CONSEQUENCES OF AN INSIGHTFUL ALGORITHM CARINA C. ZONA @CCZONA
Consequences of an Insightful Algorithm
Aug 16, 2015
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C O N S E Q U E N C E S O F A N I N S I G H T F U L A L G O R I T H M
C A R I N A C . Z O N A @ C C Z O N A
grieving
PTSD
depression
miscarriage
infertility
racial profiling
concentration camps
surveillance
sexual history
consent
assault
C O N T E N T W A R N I N G
A L G O R I T H M S I M P O S E C O N S E Q U E N C E S O N P E O P L E A L L T H E T I M E
S T E P - B Y- S T E P S E T O F O P E R AT I O N S F O R P R E D I C TA B LY A R R I V I N G AT A N O U T C O M E
A L G O R I T H M
PAT T E R N S O F I N S T R U C T I O N S , A R T I C U L AT E D I N C O D E O R F O R M U L A S
A L G O R I T H M S O F C O M P U T E R S C I E N C E & M A T H E M A T I C S
PAT T E R N S O F I N S T R U C T I O N S , A R T I C U L AT E D I N W AY S S U C H A S …
A L G O R I T H M S I N O R D I N A R Y L I F E
Ch 12, sl st to join. Rnd 1: ch 3, 17 dc. Rnd 2: ch 3, 1 dc, ch 4, skip 1 dc, *2 dc, ch 4, skip 1 dc*, repeat 5 times, sl st. Rnd 3: ch 3, 2 dc, ch 5, skip 2 ch and 1 dc, *3 dc, ch 5, skip 2 ch and 1 dc*, repeat 5 times, sl st. Rnd 4: ch 3, 3 dc, ch 5, skip 3 ch and 1 dc, *4 dc, ch 5, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 5: ch 3, 4 dc, ch 6, skip 3 ch and 1 dc, *5 dc, ch 6, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 6: ch 3, 6 dc, ch 6, skip 3 ch and 1 dc, *7 dc, ch 6, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 7: ch 3, 8 dc, ch 6, skip 3 ch and 1 dc, *9 dc, ch 6, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 8: ch 3, 10 dc, ch 6, skip 3 ch and 1 dc, *11 dc, ch 6, skip 3 ch and 1 dc*, repeat 5 times, sl st .Rnd 9: ch 3, 12 dc, ch 6, skip 3 ch and 1 dc, *13 dc, ch 6, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 10: ch 3, 14 dc, ch 7, skip 3 ch and 1 dc, *15 dc, ch 7, skip 3 ch and 1 dc*, repeat 5 times, sl st. Rnd 11: ch 3, 16 dc, ch 7, skip 4 ch and 1 dc, *17 dc, ch 7, skip 4 ch and 1 dc*, repeat 5 times, sl st. Rnd 12: ch 3, 18 dc, ch 8, skip 4 ch and 1 dc, *19 dc, ch 8, skip 4 ch and 1 dc*, repeat 5 times, sl st. Rnd 13: ch 3, 20 dc, ch 8, skip 5 ch and 1 dc, *21 dc, ch 8, skip 5 ch and 1 dc*, repeat 5 times, sl st. Rnd 14: ch 3, 16 dc, ch 8, skip 3 dc and 2 ch, 1 dc, ch 8, skip 1 dc, *17 dc, ch 8, skip 3 dc and 2 ch, 1 dc, ch 8, skip 1 dc,* repeat 5 times, sl st.
A L G O R I T H M S F O R FA S T, T R A I N A B L E , A R T I F I C I A L N E U R A L N E T W O R K S
D E E P L E A R N I N G
@ C C Z O N A
– P e t e Wa r d e n , " W h a t i s d e e p l e a r n i n g , a n d w h y s h o u l d y o u c a r e ? "
" D E E P L E A R N I N G I S A PA R T I C U L A R A P P R O A C H T O B U I L D I N G & T R A I N I N G A R T I F I C I A L N E U R A L N E T W O R K S . T H I N K O F T H E M A S D E C I S I O N -M A K I N G B L A C K B O X E S . "
@ C C Z O N A
I N P U T A r r a y o f n u m b e r s r e p r e s e n t i n g w o r d s , c o n c e p t s , o r o b j e c t s .
E X E C U T I O N R u n a s e r i e s o f f u n c t i o n s o n t h e a r r a y.
O U T P U T P re d i c t i o n o f p r o p e r t i e s u s e f u l f o r d r a w i n g i n t u i t i o n s a b o u t s i m i l a r i n p u t s .
I N P U T A r r a y o f
n u m b e r s re p re s e n t i n g w o r d s , c o n c e p t s , o r o b j e c t s
E X E C U T I O N R u n a s e r i e s o f f u n c t i o n s
o n t h e a r r a y
O U T P U T P re d i c t i o n o f
p r o p e r t i e s u s e f u l f o r d r a w i n g i n t u i t i o n s a b o u t
s i m i l a r i n p u t s
@ C C Z O N A
D e e p L e a r n i n g r e l i e s o n a n a r t i f i c i a l n e u r a l n e t w o r k ' s a u t o m a t e d d i s c o v e r y o f p a t t e r n s w i t h i n i t s t r a i n i n g d a t a s e t .
I t a p p l i e s t h o s e d i s c o v e r i e s t o d r a w i n t u i t i o n s a b o u t f u t u re i n p u t s .
WOULD Y OU L IK E T O
PLAY A N I C E GAME OF
DATA M IN ING FA I L?
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
#DATAM IN INGFA I L
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
TARGET
🔵 🔵 🔵
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@ C C Z O N A
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
SHUT TERFLY
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@ C C Z O N A
@ C C Z O N A
“ T h a n k s , S h u t t e r f l y, f o r
t h e c o n g r a t u l a t i o n s o n m y ' n e w b u n d l e o f j o y ' . I ' m h o r r i b l y i n f e r t i l e , b u t h e y, I ' m a d o p t i n g a k i t t e n , s o . . . ”
@ C C Z O N A
" I l o s t a b a b y i n
N o v e m b e r w h o
w o u l d h a v e b e e n
d u e t h i s w e e k . I t w a s l i k e h i t t i n g a
w a l l a l l o v e r a g a i n . "
@ C C Z O N A
“ T H E I N T E N T O F T H E E M A I L WA S T O TA R G E T
C U S T O M E R S W H O H AV E R E C E N T LY
H A D A B A B Y "
@ C C Z O N A
" Yo u s t a r t i m a g i n i n g w h o t h e y ' l l b e c o m e & d r e a m i n g o f
h o p e s f o r t h e i r f u t u r e . Yo u s t a r t
m a k i n g p l a n s , a n d t h e n t h e y ' r e
g o n e . I t ' s a l o n e l y
e x p e r i e n c e . "
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
FACEBOOK EMOTI ONAL CONTA I GON
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
🔵
🔵
🔵🔵
🔵
🔵🔵
🔵
🔵
@ C C Z O N A
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
FACEBOOK YEAR I N REV I EW
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
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I n a d v e r t e n t a l g o r i t h m i c c r u e l t y i s t h e r e s u l t o f c o d e t h a t w o r k s i n t h e o v e r w h e l m i n g m a j o r i t y o f c a s e s b u t d o e s n ’ t t a k e o t h e r u s e c a s e s i n t o a c c o u n t .
I N A D V E R T E N T A L G O R I T H M I C C R U E LT Y
Eric Meyer
@ C C Z O N A
"The Year in Review ad keeps coming up in my feed, rotating through different fun-and-fabulous backgrounds, as if celebrating a death, and there is no obvious way to stop it."
@ C C Z O N A
– E r i c M e y e r
I N C R E A S E AWA R E N E S S O F A N D C O N S I D E R AT I O N F O R
T H E FA I L U R E M O D E S , T H E E D G E C A S E S , T H E W O R S T- C A S E S C E N A R I O S .
@ C C Z O N A
B E H U M B L E . W E C A N N O T I N T U I T
I N N E R S TAT E , E M O T I O N S , P R I VAT E S U B J E C T I V I T Y
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
F ITB IT S EX TRACK ING
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@ C C Z O N A
@ C C Z O N A
@ C C Z O N A
@ C C Z O N A
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
UBER
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@ C C Z O N A
@ C C Z O N A
@ C C Z O N A
Informed consent is permission
freely granted (where "no" is consequence-free alternative and the default value) with informed appreciation and understanding (ahead of time) of the facts, implications, and consequences
Informed consent is permission freely granted (where "no" is consequence-free alternative and the default value) with informed appreciation & understanding (ahead of time) of the facts, implications, & consequences
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
GOOGLE ADWORDS
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@ C C Z O N A
@ C C Z O N A
– H a r v a r d U n i v e r s i t y, D i s c r i m i n a t i o n i n O n l i n e A d D e l i v e r y s t u d y ( 2 0 1 3 )
A B L A C K I D E N T I F Y I N G N A M E WA S 2 5 % M O R E L I K E LY T O R E S U LT I N A N
A D T H AT I M P L I E D A N A R R E S T R E C O R D
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
GOOGLE / FL I CKR / APPLE IMAGE ANALY S IS
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@ C C Z O N A
iPhoto Face Detection
@ C C Z O N A
Flickr Auto-Tagging
@ C C Z O N A
Flickr Auto-Tagging
@ C C Z O N A
Google Photos Auto-Categorizing
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
AFF IRM
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@ C C Z O N A
@ C C Z O N A
@ C C Z O N A
@ C C Z O N A
L E S S O N S F R O M T H E P R O F E S S I O N A L E T H I C I S T S
F L I P P I N G T H E PA R A D I G M
@ C C Z O N A
A C M C o d e o f E t h i c s
AV O I D H A R M T O O T H E R S
c o n s i d e r d e c i s i o n s ' p o t e n t i a l i m p a c t s o n o t h e r s
A V O I D H A R M
p r o j e c t t h e l i k e l i h o o d o f c o n s e q u e n c e s t o o t h e r s
A V O I D H A R M
@ C C Z O N A
A C M C o d e o f E t h i c s
C O N T R I B U T E T O H U M A N W E L L - B E I N G
m i n i m i z e n e g a t i v e c o n s e q u e n c e s t o o t h e r s
C O N T R I B U T E W E L L - B E I N G
@ C C Z O N A
@ C C Z O N A
A C M C o d e o f E t h i c s
B E H O N E S T. B E T R U S T W O R T H Y.
P r o v i d e o t h e r s w i t h f u l l d i s c l o s u re o f l i m i t a t i o n s
H O N E S T. T R U S T W O R T H Y.
@ C C Z O N A
C a l l a t t e n t i o n t o s i g n s o f r i s k o f h a r m t o o t h e r s
H O N E S T. T R U S T W O R T H Y.
@ C C Z O N A
@ C C Z O N A
A C T I V E LY C O U N T E R B I A S & I N E Q U A L I T Y
• e q u a l i t y • t o l e r a n c e • r e s p e c t • j u s t i c e • a n t i -
d i s c r i m i n a t i o n
A C T I V E LY C O U N T E R B I A S & I N E Q U A L I T Y
@ C C Z O N A
• C u l t u r e • S y s t e m s • A s s u m p t i o n s • I g n o r a n c e • M a l i c e
A C T I V E LY C O U N T E R B I A S & I N E Q U A L I T Y
@ C C Z O N A
• U n e q u a l a c c e s s t o r e s o u r c e s & p o w e r
• U n f a i r o u t c o m e s
A C T I V E LY C O U N T E R B I A S & I N E Q U A L I T Y
@ C C Z O N A
@ C C Z O N A
A U D I T O U T C O M E S
W E ' R E I N A R A C E
@ C C Z O N A
D E E P L E A R N I N G A R M S R A C E
• Facebook, Google, and Microsoft are making big bets
@ C C Z O N A
I N S I G H T F U L A L G O R I T H M S A R E G R O W I N G
• More precise in correctness
• More damaging in wrongness
E M PAT H E T I C C O D E R S
@ C C Z O N A
Identify potential harms
E M PAT H E T I C C O D E R S
@ C C Z O N A
Anticipate diverse ways to screwup
@ C C Z O N A
W E M U S T H A V E D E C I S I O N - M A K I N G A U T H O R I T Y I N T H E H A N D S O F
H I G H LY D I V E R S E
T E A M S
@ C C Z O N A
D I V E R S E . O F D I F F E R I N G K I N D , F O R M , A N D C H A R A C T E R
@ C C Z O N A
Tokenism is not diversity
@ C C Z O N A
The point of culture fit is to avoid disruption of groupthink
@ C C Z O N A
Unidimensional varietyis not diversity
@ C C Z O N A
E M PAT H E T I C C O D E R S
@ C C Z O N A
Cultivate informed consent
E M PAT H E T I C C O D E R S
@ C C Z O N A
Audit constantly
E M PAT H E T I C C O D E R S
@ C C Z O N A
Recognize bias is inherent
E M PAT H E T I C C O D E R S
@ C C Z O N A
Visionary about countering bias
E M PAT H E T I C C O D E R S
@ C C Z O N A
Aim mining tools at public benefit consequences
E M PAT H E T I C C O D E R S
@ C C Z O N A
Commit to transparency
@ C C Z O N A
PROFESSIONALS APPLY EXPERTISE &
JUDGEMENT ABOUT
HOW TO SOLVE PROBLEMS
Algorithmic Profiling
De-Anonymization
Black BoxDisparate
ImpactConsent Issues
Replicates BiasPersonally
Identifiable InfoHuman
Complexity FailUnproven Methods
Inadvertent Algorithmic
Cruelty
Uncritical Assumptions
False NeutralityHigh Risk
ConsequencesDeception Filtering
Moved Fast, Broke Things
Invasion Of Privacy
No Recourse Creepy StalkeryMessing With
Heads
Not How Valid Research Works
Data InsecurityAccurate, But
Not RightShaming Diversity Fail
❌ ❌ ❌❌ ❌
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❌ ❌❌ ❌❌ ❌ ❌ ❌ ❌
@ C C Z O N A
R E F U S E T O P L AY A L O N G .
@ C C Z O N A
T H A N K Y O U .
@ C C Z O N A
C R E D I T S
@ C C Z O N A
I M A G E U N D E R S TA N D I N G : D E E P L E A R N I N G W I T H C O N V O L U T I O N A L N E U R A L N E T S
http://www.slideshare.net/roelofp/python-for-image-understanding-deep-learning-with-convolutional-neural-nets
Roelof Pieters@graphific
@ C C Z O N A
A H I P P O C R AT I C O AT H F O R D ATA S C I E N C E
http://www.slideshare.net/roelofp/a-hippocratic-oath-for-data-science
Roelof Pieters@graphific
@ C C Z O N A
T H E E T H I C S O F B E I N G A P R O G R A M M E R
https://youtu.be/DB7ei5W1eRQ
Kate Heddleston
@heddle317
I M A G E S
• Kate Heddleston: PyCon SE 2015 video
• Roelof Pieters: Hendrik https://twitter.com/hen_drik/status/612653056421982208
• Code is made by people: Chris Eppstein https://twitter.com/chriseppstein/status/611612633335095296
• Recipe cards: Olivia Juice & Co. http://olivejuiceco.typepad.com/my_weblog/2006/04/easter_recap_an.html
• Crochet pattern & shawl: http://www.abc-knitting-patterns.com/1129.html
• Wargames font: http://www.urbanfonts.com/fonts/wargames.htm
• Space Invaders: http://www.caffination.com/backchannel/shooting-for-the-high-score-3942/
• Wheat: https://www.flickr.com/photos/paule92/9506023990/
• Eye shadows: https://www.flickr.com/photos/niallb/5300259686/
• Colored pencils: https://www.flickr.com/photos/jenson-lee/6315443914/
• Buttons: https://www.flickr.com/photos/48462557@N00/3616793654/
• Cookie face: https://www.flickr.com/photos/amayu/4462907505/in/pool-977532@N24/
• Facebook emotion marionettes: http://altlaw.info/2014/07/emotional-contagion-subliminal-messaging-where-does-it-end-for-facebook/
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A R T I C L E S
• Association for Computing Machinery Code of Ethics http://www.acm.org/about/code-of-ethics
• The 10 Commandments of Egoless Programming http://www.techrepublic.com/article/the-ten-commandments-of-egoless-programming-6353837/
• Disparate Impact Analysis is Key to Ensuring Fairness in the Age of the Algorithm http://www.datainnovation.org/2015/01/disparate-impact-analysis-is-key-to-ensuring-fairness-in-the-age-of-the-algorithm/
• On Algorithmic Fairness, Discrimination and Disparate impact. http://fairness.haverford.edu/
• Big Data's Disparate Impact http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2477899
• White House https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_may_1_2014.pdf
• Algorithmic Accountability & Transparency http://www.nickdiakopoulos.com/projects/algorithmic-accountability-reporting/
• What is Deep Learning and why should you care? http://radar.oreilly.com/2014/07/what-is-deep-learning-and-why-should-you-care.html
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C A S E S T U D I E S
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• FitBit: http://thenextweb.com/insider/2011/07/03/fitbit-users-are-inadvertently-sharing-details-of-their-sex-lives-with-the-world/
• Uber: http://www.forbes.com/sites/kashmirhill/2014/10/03/god-view-uber-allegedly-stalked-users-for-party-goers-viewing-pleasure/ & http://valleywag.gawker.com/uber-allegedly-used-god-view-to-stalk-vip-users-as-a-1642197313 & http://www.forbes.com/sites/chanellebessette/2014/11/25/does-uber-even-deserve-our-trust/
• Affirm: http://recode.net/2015/05/06/max-levchins-affirm-raises-275-million-to-make-loans/ & http://time.com/3430817/paypal-levchin-affirm-lending/ & http://www.nytimes.com/2015/01/19/technology/banking-start-ups-adopt-new-tools-for-lending.html
• Shutterfly: http://jezebel.com/shutterfly-thinks-you-just-had-a-baby-1576261631 & http://www.adweek.com/adfreak/shutterfly-congratulates-thousands-women-babies-they-didnt-have-157675 (Zuckerberg on miscarriage: https://www.facebook.com/photo.php?fbid=10102276573729791)
• Target: http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html
• Facebook Emotional Contagion Study: http://www.theguardian.com/science/head-quarters/2014/jul/01/facebook-cornell-study-emotional-contagion-ethics-breach & http://psychcentral.com/blog/archives/2014/06/23/emotional-contagion-on-facebook-more-like-bad-research-methods/
• Facebook Year in Review: http://meyerweb.com/eric/thoughts/2014/12/24/inadvertent-algorithmic-cruelty/ & http://www.theguardian.com/technology/2014/dec/29/facebook-apologises-over-cruel-year-in-review-clips
• Google AdWords: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2208240 & http://freakonomics.com/2013/04/08/how-much-does-your-name-matter-full-transcript/
• Flickr: http://www.theguardian.com/technology/2015/may/20/flickr-complaints-offensive-auto-tagging-photos
• Google Photos: https://twitter.com/jackyalcine/status/615329515909156865 & https://www.yahoo.com/tech/google-photos-mislabels-two-black-americans-as-122793782784.html
• Race & Film: http://priceonomics.com/how-photography-was-optimized-for-white-skin/ & http://www.buzzfeed.com/syreetamcfadden/teaching-the-camera-to-see-my-skin#.wkv3Jmd8O
V I D E O S
• MarI/O Machine Learning for Video Games https://youtu.be/qv6UVOQ0F44
• Algorithmic Accountability Workshop by Tow Center https://vimeo.com/125622175
@ C C Z O N A
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Noah Kantrowitz
Heidi Waterhouse
VM Brasseur
Yoz Grahame
Mike Foley
Estelle Weyl
Chris Hausler
We So Crafty
T H A N K Y O U♥
O n v i d e o :
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@ C C Z O N AC A R I N A C . Z O N A
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