CRITICAL THINKING - Cognitive Biases: Reference Dependence and Loss Aversion [HD]

Laurie Santos, a psychologist at Yale University, explains two of our classic economic biases: reference dependence and loss aversion. Using a classic scenario from Kahneman and Tversky’s studies, she explores how these two biases violate economic rationality and how they affect the choices we make every day.

(intro music)

My name is Laurie Santos.

I teach psychology at Yale University,
and today I want to talk to you about

reference dependence and loss aversion.

This lecture is part of a
series on cognitive biases.

Imagine that you're a doctor heading a
medical team that's trying to fight a new

strain of deadly flu, one that's currently
spreading at an alarming rate.

The new flu is so devastating that six
hundred million people have already

been infected, and if nothing
is done, all of them will die.

The good news is there are two, drugs
available to treat the disease and your

team can decide which one
to put into mass production.

Clinical trials show that if you go with
the first drug, drug A, you'll be able to

save two hundred million
of the infected people.

The second option is drug B, which has a

one-third chance of saving all six hundred
million people, but a two-thirds

chance that no one infected will be saved.

Which drug do you pick?

You probably thought drug
A was the best one.

After all, with drug A, two hundred
million people will be saved for sure,

which is a pretty good outcome.

But now imagine that your team is faced
with a slightly different choice.

This time, it's between drug C and drug D.

If you choose drug C, four
hundred million infected

people will die for sure.

If you choose drug D, there's a one-third chance

that no one infected will die, and a
two-thirds chance that six hundred million

infected people will die.

Which drug do you choose in this case?

I bet you probably wen with drug D.

After all, a chance that no one will
die seems like a pretty good bet.

If you picked drug A in the first scenario

and drug D in the second, you're not alone.

When behavioral economists Danny Kahneman

and Amos Tversky gave these
scenarios to college students,

seventy-two percent of people said
that drug A was better than B,

and seventy-eight percent of people
said that drug D was better than C.

But let's take a slightly different
look at both sets of outcomes.

In fact, let's depicted both choices in

terms of the number of people
who will live and die.

Here's your first choice.

Drug A will save two hundred million
people for sure, and for drug B, there's a

one-third chance that all six hundred million
infected people will be saved and a

two-thirds chance that no
one infected will be saved.

And now, let's do the same
thing for drugs C and D.

Surprisingly, you can now see
that the two options are identical.

Drugs A and C will save two hundred
million people, while four hundred million

people are certain to die.

And with both drug B and drug D, you
have a one-third chance of saving all

six hundred million people and a
two-thirds chance of saving no one.

We can argue about whether it's better to
save two hundred million people for sure,

or to take a one-third chance
of saving all of them.

But one thing should be clear from

the example: it's pretty weird for you to
prefer drug A over B at the same time as

you prefer drug D over C.

After all, they're exactly the same drugs
with slightly different labels.

Why does a simple change
in wording change our

judgments about exactly the same options?

Kahneman and Tversky figured out that this
strange effect results from two classic

biases that affect human choice,

biases known as "reference
dependence" and "loss aversion."

"Reference dependence" just refers the
fact that we think about our decisions

not in terms of absolutes, but relative
to some status quo or baseline.

This is why, when you find
a dollar on the ground,

you don't think about that dollar
as part of your entire net worth.

Instead, you think in terms
of the change that the dollar

made your status quo.

You think, "Hey, I'm one dollar richer!"

because of reference dependence, you
don't think of the options presented earlier

in terms of the absolute number of lives saved.

Instead, you frame each choice
relative to some status quo.

And that's why the wording matters.

The first scenario is described in terms

of the number of life saved.

That's your reference point.

You're thinking in terms of how many
additional lives you can save.

And in the second, you think relative

to how many less lives you can lose.

And that second part, worrying about losing

lives, leads to the second bias that's
affecting your choices: loss aversion.

Loss aversion is our reluctance to
make choices that lead to losses.

We don't like losing stuff, whether
it's money, or lives, or even candy.

We have an instinct to avoid
potential losses at all costs.

Economists have found that
loss aversion causes us to do

a bunch of irrational stuff.

Loss aversion causes people to
hold onto property that's losing in

value in the housing market, just because

they don't want to sell
their assets at a loss.

Loss aversion also leads people to
invest more poorly, even avoid risky

stocks that overall will do well, because

we're afraid of a small probability of losses.

Loss aversion causes to latch onto the

fact that drugs C and D involve losing lives.

Our aversion to any potential losses causes

us to avoid drug C and to go with drug D,

which is the chance of not losing anyone.

Our loss aversion isn't as activated

when we hear about drugs A and B.

Both of them involve saving people,
so why not go with the safe option,

drug A over drug B?

Merely describing the outcomes differently

changes which scenarios
we find more aversive.

If losses are mentioned, we want to

reduce them as much as possible,

so much so, that we take on a bit
more risk than we usually like

So describing the decision one
way, as opposed to another,

can cause us to make a
completely different choice.

even in a life-or-death decision

like this, we're at the mercy of our
minds interpret information.

And how our minds interpret information
is at the mercy of our cognitive biases.