The psychology behind irrational decisions Sara Garofalo

Let’s say you’re on a game show.

You’ve already earned $1000
in the first round

when you land on the bonus space.

Now, you have a choice.

You can either take
a $500 bonus guaranteed

or you can flip a coin.

If it’s heads, you win $1000 bonus.

If it’s tails, you get no bonus at all.

In the second round, you’ve earned $2000
when you land on the penalty space.

Now you have another choice.

You can either take a $500 loss,

or try your luck at the coin flip.

If it’s heads, you lose nothing,

but if it’s tails, you lose $1000 instead.

If you’re like most people,

you probably chose to take
the guaranteed bonus in the first round

and flip the coin in the second round.

But if you think about it,
this makes no sense.

The odds and outcomes in both rounds
are exactly the same.

So why does the second round
seem much scarier?

The answer lies in a phenomenon
known as loss aversion.

Under rational economic theory,

our decisions should follow a simple
mathematical equation

that weighs the level of risk
against the amount at stake.

But studies have found
that for many people,

the negative psychological impact
we feel from losing something

is about twice as strong as the positive
impact of gaining the same thing.

Loss aversion is one cognitive bias
that arises from heuristics,

problem-solving approaches based on
previous experience and intuition

rather than careful analysis.

And these mental shortcuts can lead
to irrational decisions,

not like falling in love

or bungee jumping off a cliff,

but logical fallacies that can easily
be proven wrong.

Situations involving probability are
notoriously bad for applying heuristics.

For instance, say you were to roll a die
with four green faces and two red faces

twenty times.

You can choose one of
the following sequences of rolls,

and if it shows up,
you’ll win $25.

Which would you pick?

In one study, 65% of the participants
who were all college students

chose sequence B

even though A is shorter
and contained within B,

in other words, more likely.

This is what’s called
a conjunction fallacy.

Here, we expect to see more green rolls,

so our brains can trick us into picking
the less likely option.

Heuristics are also terrible
at dealing with numbers in general.

In one example, students were split
into two groups.

The first group was asked whether
Mahatma Gandhi died before or after age 9,

while the second was asked whether
he died before or after age 140.

Both numbers were obviously way off,

but when the students were then asked
to guess the actual age at which he died,

the first group’s answers averaged to 50

while the second group’s averaged to 67.

Even though the clearly wrong information
in the initial questions

should have been irrelevant,

it still affected the students' estimates.

This is an example
of the anchoring effect,

and it’s often used in marketing
and negotiations

to raise the prices
that people are willing to pay.

So, if heuristics lead to
all these wrong decisions,

why do we even have them?

Well, because they can be quite effective.

For most of human history,

survival depended on making quick
decisions with limited information.

When there’s no time to logically
analyze all the possibilities,

heuristics can sometimes save our lives.

But today’s environment requires
far more complex decision-making,

and these decisions are more biased
by unconscious factors than we think,

affecting everything from health
and education

to finance and criminal justice.

We can’t just shut off
our brain’s heuristics,

but we can learn to be aware of them.

When you come to
a situation involving numbers,

probability,

or multiple details,

pause for a second

and consider that the intuitive answer
might not be the right one after all.

假设您正在参加游戏节目。

当您登陆奖励空间时,您已经在第一轮中赚取了 1000 美元。

现在,你有一个选择。

您可以
保证获得 500 美元的奖金

,也可以掷硬币。

如果是正面,您将赢得 1000 美元的奖金。

如果是反面,你根本得不到任何奖励。

在第二轮中,
当你降落在罚球区时,你已经赚了 2000 美元。

现在你有另一个选择。

您可以损失 500 美元,

也可以在掷硬币时碰碰运气。

如果是正面,您不会损失任何东西,

但如果是反面,您反而会损失 1000 美元。

如果您像大多数人一样,

您可能会选择
在第一轮中获得保证奖金

并在第二轮中掷硬币。

但如果你仔细想想,
这没有任何意义。

两轮的赔率和
结果完全相同。

那么为什么第二轮
看起来更可怕呢?

答案在于一种
被称为损失厌恶的现象。

在理性经济理论下,

我们的决策应该遵循一个简单的
数学方程式

,即权衡风险水平与
风险金额。

但研究发现
,对于许多人来说,失去某物所

产生的负面心理影响

大约
是获得同样东西所产生的积极影响的两倍。

损失厌恶是一种认知偏差
,它源于启发式

方法,即基于
先前经验和直觉

而不是仔细分析的问题解决方法。

而这些心理捷径会
导致不合理的决定,

不像坠入爱河

或蹦极跳下悬崖,

而是很容易
被证明是错误的逻辑谬误。 众所周知,

涉及概率的情况
不适合应用启发式方法。

例如,假设你要掷一个
有四个绿色面和两个红色面的骰子

二十次。

您可以选择
以下滚动顺序之一

,如果出现,
您将赢得 25 美元。

你会选哪个?

在一项研究中,65%
的全是大学生的参与者

选择了序列 B,

即使 A 更短
并且包含在 B 中

,换句话说,更有可能。

这就是所谓
的合取谬误。

在这里,我们希望看到更多的绿色卷,

所以我们的大脑可以欺骗我们
选择不太可能的选项。 一般来说,

启发式方法在处理数字方面也很糟糕

在一个例子中,学生被
分成两组。

第一组被问到
圣雄甘地是在 9 岁之前还是之后去世,

而第二组被问到
他是在 140 岁之前还是之后去世。

这两个数字显然都相差甚远,

但当学生们被
要求猜测其实际年龄时 他死了

,第一组的平均答案是 50,

而第二组的平均答案是 67。

即使最初问题中明显错误的信息

应该无关紧要,

但它仍然影响了学生的估计。


是锚定效应的一个例子

,它经常用于营销
和谈判中,

以提高
人们愿意支付的价格。

那么,如果启发式方法导致了
所有这些错误的决定,

我们为什么还要拥有它们呢?

好吧,因为它们可能非常有效。

在人类历史的大部分时间里,

生存依赖于在
有限信息的情况下做出快速决策。

当没有时间
对所有可能性进行逻辑分析时,

启发式有时可以挽救我们的生命。

但今天的环境需要
更复杂的决策

,这些决策
比我们想象的更受无意识因素的

影响,影响从健康
和教育

到金融和刑事司法的方方面面。

我们不能只是关闭
我们大脑的启发式,

但我们可以学会意识到它们。

当您遇到
涉及数字、

概率

或多个细节的情况时,请

暂停一秒钟,

并考虑一下直观的答案
可能不是正确的答案。