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Smart Heuristics
Many people are ill-equipped to handle uncertainty. But the study of smart heuristics shows that there are strategies people actually use to make good decisions that deal openly with uncertainties, rather than denying their existence.
Originally published on Edge,
March 31, 2003. Published on KurzweilAI.net April 8, 2003.
At the beginning of the 20th century, the father of modern science
fiction, Herbert George Wells, said in his writings on politics,
"If we want to have an educated citizenship in a modern technological
society, we need to teach them three things: reading, writing, and
statistical thinking." At the beginning of the 21st century,
how far have we gotten with this program? In our society, we teach
most citizens reading and writing from the time they are children,
but not statistical thinking. John Alan Paulos has called this phenomenon
innumeracy.
There are many stories documenting this problem. For instance,
there was the weather forecaster who announced on American TV that
if the probability that it will rain on Saturday is 50 percent and
the probability that it will rain on Sunday is 50 percent, the probability
that it will rain over the weekend is 100 percent. In another recent
case reported by New Scientist, an inspector in the Food and Drug
Administration visited a restaurant in Salt Lake City famous for
its quiches made from four fresh eggs. She told the owner that according
to FDA research, every fourth egg has salmonella bacteria, so the
restaurant should only use three eggs in a quiche. We can laugh
about these examples because we easily understand the mistakes involved,
but there are more serious issues. When it comes to medical and
legal issues, we need exactly the kind of education that H. G. Wells
was asking for, and we haven't gotten it.
What interests me is the question of how humans learn to live with
uncertainty. Before the scientific revolution, determinism was a
strong ideal. Religion brought about a denial of uncertainty, and
many people knew that their kin or their race was exactly the one
that God had favored. They also thought they were entitled to get
rid of competing ideas and the people that propagated them. How
does a society change from this condition into one in which we understand
that there is this fundamental uncertainty? How do we avoid the
illusion of certainty to produce the understanding that everything,
whether it be a medical test or deciding on the best cure for a
particular kind of cancer, has a fundamental element of uncertainty?
For instance, I've worked with physicians and physician-patient
associations to try to teach the acceptance of uncertainty and the
reasonable way to deal with it. Take HIV testing as an example.
Brochures published by the Illinois Department of Health say that
testing positive for HIV means that you have the virus. Thus, if
you are an average person who is not in a particular risk group
but test positive for HIV, this might lead you to choose to commit
suicide, or move to California, or do something else quite drastic.
But AIDS information in many countries is running on the illusion
of certainty. The actual situation is rather like this: If you have
about 10,000 people who are in no risk group, one of them will have
the virus, and will test positive with practical certainty. Among
the other 9,999, another one will test positive, but it's a false
positive. In this case we have two who test positive, although only
one of them actually has the virus. Knowing about these very simple
things can prevent serious disasters, of which there is unfortunately
a record.
Still, medical societies, individual doctors, and individual patients
either produce the illusion of certainty or want it. Everyone knows
Benjamin Franklin's adage that there is nothing certain in this
world except death and taxes, but the doctors I interviewed tell
me something different. They say, "If I would tell my patients
what we don't know, they would get very nervous, so it's better
not to tell them." Thus, this is one important area in which
there is a need to get people—including individual doctors
or lawyers in court—to be mature citizens and to help them
understand and communicate risks.
Representation of information is important. In the case of many
so-called cognitive illusions, the problem results from difficulties
that arise from getting along with probabilities. The problem largely
disappears the moment you give the person the information in natural
frequencies. You basically put the mind back in a situation where
it's much easier to understand these probabilities. We can prove
that natural frequencies can facilitate actual computations, and
have known for a long time that representations—whether they
be probabilities, frequencies or odds—have an impact on the
human mind. There are very few theories about how this works.
I'll give you a couple of examples relating to medical care. In
the US and many European countries, women who are 40 years old are
told to participate in mammography screening. Say that a woman takes
her first mammogram and it comes out positive. She might ask the
physician, "What does that mean? Do I have breast cancer? Or
are my chances of having it 99%, 95%, or 90% or only 50%? What do
we know at this point?" I have put the same question to radiologists
who have done mammography screening for 20 or 25 years, including
chiefs of departments. A third said they would tell this woman that,
given a positive mammogram, her chance of having breast cancer is
90%.
However, what happens when they get additional relevant information?
The chance that a woman in this age group has cancer is roughly
1%. If a woman has breast cancer, the probability that she will
test positive on a mammogram is 90%. If a woman does not have breast
cancer, the probability that she nevertheless tests positive is
some 9%. In technical terms, you have a base rate of 1%, a sensitivity
or hit rate of 90%, and a false positive rate of about 9%. So, how
do you answer this woman who's just tested positive for cancer?
As I just said, about a third of the physicians thinks it's 90%,
another third thinks the answer should be something between 50%
and 80%, and another third thinks the answer is between 1% and 10%.
Again, these are professionals with many years of experience. It's
hard to imagine a larger variability in physicians' judgments—
between 1% and 90%—and if patients knew about this variability,
they would not be very happy. This situation is typical of what
we know from laboratory experiments: namely, that when people encounter
probabilities—which are technically conditional probabilities—their
minds are clouded when they try to make an inference.
What we do is to teach these physicians tools that change the representation
so that they can see through the problem. We don't send them to
a statistics course, since they wouldn't have the time to go in
the first place, and most likely they wouldn't understand it because
they would be taught probabilities again. But how can we help them
to understand the situation?
Let's change the representation using natural frequencies, as if
the physician would have observed these patients him- or herself.
One can communicate the same information in the following, much
more simple way. Think about 100 women. One of them has breast cancer.
This was the 1%. She likely tests positive; that's the 90%. Out
of 99 who do not have breast cancer another 9 or 10 will test positive.
So we have one in 9 or 10 who tests positive. How many of them actually
has cancer? One out of ten. That's not 90%, that's not 50%, that's
one out of ten.
Here we have a method that enables physicians to see through the
fog just by changing the representation, turning their innumeracy
into insight. Many of these physicians have carried this innumeracy
around for decades and have tried to hide it. When we interview
them, they obviously admit it, saying, "I don't know what to
do with these numbers. I always confuse these things." Here
we have a chance to use very simple tools to help those patients
and physicians to understand what the risks are and which enable
them to have a reasonable reaction to what to do. If you take the
perspective of a patient—that this test means that there is
a 90% chance you have cancer—you can imagine what emotions
set in, emotions that do not help her to reason the right way. But
informing her that only one out of ten women who tests positive
actually has cancer would help her to have a cooler attitude and
to make more reasonable decisions.
[Continued on Edge.org.]
© 2003 Edge
Foundation, Inc. Reprinted with permission.
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Mind·X Discussion About This Article:
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Heuristics And Life Decisions
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All my life I have practised probability, as the basis of taking very important decisions.
For example, when I was in Dar-es-Salaam, in Tanzania, East Africa, I had to decide whether I should buy a car or depend on the company car for transport. Although, buying Car was very attractive, the company financing it, and I could take it back to India, where Imported Cars at that time fetched a huge premium, I decided against it.
The basis was simple probability calculation of Car Fatalities due to Road Accidents- most accidents taking place due to drunken driving at speed by local drivers. My worst fears were confirmed a few months later when the Prime Minister of the countrywas killed in an accident, on the same road/ place where I was planning to drive for next three years.
The next example, is even more interesting.
I ran a life expectancy test based on life style and probability of dying - taking into accont, smoking,dringing, excercises, diabetes, heart, blood pressure etc. into account.
The chart predicted a life expectancy of 400 weeks, as remaining life. ( This(Death) was to come when I was going to be 70 in December 2001.)
I have a very good medical history, with no heart trouble, blood pressure, or related diseases.
Then exactly in November 2001, when Iwas on my way to an International Seminar on 'Mobility-Transportation Model', I suddenly collapsed, while a Delhi Road, with the famous Killer Bus roaring towards me.
The traffic stopped in time, and I was taken to the hospital, where a Pacemaker was installed, connecting my heart to a battery, which is sending timing signal/ electric shock to my heart and I am fine now.
Well, the probability of a test for prediction of life expectancy being so accurate is very low.
Exactly that is the point.
However, today I am alive, after having been clinically and predictably dead, only because I used the science of probability to decide my course of action in real time and in real life..
Only becuse i didnot die in a road accident in Africa, and got medical help-'pacemaker' in time.
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