hello so projected here you have the image of the Italian village where I
image of the Italian village where I
image of the Italian village where I grew up it’s at the bottom of a valley
grew up it’s at the bottom of a valley
grew up it’s at the bottom of a valley at the beginning of the Alps and it’s
at the beginning of the Alps and it’s
at the beginning of the Alps and it’s close-knit community was very good for
close-knit community was very good for
close-knit community was very good for me as I grew up it fostered my sense of
me as I grew up it fostered my sense of
me as I grew up it fostered my sense of health itself but it was an environment
health itself but it was an environment
health itself but it was an environment where there’s no science not only I
where there’s no science not only I
where there’s no science not only I never met or know of a scientist but I
never met or know of a scientist but I
never met or know of a scientist but I grew up convinced that scientists were a
grew up convinced that scientists were a
grew up convinced that scientists were a different kind of people they lived in a
different kind of people they lived in a
different kind of people they lived in a world that had nothing to do with mine
world that had nothing to do with mine
world that had nothing to do with mine so I think of it as a mine or miracle
so I think of it as a mine or miracle
so I think of it as a mine or miracle that I am a scientist nowadays the type
that I am a scientist nowadays the type
that I am a scientist nowadays the type of scientist I am though I don’t get to
of scientist I am though I don’t get to
of scientist I am though I don’t get to make discoveries in physics or biology
make discoveries in physics or biology
make discoveries in physics or biology or medicine rather I help researchers in
or medicine rather I help researchers in
or medicine rather I help researchers in all of these fields understand when they
all of these fields understand when they
all of these fields understand when they have a discovery how to interpret data
have a discovery how to interpret data
have a discovery how to interpret data to foster their research and today I
to foster their research and today I
to foster their research and today I would like to share with you some of the
would like to share with you some of the
would like to share with you some of the steps that scientists take to interpret
steps that scientists take to interpret
steps that scientists take to interpret data and to use them to build up their
data and to use them to build up their
data and to use them to build up their science work I like to do so because I
science work I like to do so because I
science work I like to do so because I think they are the logic and the mindset
think they are the logic and the mindset
think they are the logic and the mindset that’s behind them it’s important not
that’s behind them it’s important not
that’s behind them it’s important not only for scientists but for all of us as
only for scientists but for all of us as
only for scientists but for all of us as human beings and citizens so first of
human beings and citizens so first of
human beings and citizens so first of all let me convince you that there is
all let me convince you that there is
all let me convince you that there is something to talk about and things are
something to talk about and things are
something to talk about and things are not trivially self-evident to do so I
not trivially self-evident to do so I
not trivially self-evident to do so I would like to take you through a little
would like to take you through a little
would like to take you through a little journey of the some of the debates that
journey of the some of the debates that
journey of the some of the debates that we have in the press about the role of
we have in the press about the role of
we have in the press about the role of science data and sustainer the truth
science data and sustainer the truth
science data and sustainer the truth first of all there is the acknowledgment
first of all there is the acknowledgment
first of all there is the acknowledgment that nowadays we have a lot of data and
that nowadays we have a lot of data and
that nowadays we have a lot of data and indeed you can think about the big
indeed you can think about the big
indeed you can think about the big digital footprint that each of us has
digital footprint that each of us has
digital footprint that each of us has the movies we like the songs we listened
the movies we like the songs we listened
the movies we like the songs we listened to the people we talked to the topics
to the people we talked to the topics
to the people we talked to the topics that engages the stuff we buy how many
that engages the stuff we buy how many
that engages the stuff we buy how many steps we take a day everything is
steps we take a day everything is
steps we take a day everything is digitally recorded and can be possibly
digitally recorded and can be possibly
digitally recorded and can be possibly mined in addition to this data that it’s
mined in addition to this data that it’s
mined in addition to this data that it’s passively gathered technology has opened
passively gathered technology has opened
passively gathered technology has opened for us the opportunity to explore and
for us the opportunity to explore and
for us the opportunity to explore and measure variables that were completely
measure variables that were completely
measure variables that were completely out of our reach not too long ago for
out of our reach not too long ago for
out of our reach not too long ago for example I work in general
example I work in general
example I work in general texts and it’s now cheap and easy to get
texts and it’s now cheap and easy to get
texts and it’s now cheap and easy to get the entire DNA sequence of an individual
the entire DNA sequence of an individual
the entire DNA sequence of an individual we can measure the expression level of
we can measure the expression level of
we can measure the expression level of 20 30 thousands of genes in different
20 30 thousands of genes in different
20 30 thousands of genes in different tissues in our body and even at the
tissues in our body and even at the
tissues in our body and even at the single cell level medical imaging it’s
single cell level medical imaging it’s
single cell level medical imaging it’s very sophisticated in a high resolution
very sophisticated in a high resolution
very sophisticated in a high resolution and so on and so forth we indeed have
and so on and so forth we indeed have
and so on and so forth we indeed have much more data than we ever had before
much more data than we ever had before
much more data than we ever had before these abundance of data has generated a
these abundance of data has generated a
these abundance of data has generated a certain buoyancy there are many people
certain buoyancy there are many people
certain buoyancy there are many people that reflect on the opportunity that
that reflect on the opportunity that
that reflect on the opportunity that this presents and there is the
this presents and there is the
this presents and there is the convention out there that with all of
convention out there that with all of
convention out there that with all of these data we’re going to be able to
these data we’re going to be able to
these data we’re going to be able to tackle scientific questions any sort of
tackle scientific questions any sort of
tackle scientific questions any sort of question with much more precision in
question with much more precision in
question with much more precision in some of this discussion you’ll see
some of this discussion you’ll see
some of this discussion you’ll see different degrees of criticism on the
different degrees of criticism on the
different degrees of criticism on the traditional way of doing science but
traditional way of doing science but
traditional way of doing science but overall it’s a very optimistic view
overall it’s a very optimistic view
overall it’s a very optimistic view there is the notion fundamentally that
there is the notion fundamentally that
there is the notion fundamentally that with the data we are going to be able to
with the data we are going to be able to
with the data we are going to be able to get closer through the truth that we
get closer through the truth that we
get closer through the truth that we ever had before while there is this
ever had before while there is this
ever had before while there is this optimistic trend there is also a more
optimistic trend there is also a more
optimistic trend there is also a more pessimistic one that is linked to the
pessimistic one that is linked to the
pessimistic one that is linked to the fact that unfortunately a number of
fact that unfortunately a number of
fact that unfortunately a number of results published in a reputable
results published in a reputable
results published in a reputable scientific journal turned out to be
scientific journal turned out to be
scientific journal turned out to be unrep reducible that is when other
unrep reducible that is when other
unrep reducible that is when other scientists tried to redo the same
scientists tried to redo the same
scientists tried to redo the same experiment they did not get the same
experiment they did not get the same
experiment they did not get the same results this is very serious business
results this is very serious business
results this is very serious business and indeed the National Academy of
and indeed the National Academy of
and indeed the National Academy of Science for example has launched a
Science for example has launched a
Science for example has launched a series of initiatives to understand
series of initiatives to understand
series of initiatives to understand what’s behind this lack of
what’s behind this lack of
what’s behind this lack of reproducibility and it is a serious
reproducibility and it is a serious
reproducibility and it is a serious business because if this is the case we
business because if this is the case we
business because if this is the case we end up undermining the public confidence
end up undermining the public confidence
end up undermining the public confidence in science and indeed you can already
in science and indeed you can already
in science and indeed you can already see that there is a very serious
see that there is a very serious
see that there is a very serious challenge to scientific theory and even
challenge to scientific theory and even
challenge to scientific theory and even to recorded data a challenge that it’s
to recorded data a challenge that it’s
to recorded data a challenge that it’s based on emphasizing the fact that
based on emphasizing the fact that
based on emphasizing the fact that theories are not the truth and the data
theories are not the truth and the data
theories are not the truth and the data can be subject to different
can be subject to different
can be subject to different interpretation this is a mixed
interpretation this is a mixed
interpretation this is a mixed family negative view because if you
family negative view because if you
family negative view because if you think that there’s no truth out there to
think that there’s no truth out there to
think that there’s no truth out there to be reached there is no way we can
be reached there is no way we can
be reached there is no way we can progress towards it so why can we have
progress towards it so why can we have
progress towards it so why can we have such a disparate views of the importance
such a disparate views of the importance
such a disparate views of the importance of data and how easy it is to get to the
of data and how easy it is to get to the
of data and how easy it is to get to the truth it’s because doing science is not
truth it’s because doing science is not
truth it’s because doing science is not a simple matter let’s take a step back
a simple matter let’s take a step back
a simple matter let’s take a step back and rely on the help of people that have
and rely on the help of people that have
and rely on the help of people that have thought about these problems for a long
thought about these problems for a long
thought about these problems for a long time and let’s talk about you Hume
time and let’s talk about you Hume
time and let’s talk about you Hume formalize the problems here in terms of
formalize the problems here in terms of
formalize the problems here in terms of the problem of induction he notes that
the problem of induction he notes that
the problem of induction he notes that no matter how many white white swans we
no matter how many white white swans we
no matter how many white white swans we see we cannot conclude that all the
see we cannot conclude that all the
see we cannot conclude that all the white all the swans are white there
white all the swans are white there
white all the swans are white there might be one Black Swan out there that
might be one Black Swan out there that
might be one Black Swan out there that we have not yet seen generally speaking
we have not yet seen generally speaking
we have not yet seen generally speaking we cannot reach a general conclusion
we cannot reach a general conclusion
we cannot reach a general conclusion from individual observations no matter
from individual observations no matter
from individual observations no matter how many they are and no matter how
how many they are and no matter how
how many they are and no matter how thoroughly we go through them maybe with
thoroughly we go through them maybe with
thoroughly we go through them maybe with the aid of a computer it’s simply a
the aid of a computer it’s simply a
the aid of a computer it’s simply a logical fallacy this is a rather
logical fallacy this is a rather
logical fallacy this is a rather surprising fact because that’s what we
surprising fact because that’s what we
surprising fact because that’s what we all do all the time we look around
all do all the time we look around
all do all the time we look around ourselves make observations and make
ourselves make observations and make
ourselves make observations and make conclusions from them now I think we can
conclusions from them now I think we can
conclusions from them now I think we can all accept that as individuals we mind
all accept that as individuals we mind
all accept that as individuals we mind not in a person will may not act in a
not in a person will may not act in a
not in a person will may not act in a perfectly rational fashion but we are
perfectly rational fashion but we are
perfectly rational fashion but we are certainly not ready to accept that
certainly not ready to accept that
certainly not ready to accept that science is not a rational business so
science is not a rational business so
science is not a rational business so where do we go from there is it
where do we go from there is it
where do we go from there is it impossible to do science it is not and
impossible to do science it is not and
impossible to do science it is not and popper at the beginning of last century
popper at the beginning of last century
popper at the beginning of last century helped us formalize this clearly he
helped us formalize this clearly he
helped us formalize this clearly he noted that while it is true that we
noted that while it is true that we
noted that while it is true that we cannot conclude that all swans are white
cannot conclude that all swans are white
cannot conclude that all swans are white simply looking at many white swans we
simply looking at many white swans we
simply looking at many white swans we can clearly disprove this statement the
can clearly disprove this statement the
can clearly disprove this statement the moment we see a Black Swan it is not
moment we see a Black Swan it is not
moment we see a Black Swan it is not possible to prove that the theory is
possible to prove that the theory is
possible to prove that the theory is right on the basis of individual
right on the basis of individual
right on the basis of individual observations but it is possible to prove
observations but it is possible to prove
observations but it is possible to prove it that it’s wrong so the way to connect
it that it’s wrong so the way to connect
it that it’s wrong so the way to connect abstract truth within empirical
abstract truth within empirical
abstract truth within empirical observations it’s through the scientific
observations it’s through the scientific
observations it’s through the scientific method
method
method poppers describe the way scientists act
poppers describe the way scientists act
poppers describe the way scientists act in the following with the following
in the following with the following
in the following with the following example he says scientists create a
example he says scientists create a
example he says scientists create a theory from this theory they make
theory from this theory they make
theory from this theory they make deductions and then they go out and try
deductions and then they go out and try
deductions and then they go out and try to test this deduction they try to prove
to test this deduction they try to prove
to test this deduction they try to prove the theory wrong and if they do not
the theory wrong and if they do not
the theory wrong and if they do not succeed it does not mean that the theory
succeed it does not mean that the theory
succeed it does not mean that the theory has been proven right it’s simply
has been proven right it’s simply
has been proven right it’s simply corroborated by the data and if instead
corroborated by the data and if instead
corroborated by the data and if instead it’s a bad theory we can prove it wrong
it’s a bad theory we can prove it wrong
it’s a bad theory we can prove it wrong easily and we move on
easily and we move on
easily and we move on and that’s exactly what scientists do it
and that’s exactly what scientists do it
and that’s exactly what scientists do it may seems a bit awkward to think of
may seems a bit awkward to think of
may seems a bit awkward to think of trying to prove it your theory wrong but
trying to prove it your theory wrong but
trying to prove it your theory wrong but let me give you an example and think
let me give you an example and think
let me give you an example and think about climate change the status quo what
about climate change the status quo what
about climate change the status quo what everybody would believe to start with is
everybody would believe to start with is
everybody would believe to start with is that the determinant of climates stay
that the determinant of climates stay
that the determinant of climates stay the same over time now what scientists
the same over time now what scientists
the same over time now what scientists might try to do is to say well do we see
might try to do is to say well do we see
might try to do is to say well do we see evidence in the data that this cannot
evidence in the data that this cannot
evidence in the data that this cannot possibly be true
possibly be true
possibly be true can we contradict this hypothesis and
can we contradict this hypothesis and
can we contradict this hypothesis and now when you think about climate change
now when you think about climate change
now when you think about climate change you realize that even if it is logically
you realize that even if it is logically
you realize that even if it is logically possible to prove that the theory is
possible to prove that the theory is
possible to prove that the theory is wrong on the basis of observations it is
wrong on the basis of observations it is
wrong on the basis of observations it is not trivial because climate it’s such a
not trivial because climate it’s such a
not trivial because climate it’s such a complex things that you can explain
complex things that you can explain
complex things that you can explain almost every pattern that you see on the
almost every pattern that you see on the
almost every pattern that you see on the basis of every theory there are so many
basis of every theory there are so many
basis of every theory there are so many variables that you have to account for
variables that you have to account for
variables that you have to account for and because climate it’s so complex
and because climate it’s so complex
and because climate it’s so complex let’s try to abstract and consider a
let’s try to abstract and consider a
let’s try to abstract and consider a much simpler hypothesis that still
much simpler hypothesis that still
much simpler hypothesis that still allows us to make the reflection that
allows us to make the reflection that
allows us to make the reflection that I’m trying to do suppose you find a coin
I’m trying to do suppose you find a coin
I’m trying to do suppose you find a coin in your backyard and your hypothesis is
in your backyard and your hypothesis is
in your backyard and your hypothesis is that this coin is unbiased you want to
that this coin is unbiased you want to
that this coin is unbiased you want to test it and you think that to test it
test it and you think that to test it
test it and you think that to test it for example you could flip the coin 10
for example you could flip the coin 10
for example you could flip the coin 10 times and see what your outcomes are you
times and see what your outcomes are you
times and see what your outcomes are you could see anywhere from 0 to 10 heads
could see anywhere from 0 to 10 heads
could see anywhere from 0 to 10 heads even if the coin is unbiased so where is
even if the coin is unbiased so where is
even if the coin is unbiased so where is your contradiction here is where
your contradiction here is where
your contradiction here is where statistics and my day job comes in
statistics and my day job comes in
statistics and my day job comes in Fisher was a contemporary earth copper
Fisher was a contemporary earth copper
Fisher was a contemporary earth copper and formalized for us a way of reasoning
and formalized for us a way of reasoning
and formalized for us a way of reasoning the scientists use all the time his
the scientists use all the time his
the scientists use all the time his well when your hypothesis cannot be
well when your hypothesis cannot be
well when your hypothesis cannot be strictly logically contradicted on the
strictly logically contradicted on the
strictly logically contradicted on the basis of the data because multiple
basis of the data because multiple
basis of the data because multiple outcomes are possible what you should do
outcomes are possible what you should do
outcomes are possible what you should do is to calculate the probability of the
is to calculate the probability of the
is to calculate the probability of the outcomes under your hypothesis and see
outcomes under your hypothesis and see
outcomes under your hypothesis and see if what you get to see in reality it’s
if what you get to see in reality it’s
if what you get to see in reality it’s likely or not so in the case of the coin
likely or not so in the case of the coin
likely or not so in the case of the coin flips for example we could evaluate the
flips for example we could evaluate the
flips for example we could evaluate the probability that we see at most one hat
probability that we see at most one hat
probability that we see at most one hat or at most one tail in out of ten flips
or at most one tail in out of ten flips
or at most one tail in out of ten flips and if our coin is fair that’s just two
and if our coin is fair that’s just two
and if our coin is fair that’s just two out of a hundred so you are going to say
out of a hundred so you are going to say
out of a hundred so you are going to say well if I just saw at most one hat
well if I just saw at most one hat
well if I just saw at most one hat that’s quite unlikely I am going to
that’s quite unlikely I am going to
that’s quite unlikely I am going to reject the hypothesis that my coin is
reject the hypothesis that my coin is
reject the hypothesis that my coin is unbiased so now we got to see what it’s
unbiased so now we got to see what it’s
unbiased so now we got to see what it’s a scientific discovery a scientific
a scientific discovery a scientific
a scientific discovery a scientific discovery it’s not a positive
discovery it’s not a positive
discovery it’s not a positive affirmative statement I have found this
affirmative statement I have found this
affirmative statement I have found this new pattern it’s rather a very nuanced
new pattern it’s rather a very nuanced
new pattern it’s rather a very nuanced one we say that we have a discovery when
one we say that we have a discovery when
one we say that we have a discovery when the patterns we get to see in the data
the patterns we get to see in the data
the patterns we get to see in the data are very unlikely under the current
are very unlikely under the current
are very unlikely under the current understanding of the world
understanding of the world
understanding of the world now it’s nuanced and so you can see that
now it’s nuanced and so you can see that
now it’s nuanced and so you can see that it’s not something that leads itself
it’s not something that leads itself
it’s not something that leads itself well to tweets or headlines or that
well to tweets or headlines or that
well to tweets or headlines or that immediately arouses the enthusiasm of
immediately arouses the enthusiasm of
immediately arouses the enthusiasm of donors but it’s not nuanced because
donors but it’s not nuanced because
donors but it’s not nuanced because scientists don’t know how to stand up
scientists don’t know how to stand up
scientists don’t know how to stand up and make their choices may make
and make their choices may make
and make their choices may make decisions it’s new ones because they are
decisions it’s new ones because they are
decisions it’s new ones because they are hope themselves to very high standards
hope themselves to very high standards
hope themselves to very high standards they are not going to say things that
they are not going to say things that
they are not going to say things that are false let’s go back to the big data
are false let’s go back to the big data
are false let’s go back to the big data with which we started and see does the
with which we started and see does the
with which we started and see does the abundance of data in our day and age
abundance of data in our day and age
abundance of data in our day and age change the way we do science in many
change the way we do science in many
change the way we do science in many ways it does substantially it does
ways it does substantially it does
ways it does substantially it does because having a lot of data allows us
because having a lot of data allows us
because having a lot of data allows us to test many more hypotheses than we
to test many more hypotheses than we
to test many more hypotheses than we ever were before and in fact we get to
ever were before and in fact we get to
ever were before and in fact we get to see the data even before we formulate
see the data even before we formulate
see the data even before we formulate our hypothesis to fix ideas let’s
our hypothesis to fix ideas let’s
our hypothesis to fix ideas let’s consider the case of cancer biomarkers
consider the case of cancer biomarkers
consider the case of cancer biomarkers unfortunately for many cancers we have
unfortunately for many cancers we have
unfortunately for many cancers we have very little therapists
very little therapists
very little therapists and all of these therapies have serious
and all of these therapies have serious
and all of these therapies have serious side effects and people react different
side effects and people react different
side effects and people react different to different therapies so it will be
to different therapies so it will be
to different therapies so it will be wonderful if for one patient we were to
wonderful if for one patient we were to
wonderful if for one patient we were to know what is the best treatment for this
know what is the best treatment for this
know what is the best treatment for this patient so that he gets immediately
patient so that he gets immediately
patient so that he gets immediately better and he doesn’t suffer useless
better and he doesn’t suffer useless
better and he doesn’t suffer useless side effects and unfortunately we don’t
side effects and unfortunately we don’t
side effects and unfortunately we don’t know how to do this treatment assignment
know how to do this treatment assignment
know how to do this treatment assignment well so scientists are working very hard
well so scientists are working very hard
well so scientists are working very hard to find biomarkers that is lab tests you
to find biomarkers that is lab tests you
to find biomarkers that is lab tests you could do to somebody to decide what is
could do to somebody to decide what is
could do to somebody to decide what is the best treatment how do they do them
the best treatment how do they do them
the best treatment how do they do them today because it’s so easy to get data
today because it’s so easy to get data
today because it’s so easy to get data what they’ll do for example its measured
what they’ll do for example its measured
what they’ll do for example its measured the expression level of twenty thirty
the expression level of twenty thirty
the expression level of twenty thirty thousand genes in the tissue of the
thousand genes in the tissue of the
thousand genes in the tissue of the cancer prior to treatment and then see
cancer prior to treatment and then see
cancer prior to treatment and then see if the expression levels of any of these
if the expression levels of any of these
if the expression levels of any of these genes correlates with outcome twenty
genes correlates with outcome twenty
genes correlates with outcome twenty years ago they would not have been able
years ago they would not have been able
years ago they would not have been able to do this they would have had to limit
to do this they would have had to limit
to do this they would have had to limit themselves to a handful of protein that
themselves to a handful of protein that
themselves to a handful of protein that they would have picked on the basis of
they would have picked on the basis of
they would have picked on the basis of their prior knowledge so you can see
their prior knowledge so you can see
their prior knowledge so you can see it’s great progress we can cast a wide
it’s great progress we can cast a wide
it’s great progress we can cast a wide net we don’t have to rely on limited
net we don’t have to rely on limited
net we don’t have to rely on limited prior knowledge but testing a lot of
prior knowledge but testing a lot of
prior knowledge but testing a lot of things comes with some problems let’s go
things comes with some problems let’s go
things comes with some problems let’s go back to our coin flip example we sort of
back to our coin flip example we sort of
back to our coin flip example we sort of agreed that we would reject the
agreed that we would reject the
agreed that we would reject the hypothesis that the coin is unbiased if
hypothesis that the coin is unbiased if
hypothesis that the coin is unbiased if I get to see at most one head or at most
I get to see at most one head or at most
I get to see at most one head or at most one tail because that happens two times
one tail because that happens two times
one tail because that happens two times out of a hundred now imagine you do that
out of a hundred now imagine you do that
out of a hundred now imagine you do that test for twenty thousand coins even if
test for twenty thousand coins even if
test for twenty thousand coins even if all the coins are unbiased you are going
all the coins are unbiased you are going
all the coins are unbiased you are going to expect that four hundred such coins
to expect that four hundred such coins
to expect that four hundred such coins will come up with this outcome so you
will come up with this outcome so you
will come up with this outcome so you will reject the hypothesis of them being
will reject the hypothesis of them being
will reject the hypothesis of them being unbiased broadly four hundred times you
unbiased broadly four hundred times you
unbiased broadly four hundred times you might discover four hundred genes that
might discover four hundred genes that
might discover four hundred genes that seem to be good biomarkers for cancer
seem to be good biomarkers for cancer
seem to be good biomarkers for cancer even if they have really nothing to do
even if they have really nothing to do
even if they have really nothing to do with it now this phenomenon has
with it now this phenomenon has
with it now this phenomenon has something to do with the lack of
something to do with the lack of
something to do with the lack of reproducibility that I mentioned at the
reproducibility that I mentioned at the
reproducibility that I mentioned at the beginning and one way of rationalizing
beginning and one way of rationalizing
beginning and one way of rationalizing it is to see that if you look hard
it is to see that if you look hard
it is to see that if you look hard enough you are going to find
enough you are going to find
enough you are going to find if you go out and you look at
if you go out and you look at
if you go out and you look at correlation between every possible pair
correlation between every possible pair
correlation between every possible pair of variable Under the Sun you’re going
of variable Under the Sun you’re going
of variable Under the Sun you’re going to find pairs of variables that seem to
to find pairs of variables that seem to
to find pairs of variables that seem to correlate even if they have nothing to
correlate even if they have nothing to
correlate even if they have nothing to do with each other so scientists are
do with each other so scientists are
do with each other so scientists are aware of this fact sometimes they forget
aware of this fact sometimes they forget
aware of this fact sometimes they forget X please especially when the number of
X please especially when the number of
X please especially when the number of hypotheses tested it’s not explicit but
hypotheses tested it’s not explicit but
hypotheses tested it’s not explicit but most of the time they are very aware and
most of the time they are very aware and
most of the time they are very aware and they try to correct for this phenomenon
they try to correct for this phenomenon
they try to correct for this phenomenon so if you think back of our coin flip
so if you think back of our coin flip
so if you think back of our coin flip examples they may decide that if we are
examples they may decide that if we are
examples they may decide that if we are testing 20000 coins we are going to up
testing 20000 coins we are going to up
testing 20000 coins we are going to up the ante for our surprise level we are
the ante for our surprise level we are
the ante for our surprise level we are not going to declare a coin unbiased as
not going to declare a coin unbiased as
not going to declare a coin unbiased as long as I see at most one head or one
long as I see at most one head or one
long as I see at most one head or one tail but I only want to see only heads
tail but I only want to see only heads
tail but I only want to see only heads or only tails I want to have a very very
or only tails I want to have a very very
or only tails I want to have a very very biased result that takes care of some of
biased result that takes care of some of
biased result that takes care of some of the false positives because now this is
the false positives because now this is
the false positives because now this is a very unlikely event but it makes it
a very unlikely event but it makes it
a very unlikely event but it makes it difficult for us to find the coins that
difficult for us to find the coins that
difficult for us to find the coins that are really biased and it also gives us a
are really biased and it also gives us a
are really biased and it also gives us a very skewed view of the world because
very skewed view of the world because
very skewed view of the world because now we are going to focus our attention
now we are going to focus our attention
now we are going to focus our attention only on those coins that gave us only
only on those coins that gave us only
only on those coins that gave us only heads or only tails we are going to
heads or only tails we are going to
heads or only tails we are going to think that they are extremely biased we
think that they are extremely biased we
think that they are extremely biased we are going to think of their probability
are going to think of their probability
are going to think of their probability of heads it’s 1 or 0 and that might not
of heads it’s 1 or 0 and that might not
of heads it’s 1 or 0 and that might not be the case because the outcome of the
be the case because the outcome of the
be the case because the outcome of the experiment is somewhat random
experiment is somewhat random
experiment is somewhat random nevertheless so an analogy that might be
nevertheless so an analogy that might be
nevertheless so an analogy that might be useful here is that of the winner’s
useful here is that of the winner’s
useful here is that of the winner’s curse in auctions the person that walks
curse in auctions the person that walks
curse in auctions the person that walks home with the work of art it’s very
home with the work of art it’s very
home with the work of art it’s very happy because they got to bring home the
happy because they got to bring home the
happy because they got to bring home the things that they loved at the same time
things that they loved at the same time
things that they loved at the same time they are keenly aware that they might
they are keenly aware that they might
they are keenly aware that they might have paid too much because after all
have paid too much because after all
have paid too much because after all they were the only person in the room
they were the only person in the room
they were the only person in the room ready to put out that amount of money
ready to put out that amount of money
ready to put out that amount of money for that piece so when we are very
for that piece so when we are very
for that piece so when we are very selective in finding out which genes
selective in finding out which genes
selective in finding out which genes might be the one that is associated with
might be the one that is associated with
might be the one that is associated with treatment we are going to get a bias
treatment we are going to get a bias
treatment we are going to get a bias picked picture of the actual role of
picked picture of the actual role of
picked picture of the actual role of that gene
that gene
that gene so I’ve taken you for a lot of complex
so I’ve taken you for a lot of complex
so I’ve taken you for a lot of complex and abstract reasoning and let’s try to
and abstract reasoning and let’s try to
and abstract reasoning and let’s try to summarize what I would like my message
summarize what I would like my message
summarize what I would like my message to be firstly I hope I would convince
to be firstly I hope I would convince
to be firstly I hope I would convince you that the data does not stick by
you that the data does not stick by
you that the data does not stick by itself we need a very sophisticated
itself we need a very sophisticated
itself we need a very sophisticated reasoning to see how we can use the data
reasoning to see how we can use the data
reasoning to see how we can use the data to learn from it and what type of
to learn from it and what type of
to learn from it and what type of statements we can make then I think that
statements we can make then I think that
statements we can make then I think that it’s absolutely true that having a lot
it’s absolutely true that having a lot
it’s absolutely true that having a lot of data has changed the way we do
of data has changed the way we do
of data has changed the way we do science and we have to change also the
science and we have to change also the
science and we have to change also the paradigm that we have grown used I’m
paradigm that we have grown used I’m
paradigm that we have grown used I’m sure you also all studied in high school
sure you also all studied in high school
sure you also all studied in high school that you formulate an hypothesis that
that you formulate an hypothesis that
that you formulate an hypothesis that you get the data to test it and you see
you get the data to test it and you see
you get the data to test it and you see if you validate it or not well now we
if you validate it or not well now we
if you validate it or not well now we get data before we formulate our
get data before we formulate our
get data before we formulate our hypothesis so how is our machinery going
hypothesis so how is our machinery going
hypothesis so how is our machinery going to change people are working very
to change people are working very
to change people are working very actively on this all over the world and
actively on this all over the world and
actively on this all over the world and partially also at Stanford in your
partially also at Stanford in your
partially also at Stanford in your backyard as I said a lot of abstract
backyard as I said a lot of abstract
backyard as I said a lot of abstract concepts and maybe if I told you a
concepts and maybe if I told you a
concepts and maybe if I told you a success story in science you would have
success story in science you would have
success story in science you would have been more inspiring and more catchy and
been more inspiring and more catchy and
been more inspiring and more catchy and so I’m sorry I did not deliver that but
so I’m sorry I did not deliver that but
so I’m sorry I did not deliver that but I’m only very partially sorry because my
I’m only very partially sorry because my
I’m only very partially sorry because my goal here was to reaffirm complexity
goal here was to reaffirm complexity
goal here was to reaffirm complexity science it’s not easy just as life is
science it’s not easy just as life is
science it’s not easy just as life is not easy and we cannot get away with it
not easy and we cannot get away with it
not easy and we cannot get away with it if we limit ourselves to statements that
if we limit ourselves to statements that
if we limit ourselves to statements that we can make in a hundred and forty
we can make in a hundred and forty
we can make in a hundred and forty characters we are not going to go to
characters we are not going to go to
characters we are not going to go to very interesting places slogans are
very interesting places slogans are
very interesting places slogans are powerful they’re catchy but they are
powerful they’re catchy but they are
powerful they’re catchy but they are also very dangerous so let me conclude
also very dangerous so let me conclude
also very dangerous so let me conclude with some poetry rimmel a V was an
with some poetry rimmel a V was an
with some poetry rimmel a V was an Italian Jew and he was imprisoned in aus
Italian Jew and he was imprisoned in aus
Italian Jew and he was imprisoned in aus which in the books he wrote about his
which in the books he wrote about his
which in the books he wrote about his experience he recounts an episode when
experience he recounts an episode when
experience he recounts an episode when one of his fellow prisoners looking for
one of his fellow prisoners looking for
one of his fellow prisoners looking for some destruction asked him for lessons
some destruction asked him for lessons
some destruction asked him for lessons in Italian and so he starts teaching the
in Italian and so he starts teaching the
in Italian and so he starts teaching the basics of it all
basics of it all
basics of it all and thinking of his mother tongue he
and thinking of his mother tongue he
and thinking of his mother tongue he ends up reciting for his fellow prisoner
ends up reciting for his fellow prisoner
ends up reciting for his fellow prisoner a few verses from Dante’s Divine Comedy
a few verses from Dante’s Divine Comedy
a few verses from Dante’s Divine Comedy in the hell they sat in this setting the
in the hell they sat in this setting the
in the hell they sat in this setting the poet meets alesis who finds himself in
poet meets alesis who finds himself in
poet meets alesis who finds himself in hell because he did not respect
hell because he did not respect
hell because he did not respect boundaries he pushed his boat out of the
boundaries he pushed his boat out of the
boundaries he pushed his boat out of the limits of the world that he was supposed
limits of the world that he was supposed
limits of the world that he was supposed to be in Dante
to be in Dante
to be in Dante puts Ulysses in hell but he’s very
puts Ulysses in hell but he’s very
puts Ulysses in hell but he’s very admired he really admires him so in
admired he really admires him so in
admired he really admires him so in Elise’s word he puts in Ulysses mouth a
Elise’s word he puts in Ulysses mouth a
Elise’s word he puts in Ulysses mouth a little speech to his fellow travelers
little speech to his fellow travelers
little speech to his fellow travelers and in this speech Ulysses is trying to
and in this speech Ulysses is trying to
and in this speech Ulysses is trying to convince them not to go home to Ithaca
convince them not to go home to Ithaca
convince them not to go home to Ithaca but to continue the exploration there
but to continue the exploration there
but to continue the exploration there are words that every Italian know
are words that every Italian know
are words that every Italian know because we studied them in high school
because we studied them in high school
because we studied them in high school but they have a very profound resonance
but they have a very profound resonance
but they have a very profound resonance spoken from ours which because they
spoken from ours which because they
spoken from ours which because they remind us that we are all called to be
remind us that we are all called to be
remind us that we are all called to be scientists we are all called to use our
scientists we are all called to use our
scientists we are all called to use our logic our brain as much as we can to
logic our brain as much as we can to
logic our brain as much as we can to keep our prejudice at bay and to work as
keep our prejudice at bay and to work as
keep our prejudice at bay and to work as hard as we can to increase our
hard as we can to increase our
hard as we can to increase our understanding of the world around us and
understanding of the world around us and
understanding of the world around us and if we don’t do that we incur in grave
if we don’t do that we incur in grave
if we don’t do that we incur in grave danger
danger
danger so the Italian turd Sina sounds like
so the Italian turd Sina sounds like
so the Italian turd Sina sounds like considerate love ostracism Enza fatten
considerate love ostracism Enza fatten
considerate love ostracism Enza fatten on foster fever coma bruty matter seguir
on foster fever coma bruty matter seguir
on foster fever coma bruty matter seguir veer to TA and Kenosha Anza and here you
veer to TA and Kenosha Anza and here you
veer to TA and Kenosha Anza and here you have the translation you find in one of
have the translation you find in one of
have the translation you find in one of ladies translations think of your breed
ladies translations think of your breed
ladies translations think of your breed for brutish ignorance your mettle was
for brutish ignorance your mettle was
for brutish ignorance your mettle was not made you were made men to follow
not made you were made men to follow
not made you were made men to follow after knowledge and excellence
”
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