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