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The Tragedy of Bias in 
Technical Hiring 
in Five Acts 
Kelsey Foley 
Oct 10, 2014 
2014 
#GHC14 
2014
Why are there so few women in tech? 
1. “The Pipeline” – not enough trained women 
2014
Why are there so few women in tech? 
1. “The Pipeline” – not enough trained women 
1. Industry doesn’t know how to recruit and 
2014 
hire women. 
1. Industry doesn’t know how to retain women. 
(Hint: Industry must hire women before retaining them!)
Synopsis 
 The Birthplace of Bias – and how to 
combat it 
 How bias manifests in: 
− Job descriptions 
− The Interview Process 
− The Hire or No-Hire Decision 
2014
Act 1: The Players 
“All the world’s a stage, and all the men 
and women merely players.” 
- William Shakespeare, As You Like It 
2014
Meet Julie Ette: 
2014 
• BS in CS from StateU 
• 5 years work experience with two 
mobile software companies 
• Looking for a new job
Meet Monty and Ben: 
2014 
Monty Gue, 
Engineering manager at 
hot mobile startup Roam.io 
Ben Volio, 
Technical recruiter at 
Roam.io
Will Julie find a match with Monty’s team? 
2014 
Let’s find out…
Act 2: The Birthplace of Bias 
“Wisely and slow. They stumble that run fast.” 
- William Shakespeare, Romeo and Juliet 
2014
The Two-Systems Model of Judgment and Choice 
System 1 Thinking: 
 Fast 
 Effortless 
 Automatic, involuntary 
 Takes mental short cuts 
 Driven by impressions, 
patterns, intuitions, 
memories, and feelings 
 Prone to error and bias 
2014 
unless checked by 
System 2 
System 2 Thinking: 
 Slow 
 Effortful, limited energy 
budget 
 Conscious engagement 
required 
 Can be lazy 
 Applies methodical, 
reasoned, and coherent 
thinking to the System 1 
raw data 
(Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux. 2011.)
System 1 Source Data 
Comes from the cultural soup we experience 
every day since infancy: 
• Role models - parents, teachers, siblings, and 
caregivers 
• TV, books, music, and cultural memes 
• Peers and their own source data! 
System 1 creates a meaningful story from 
our senses and experiences! 
(Efforts to fix The Pipeline change the next generation’s patterns.) 
2014
The Birthplace of Bias 
Cognitive bias happens when System 1 
decides without System 2 helping to 
catch errors, assumptions, biases, and 
mental short cuts! 
(We all do this! Don’t feel bad. It’s part of being human!) 
2014
Tech Company Culture Exacerbates Bias 
“People who are cognitively busy are also 
more likely to make selfish choices, use 
sexist language, and make superficial 
judgments in social situations…. but of 
course cognitive load is not the only cause 
of weakened self-control. A few drinks have 
the same effect, as does a sleepless night.” 
- Dr. Daniel Kahneman, Thinking, Fast and Slow, pp.41 
2014
Common Biases in Hiring 
2014 
 Casuistry 
− using specious reasoning to rationalize behavior 
or decisions 
 The Halo Effect 
− First impressions influence later experience 
 Affect Heuristic 
− People answer an easy question with System 1 
instead of a harder one with System 2
Common Biases in Hiring 
2014 
 Confirmation Bias 
− Seeking data that confirms our ideas 
 Fundamental Attribution Error, or the 
Negativity Effect 
− Over-emphasizing traits in others while 
under-emphasizing situations (luck) in 
ourselves
Common Biases in Hiring 
 Predicting by Representativeness 
− Making decisions using association with a 
2014 
stereotype 
 Projection Bias 
− Unconsciously assuming that others share 
our own perspectives, thoughts, and values
So… How do we overcome our biases? 
“What can be done about biases? How can we 
improve judgments and decisions, both our own and 
those of the institutions that we serve and that serve 
us?... 
The way to block errors that originate in System 1 is 
simple in principle: recognize the signs that you are 
in a cognitive minefield, slow down, and ask for 
reinforcement from System 2. Unfortunately, this 
sensible procedure is least likely to be applied when 
it is needed most.” 
- Dr. Daniel Kahneman, Thinking, Fast and Slow, pp.417 
2014
System 1 in Interviews 
“The optimal time to make a decision about the candidate is 
about three minutes after the end of the interview…. I ask 
interviewers to write immediate feedback after the interview, 
either a “hire” or “no hire”, followed by a one or two paragraph 
justification. It’s due 15 minutes after the interview ends.” 
“Never say “Maybe, I can’t tell.” If you can’t tell, that means No 
Hire. It’s really easier than you’d think. Can’t tell? Just say no! If 
you are on the fence, that means No Hire… Mechanically 
translate all the waffling to “no” and you’ll be all right.” 
- Joel Spolsky, The Guerrilla Guide to Interviewing v3.0, Oct 25, 2006 
http://www.joelonsoftware.com/articles/GuerrillaInterviewing3.html 
2014
Act 3: Attracting Diverse Candidates 
2014
Subtle Cues in Job Descriptions 
The purpose of a job description? 
1. Internal: communicate hiring requirements 
2. External: promote the job and company 
How can the job description project bias? 
(See also: Gaucher, D., Friesen, J., & Kay, A. C. (2011, March 7). Evidence That 
Gendered Wording in Job Advertisements Exists and Sustains Gender Inequality. Journal 
of Personality and Social Psychology. ) 
2014
Bad (and real!) examples 
“Do you have a passion for quality gaming and auto 
racing? XXXX Game Studios is hiring! 
You are a Senior Software Development Engineer 
with broad game development experience and world-class 
software engineering skills. You’re the kind of 
person who drives projects to completion, sometimes 
across multiple functions and groups.” 
(See any Projection Bias? Casuistry? Representativeness?) 
2014
Bad (and real!) examples 
“The Application Programmer Analyst plays a vital role on 
the ZZZZ Medical Group Support team, demonstrating our 
values of patient-centered care and service; respect, caring 
and compassion; teamwork and partnership; continuous 
learning and improvement; and leadership. 
In this position you will: 
Enhance existing computer programs to add value 
throughout the organization…” 
(Representative stereotypes exist for female-dominated roles too) 
2014
Bad (and real!) examples 
“QQQ Software runs a developer paradise: the latest technologies 
and platforms and an elite team of great developers. No résumé 
needed! Great work speaks for itself. We'd love links to your GitHub or 
StackExchange profile! 
Your Profile: 
You live, eat and dream about code and test! Your drive to know 
more and do better makes you evolve...” 
(Projection Bias and Representativeness) 
2014
Some recent (real!) examples 
Education Required: 
BS (Technical ), Masters preferred 
Experience Required: 
Prior experience at the Director level or equivalent 
Physical Requirements: 
Must be able to execute a two-handed reverse dunk on a ten-foot 
rim without the aid of a trampoline. 
2014
Who wants these as 
coworkers? 
(And why are they all holding weapons?) 
2014
To Attract More Diverse Candidates: 
 Be aware of the impact of language. 
 Write job descriptions that don’t create role biases! 
− Look carefully for values, traits, behaviors, and 
2014 
motivations 
− Find gender-neutral ways to “sell” the job 
 Circulate several versions to attract candidates 
with diverse motivations and career objectives. 
 Get people with different perspectives to edit job 
descriptions – how would someone in marketing 
write an engineering job description?
Monty’s JD Ben’s JD 
Roam.io is hiring versatile 
software engineers with a passion 
for making products that impact 
our customer’s lives. Our 
developers support and 
challenges each other to 
continuously learn and improve. 
We believe in working at a 
sustainable pace following Agile 
philosophies. Roam.io offers 
flexible schedules and a 
respectful and fun work 
environment. Join us and make a 
difference! 
Do you live, breathe, eat, and 
dream about coding and mobile? 
Do you crave fanfare and 
adulation from users? Roam.io is 
hiring! We’re looking for software 
geeks who can thrive in our high-energy 
2014 
open office environment. 
We offer great benefits, free food 
and beer, foosball, and tons of 
fun. Come join our elite team and 
push the barriers in mobile 
technology! 
(Which one would Julie apply for? What about Julio?)
Act 4: The Interview 
2014
The Classic Software Interview 
 Short call with a recruiter 
 A technical phone screen, some coding 
 On-site interview with 4-6 sessions, all 
with heavy coding 
 Many tech companies do no training on 
how to interview 
− Some focus on legal areas of questioning 
− A few give training but do not monitor how 
these techniques are used in interviews 
2014
How effective are tech interviews? 
“For the record, we don’t think that the way 
interviewing is done today is necessarily the 
way it should be done. The current paradigm 
puts too much emphasis on the ability to solve 
puzzles and familiarity with a relatively limited 
body of knowledge, and it generally fails to 
measure a lot of the skills that are critical to 
success in industry.” 
- Mongan, John, Eric Giguere, and Noah Kindler. Programming 
Interviews Exposed: Secrets to Landing Your Next Job, 2013, pp. xxvi 
2014
Schmidt, F.L. & Hunter, J.E. (1998) The validity and utility of selection methods in personnel 
psychology: Practical and theoretical implications of 85 years of research findings,” Psychological 
Bulletin, 124, 262–274. 
Personnel Measures Predictive Validity (r) 
Work sample tests 0.54 
General cognitive ability 
0.51 
tests 
2014 
Employment interviews, 
structured 
0.51 
Job knowledge tests 0.48 
Behavioral questions 0.45 
Employment interviews, 
0.38 
unstructured 
Reference checks 0.26 
Job experience 0.18 
Years of education 0.10 
Age -0.01
What can this look like in practice? 
 Train interviewers about cognitive biases 
 Ask some coding questions 
 Also ask behavioral, work habits, and job 
knowledge questions to assess all the 
other success factors 
 A great resource for technical managers to 
use with their teams is this book: 
Rothman, Johanna. Hiring Geeks That Fit. Rothman 
Consulting Group, Inc. 2013. 
2014
Julie’s interview: 
2014 
Welcome with recruiter Ben Volio 
Software lifecycle, Agile, communication style, 
personal work habits with Merlin Cutio 
Petra Escalus: CS fundamentals - complexity, networks, 
threads, databases, OS 
Ty Balt and Amy Bram: lunch at Café Verona 
and behavioral and culture fit 
Cindy Paris: mad programming skillz - languages, algorithms, 
data structures, coding 
Phil Laurence: Debugging and testing in mobile & embedded 
Finish with Hiring Manager Monty Gue
Interviewing is bi-directional! 
Julie is also evaluating: 
− The manager 
− Potential coworkers 
− The company 
− The workplace environment 
− The technology stack 
The interview experience will impact Julie’s 
final decision! 
2014
Act 5: The Decision 
2014
The Post-Interview Debrief 
 Review job requirements first 
 Avoid the Affect Heuristic! 
− Ask: “What evidence did you see that Julie has the skills 
for job requirement #1?” 
− Don’t ask: “What did you think of Julie?” 
 Watch for cognitive landmines: 
− personality traits, intuitions, impressions, or stereotypes, 
− Slow down, engage System 2 
− Dig into possible bias with questions 
 Give a numerical score for each job requirement 
− Numerical scores engage System 2 
− Don’t use “hire” or “no hire” which uses System 1. 
2014
Epilogue 
“If this were play'd upon a stage now, I 
could condemn it as an improbable fiction.” 
- William Shakespeare, Twelfth Night 
2014
Outcomes 
Changing technical interviews won’t convert 
every hire from a tragedy to a romance… 
But, it sets the stage for candidates of all 
kinds to audition on equal terms. 
2014
And what of Julie and fair Roam.io? 
2014
Thank you! 
Want to use #System2Hiring in 
your workplace? 
Or: 
Want to experience 
#System2Hiring yourself? 
My team is hiring! 
2014 
Kelsey Foley 
kelsey@moz.com 
@EnigmaticKelsey
Got Feedback? 
Rate and Review the session using the 
GHC Mobile App 
To download visit www.gracehopper.org 
2014

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The Tragedy of Bias in Technical Hiring in Five Acts (Grace Hopper 2014)

  • 1. The Tragedy of Bias in Technical Hiring in Five Acts Kelsey Foley Oct 10, 2014 2014 #GHC14 2014
  • 2. Why are there so few women in tech? 1. “The Pipeline” – not enough trained women 2014
  • 3. Why are there so few women in tech? 1. “The Pipeline” – not enough trained women 1. Industry doesn’t know how to recruit and 2014 hire women. 1. Industry doesn’t know how to retain women. (Hint: Industry must hire women before retaining them!)
  • 4. Synopsis  The Birthplace of Bias – and how to combat it  How bias manifests in: − Job descriptions − The Interview Process − The Hire or No-Hire Decision 2014
  • 5. Act 1: The Players “All the world’s a stage, and all the men and women merely players.” - William Shakespeare, As You Like It 2014
  • 6. Meet Julie Ette: 2014 • BS in CS from StateU • 5 years work experience with two mobile software companies • Looking for a new job
  • 7. Meet Monty and Ben: 2014 Monty Gue, Engineering manager at hot mobile startup Roam.io Ben Volio, Technical recruiter at Roam.io
  • 8. Will Julie find a match with Monty’s team? 2014 Let’s find out…
  • 9. Act 2: The Birthplace of Bias “Wisely and slow. They stumble that run fast.” - William Shakespeare, Romeo and Juliet 2014
  • 10. The Two-Systems Model of Judgment and Choice System 1 Thinking:  Fast  Effortless  Automatic, involuntary  Takes mental short cuts  Driven by impressions, patterns, intuitions, memories, and feelings  Prone to error and bias 2014 unless checked by System 2 System 2 Thinking:  Slow  Effortful, limited energy budget  Conscious engagement required  Can be lazy  Applies methodical, reasoned, and coherent thinking to the System 1 raw data (Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux. 2011.)
  • 11. System 1 Source Data Comes from the cultural soup we experience every day since infancy: • Role models - parents, teachers, siblings, and caregivers • TV, books, music, and cultural memes • Peers and their own source data! System 1 creates a meaningful story from our senses and experiences! (Efforts to fix The Pipeline change the next generation’s patterns.) 2014
  • 12. The Birthplace of Bias Cognitive bias happens when System 1 decides without System 2 helping to catch errors, assumptions, biases, and mental short cuts! (We all do this! Don’t feel bad. It’s part of being human!) 2014
  • 13. Tech Company Culture Exacerbates Bias “People who are cognitively busy are also more likely to make selfish choices, use sexist language, and make superficial judgments in social situations…. but of course cognitive load is not the only cause of weakened self-control. A few drinks have the same effect, as does a sleepless night.” - Dr. Daniel Kahneman, Thinking, Fast and Slow, pp.41 2014
  • 14. Common Biases in Hiring 2014  Casuistry − using specious reasoning to rationalize behavior or decisions  The Halo Effect − First impressions influence later experience  Affect Heuristic − People answer an easy question with System 1 instead of a harder one with System 2
  • 15. Common Biases in Hiring 2014  Confirmation Bias − Seeking data that confirms our ideas  Fundamental Attribution Error, or the Negativity Effect − Over-emphasizing traits in others while under-emphasizing situations (luck) in ourselves
  • 16. Common Biases in Hiring  Predicting by Representativeness − Making decisions using association with a 2014 stereotype  Projection Bias − Unconsciously assuming that others share our own perspectives, thoughts, and values
  • 17. So… How do we overcome our biases? “What can be done about biases? How can we improve judgments and decisions, both our own and those of the institutions that we serve and that serve us?... The way to block errors that originate in System 1 is simple in principle: recognize the signs that you are in a cognitive minefield, slow down, and ask for reinforcement from System 2. Unfortunately, this sensible procedure is least likely to be applied when it is needed most.” - Dr. Daniel Kahneman, Thinking, Fast and Slow, pp.417 2014
  • 18. System 1 in Interviews “The optimal time to make a decision about the candidate is about three minutes after the end of the interview…. I ask interviewers to write immediate feedback after the interview, either a “hire” or “no hire”, followed by a one or two paragraph justification. It’s due 15 minutes after the interview ends.” “Never say “Maybe, I can’t tell.” If you can’t tell, that means No Hire. It’s really easier than you’d think. Can’t tell? Just say no! If you are on the fence, that means No Hire… Mechanically translate all the waffling to “no” and you’ll be all right.” - Joel Spolsky, The Guerrilla Guide to Interviewing v3.0, Oct 25, 2006 http://www.joelonsoftware.com/articles/GuerrillaInterviewing3.html 2014
  • 19. Act 3: Attracting Diverse Candidates 2014
  • 20. Subtle Cues in Job Descriptions The purpose of a job description? 1. Internal: communicate hiring requirements 2. External: promote the job and company How can the job description project bias? (See also: Gaucher, D., Friesen, J., & Kay, A. C. (2011, March 7). Evidence That Gendered Wording in Job Advertisements Exists and Sustains Gender Inequality. Journal of Personality and Social Psychology. ) 2014
  • 21. Bad (and real!) examples “Do you have a passion for quality gaming and auto racing? XXXX Game Studios is hiring! You are a Senior Software Development Engineer with broad game development experience and world-class software engineering skills. You’re the kind of person who drives projects to completion, sometimes across multiple functions and groups.” (See any Projection Bias? Casuistry? Representativeness?) 2014
  • 22. Bad (and real!) examples “The Application Programmer Analyst plays a vital role on the ZZZZ Medical Group Support team, demonstrating our values of patient-centered care and service; respect, caring and compassion; teamwork and partnership; continuous learning and improvement; and leadership. In this position you will: Enhance existing computer programs to add value throughout the organization…” (Representative stereotypes exist for female-dominated roles too) 2014
  • 23. Bad (and real!) examples “QQQ Software runs a developer paradise: the latest technologies and platforms and an elite team of great developers. No résumé needed! Great work speaks for itself. We'd love links to your GitHub or StackExchange profile! Your Profile: You live, eat and dream about code and test! Your drive to know more and do better makes you evolve...” (Projection Bias and Representativeness) 2014
  • 24. Some recent (real!) examples Education Required: BS (Technical ), Masters preferred Experience Required: Prior experience at the Director level or equivalent Physical Requirements: Must be able to execute a two-handed reverse dunk on a ten-foot rim without the aid of a trampoline. 2014
  • 25. Who wants these as coworkers? (And why are they all holding weapons?) 2014
  • 26. To Attract More Diverse Candidates:  Be aware of the impact of language.  Write job descriptions that don’t create role biases! − Look carefully for values, traits, behaviors, and 2014 motivations − Find gender-neutral ways to “sell” the job  Circulate several versions to attract candidates with diverse motivations and career objectives.  Get people with different perspectives to edit job descriptions – how would someone in marketing write an engineering job description?
  • 27. Monty’s JD Ben’s JD Roam.io is hiring versatile software engineers with a passion for making products that impact our customer’s lives. Our developers support and challenges each other to continuously learn and improve. We believe in working at a sustainable pace following Agile philosophies. Roam.io offers flexible schedules and a respectful and fun work environment. Join us and make a difference! Do you live, breathe, eat, and dream about coding and mobile? Do you crave fanfare and adulation from users? Roam.io is hiring! We’re looking for software geeks who can thrive in our high-energy 2014 open office environment. We offer great benefits, free food and beer, foosball, and tons of fun. Come join our elite team and push the barriers in mobile technology! (Which one would Julie apply for? What about Julio?)
  • 28. Act 4: The Interview 2014
  • 29. The Classic Software Interview  Short call with a recruiter  A technical phone screen, some coding  On-site interview with 4-6 sessions, all with heavy coding  Many tech companies do no training on how to interview − Some focus on legal areas of questioning − A few give training but do not monitor how these techniques are used in interviews 2014
  • 30. How effective are tech interviews? “For the record, we don’t think that the way interviewing is done today is necessarily the way it should be done. The current paradigm puts too much emphasis on the ability to solve puzzles and familiarity with a relatively limited body of knowledge, and it generally fails to measure a lot of the skills that are critical to success in industry.” - Mongan, John, Eric Giguere, and Noah Kindler. Programming Interviews Exposed: Secrets to Landing Your Next Job, 2013, pp. xxvi 2014
  • 31. Schmidt, F.L. & Hunter, J.E. (1998) The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings,” Psychological Bulletin, 124, 262–274. Personnel Measures Predictive Validity (r) Work sample tests 0.54 General cognitive ability 0.51 tests 2014 Employment interviews, structured 0.51 Job knowledge tests 0.48 Behavioral questions 0.45 Employment interviews, 0.38 unstructured Reference checks 0.26 Job experience 0.18 Years of education 0.10 Age -0.01
  • 32. What can this look like in practice?  Train interviewers about cognitive biases  Ask some coding questions  Also ask behavioral, work habits, and job knowledge questions to assess all the other success factors  A great resource for technical managers to use with their teams is this book: Rothman, Johanna. Hiring Geeks That Fit. Rothman Consulting Group, Inc. 2013. 2014
  • 33. Julie’s interview: 2014 Welcome with recruiter Ben Volio Software lifecycle, Agile, communication style, personal work habits with Merlin Cutio Petra Escalus: CS fundamentals - complexity, networks, threads, databases, OS Ty Balt and Amy Bram: lunch at Café Verona and behavioral and culture fit Cindy Paris: mad programming skillz - languages, algorithms, data structures, coding Phil Laurence: Debugging and testing in mobile & embedded Finish with Hiring Manager Monty Gue
  • 34. Interviewing is bi-directional! Julie is also evaluating: − The manager − Potential coworkers − The company − The workplace environment − The technology stack The interview experience will impact Julie’s final decision! 2014
  • 35. Act 5: The Decision 2014
  • 36. The Post-Interview Debrief  Review job requirements first  Avoid the Affect Heuristic! − Ask: “What evidence did you see that Julie has the skills for job requirement #1?” − Don’t ask: “What did you think of Julie?”  Watch for cognitive landmines: − personality traits, intuitions, impressions, or stereotypes, − Slow down, engage System 2 − Dig into possible bias with questions  Give a numerical score for each job requirement − Numerical scores engage System 2 − Don’t use “hire” or “no hire” which uses System 1. 2014
  • 37. Epilogue “If this were play'd upon a stage now, I could condemn it as an improbable fiction.” - William Shakespeare, Twelfth Night 2014
  • 38. Outcomes Changing technical interviews won’t convert every hire from a tragedy to a romance… But, it sets the stage for candidates of all kinds to audition on equal terms. 2014
  • 39. And what of Julie and fair Roam.io? 2014
  • 40. Thank you! Want to use #System2Hiring in your workplace? Or: Want to experience #System2Hiring yourself? My team is hiring! 2014 Kelsey Foley kelsey@moz.com @EnigmaticKelsey
  • 41. Got Feedback? Rate and Review the session using the GHC Mobile App To download visit www.gracehopper.org 2014

Hinweis der Redaktion

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