May 6th, 2010 the Dow Jones Industrial Average plunged about 1000 points only to recover those losses within minutes – this was the Flash Crash. No catastrophes or physical events caused this swing, it was the black boxes of stock market algorithms. Black boxes a lot like Google’s. How do we prepare for the future when even Google doesn’t know how its algorithm works?D
6. 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
7. 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
11. @ K E LV I N N E W M A N
I thought maybe it’s the Dunning-Kruger effect.
Adam Sundana
12. @ 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.
13. but it was more than that
@ K E LV I N N E W M A NEva Rinaldi
14. 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
@ K E LV I N N E W M A N
15. 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
@ K E LV I N N E W M A N
16. 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
17. this presentation isn't about
one weird trick to get better
rankings ...
@ K E LV I N N E W M A N
18. it’s about me dealing with the realisation that I didn’t understand
Google, quite as much, as I thought I did.
19. & 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
@ K E LV I N N E W M A N
27. the first story takes place at the University of Sussex
@ K E LV I N N E W M A N
28. 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 .
@ K E LV I N N E W M A N
29. 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
@ K E LV I N N E W M A N
30. 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
31. 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
32. 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
@ K E LV I N N E W M A N
33. B U T O U R S T O RY I S N ’ T
A B O U T T H E M
@ K E LV I N N E W M A N
34. 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
@ K E LV I N N E W M A N
35. H A D
A W E S O M E
K I D S
@ K E LV I N N E W M A N
36. 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
@ K E LV I N N E W M A N
38. 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
@ K E LV I N N E W M A N
39. 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
40. 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
@ K E LV I N N E W M A N
41. 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
42. S U R V I VA L
O F T H E
F I T T E S T
@ K E LV I N N E W M A N
43. S U R V I VA L
O F T H E
F I T T E S T
@ K E LV I N N E W M A N
44. S U R V I VA L
O F T H E
F I T T E S T
@ K E LV I N N E W M A N
45. 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
46. 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
47. 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
@ K E LV I N N E W M A N
48. By generation #220 there were some encouraging signs.
Generation #1400 had a fifty percent success rate.
Just after #4000 it worked.
@ K E LV I N N E W M A N
49. 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
@ K E LV I N N E W M A N
50. 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.
@ K E LV I N N E W M A N
51. When machines teach themselves; they
solve problems in ways we can't
understand or reverse engineer.
60. 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
@ K E LV I N N E W M A N
61. The index fell by thousand points or 9%
Twenty minutes later it had bounced back six hundred points.
@ K E LV I N N E W M A N
62. 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
@ K E LV I N N E W M A N
64. W H Y D I D I T H A P P E N ?
@ K E LV I N N E W M A N
65. FAT F I N G E R S
T H E T H E O R I E S
JD Hancock @ K E LV I N N E W M A N
66. JD Hancock
T H E G L I T C H
T H E T H E O R I E S
@ K E LV I N N E W M A N
67. 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
T H E T H E O R I E S
JD Hancock @ K E LV I N N E W M A N
68. 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
@ K E LV I N N E W M A N
69. Algorithms can react in peculiar ways
when they come into contact with other
algorithms, and the real world
71. 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
@ K E LV I N N E W M A N
74. N O T R E A L LY D R . I A N M A L C O L M
Jamie Henderson
75. 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
@ K E LV I N N E W M A N
76. 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.
@ K E LV I N N E W M A N
77. “ 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 . ”
@ K E LV I N N E W M A N
Edward Norton Lorenz
78. 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
79. 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
80. The weather is s
complex & chaotic
system
@ K E LV I N N E W M A N
82. C O M P L E X ≠ C O M P L I C AT E D
@ K E LV I N N E W M A N
83. 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
The Relationship Between
Cause And Effect Requires
Expert Knowledge
The Relationship Between
Cause And Effect Is Hard
To Determine
@ K E LV I N N E W M A N
84. Even with billions at stake, the world’s
greatest scientists cannot predict the
outcomes of a complex and chaotic
system with precision
85. 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 ?
@ K E LV I N N E W M A N
86. 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
87. 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
88. A N D H E H A S N ’ T
G O T A B L O O D Y
C L U E .
@ K E LV I N N E W M A N
89. 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
90. 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
@ K E LV I N N E W M A N
93. When machines teach themselves; they
solve problems in ways we can't
understand or reverse engineer.
JD Hancock @ K E LV I N N E W M A N
94. Algorithms can react in peculiar ways when
they come into contact with other
algorithms, and the real world
JD Hancock @ K E LV I N N E W M A N
95. 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.
@ K E LV I N N E W M A N
96. Even with billions at
stake, the world’s
greatest scientists
cannot predict the
outcomes of a
complex and chaotic
system with precision
Noah
@ K E LV I N N E W M A N
97. In a complex and chaotic systems the relationship between cause
and effect is very hard to determine
@ K E LV I N N E W M A N
98. I used to think the search algorithms work like clocks
Arjan Richter @ K E LV I N N E W M A N
103. “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
104. “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
118. 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.
@ K E LV I N N E W M A N
119. Our box contains all of the Google Algorithm on a USB key,
would you open it?
@ K E LV I N N E W M A N
120. @ K E LV I N N E W M A N
Slides - http://bit.ly/theflashcrash