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Kaaren Hanson
@K AARENHANSON
ELIMINATE THE GAP
BIASGENDER
22% 27% 28% 24%
30%
18%
36%
33% 32% 31%
36%
26%
50%female
population
DIVERSITY IN TECH LEADERSHIP
Uber Facebook Apple Goog...
36%
33% 32% 31%
36%
26%
22% 27% 28% 24%
30%
18%
50%female
population
DIVERSITY IN TECH LEADERSHIP
Uber Facebook Apple Goog...
Female Designers make 79% of what Male designers make
Female Developers make 72% of what Male developers make
Developer ci...
$1800
$1000
$1400
$600
$200
Men
77%
78% 77%
74%
74%
Median weekly earnings by level of education and gender, 2016
Women
Le...
45%Middle school
girls
42%Middle school
boys
National Assessment of Educational Progress, 2016
girls and boys proficient i...
49, Liana Christin Landivar, Disparities in STEM Employment by Sex, Race, and Hispanic Origin: American Community Survey R...
BIASGENDER
IMPLICIT PERVASIVE&
5 HRS/DAY ON TV
Source: Nielsen 2016 Audience Report
11 HRS/DAY ON MEDIA
Source: Nielsen 2016 Audience Report
5 HRS/DAY ON TV
The bechtel test:
two women have names +
talk to each other about something besides a man
The bechtel test:
50% FAIL
OFFILMS
two women have names +
talk to each other about something besides a man
WTF?!~17%WOMEN
WTF?!~17%WOMEN
The reel truth:
women aren't seen or heard
2x
In 2015, male characters
received 2x the amount
of screen time as female
cha...
The reel truth:
women aren't seen or heard
2x
In 2015, male characters
spoke 2x as often as
female characters in the
top b...
79%
The reel truth:
women aren't portrayed
as professionals
21% of main character women have STEM 

careers vs. 79% of mal...
Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html
Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html
Assertive
Competent
Strategic
I...
Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html
Assertive
Competent
Strategic
I...
Men and women have
very different experiences
Men and women have
very different experiences
Women are more likely to be told they're "too aggressive"10x
Women are interrupted more than men3-5x
Men and women have
very different experiences
Women are more likely to be told the...
Women are more likely to be told they're "too aggressive"10x
Women are interrupted more than men3-5x
Women are more likely...
36%
33% 32% 31%
36%
26%
22% 27% 28% 24%
30%
18%
50%female
population
DIVERSITY IN TECH LEADERSHIP Women employees
Uber Fac...
What do we as leaders do?
*pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return...
*pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return...
*pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return...
*pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return...
2 no assholes
anywhere!
One Jerk can reduce
team performance by
30-40%
3 point out
gender bias
Example 1
‣ Strategy background
‣ 3 yrs Marketing
‣ PM VP
‣ 15+ yrs PM experience
Hiring A PM LeADER
Example 1
‣ Strategy background
‣ 3 yrs Marketing
‣ "Seems like a go-
getter"
‣ PM VP
‣ 15+ yrs PM experience
‣ "Hmmm... W...
‣ "Emotional" vs.

"Passionate"
‣ "Pushy" vs. 

"Assertive"
Women are
more likely to receive
critical subjective feedback
...
Direct
Disruptor
Passionate
Takes control
Assertive
Honest
Takes his time
Quick
Analytical
Follow his gut
Expert
Abrasive
...
‣ When people are interrupted
‣ When ideas are mis-attributed
Example 3
meetings
call it out!
reiterate 's name when
you reinforce her point.
That matters ... a lot!
celebrate the positive
"I noticed that you..."
4 lean into operating
mechanisms
Example 1
hiring
1 female and 1 male paired interviewers
"It was so weird, she would ask him a question
and he would respond to me!"
Example 1
hiring
1 female and 1 male paired in...
Bring all senior
people, one at a time,
to share their work
Example 2
talent visibility
Example 3
talent reviews
Review the work 

(aka the designs) 

at calibration
first
5 test the
BOUNDARIES
HARRY POTTER AND THE SORCERER'S STONE, WARNER BROS.
“YOU DON’T KNOW WHERE
THE BOUNDARIES ARE UNTIL
YOU HIT THEM.” Justin Sherman
Kaaren Hanson
@K AARENHANSON
THANK YOU
UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"
UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"
UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"
UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"
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UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"

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UX STRAT USA 2017 presentation by Kaaren Hansen, Product Design Director, Facebook

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  • DOWNLOAD FULL BOOKS, INTO AVAILABLE FORMAT ......................................................................................................................... ......................................................................................................................... 1.DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... 1.DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/y3nhqquc } ......................................................................................................................... ......................................................................................................................... ......................................................................................................................... .............. Browse by Genre Available eBooks ......................................................................................................................... Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult,
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UX STRAT USA 2017: Kaaren Hansen, "How to Develop More Diverse Design Leadership"

  1. 1. Kaaren Hanson @K AARENHANSON ELIMINATE THE GAP
  2. 2. BIASGENDER
  3. 3. 22% 27% 28% 24% 30% 18% 36% 33% 32% 31% 36% 26% 50%female population DIVERSITY IN TECH LEADERSHIP Uber Facebook Apple Google Twitter Microsoft Women employees Women in leadership Source: Tech Insider March 28, 2017
  4. 4. 36% 33% 32% 31% 36% 26% 22% 27% 28% 24% 30% 18% 50%female population DIVERSITY IN TECH LEADERSHIP Uber Facebook Apple Google Twitter Microsoft Women employees Women in leadership Source: Tech Insider March 28, 2017
  5. 5. Female Designers make 79% of what Male designers make Female Developers make 72% of what Male developers make Developer citation: Fortune, 11/16/2016. Valentina Zarya Designer Citation: Wall Street Journal "What's your pay gap?"May 17, 2016
  6. 6. $1800 $1000 $1400 $600 $200 Men 77% 78% 77% 74% 74% Median weekly earnings by level of education and gender, 2016 Women Less than a high school diploma High school graduate Some college or associate degree Bachelor's degree Advanced degree Source: U.S Census Bureau, Current Population Survey, reported in U.S. Department of Labor, U.S. Bureau of Labor Statistics, 2016 Usual Weekly Earnings Summary, Economic News Release DSDL-17-0105, Table 9
  7. 7. 45%Middle school girls 42%Middle school boys National Assessment of Educational Progress, 2016 girls and boys proficient in STEM
  8. 8. 49, Liana Christin Landivar, Disparities in STEM Employment by Sex, Race, and Hispanic Origin: American Community Survey Reports (US Census Bureau, September 2013): p.7. But... women make up only 25% of people in stem occupations 25% women
  9. 9. BIASGENDER IMPLICIT PERVASIVE&
  10. 10. 5 HRS/DAY ON TV Source: Nielsen 2016 Audience Report
  11. 11. 11 HRS/DAY ON MEDIA Source: Nielsen 2016 Audience Report 5 HRS/DAY ON TV
  12. 12. The bechtel test: two women have names + talk to each other about something besides a man
  13. 13. The bechtel test: 50% FAIL OFFILMS two women have names + talk to each other about something besides a man
  14. 14. WTF?!~17%WOMEN
  15. 15. WTF?!~17%WOMEN
  16. 16. The reel truth: women aren't seen or heard 2x In 2015, male characters received 2x the amount of screen time as female characters. 2x
  17. 17. The reel truth: women aren't seen or heard 2x In 2015, male characters spoke 2x as often as female characters in the top box office movies. In 2015, male characters received 2x the amount of screen time as female characters. 2x
  18. 18. 79% The reel truth: women aren't portrayed as professionals 21% of main character women have STEM 
 careers vs. 79% of male characters. 21% (2012 Geena Davis report)
  19. 19. Helpful Expressive Friendly Nurturing https://implicit.harvard.edu/implicit/takeatest.html
  20. 20. Helpful Expressive Friendly Nurturing https://implicit.harvard.edu/implicit/takeatest.html Assertive Competent Strategic Independent
  21. 21. Helpful Expressive Friendly Nurturing https://implicit.harvard.edu/implicit/takeatest.html Assertive Competent Strategic Independent Leadership
  22. 22. Men and women have very different experiences
  23. 23. Men and women have very different experiences Women are more likely to be told they're "too aggressive"10x
  24. 24. Women are interrupted more than men3-5x Men and women have very different experiences Women are more likely to be told they're "too aggressive"10x
  25. 25. Women are more likely to be told they're "too aggressive"10x Women are interrupted more than men3-5x Women are more likely to be hired when auditions are blind6x Men and women have very different experiences
  26. 26. 36% 33% 32% 31% 36% 26% 22% 27% 28% 24% 30% 18% 50%female population DIVERSITY IN TECH LEADERSHIP Women employees Uber Facebook Apple Google Twitter Microsoft Women in leadership
  27. 27. What do we as leaders do?
  28. 28. *pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return a smoothed version ofimage*/public Color[][] smooth(Color[][]image, int neighberhoodSize){ //check preconditionassert image != null && image.length> 1 && image[0].length > 1&& ( neighberhoodSize > 0 ) &&rectangularMatrix( image ): "Violation of precondition:smooth";Color[][] result = newColor[image.length][image[0].length];for(int row = 0; row < image.length;row++){ for(int col = 0; col <image[0].length; col++){ result[row][col] =aveOfNeighbors(image, row, col,neighberhoodSize);}}return result;} // helper method that determines theaverage color of a neighberhood// around a particular cell.private Color aveOfNeighbors(Color[][]image, int row, int col, intneighberhoodSize){ int numNeighbors = 0;int red = 0;int green = 0;int blue = 0;for(int r = row - neighberhoodSize; r<= row + neighberhoodSize; r++){ for(int c = col -neighberhoodSize; c <= col +neighberhoodSize; c++){ if( inBounds( image, r, c ) ){ numNeighbors++;red += image[r][c].getRed();green += image[r][c].getGreen();blue += image[r][c].getBlue();}}}assert numNeighbors > 0;return new Color( red / numNeighbors,green / numNeighbors, blue /numNeighbors );}//helper method to determine if givencoordinates are in boundsprivate boolean inBounds(Color[][]image, int row, int col){ return (row >= 0) && (row <=image.length) && (col >= 0)&& (col < image[0].length);}//private method to ensure mat isrectangularprivate booleanrectangularMatrix( Color[][] mat ){ boolean isRectangular = true;int row = 1;final int COLUMNS = mat[0].length;while( isRectangular && row <mat.length ){ isRectangular = ( mat[row].length== COLUMNS );row++;}return isRectangular; 1 CRACK THE CODE!
  29. 29. *pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return a smoothed version ofimage*/public Color[][] smooth(Color[][]image, int neighberhoodSize){ //check preconditionassert image != null && image.length> 1 && image[0].length > 1&& ( neighberhoodSize > 0 ) &&rectangularMatrix( image ): "Violation of precondition:smooth";Color[][] result = newColor[image.length][image[0].length];for(int row = 0; row < image.length;row++){ for(int col = 0; col <image[0].length; col++){ result[row][col] =aveOfNeighbors(image, row, col,neighberhoodSize);}}return result;} // helper method that determines theaverage color of a neighberhood// around a particular cell.private Color aveOfNeighbors(Color[][]image, int row, int col, intneighberhoodSize){ int numNeighbors = 0;int red = 0;int green = 0;int blue = 0;for(int r = row - neighberhoodSize; r<= row + neighberhoodSize; r++){ for(int c = col -neighberhoodSize; c <= col +neighberhoodSize; c++){ if( inBounds( image, r, c ) ){ numNeighbors++;red += image[r][c].getRed();green += image[r][c].getGreen();blue += image[r][c].getBlue();}}}assert numNeighbors > 0;return new Color( red / numNeighbors,green / numNeighbors, blue /numNeighbors );}//helper method to determine if givencoordinates are in boundsprivate boolean inBounds(Color[][]image, int row, int col){ return (row >= 0) && (row <=image.length) && (col >= 0)&& (col < image[0].length);}//private method to ensure mat isrectangularprivate booleanrectangularMatrix( Color[][] mat ){ boolean isRectangular = true;int row = 1;final int COLUMNS = mat[0].length;while( isRectangular && row <mat.length ){ isRectangular = ( mat[row].length== COLUMNS );row++;}return isRectangular; return recruiters' calls
  30. 30. *pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return a smoothed version ofimage*/public Color[][] smooth(Color[][]image, int neighberhoodSize){ //check preconditionassert image != null && image.length> 1 && image[0].length > 1&& ( neighberhoodSize > 0 ) &&rectangularMatrix( image ): "Violation of precondition:smooth";Color[][] result = newColor[image.length][image[0].length];for(int row = 0; row < image.length;row++){ for(int col = 0; col <image[0].length; col++){ result[row][col] =aveOfNeighbors(image, row, col,neighberhoodSize);}}return result;} // helper method that determines theaverage color of a neighberhood// around a particular cell.private Color aveOfNeighbors(Color[][]image, int row, int col, intneighberhoodSize){ int numNeighbors = 0;int red = 0;int green = 0;int blue = 0;for(int r = row - neighberhoodSize; r<= row + neighberhoodSize; r++){ for(int c = col -neighberhoodSize; c <= col +neighberhoodSize; c++){ if( inBounds( image, r, c ) ){ numNeighbors++;red += image[r][c].getRed();green += image[r][c].getGreen();blue += image[r][c].getBlue();}}}assert numNeighbors > 0;return new Color( red / numNeighbors,green / numNeighbors, blue /numNeighbors );}//helper method to determine if givencoordinates are in boundsprivate boolean inBounds(Color[][]image, int row, int col){ return (row >= 0) && (row <=image.length) && (col >= 0)&& (col < image[0].length);}//private method to ensure mat isrectangularprivate booleanrectangularMatrix( Color[][] mat ){ boolean isRectangular = true;int row = 1;final int COLUMNS = mat[0].length;while( isRectangular && row <mat.length ){ isRectangular = ( mat[row].length== COLUMNS );row++;}return isRectangular; negotiate return recruiters' calls
  31. 31. *pre: image != null, image.length > 1,image[0].length > 1* image is a rectangular matrix,neighberhoodSize > 0*post: return a smoothed version ofimage*/public Color[][] smooth(Color[][]image, int neighberhoodSize){ //check preconditionassert image != null && image.length> 1 && image[0].length > 1&& ( neighberhoodSize > 0 ) &&rectangularMatrix( image ): "Violation of precondition:smooth";Color[][] result = newColor[image.length][image[0].length];for(int row = 0; row < image.length;row++){ for(int col = 0; col <image[0].length; col++){ result[row][col] =aveOfNeighbors(image, row, col,neighberhoodSize);}}return result;} // helper method that determines theaverage color of a neighberhood// around a particular cell.private Color aveOfNeighbors(Color[][]image, int row, int col, intneighberhoodSize){ int numNeighbors = 0;int red = 0;int green = 0;int blue = 0;for(int r = row - neighberhoodSize; r<= row + neighberhoodSize; r++){ for(int c = col -neighberhoodSize; c <= col +neighberhoodSize; c++){ if( inBounds( image, r, c ) ){ numNeighbors++;red += image[r][c].getRed();green += image[r][c].getGreen();blue += image[r][c].getBlue();}}}assert numNeighbors > 0;return new Color( red / numNeighbors,green / numNeighbors, blue /numNeighbors );}//helper method to determine if givencoordinates are in boundsprivate boolean inBounds(Color[][]image, int row, int col){ return (row >= 0) && (row <=image.length) && (col >= 0)&& (col < image[0].length);}//private method to ensure mat isrectangularprivate booleanrectangularMatrix( Color[][] mat ){ boolean isRectangular = true;int row = 1;final int COLUMNS = mat[0].length;while( isRectangular && row <mat.length ){ isRectangular = ( mat[row].length== COLUMNS );row++;}return isRectangular; negotiate meet with senior leaders return recruiters' calls
  32. 32. 2 no assholes anywhere!
  33. 33. One Jerk can reduce team performance by 30-40%
  34. 34. 3 point out gender bias
  35. 35. Example 1 ‣ Strategy background ‣ 3 yrs Marketing ‣ PM VP ‣ 15+ yrs PM experience Hiring A PM LeADER
  36. 36. Example 1 ‣ Strategy background ‣ 3 yrs Marketing ‣ "Seems like a go- getter" ‣ PM VP ‣ 15+ yrs PM experience ‣ "Hmmm... Why did it take her so long?" Hiring A PM LeADER
  37. 37. ‣ "Emotional" vs.
 "Passionate" ‣ "Pushy" vs. 
 "Assertive" Women are more likely to receive critical subjective feedback Example 2 performance reviews 50%
  38. 38. Direct Disruptor Passionate Takes control Assertive Honest Takes his time Quick Analytical Follow his gut Expert Abrasive Disruptive Emotional Bossy Pushy Judgmental Takes too long Impulsive Needs to follow her gut Irrational Show off thecooperreview.com Feedback cheat sheet Men woMen
  39. 39. ‣ When people are interrupted ‣ When ideas are mis-attributed Example 3 meetings call it out!
  40. 40. reiterate 's name when you reinforce her point. That matters ... a lot! celebrate the positive "I noticed that you..."
  41. 41. 4 lean into operating mechanisms
  42. 42. Example 1 hiring 1 female and 1 male paired interviewers
  43. 43. "It was so weird, she would ask him a question and he would respond to me!" Example 1 hiring 1 female and 1 male paired interviewers
  44. 44. Bring all senior people, one at a time, to share their work Example 2 talent visibility
  45. 45. Example 3 talent reviews Review the work 
 (aka the designs) 
 at calibration first
  46. 46. 5 test the BOUNDARIES
  47. 47. HARRY POTTER AND THE SORCERER'S STONE, WARNER BROS.
  48. 48. “YOU DON’T KNOW WHERE THE BOUNDARIES ARE UNTIL YOU HIT THEM.” Justin Sherman
  49. 49. Kaaren Hanson @K AARENHANSON THANK YOU

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