[Music]
if there’s one city in the world where
it’s hard to find a place to buy or rent
it’s Sydney if you try to find a home
here recently you’re familiar with the
problem every time you walk into an open
house you get some information about
what’s out there and what’s on the
market but every time you walk out
you’re running the risk of the very best
place passing you by so how do you know
when to switch from looking to being
ready to make an offer this is such a
cruel and familiar problem that it might
come as a surprise that it has a simple
solution 37%
if you want to maximize the probability
that you find the very best place you
should look at 37% of what’s on the
market and then make an offer on the
next place you see which is better than
anything that you’ve seen so far or if
you’re looking for a month take 37
percent of that time 11 days to set a
standard and then you’re ready to act we
know this because trying to find a place
to live is an example of an optimal
stopping problem a class of problems
that has been studied extensively by
mathematicians and computer scientists
I’m a computational cognitive scientist
I spend my time trying to understand how
it is that human minds work from our
amazing successes to our dismal failures
to do that I think about the
computational structure of the problems
that arise in everyday life and compare
the ideal solutions for those problems
to the way that we actually behave as a
side effect I get to see how applying a
little bit of computer science can make
human decision-making easier I have a
personal motivation for this growing up
in Perth as an overly cerebral kid
I would always try and act in the way
that I thought was rational reasoning
through every decision trying to figure
out the very best action to take but
this is an approach that doesn’t scale
up when you start to run into the sorts
of problems that arise in adult life at
one point I even tried to break up with
my girlfriend because trying to take
into account her preferences as well as
my own and then find perfect solutions
was just leaving me exhausted she
pointed out that I was taking the wrong
approach to solving this problem and she
later became my wife whether it’s as
basic as trying to decide what
restaurant to go to or as important as
trying to despair decide who to spend
the rest of your life with human lives
are filled with computational problems
that are just too hard to solve by
applying sheer effort for those problems
it’s worth consulting the experts
computer scientists when you’re looking
for life advice computer scientists
probably aren’t the first people you
think to talk to living life like a
computer stereotypically deterministic
exhaustive and exact doesn’t sound like
a lot of fun but thinking about the
computer science of human decisions
reveals that in fact we’ve got this
backwards when applied to the sorts of
difficult problems that arise in human
lives the way that computers actually
solve those problems looks a lot more
like the way that people really act take
the example of trying to decide what
restaurant to go to this is a problem as
a particular computational structure
you’ve got a set of options you’re going
to choose one of those options and
you’re going to face exactly the same
decision tomorrow in that situation you
run up against what computer scientists
call the Explorer exploit trade-off you
have to make a decision about whether
you’re going to try something new
exploring gathering some information
that you might be able to use in the
future or whether you’re going to go to
a place that you already know is pretty
good exploiting the information that
you’ve already gathered so far the
Explorer exploit trade-off shows up
anytime you have to choose between
trying something new and going with
something that you already know is
pretty good whether it’s listening to
music
or trying to decide who you’re going to
spend time with it’s also the problem
that technology companies face when
they’re trying to do something like
decide what ad to show on a webpage
should they show a new ad and learn
something about it or should they show
you an ad that they already know there’s
a pretty good chance you’re going to
click on over the last 60 years computer
scientists have made a lot of progress
understanding the Explorer exploit
trade-off and their results offer some
surprising insights when you’re trying
to decide what restaurant to go to the
first question you should ask yourself
is how much longer you’re going to be in
town if you’re just going to be there
for a short time then you should exploit
there’s no point gathering information
just go to a place you already know is
good but if you’re going to be there for
a longer time explore try something new
because the information you get is
something that can improve your choices
in the future the value of information
increases the more opportunities you’re
going to have to use it this principle
can give us insight into the structure
of a human life as well babies don’t
have a reputation for being particularly
rational they’re always trying new
things and you know trying to stick them
in their mouths but in fact this is
exactly what they should be doing there
in the explore phase of their lives and
some of those things could turn out to
be delicious at the other end of the
spectrum the old guy who always goes to
the same restaurant and always eats the
same thing isn’t boring
he’s optimal
he’s exploiting the knowledge that he’s
earned through a lifetime’s experience
more generally knowing about the
Explorer exploit trade-off can make it a
little easier for you to sort of relax
and go easier on yourself when you’re
trying to make a decision you don’t have
to go to the very best restaurant every
night
take a chance try something new explore
you might learn something and the
information that you gain is going to be
worth more than one pretty good dinner
computer science can also help but to
make it easier on us and other places at
home and in the office if you’ve ever
had to tidy up your wardrobe you run
into a particularly agonizing decision
you have to decide what things you’re
going to keep and what things you’re
going to give away Martha Stewart turns
out to have thought very hard about this
and she has some good advice
she says ask yourself four questions how
long have I had it does it still
function is it a duplicate of something
that I already own and when was the last
time I wore it or used it but there’s
another group of experts who perhaps
thought even harder about this problem
and they would say that one of these
questions is more important than the
others those experts the people who
design the memory systems of computers
most computers have two kinds of memory
systems a fast memory system like a set
of memory chips that has limited
capacity because those chips are
expensive and a slow memory system which
is much larger in order for the computer
to operate as efficiently as possible
you want to try and make sure that the
pieces of information that you want to
access are in the fast memory system so
that you can get to them quickly each
time you access a piece of information
it’s loaded into the fast memory and the
computer has to decide which item it has
to remove from that memory because it
has limited capacity over the years
computer scientists have tried a few
different strategies for deciding what
to remove from the fast memory they’ve
tried things like choosing something at
random or applying what’s called the
first-in-first-out principle which means
removing the item which has been in the
memory for the longest but the strategy
that’s most effective focuses on the
items which have been least recently
used this says if you’re going to decide
to remove something from memory
what you should take out is the thing
which was last accessed the furthest in
the past and there’s a certain kind of
logic to this if it’s been a long time
since you last access that piece of
information it’s probably gonna be a
long time before you’re going to need to
access it again your wardrobe is just
like the computer’s memory you have
limited capacity and you need to try and
get in there the things that you want
that you’re that you’re most likely to
need so that you can get to them as
quickly as possible
recognizing that maybe it’s worth
applying the least recently used
principle to organizing your wardrobe as
well so if we go back to Martha’s for
questions the computer scientists would
say that of these the last one is the
most important this idea of organizing
things so that the things you’re most
likely to need are most accessible can
also be applied in your office the
Japanese economist Yukio Noguchi
actually invented a filing system that
has exactly this property he started
with a cardboard box and he put his
documents into the box from the left
hand side each time he’d add a document
he’d move what was in there along and
he’d add that document to the left-hand
side of the box and each time he
accessed a document he’d take it out
consult it and put it back in on the
left-hand side as a result the documents
would be ordered from left to right by
how recently they’d been used and he
found that he could very quickly find
what he was looking for by starting at
the left hand side of the box and
working his way to the right before you
– how him and implement this filing
system
it’s worth recognizing that you probably
already have that pile of papers on your
desk
typically maligned as messy and
disorganized a pile of papers is in fact
perfectly organized as long as you when
you take a paper out and put it back on
the top of the the pile then those
papers are going to be ordered from top
to bottom by how recently they were used
and you can probably pretty quickly find
what you’re looking for by starting at
the top of the pile organizing your
wardrobe or your desk are probably not
the most pressing problems in your life
sometimes the problems that we have to
solve are simply very very hard but even
in those cases computer science can
offer some strategies and perhaps some
solace the best algorithms are about
doing what makes the most sense in the
least amount of time when computers face
hard problems they deal with them by
making them into simpler problems by
making use of randomness by removing
constraints or by allowing
approximations solving those simpler
problems can give you insight into the
harder problems and sometimes produces
pretty good solutions in their own right
knowing all of this has helped me to
relax when I have to make decisions you
take the 37 percent rule for finding a
home as an example there’s no way that
you can consider all of the options so
you have to take a chance and even if
you follow the optimal strategy you’re
not guaranteed a perfect outcome if you
follow the 37 percent rule the
probability that you find the very best
place is funnily enough 37 percent you
fail most of the time but that’s the
best that you can do ultimately computer
science can help to make us more
forgiving of our own limitations you
can’t control outcomes just processes
and as long as you’ve used the best
process you’ve done the best that you
can sometimes those best processes
involve taking a chance not considering
all of your options or being willing to
settle for a pretty good solution these
are the concessions that we make when we
turn irrational they’re what being
rational means thank you
[Applause]
[Music]
if there’s one city in the world where
it’s hard to find a place to buy or rent
it’s Sydney if you try to find a home
here recently you’re familiar with the
problem every time you walk into an open
house you get some information about
what’s out there and what’s on the
market but every time you walk out
you’re running the risk of the very best
place passing you by so how do you know
when to switch from looking to being
ready to make an offer this is such a
cruel and familiar problem that it might
come as a surprise that it has a simple
solution 37%
if you want to maximize the probability
that you find the very best place you
should look at 37% of what’s on the
market and then make an offer on the
next place you see which is better than
anything that you’ve seen so far or if
you’re looking for a month take 37
percent of that time 11 days to set a
standard and then you’re ready to act we
know this because trying to find a place
to live is an example of an optimal
stopping problem a class of problems
that has been studied extensively by
mathematicians and computer scientists
I’m a computational cognitive scientist
I spend my time trying to understand how
it is that human minds work from our
amazing successes to our dismal failures
to do that I think about the
computational structure of the problems
that arise in everyday life and compare
the ideal solutions for those problems
to the way that we actually behave as a
side effect I get to see how applying a
little bit of computer science can make
human decision-making easier I have a
personal motivation for this growing up
in Perth as an overly cerebral kid
I would always try and act in the way
that I thought was rational reasoning
through every decision trying to figure
out the very best action to take but
this is an approach that doesn’t scale
up when you start to run into the sorts
of problems that arise in adult life at
one point I even tried to break up with
my girlfriend because trying to take
into account her preferences as well as
my own and then find perfect solutions
was just leaving me exhausted she
pointed out that I was taking the wrong
approach to solving this problem and she
later became my wife whether it’s as
basic as trying to decide what
restaurant to go to or as important as
trying to despair decide who to spend
the rest of your life with human lives
are filled with computational problems
that are just too hard to solve by
applying sheer effort for those problems
it’s worth consulting the experts
computer scientists when you’re looking
for life advice computer scientists
probably aren’t the first people you
think to talk to living life like a
computer stereotypically deterministic
exhaustive and exact doesn’t sound like
a lot of fun but thinking about the
computer science of human decisions
reveals that in fact we’ve got this
backwards when applied to the sorts of
difficult problems that arise in human
lives the way that computers actually
solve those problems looks a lot more
like the way that people really act take
the example of trying to decide what
restaurant to go to this is a problem as
a particular computational structure
you’ve got a set of options you’re going
to choose one of those options and
you’re going to face exactly the same
decision tomorrow in that situation you
run up against what computer scientists
call the Explorer exploit trade-off you
have to make a decision about whether
you’re going to try something new
exploring gathering some information
that you might be able to use in the
future or whether you’re going to go to
a place that you already know is pretty
good exploiting the information that
you’ve already gathered so far the
Explorer exploit trade-off shows up
anytime you have to choose between
trying something new and going with
something that you already know is
pretty good whether it’s listening to
music
or trying to decide who you’re going to
spend time with it’s also the problem
that technology companies face when
they’re trying to do something like
decide what ad to show on a webpage
should they show a new ad and learn
something about it or should they show
you an ad that they already know there’s
a pretty good chance you’re going to
click on over the last 60 years computer
scientists have made a lot of progress
understanding the Explorer exploit
trade-off and their results offer some
surprising insights when you’re trying
to decide what restaurant to go to the
first question you should ask yourself
is how much longer you’re going to be in
town if you’re just going to be there
for a short time then you should exploit
there’s no point gathering information
just go to a place you already know is
good but if you’re going to be there for
a longer time explore try something new
because the information you get is
something that can improve your choices
in the future the value of information
increases the more opportunities you’re
going to have to use it this principle
can give us insight into the structure
of a human life as well babies don’t
have a reputation for being particularly
rational they’re always trying new
things and you know trying to stick them
in their mouths but in fact this is
exactly what they should be doing there
in the explore phase of their lives and
some of those things could turn out to
be delicious at the other end of the
spectrum the old guy who always goes to
the same restaurant and always eats the
same thing isn’t boring
he’s optimal
he’s exploiting the knowledge that he’s
earned through a lifetime’s experience
more generally knowing about the
Explorer exploit trade-off can make it a
little easier for you to sort of relax
and go easier on yourself when you’re
trying to make a decision you don’t have
to go to the very best restaurant every
night
take a chance try something new explore
you might learn something and the
information that you gain is going to be
worth more than one pretty good dinner
computer science can also help but to
make it easier on us and other places at
home and in the office if you’ve ever
had to tidy up your wardrobe you run
into a particularly agonizing decision
you have to decide what things you’re
going to keep and what things you’re
going to give away Martha Stewart turns
out to have thought very hard about this
and she has some good advice
she says ask yourself four questions how
long have I had it does it still
function is it a duplicate of something
that I already own and when was the last
time I wore it or used it but there’s
another group of experts who perhaps
thought even harder about this problem
and they would say that one of these
questions is more important than the
others those experts the people who
design the memory systems of computers
most computers have two kinds of memory
systems a fast memory system like a set
of memory chips that has limited
capacity because those chips are
expensive and a slow memory system which
is much larger in order for the computer
to operate as efficiently as possible
you want to try and make sure that the
pieces of information that you want to
access are in the fast memory system so
that you can get to them quickly each
time you access a piece of information
it’s loaded into the fast memory and the
computer has to decide which item it has
to remove from that memory because it
has limited capacity over the years
computer scientists have tried a few
different strategies for deciding what
to remove from the fast memory they’ve
tried things like choosing something at
random or applying what’s called the
first-in-first-out principle which means
removing the item which has been in the
memory for the longest but the strategy
that’s most effective focuses on the
items which have been least recently
used this says if you’re going to decide
to remove something from memory
what you should take out is the thing
which was last accessed the furthest in
the past and there’s a certain kind of
logic to this if it’s been a long time
since you last access that piece of
information it’s probably gonna be a
long time before you’re going to need to
access it again your wardrobe is just
like the computer’s memory you have
limited capacity and you need to try and
get in there the things that you want
that you’re that you’re most likely to
need so that you can get to them as
quickly as possible
recognizing that maybe it’s worth
applying the least recently used
principle to organizing your wardrobe as
well so if we go back to Martha’s for
questions the computer scientists would
say that of these the last one is the
most important this idea of organizing
things so that the things you’re most
likely to need are most accessible can
also be applied in your office the
Japanese economist Yukio Noguchi
actually invented a filing system that
has exactly this property he started
with a cardboard box and he put his
documents into the box from the left
hand side each time he’d add a document
he’d move what was in there along and
he’d add that document to the left-hand
side of the box and each time he
accessed a document he’d take it out
consult it and put it back in on the
left-hand side as a result the documents
would be ordered from left to right by
how recently they’d been used and he
found that he could very quickly find
what he was looking for by starting at
the left hand side of the box and
working his way to the right before you
– how him and implement this filing
system
it’s worth recognizing that you probably
already have that pile of papers on your
desk
typically maligned as messy and
disorganized a pile of papers is in fact
perfectly organized as long as you when
you take a paper out and put it back on
the top of the the pile then those
papers are going to be ordered from top
to bottom by how recently they were used
and you can probably pretty quickly find
what you’re looking for by starting at
the top of the pile organizing your
wardrobe or your desk are probably not
the most pressing problems in your life
sometimes the problems that we have to
solve are simply very very hard but even
in those cases computer science can
offer some strategies and perhaps some
solace the best algorithms are about
doing what makes the most sense in the
least amount of time when computers face
hard problems they deal with them by
making them into simpler problems by
making use of randomness by removing
constraints or by allowing
approximations solving those simpler
problems can give you insight into the
harder problems and sometimes produces
pretty good solutions in their own right
knowing all of this has helped me to
relax when I have to make decisions you
take the 37 percent rule for finding a
home as an example there’s no way that
you can consider all of the options so
you have to take a chance and even if
you follow the optimal strategy you’re
not guaranteed a perfect outcome if you
follow the 37 percent rule the
probability that you find the very best
place is funnily enough 37 percent you
fail most of the time but that’s the
best that you can do ultimately computer
science can help to make us more
forgiving of our own limitations you
can’t control outcomes just processes
and as long as you’ve used the best
process you’ve done the best that you
can sometimes those best processes
involve taking a chance not considering
all of your options or being willing to
settle for a pretty good solution these
are the concessions that we make when we
turn irrational they’re what being
rational means thank you
[Applause]
[Music]
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