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

1. Kaaren Hanson
@K AARENHANSON
ELIMINATE THE GAP

3. BIASGENDER

4. 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

5. 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

6. 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

7. $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

8. 45%Middle school
girls
42%Middle school
boys
National Assessment of Educational Progress, 2016
girls and boys proficient in STEM

9. 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

10. BIASGENDER
IMPLICIT PERVASIVE&

11. 5 HRS/DAY ON TV
Source: Nielsen 2016 Audience Report

12. 11 HRS/DAY ON MEDIA
Source: Nielsen 2016 Audience Report
5 HRS/DAY ON TV

14. The bechtel test:
two women have names +
talk to each other about something besides a man

15. The bechtel test:
50% FAIL
OFFILMS
two women have names +
talk to each other about something besides a man

18. WTF?!~17%WOMEN

19. WTF?!~17%WOMEN

20. 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

21. 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

22. 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)

23. Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html

24. Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html
Assertive
Competent
Strategic
Independent

25. Helpful
Expressive
Friendly
Nurturing
https://implicit.harvard.edu/implicit/takeatest.html
Assertive
Competent
Strategic
Independent
Leadership

26. Men and women have
very different experiences

27. Men and women have
very different experiences
Women are more likely to be told they're "too aggressive"10x

28. 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

29. 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

30. 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

31. What do we as leaders do?

32. *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!

33. *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

34. *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

35. *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

36. 2 no assholes
anywhere!

37. One Jerk can reduce
team performance by
30-40%

38. 3 point out
gender bias

39. Example 1
‣ Strategy background
‣ 3 yrs Marketing
‣ PM VP
‣ 15+ yrs PM experience
Hiring A PM LeADER

40. 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

41. ‣ "Emotional" vs.
"Passionate"
‣ "Pushy" vs.
"Assertive"
Women are
more likely to receive
critical subjective feedback
Example 2
performance reviews
50%

42. 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

43. ‣ When people are interrupted
‣ When ideas are mis-attributed
Example 3
meetings
call it out!

44. reiterate 's name when
you reinforce her point.
That matters ... a lot!
celebrate the positive
"I noticed that you..."

45. 4 lean into operating
mechanisms

46. Example 1
hiring
1 female and 1 male paired interviewers

47. "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

48. Bring all senior
people, one at a time,
to share their work
Example 2
talent visibility

49. Example 3
talent reviews
Review the work
(aka the designs)
at calibration
first

50. 5 test the
BOUNDARIES

51. HARRY POTTER AND THE SORCERER'S STONE, WARNER BROS.

52. “YOU DON’T KNOW WHERE
THE BOUNDARIES ARE UNTIL
YOU HIT THEM.” Justin Sherman

53. Kaaren Hanson
@K AARENHANSON
THANK YOU