interviewed Genovese’s neighbors the
morning after the murder, and the Times’s reporter
reinterviewed some of them. When asked why they hadn’t
intervened or at least called the police, they offered a
variety of excuses:
“We thought it was a lovers’ quarrel.”
“We went to the window to see what was happening
but the light from our bedroom made it difficult to see the
street.”
“I was tired. I went back to bed.”
The article wasn’t very long—barely fourteen hundred
words—but its impact was immediate and explosive.
There seemed to be general agreement that the thirty-eight
witnesses in Kew Gardens represented a new low in
human civilization. Politicians, theologians, and editorial
writers lambasted the neighbors for their apathy. Some
even called for the neighbors’ addresses to be published
so justice could be done.
The incident so deeply shook the nation that over the
next twenty years, it inspired more academic research on
bystander apathy than the Holocaust.
To mark the thirtieth anniversary, President Bill
Clinton visited New York City and spoke about the crime:
“It sent a chilling message about what had happened at
that time in a society, suggesting that we were each of us
not simply in danger but fundamentally alone.”
More than thirty-five years later, the horror lived on in
The Tipping Point, Malcolm Gladwell’s groundbreaking
book about social behavior, as an example of the
“bystander effect,” whereby the presence of multiple
witnesses at a tragedy can actually inhibit intervention.
Today, more than forty years later, the Kitty Genovese
saga appears in all ten of the top-selling undergraduate
textbooks for social psychology. One text describes the
witnesses remaining “at their windows in fascination for
the 30 minutes it took her assailant to complete his grisly
deed, during which he returned for three separate attacks.”
How on earth could thirty-eight people stand by and
watch as their neighbor was brutalized? Yes, economists
always talk about how self-interested we are, but doesn’t
this demonstration of self-interest practically defy logic?
Does our apathy really run so deep?
The Genovese murder, coming just a few months after
President John F. Kennedy’s assassination, seemed to
signal a sort of social apocalypse. Crime was exploding in
cities all across the United States, and no one seemed
capable of stopping it.
For decades, the rate of violent and property crimes in
the United States had been steady and relatively low. But
levels began to rise in the mid-1950s. By 1960, the crime
rate was 50 percent higher than it had been in 1950; by
1970, the rate had quadrupled.
Why?
It was hard to say. So many changes were
simultaneously rippling through American society in the
1960s—a population explosion, a growing antiauthoritarian sentiment, the expansion of civil rights, a
wholesale shift in popular culture—that it wasn’t easy to
isolate the factors driving crime.
Imagine, for instance, you want to know whether
putting more people in prison really lowers the crime rate.
This question isn’t as obvious as it may seem. Perhaps the
resources devoted to catching and jailing criminals could
have been used more productively. Perhaps every time a
bad guy is put away, another criminal rises up to take his
place.
To answer this question with some kind of scientific
certainty, what you’d really like to do is conduct an
experiment. Pretend you could randomly select a group of
states and command each of them to release 10,000
prisoners. At the same time, you could randomly select a
different group of states and have them lock up 10,000
people, misdemeanor offenders perhaps, who otherwise
wouldn’t have gone to prison. Now sit back, wait a few
years, and measure the crime rate in those two sets of
states. Voilà! You’ve just run the kind of randomized,
controlled experiment that lets you determine the
relationship between variables.
Unfortunately, the governors of those random states
probably wouldn’t take too kindly to your experiment.
Nor would the people you sent to prison in some states or
the next-door neighbors of the prisoners you freed in
others. So your chances of actually conducting this
experiment are zero.
That’s why researchers often rely on what is known as
a natural experiment, a set of conditions that mimic the
experiment you want to conduct but, for whatever reason,
cannot. In this instance, what you want is a radical change
in the prison population of various states for reasons that
have nothing to do with the amount of crime in those
states.
Happily, the American Civil Liberties Union was good
enough to create just such an experiment. In recent
decades, the ACLU has filed lawsuits against dozens of
states to protest overcrowded prisons. Granted, the choice
of states is hardly random. The ACLU sues where prisons
are most crowded and where it has the best chance of
winning. But the crime trends in states sued by the ACLU
look very similar to trends in other states.
The ACLU wins virtually all of these cases, after
which the state is ordered to reduce overcrowding by
letting some prisoners free. In the three years after such
court decisions, the prison population in these states falls
by 15 percent relative to the rest of the country.
What do those freed prisoners do? A whole lot of
crime. In the three years after the ACLU wins a case,
violent crime rises by 10 percent and property crime by 5
percent in the affected states.
So it takes some work, but using indirect approaches
like natural experiments can help us look back at the
dramatic crime increase of the 1960s and find some
explanations.
One major factor was the criminal-justice system itself.
The ratio of arrests per crime fell dramatically during the
1960s, for both property and violent crime. But not only
were the police catching a smaller share of the criminals;
the courts were less likely to lock up those who were
caught. In 1970, a criminal could expect to spend an
astonishing 60 percent less time behind bars than he
would have for the same crime committed a decade
earlier. Overall, the decrease in punishment during the
1960s seems to be responsible for roughly 30 percent of
the rise in crime.
The postwar baby boom was another factor. Between
1960 and 1980, the fraction of the U.S. population
between the ages of fifteen and twenty-four rose by nearly
40 percent, an unprecedented surge in the age group most
at risk for criminal involvement. But even such a radical
demographic shift can only account for about 10 percent
of the increase in crime.
So together, the baby boom and the declining rate of
imprisonment explain less than half of the crime spike.
Although a host of other hypotheses have been advanced
—including the great migration of African Americans
from the rural South to northern cities and the return of
Vietnam vets scarred by war—all of them combined still
cannot explain the crime surge. Decades later, most
criminologists remain perplexed.
The answer might be right in front of our faces,
literally: television. Maybe Beaver Cleaver and his
picture-perfect TV family weren’t just a casualty of the
changing times (Leave It to Beaver was canceled in 1963,
the same year Kennedy was assassinated). Maybe they
were actually a cause of the problem.
People have long posited that violent TV shows lead to
violent behavior, but that claim is not supported by data.
We are making an entirely different argument here. Our
claim is that children who grew up watching a lot of TV,
even the most innocuous family-friendly shows, were
more likely to engage in crime when they got older.
Testing this hypothesis isn’t easy. You can’t just
compare a random bunch of kids who watched a lot of TV
with those who didn’t. The ones who were glued to the
TV are sure to differ from the other children in countless
ways beyond their viewing habits.
A more believable strategy might be to compare cities
that got TV early with those that got it much later.
We wrote earlier that cable TV came to different parts
of India at different times, a staggered effect that made it
possible to measure TV’s impact on rural Indian women.
The initial rollout of TV in the United States was even
bumpier. This was mainly due to a four-year interruption,
from 1948 to 1952, when the Federal Communications
Commission declared a moratorium on new stations so
the broadcast spectrum could be reconfigured.
Some places in the United States started receiving
signals in the mid-1940s while others had no TV until a
decade later. As it turns out, there is a stark difference in
crime trends between cities that got TV early and those
that got it late. These two sets of cities had similar rates of
violent crime before the introduction of TV. But by 1970,
violent crime was twice as high in the cities that got TV
early relative to those that got it late. For property crime,
the early-TV cities started with much lower rates in the
1940s than the late-TV cities, but ended up with much
higher rates.
There may of course be other differences between the
early-TV cities and the late-TV cities. To get around that,
we can compare children born in the same city in, say,
1950 and 1955. So in a city that got TV in 1954, we are
comparing one age group that had no TV for the first four
years of life with another that had TV the entire time.
Because of the staggered introduction of TV, the cutoff
between the age groups that grew up with and without TV
in their early years varies widely across cities. This leads
to specific predictions about which cities will see crime
rise earlier than others—as well as the age of the
criminals doing the crimes.
So did the introduction of TV have any discernible
effect on a given city’s crime rate?
The answer seems to be yes, indeed. For every extra
year a young person was exposed to TV in his first 15
years, we see a 4 percent increase in the number of
property-crime arrests later in life and a 2 percent increase
in violent-crime arrests. According to our analysis, the
total impact of TV on crime in the 1960s was an increase
of 50 percent in property crimes and 25 percent in violent
crimes.
Why did TV have this dramatic effect?
Our data offer no firm answers. The effect is largest for
children who had extra TV exposure from birth to age
four. Since most four-year-olds weren’t watching violent
shows, it’s hard to argue that content was the problem.
It may be that kids who watched a lot of TV never got
properly socialized, or never learned to entertain
themselves. Perhaps TV made the have-nots want the
things the haves had, even if it meant stealing them. Or
maybe it had nothing to do with the kids at all; maybe
Mom and Dad became derelict when they discovered that
watching TV was a lot more entertaining than taking care
of the kids.
Or maybe early TV programs somehow encouraged
criminal behavior. The Andy Griffith Show, a huge hit that
debuted in 1960, featured a friendly sheriff who didn’t
carry a gun and his extravagantly inept deputy, named
Barney Fife. Could it be that all the would-be criminals
who watched this pair on TV concluded that the police
simply weren’t worth being afraid of?
As a society, we’ve come to accept that some bad apples
will commit crimes. But that still doesn’t explain why
none of Kitty Genovese’s neighbors—regular people,
good people—stepped in to help. We all witness acts of
altruism, large and small, just about every day. (We may
even commit some ourselves.) So why didn’t a single
person exhibit altruism on that night in Queens?
A question like this may seem to fall beyond the realm
of economics. Sure, liquidity crunches and oil prices and
even collateralized debt obligations—but social behaviors
like altruism? Is that really what economists do?
For hundreds of years, the answer was no. But around
the time of the Genovese murder, a few renegade
economists had begun to care deeply about such things.
Chief among them was Gary Becker, whom we met
earlier, in this book’s introduction. Not satisfied with just
measuring the economic choices people make, Becker
tried to incorporate the sentiments they attached to such
choices.
Some of Becker’s most compelling research concerned
altruism. He argued, for instance, that the same person
who might be purely selfish in business could be
exceedingly altruistic among people he knew—although,
importantly (Becker is an economist, after all), he
predicted that altruism even within a family would have a
strategic element. Years later, the economists Doug
Bernheim, Andrei Shleifer, and Larry Summers
empirically demonstrated Becker’s point. Using data from
a U.S. government longitudinal study, they showed that
an elderly parent in a retirement home is more likely to be
visited by his grown children if they are expecting a
sizable inheritance.
But wait, you say: maybe the offspring of wealthy
families are simply more caring toward their elderly
parents?
A reasonable conjecture—in which case you’d expect
an only child of wealthy parents to be especially dutiful.
But the data show no increase in retirement-home visits if
a wealthy family has only one grown child; there need to
be at least two. This suggests that the visits increase
because of competition between siblings for the parent’s
estate. What might look like good old-fashioned
intrafamilial altruism may be a sort of prepaid inheritance
tax.
Some governments, wise to the ways of the world,
have gone so far as to legally require grown children to
visit or support their aging moms and dads. In Singapore,
the law is known as the Maintenance of Parents Act.
Still, people appear to be extraordinarily altruistic, and
not just within their own families. Americans in particular
are famously generous, donating about $300 billion a year
to charity, more than 2 percent of the nation’s GDP. Just
think back to the last hurricane or earthquake that killed a
lot of people, and recall how Good Samaritans rushed
forward with their money and time.
But why?
Economists have traditionally assumed that the typical
person makes rational decisions in line with his own selfinterest. So why should this rational fellow—Homo
economicus, he is usually called—give away some of his
hard-earned cash to someone he doesn’t know in a place
he can’t pronounce in return for nothing more than a
warm, fuzzy glow?
Building on Gary Becker’s work, a new generation of
economists decided it was time to understand altruism in
the world at large. But how? How can we know whether
an act is altruistic or self-serving? If you help rebuild a
neighbor’s barn, is it because you’re a moral person or
because you know your own barn might burn down
someday? When a donor gives millions to his alma mater,
is it because he cares about the pursuit of knowledge or
because he gets his name plastered on the football
stadium?
Sorting out such things in the real world is extremely
hard. While it is easy to observe actions—or, in the Kitty
Genovese case, inaction—it is much harder to understand
the intentions behind an action.
Is it possible to use natural experiments, like the
ACLU-prison scenario, to measure altruism? You might
consider, for instance, looking at a series of calamities to
see how much charitable contribution they produce. But
with so many variables, it would be hard to tease out the
altruism from everything else. A crippling earthquake in
China is not the same as a scorching drought in Africa,
which is not the same as a devastating hurricane in New
Orleans. Each disaster has its own sort of “appeal”—and,
just as important, donations are heavily influenced by
media coverage. One recent academic study found that a
given disaster received an 18 percent spike in charitable
aid for each seven-hundred-word newspaper article and a
13 percent spike for every sixty seconds of TV news
coverage. (Anyone hoping to raise money for a Third
World disaster had better hope it happens on a slow news
day.) And such disasters are by their nature anomalies—
especially noisy ones, like shark attacks—that probably
don’t have much to say about our baseline altruism.
In time, those renegade economists took a different
approach: since altruism is so hard to measure in the real
world, why not peel away all the real world’s inherent
complexities by bringing the subject into the laboratory?
Laboratory experiments are of course a pillar of the
physical sciences and have been since Galileo Galilei
rolled a bronze ball down a length of wooden molding to
test his theory of acceleration. Galileo believed—
correctly, as it turned out—that a small creation like his
could lead to a better understanding of the greatest
creations known to humankind: the earth’s forces, the
order of the skies, the workings of human life itself.
More than three centuries later, the physicist Richard
Feynman reasserted the primacy of this belief. “The test
of all knowledge is experiment,” he said. “Experiment is
the sole judge of scientific ‘truth.’” The electricity you
use, the cholesterol drug you swallow, the page or screen
or…
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