From bias to belonging talk slides
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The document discusses the importance of addressing bias and stereotypes in tech communities, particularly in relation to gender and ethnicity. It emphasizes the negative impacts of bias, such as discrimination and missed opportunities, and provides strategies for challenging personal biases during hiring and interactions. Additionally, it highlights the need for continuous self-reflection and education to foster inclusive environments.
From bias to belonging talk slides
- 2. FROM BIAS TO BELONGING Creating inclusive Tech Communities
- 3. ARISA FUKUZAKI DevRel Engineer at Storyblok GirlCode Ambassador GDE, Web Technologies 🥑 👩🏻💻 Girl Code Coffee Chat Host 🎙️
- 4. JOSEFINE SCHAEFER DevRel Engineer at Storyblok GirlCode Ambassador GDE, Web Technologies 🥑 👩🏻💻 Girl Code Coffee Chat Host 🎙️
- 6. 01 - BIAS VS. STEREOTYPES 02 - BIAS 101 03 - QUIZ TIME 03 - TAKE AWAY
- 7. WHAT PEOPLE IMAGINE ABOUT OUR (DEV’S) PERSONALITY
- 8. Video games
- 14. STEREOTYPES Preconveived idea attributing certain characteristics to a group Often oversimplified & exaggerated Consciously endorsed & Intentional
- 15. VS. BIAS Mostly unconconscious Tendency or preference towards a particular perspective or result Interferes with the ability to be impartial, unprejudiced & objective
- 16. WHERE DOES BIAS COMES?
- 17. DANGER
- 19. HOW CAN BIAS HURT US? WHY SHOULD YOU CARE?
- 20. Discrimination & Inequity Lower Performance Missed Opportunity for Growth Higher Turnover & Difficulty attracting Talent
- 22. WHAT PEOPLE THINK WE (DEVS) DO & REALITY
- 24. WHAT OUR FAMILY & FRIENDS THINK WE CAN DO
- 26. BIAS CREATES WRONG IMAGES OF PEOPLE
- 27. BIAS IS A BUG IN THE SYSTEM
- 28. UNFORTUNATELY, OUR TECH WORLD IS NOT AN EXCEPTION
- 30. STACK OVERFLOW 2022 Demographics STATE OF JAVASCRIPT 2022 Demographics
- 31. GENDER WOMEN MEN NON-BINARY, GENDER QUEER/NON-CONFIRMING 5.1% 91.8% 1.6% STACK OVERFLOW WOMEN MEN NON-BINARY, GENDER QUEER/NON-CONFIRMING 4% 70.1% 1.1% STATE OF JS
- 32. 0% 20% 40% 60% 80% White Asian Hispanic/Latino/a Middle Eastern African RACE & ETHNICITY 76.63% 19.18% 5.71% 4.1% 3.3% 0% 20% 40% 60% White Asian Hispanic/Latino/a Middle Eastern African 50.2% 11.9% 7.1% 3% 2.8% STACK OVERFLOW STATE OF JS
- 33. < 18 18-24 25-34 35-44 45-54 55-64 >65 40% 30% 20% 10% 0% AGE <= 18 19-24 25-34 35-44 45-54 55-64 >65 40% 30% 20% 10% 0% STACK OVERFLOW STATE OF JS
- 34. HOW MANY OF THE BOXES DO YOU TICK? ARE YOU PART OF THE MAJORITY?
- 35. HOW DO YOU DESCRIBE THE MAJORITY OF THE DEVS BASED ON THESE DEMOGRAPHICS?
- 37. IS THIS AN ACCURATE REPRESENTATION OF THE DEV COMMUNITY?
- 38. IS THIS AN ACCURATE REPRESENTATION OF THE DEV COMMUNITY? SORT OF!?
- 39. 0% 5% 10% 15% 20% USA Germany France UK India Canada Poland Brazil COUNTRY OR REGION: STATE OF JS
- 41. CURRENT DEMOGRAPHICS HOW THE MINORITY FEELS “Should I fit into the majority to avoid standing out in a bad way?”
- 42. CURRENT DEMOGRAPHICS HOW THE MINORITY FEELS “Should I fit into the majority to avoid standing out in a bad way?” Confronted with lot’s of (unconscious) bias that adds up to the mounting pressure.
- 43. QUICK EXERCISES
- 44. 1: EVERYONE TAKES DIFFERENTLY APPEARANCE You are at the conf booth & went to talk to people there. A woman there was showing you a quick demo:
- 45. 1: EVERYONE TAKES DIFFERENTLY APPEARANCE You are at the conf booth & went to talk to people there. A woman there was showing you a quick demo: A: You said to her “You don’t look like a dev. It’s amazing how you can explain me!“
- 46. 1: EVERYONE TAKES DIFFERENTLY APPEARANCE B: Don’t make comments about how you didn’t expect women to be devs even if you wondered. You are at the conf booth & went to talk to people there. A woman there was showing you a quick demo: A: You said to her “You don’t look like a dev. It’s amazing how you can explain me!“
- 47. 1: EVERYONE TAKES DIFFERENTLY APPEARANCE B: Don’t make comments about how you didn’t expect women to be devs even if you wondered. You are at the conf booth & went to talk to people there. A woman there was showing you a quick demo: A: You said to her “You don’t look like a dev. It’s amazing how you can explain me!“
- 48. 1: EVERYONE TAKES DIFFERENTLY APPEARANCE A woman at the conf booth: “Why did this person think I’m not a dev? Is it because I’m a woman?” “You don’t look like a dev. It’s amazing how you can explain me!“
- 49. 2: ASK BEFORE YOU ASSUME CULTURE Colleague B (man, Korean) is new to the company. You wanted to greet him in his cultural way:
- 50. 2: ASK BEFORE YOU ASSUME CULTURE Colleague B (man, Korean) is new to the company. You wanted to greet him in his cultural way: A: You greet him with what you watched in the movie with 🙏
- 51. 2: ASK BEFORE YOU ASSUME CULTURE B: You ask him how to greet in his culture and follow what he tells you the way to greet. Colleague B (man, Korean) is new to the company. You wanted to greet him in his cultural way: A: You greet him with what you watched in the movie with 🙏
- 52. 2: ASK BEFORE YOU ASSUME CULTURE B: You ask him how to greet in his culture and follow what he tells you the way to greet. Colleague B (man, Korean) is new to the company. You wanted to greet him in his cultural way: A: You greet him with what you watched in the movie with 🙏
- 53. 2: ASK BEFORE YOU ASSUME CULTURE Colleague B: “🙏is not universal in all Asian countries... I feel a bit offended...” Greet him with what you watched in the movie with 🙏
- 54. 3. BIAS IN HIRING & PROMOTIONS HIRING You are a manager & have two candidates with equal qualifications, but only one spot to fill. Your gut feeling gears towards the male:
- 55. HIRING 3. BIAS IN HIRING & PROMOTIONS You are a manager & have two candidates with equal qualifications, but only one spot to fill. Your gut feeling gears towards the male: A: You go with your gut and hire Boris, who looks just like you.
- 56. HIRING B: You challenge your bias, compare team and cultural fit, qualifications and get a second opinion to make sure you are getting the best candidate. You are a manager & have two candidates with equal qualifications, but only one spot to fill. Your gut feeling gears towards the male: A: You go with your gut and hire Boris, who looks just like you. 3. BIAS IN HIRING & PROMOTIONS
- 57. HIRING 3. BIAS IN HIRING & PROMOTIONS B: You challenge your bias, compare team and cultural fit, qualifications and get a second opinion to make sure you are getting the best candidate. You are a manager & have two candidates with equal qualifications, but only one spot to fill. Your gut feeling gears towards the male: A: You go with your gut and hire Boris, who looks just like you.
- 58. HIRING Everyone has bias subconsciously. Try to keep in your mind to make decisions with a second opinion instead of your instinct. 3. BIAS IN HIRING & PROMOTIONS A: You go with your gut and hire Boris, who looks just like you.
- 60. TAKEAWAY Don’t worry, we are all biased.
- 62. BUT We can continually reflect on our personal biases. And we should. Listen and Learn
- 63. BUT We can continually reflect on our personal biases. And we should. Listen and Learn Challenge Your Own Biases & Stereotypes
- 64. BUT We can continually reflect on our personal biases. And we should. Listen and Learn Challenge Your Own Biases & Stereotypes Educate yourself
- 65. BUT We can continually reflect on our personal biases. And we should. Listen and Learn Challenge Your Own Biases & Stereotypes Educate yourself Seek Feedback
- 66. BUT We can continually reflect on our personal biases. And we should. Listen and Learn Challenge Your Own Biases & Stereotypes Educate yourself Seek Feedback Use Data (carefully), Metrics & Structures
- 67. BUT We can continually reflect on our personal biases. And we should. Listen and Learn Challenge Your Own Biases & Stereotypes Educate yourself Seek Feedback Use Data (carefully), Metrics & Structures Accept and Recognize your own Biases
- 68. FEEDBACK/ COMMENTS will help us improve to present high-quality talks.