What the Flash Crash & Black Boxes can teach us about the Search #searchlove @kelvinnewman

W H AT T H E F L A S H C R A S H & B L A C K
B O X E S C A N T E A C H U S A B O U T T H E
F U T U R E O F S E A R C H .
@ K E LV I N N E W M A N

W H AT ’ S Y O U R J O B ?

Understanding
Customers
Understanding
who pays the
bills
Understanding
Google

Ability
Time

Pop!Tech
“Practice isn't the thing you do once you're good.
It's the thing you do that makes you good.”
― Malcolm Gladwell, Outliers: The Story of Success

On some Malcolm Gladwell, David Bowie meets
Kanye shit,
This is dedication,
A life lived for art is never a life wasted,
Ten thousand hours felt like ten thousand hands,
Ten thousands hands, they carry me.
― Macklemore - Ten Thousand Hours
floshe24 @ K E LV I N N E W M A N

Understanding
Customers
Understanding
who pays the
bills
Understanding
Google
A+
A+
D-

I thought maybe it’s the Dunning-Kruger effect.
Adam Sundana

@ K E LV I N N E W M A NAdam Sundana
The Dunning–Kruger effect is a cognitive bias manifesting in
unskilled individuals suffering from illusory superiority,
mistakenly rating their ability much higher than is accurate.
This bias is attributed to a metacognitive inability of the
unskilled to recognize their ineptitude.
Conversely, people with true ability tend to underestimate their
relative competence based on the erroneous or exaggerated
claims made by unskilled people.

but it was more than that
@ K E LV I N N E W M A NEva Rinaldi

T H I N G S I T H O U G H T W E R E T R U E ;
N O L O N G E R W E R E

T H I N G S I S A I D W O R K E D
N O L O N G E R W O R K E D

A N D T H AT 3 5 , 0 0 0 W O R D E B O O K
I W R O T E A B O U T L I N K B U I L D I N G

this presentation isn't about
one weird trick to get better
rankings ...

it’s about me dealing with the realisation that I didn’t understand
Google, quite as much, as I thought I did.

& I T W I L L C H A N G E
T H E WAY Y O U T H I N K
A B O U T H O W S E A R C H
E N G I N E S W O R K

Which is important…
Red Touch Media @ K E LV I N N E W M A N

B E C A U S E , W E N E E D T O
T H I N K M O R E ( A B O U T
H O W W E T H I N K . )

T H E P R O P

three stories

three lessons

three things to do…

Story One

the first story takes place at the University of Sussex

S O M E G R E AT P E O P L E
H AV E S T U D I E D T H E R E .

I A N M C E WA N
N O V E L I S T A N D A U T H O R O F O S C A R W I N N I N G A T O N E M E N T

V I R G I N I A WA D E
T H R E E T I M E G R A N D - S L A M W I N N E R

M I C H A E L B U E R K
L E G E N D A RY B R O A D C A S T E R

K E LV I N N E W M A N
B L O K E W H O U S E D T O D J A T T H E S T U D E N T U N I O N

B U T O U R S T O RY I S N ’ T
A B O U T T H E M

A N D H O W T H E Y M E T
T H E PA R T N E R S O F
T H E I R D R E A M S

H A D
A W E S O M E
K I D S

A N D I N E X P L I C A B LY
P L AY E D
S W I N G - B A L L O N
T H E S TA G E W H E R E
A B B A W O N
E U R O V I S I O N

I T ’ S A B O U T

D R . A D R I A N T H O M P S O N
E V O L U T I O N A RY & A D A P T I V E S Y S T E M S G R O U P

U N I V E R S I T Y O F S U S S E X , 1 9 9 6
D E PA R T M E N T O F I N F O R M A T I C S

H E A S K E D
C O U L D A C I R C U I T “ E V O LV E ”
T O S O LV E A P R O B L E M

S U R V I VA L O F T H E F I T T E S T A P P L I E D
T O C I R C U I T S
T H E E X P E R I M E N T

S U R V I VA L
O F T H E
F I T T E S T

T H E F I T T E S T W I N O U T
AT T H E E X P E N S E O F
T H E I R R I VA L S B E C A U S E
T H E Y S U C C E E D I N
A D A P T I N G
T H E M S E LV E S T O T H E I R
E N V I R O N M E N T
C H A R L E S D A R W I N
www.CGPGrey.com @ K E LV I N N E W M A N

P R I M O R D I A L D ATA S O U P O F R A N D O M
O N E S A N D Z E R O S

T H E F I R S T H U N D R E D G E N E R AT I O N S W E R E
L I T T L E B E T T E R T H A N R A N D O M G U E S S E S
JD Hancock

By generation #220 there were some encouraging signs.
Generation #1400 had a fifty percent success rate.
Just after #4000 it worked.

S O M E T H I N G S T R A N G E H A P P E N E D
I T W O R K E D B U T
JD Hancock

The circuit solved the problem using thirty-seven logic
gates.
Five logic cells were connected in ways which wouldn't allow
them to influence how the circuit worked.
But if you removed them the chip stopped working.

When machines teach themselves; they
solve problems in ways we can't
understand or reverse engineer.

Story Two

Mike McCarthy
A former marketer for
mortgage company
Quinn Dombrowski @ K E LV I N N E W M A N

Southern California.
2:45 PM, 6th of May 2010.
Jayseaka @ K E LV I N N E W M A N

Mike tried to sell shares he inherited, that should have
been worth about $45k but actually sold for closer to $28k

Moments before each share was selling for $60.
Minutes later they’d returned to that price

T H E L O W E S T P R I C E I N
S E V E N Y E A R S .

it quickly spread across the
whole market

B I G G E S T O N E D AY D R O P
I N T H E D O W J O N E S
I N D U S T R I A L AV E R A G E ’ S
1 1 8 Y E A R H I S T O RY

The index fell by thousand points or 9%
Twenty minutes later it had bounced back six hundred points.

T H I R T Y O F T H E U S ’ S B I G G E S T
C O M PA N I E S H A D I N S TA N T LY L O S T
9 % O F T H E I R VA L U E

JD Hancock @ K E LV I N N E W M A N

W H Y D I D I T H A P P E N ?

FAT F I N G E R S
T H E T H E O R I E S

JD Hancock
T H E G L I T C H

T H E I M PA C T O F H I G H
F R E Q U E N C Y T R A D E R S

JD Hancock
I T M AY H AV E B E E N A L L O F
T H E S E R E A S O N S , O R N O N E
O F T H E M .
T H E S Y S T E M I S T O O
C O M P L E X T O U N D E R S TA N D
B U T T H E A L G O B E H AV E D A S
T H E Y S H O U L D
T H E R E A L I T Y

Algorithms can react in peculiar ways
when they come into contact with other
algorithms, and the real world

Story Three

D R . I A N M A L C O L M
M A T H E M A T I C I A N A T T H E U N I V E R S I T Y O F T E X A S A T A U S T I N
Jamie Henderson

Isla Nublar, Costa Rica

N O T R E A L LY D R . I A N M A L C O L M
Jamie Henderson

http://brandonbird.com/
D R . I A N M A L C O L M
A C T U A L LY F I C T I O N A L C H A R A C T E R I N J U R A S S I C PA R K

J U R A S S I C PA R K D O E S A N
E X C E L L E N T J O B O F E X P L A I N I N G
C H A O S T H E O RY.

“ W H E N T H E P R E S E N T D E T E R M I N E S T H E F U T U R E ,
B U T T H E A P P R O X I M AT E P R E S E N T D O E S N O T
A P P R O X I M AT E LY D E T E R M I N E T H E F U T U R E . ”
Edward Norton Lorenz

P H Y S I C S I S G O O D AT D E S C R I B I N G
C E R TA I N K I N D S O F B E H AV I O U R
L I N E A R E Q U A T I O N S
Niki Odolphie @ K E LV I N N E W M A N

55Laney69 @ K E LV I N N E W M A N
E V E N I F Y O U K N E W E V E RY T H I N G A B O U T H O W T H E
W E AT H E R W O R K E D Y O U S T I L L C O U L D N ’ T P R E D I C T I T
N O N - L I N E A R E Q U A T I O N S

The weather is s
complex & chaotic
system

C O M P L E X ≠ C O M P L I C AT E D

D I F F E R E N C E B E T W E E N S I M P L E ,
C O M P L I C AT E D A N D C O M P L E X S Y S T E M S
Simple Systems Complicated Systems Complex Systems
Like Following A Recipe
For A Meal
Like Sending A Rocket To
The Moon
Like Being A Parent To A
Child
The Relationship Between
Cause And Effect Is
Obvious
Cause And Effect Requires
Expert Knowledge
Cause And Effect Is Hard
To Determine

Even with billions at stake, the world’s
greatest scientists cannot predict the
outcomes of a complex and chaotic
system with precision

S O W H AT ’ S T H I S G O T
T O D O W I T H S E A R C H ?

H E D O E S N ’ T K N O W H O W G O O G L E
W O R K S
Steve Jurvetson @ K E LV I N N E W M A N

H E C A N ’ T K N O W H O W G O O G L E W O R K S
storyspinn @ K E LV I N N E W M A N

A N D H E H A S N ’ T
G O T A B L O O D Y
C L U E .

G O O G L E ’ S A L G O I S P E R F E C T E X A M P L E
O F A C O M P L E X & C H A O T I C S Y S T E M
Les Chatfield

A R E A M A C H I N E
L E A R N I N G C O M PA N Y

http://research.google.com/pubs/
ArtificialIntelligenceandMachineLearning.html
i

$400 Million on AI Company

When machines teach themselves; they
solve problems in ways we can't
understand or reverse engineer.

Algorithms can react in peculiar ways when
they come into contact with other
algorithms, and the real world

When Google release an update or change to their algorithm they
can never fully anticipate how it will work in real world
nor how the real world will react to that change.

Even with billions at
stake, the world’s
greatest scientists
cannot predict the
outcomes of a
complex and chaotic
system with precision
Noah

In a complex and chaotic systems the relationship between cause
and effect is very hard to determine

I used to think the search algorithms work like clocks
Arjan Richter @ K E LV I N N E W M A N

they’re more like clouds
jojo nicdao @ K E LV I N N E W M A N

Or actually closer to
how the climate works.
Evil Twin21401 @ K E LV I N N E W M A N

I’m not saying small scale search experiment are a waste of time.

Well actually I am.

“You don’t need a weatherman to
know which way the wind blows”
Alberto Cabello @ K E LV I N N E W M A N

“You don’t need a weatherman to
know which way the wind blows”
goblinbox @ K E LV I N N E W M A N
there’s a difference between interesting and useful

or actually three books to read

A N D F I N A L LY,
T H I N K A B O U T H O W Y O U
T H I N K A B O U T G O O G L E

B U T W H A T A B O U T T H E
B O X

E S S E N T I A L LY I T ’ S A
M A C G U F F I N

W H A T I S A M A C G U F F I N ?

T H E O B J E C T T H AT D R I V E S T H E S T O RY F O R WA R D A N D
I S O F V I TA L I M P O R TA N T T O B O T H T H E H E R O E S A N D
V I L L A I N S E V E N I F T H E S P E C I F I C S O F T H E O B J E C T
I T S E L F R E M A I N O B S C U R E O R A R E U N I M P O R TA N T.

Our box contains all of the Google Algorithm on a USB key,
would you open it?

What the Flash Crash & Black Boxes can teach us about the Search #searchlove @kelvinnewman

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