How algorithms shape our world Kevin Slavin
this is a photograph by the artist
Michael Najjar and it’s real in the
sense that he went there to Argentina to
take the photo but it’s also a fiction
there’s a lot of work that went into it
after that and what he’s done is he’s
actually reshaped digitally all of the
contours of the mountains to follow the
vicissitudes of the Dow Jones index so
what you see that precipice that high
precipice with the valley is the 2008
financial crisis the photo was made when
we were deep in the valley over there I
don’t know where we are now this is the
Hang Seng Index or Hong Kong and similar
topography I wonder why and this is art
right this is metaphor but I think the
point is is that this is metaphor with
teeth and it’s with those teeth that I
want to propose today that we rethink a
little bit about the role of
contemporary math not just financial
math but math in general that it’s
transition from being something that we
sort of extract and derive from the
world to something that actually starts
to shape it the world around us in the
world inside us and it specifically
algorithms which are basically the math
that computers used to decide stuff they
acquire the sensibility of truth because
they repeat over and over again and they
kind of ossify and calcify and they kind
of become real and I was thinking about
this of all places on a transatlantic
flight a couple years ago because I
happen to be seated next to a Hungarian
physicist about my age and we were
talking about what life was like during
the Cold War for physicists in Hungary
and I said so what were you doing and he
said well we were mostly breaking
stealth and I said that’s a good job
that’s interesting how does that work
and so to understand that you have to
understand a little bit about how
stealth works and so this is a
oversimplification but basically it’s
not like you can just pass a radar
signal right through 156 tons of steel
in the sky it’s not just going to
disappear
but if you can take this big massive
thing and you could turn it into a
million little things something like a
flock of birds well then the radar
that’s looking for that has to be able
to see every flock of birds in the sky
and if you’re a radar that’s a really
bad job and he said yeah he said but
that’s if you’re a radar he said so we
didn’t use a radar we built a black box
that was looking for electrical signals
electronic communication and whenever we
saw a flock of birds that had electronic
communication we thought probably has
something to do with the Americans and I
said yeah that’s that’s good that’s good
so you’ve effectively negated 60 years
of aeronautical research what’s your act
to you know like what do you do when you
grow up and he said he said well you
know financial services and I said oh
because those have been in the news
lately and I said I said how does that
work and I said well there’s 2,000
physicists on Wall Street now and I’m
one of them and I said well so what’s
the black box for Wall Street and he
said well it’s funny that you asked that
because it’s actually called black box
trading and it’s also sometimes called
algo trading algorithmic trading and
algorithmic trading involved in part
because institutional traders have the
same problems that the United States
airforce had which is that they’re
moving these positions whether it’s
Procter and Gamble or etc or whatever
they’re moving like a million shares of
something through the market and if they
do that all at once it’s like playing
poker and just going all-in right away
right you just tip your hand and so they
have to find a way and they use
algorithms to do this to break up that
big thing into a million little
transactions and the magic and the
horror of that is is that the same math
that you use to break up the big thing
into a million little things can be used
to find a million little things and sew
them back together and figure out what’s
actually happening in the market so if
you need to have some image of what’s
happening in the stock market right now
what you can picture is a bunch of
algorithms that are basically programmed
to hide
and a bunch of algorithms that are
programmed to go find them and act and
all of that’s great and it’s fine and
that’s 70% of the United States stock
where 70% of the operating system
formerly known as your pension your your
mortgage and what could go wrong right
what could go wrong is is that a year
ago 9% of the entire market just
disappears in five minutes and they
called it the flash crash of 2:45 right
all of a sudden 9% just goes away and
nobody to this day can even agree on
what happened because nobody ordered it
nobody asked for it nobody had any
control over what was actually happening
all they had was just a monitor in front
of them that had the numbers on it and
just a red button that said stop and
that’s the thing right is is that we’re
writing things we’re writing these
things that we can no longer read and
it’s we’ve we’ve rendered something kind
of illegible and we’ve lost the sense of
what’s actually happening in this world
that we’ve made and we’re starting to
make our way there’s a company in Boston
called Nanak’s and they use math and
magic and I don’t know what and they
reach in to all the market data and they
find actually sometimes some of these
algorithms and they when they find them
they they pull them out and they pin
them to the wall like butterflies and
they do what we’ve always done when
confronted with huge amounts of data
that we don’t understand which is that
they give them a name and a story so
this is one that they found they called
the knife the carnival the Boston
shuffler Twilight and the gag is that of
course these aren’t just running through
the market right you can find these
kinds of things
wherever you look once you learn how to
look for them right you can find it here
this book about flies that you may have
been looking at on Amazon you may have
noticed it when its price started at 1.7
million dollars it’s
out-of-print still if you had bought it
at 1.7 it would have been a bargain a
few hours later it had gone up to twenty
three point six million dollars plus
shipping and handling and the question
is nobody was buying or selling anything
what was happening and you see this
behavior on Amazon as surely as you see
it on Wall Street and when you see this
kind of behavior what you see is the
evidence of algorithms in conflict
algorithms locked in loops with each
other without any human oversight
without any adult supervision to say
actually 1.7 million is plenty you stick
with it and as with Amazon so it is with
Netflix and so Netflix has gone through
several different algorithms over the
years they started with cinema and
they’ve they’ve tried a bunch of others
there’s dinosaur planet there’s gravity
they’re using pragmatic chaos now
pragmatic chaos is like all of Netflix
algorithms trying to do the same thing
it’s trying to get a grasp on you on the
firmware inside the human skull so that
it can recommend what movie you might
want to watch next which is a very very
difficult problem but the difficulty of
the problem and the fact that we don’t
really quite have it down it doesn’t
take away from the effects the pragmatic
chaos has bring out a chaos like all
Netflix algorithms determines in the end
60% of what movies end up being rented
right so one piece of code with one idea
about you is responsible for 60% of
those movies but what if you could rate
those movies before they get made right
wouldn’t that be handy well so a few
data scientists from the UK or in
Hollywood and they have story algorithms
and company called epic oh jokes and you
can run your script through there and
they can tell you quantifiably that
that’s a 30 million dollar movie or a
200 million dollar movie and the thing
is is that this isn’t Google right this
isn’t information
these aren’t financial stats this is
culture and what you see here or what
you don’t really see normally is is that
these are the physics of culture and if
these algorithms like the algorithms on
Wall
Street just crashed one day and went
awry how would we know what would it
look like and they’re in your house
right there in your house right these
are two algorithms competing for your
living room these are two different
cleaning robots that have very different
ideas about what clean means and you can
see it if you slow it down and attach
lights to them and there’s sort of like
secret architects in your bedroom yeah
and the idea that architecture itself is
somehow subject to algorithmic
optimization is not far-fetched it’s
super real and it’s happening around you
you feel it most when you’re in a sealed
metal box a new style elevator they’re
called destination control elevators
these are the ones where if to press
what floor you’re going to go to before
you get in the elevator and it uses
what’s called a bin packing algorithm so
none of this mishegoss of just letting
everybody go into whatever car they want
everybody wants to go the tenth floor
goes into car two and everybody wants to
go the third floor goes into car five
and the problem with that is is that
people freak out people panic and you
see why right you see why it’s because
the elevator is missing some important
instrumentation like the buttons right
like the things that people use all it
has is just the number that moves up or
down and that red button that says stop
and this is what we’re designing for
we’re designing for this kind of machine
dialect
all right and how far can you take that
how far can you take it you can take it
really really far and so let me take it
back
to Wall Street okay because the
algorithms of Wall Street are dependent
on one quality above all else which is
speed and they operate on milliseconds
and microseconds and just to give you a
sense of what microseconds are it takes
you five hundred thousand microseconds
just to click a mouse but if you’re a
Wall Street algorithm and you’re five
microseconds behind you’re a loser so if
you were an algorithm you’d look for an
architect like the one that I met in
Frankfurt who was hollowing out a
skyscraper throwing out all the
furniture all the infrastructure for
human use and just running
steel on the floors to get ready for the
stacks of servers to go in all so that
an algorithm could get close to the
internet and you think of the Internet
as this kind of distributed system and
of course it is but it’s distributed
from places right in New York this is
where it’s distributed from its carrier
hotel located on Hudson Street and this
is really where the wires come right up
into the city and the reality is is that
the further away you are from that
you’re a few microseconds behind every
time these guys down a Wall Street Marco
Polo and Cherokee Nation they’re eight
microseconds behind all these guys going
in to the empty buildings being hollowed
out up around the carrier hotel right
and that’s going to keep happening we’re
going to keep hollowing them out because
you inch for inch and pound for pound
and dollar for dollar none of you could
squeeze revenue out of that space like
the Boston shuffler could but if you
zoom out if you zoom out you would see
an 825 mile trench between New York City
and Chicago’s been built over the last
few years by a company called spread
networks this is a fiber-optic cable
that was laid between those two cities
to just be able to traffic one signal 37
times faster than you can click a mouse
just for these algorithms just for the
carnival and the knife and when you
think about this that we’re running
through the United States with dynamite
and rock saws so that an algorithm can
close the deal three microseconds faster
all for a communications framework that
no human will ever know that’s a kind of
manifest destiny and we’ll always look
for a new frontier and fortunately we
have our work cut out for us this is
just theoretical this is some
mathematicians at MIT and the truth is I
don’t really understand a lot of what
they’re talking about it involves light
cones and quantum entanglement and I
don’t really understand any of that but
I can
this map and what this map says is is
that if you’re trying to make money on
the markets where the red dots are
that’s where people are where the cities
are your going to have to put the
servers where the blue dots are to do
that most effectively and the thing that
you might have noticed about those blue
dots is that a lot of them are in the
middle of the ocean so that’s what we’ll
do we’ll build bubbles or something or
or platforms will actually part the
water right to pull money out of the air
because it’s a bright future if you’re
an algorithm and it’s not the money
that’s so interesting actually it’s what
the money motivates right that we’re
actually terraforming the earth itself
with this kind of algorithmic efficiency
and in that light you go back and you
look at Michael no jars photographs and
you realize that they’re not metaphor
they’re prophecy right they’re prophecy
for the kind of seismic terrestrial
effects of the math that we’re making
and the the landscape was always made by
this sort of weird uneasy collaboration
between nature and man but now there’s
this kind of third co-evolutionary force
algorithms the Boston shuffler the
carnival and we will have to understand
those as nature and in a way they are
thank