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What Works: Gender Equality by Design
Gender equality is a moral and a business imperative. But unconscious bias holds us back, and de-biasing people s minds has proven to be difficult and expensive. Diversity training programs have had limited success, and individual effort alone often invites backlash. Behavioral design offers a new solution. By de-biasing organizations instead of individuals, we can make smart changes that have big impacts. Presenting research-based solutions, Iris Bohnet hands us the tools we need to move the needle in classrooms and boardrooms, in hiring and promotion, benefiting businesses, governments, and the lives of millions.
"What Works" is built on new insights into the human mind. It draws on data collected by companies, universities, and governments in Australia, India, Norway, the United Kingdom, the United States, Zambia, and other countries, often in randomized controlled trials. It points out dozens of evidence-based interventions that could be adopted right now and demonstrates how research is addressing gender bias, improving lives and performance. "What Works" shows what more can be done often at shockingly low cost and surprisingly high speed.
"What Works" is built on new insights into the human mind. It draws on data collected by companies, universities, and governments in Australia, India, Norway, the United Kingdom, the United States, Zambia, and other countries, often in randomized controlled trials. It points out dozens of evidence-based interventions that could be adopted right now and demonstrates how research is addressing gender bias, improving lives and performance. "What Works" shows what more can be done often at shockingly low cost and surprisingly high speed.
385 pages, Hardcover
First published March 8, 2016
About the author
Iris Bohnet
10 books28 followersIris Bohnet, Professor of Public Policy, is a behavioral economist at Harvard Kennedy School, combining insights from economics and psychology to improve decision-making in organizations and society, often with a gender or cross-cultural perspective. She is the author of What Works: Gender Equality by Design, published by Harvard University Press in 2016. Her most recent research examines behavioral design to de-bias how we live, learn and work. Professor Bohnet served as the academic dean of the Kennedy School, is the director of its Women and Public Policy Program, the co-chair (with Max Bazerman) of the Behavioral Insights Group, an associate director of the Harvard Decision Science Laboratory, and the faculty chair of the executive program “Global Leadership and Public Policy for the 21st Century” for the World Economic Forum’s Young Global Leaders. She serves on the boards of directors of Credit Suisse Group and University of Lucerne, as well as the advisory boards of the Vienna University of Economics and Business, EDGE and Applied, as well as numerous academic journals. She is a member of the Global Agenda Council on Behavior of the World Economic Forum.
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September 13, 2016
This book was SO much better than I anticipated, and I am glad I happened across a recommendation for it. Iris Bohnet says in the back that this was a 10 year project, and in my opinion that shows in the level of concise, fascinating, and actionable material.
As a game designer, the details on how to affect behavioral change were delicious. She does a great job of setting up how each chapter problem generally manifests, common mistakes to fix it, ways change have backfired, and successful methods of altering mindsets. The amount of research she references is pure bliss. In fact, it's almost 100 pages of citations in the end of this book if you want to dive into any or all of the studies she mentions.
While the book title seems to infer this is entirely about gender biases (specifically between women/men), I can assure you it's not. That is the main focus however there are SO MANY OTHER things to be gleaned, from ethnic diversity and biases, to how one might more effectively phrase marketing/collection letters to inspire the desired behavioral response.
Honestly there is so much I loved about this book I'm struggling to do it justice in a review, but I HIGHLY recommend it if you have any sort of curiosity in this realm.
As a game designer, the details on how to affect behavioral change were delicious. She does a great job of setting up how each chapter problem generally manifests, common mistakes to fix it, ways change have backfired, and successful methods of altering mindsets. The amount of research she references is pure bliss. In fact, it's almost 100 pages of citations in the end of this book if you want to dive into any or all of the studies she mentions.
While the book title seems to infer this is entirely about gender biases (specifically between women/men), I can assure you it's not. That is the main focus however there are SO MANY OTHER things to be gleaned, from ethnic diversity and biases, to how one might more effectively phrase marketing/collection letters to inspire the desired behavioral response.
Honestly there is so much I loved about this book I'm struggling to do it justice in a review, but I HIGHLY recommend it if you have any sort of curiosity in this realm.
October 24, 2018
I read this book for my work book club, and and I took down a LOT of notes. My library didn't have a copy, so I bought my own, which I NEVER do, but now I'm glad I did it because I kept my pages tabbed for future reference. We had a really good discussion about Chapter 6, which is about interviewing and hiring, and it was so interesting to hear different teams' methods and what people think "culture fit" means. I think this book is best read slowly and as a conversation-starter. Each section is about 20 pages long, with lots of callbacks to research studies, so you need decent stamina. But if you read it slowly and take in the design "cheat sheet" at the end of each chapter, and use those ideas to prompt conversation, that can be constructive. Mowing through it in a week was not ideal, but it was necessary, and it worked fine for me. I am no fan of business books overall, and this one is particularly academic and fairly dry, so fair warning. It was valuable for me, and I'm glad to have read it. There's a lot in this book about bias, and it only reinforced my paranoia that my brain is broken and I can never trust my intuition. Good times!
---
The Promise of Behavioral Design
Gender equality is not just a numbers game. Numbers matter, but how those numbers came to be and how they work with each other is quite possibly even more important. (8)
This fear of trying new things and failing is a real constraint. It is also the one that I had underestimated most. Learning is my business and, naively, I expected everyone to be keen on uncovering past mistakes and improving their decision making. However, in some organizations, acknowledging past errors is risky. Thus, while the CEO or the president might be enthusiastic about discovering mistakes and piloting a new idea, managers at all levels might well feel threatened. To circumvent this, governments and corporations must create safe spaces for experimentation where mistakes are taken as an opportunity to learn. (13)
Replacing intuition, informal networks, and traditional rules of thumb with quantifiable data and rigorous analysis is a first step toward overcoming gender bias. (15)
Di-Biasing Minds is Hard
…for de-biasing to have any meaningful impact, it must involve at a minimum the following four steps: awareness of the possibility of bias; understanding the direction of the bias; immediate feedback when falling prey to the bias, and a training program with regular feedback, analysis, and coaching. (Baruch Fischhoff, 51)
Given all the evidence, what should an organization determine to run a diversity training do? I urge companies to refocus the training on capacity building and adopt the framework unfreeze-change-refreeze… You should not just focus on raising awareness, but also offer specific tools that help people make better decisions. Finally, think of ways you can refreeze the new insights gained and the new behaviors learned. (58; citing Judgment in Managerial Decision Making, by Max Bazerman and Don Moore)
Doing It Yourself is Risky
Gender effects [on pay] appeared primarily when the situational cues regarding expected behavior were ambiguous. When, for example, cues about a position’s typical wage range were clear, women were as good at negotiating as men. (68)
Increasing transparency is low-hanging fruit. It is an easy and practical de-biasing design. Failing to do it is not just ethical dubious, it is very much like leaving the most fertile plot you own undertilled. (81)
Getting Help Only Takes You So Far
A 2014 study in Germany, Austria, and Switzerland went as far as to suggest that these [leadership development] programs might even be counterproductive. “Women are stuck in development and coaching programs while the men get the jobs.” (83)
Sponsors [as compared with mentors] make sure their proteges get visibility and are considered for promising opportunities. They negotiate on their behalf for interesting job assignments, promotions, and pay increases. Sponsors either vicariously or directly benefit from their proteges’ successes. Some firms even hold sponsors accountable for how well their proteges do and reflect this in their pay. Why mentors of women did not become sponsors isn’t clear. … But what was clear was that by 2010 [since 1996], the men in the sample had received 15 percent more promotions than their female colleagues. (87)
Follow-through should also be an integral part of our leadership development programs. (95)
Applying Data to People Decisions
Look up: Logib, an online tool to measure how well companies do in terms of gender pay equity (111)
…the real challenge organizations face is how to design evaluation and compensation procedures that balance the costs of supervisor bias with the benefits of an informed supervisor’s discretion. (117)
“the greatest failure of I-O [industrial and organizational] psychology”: the inability to get employers to rely on “decision aids,” including tests, structured interviews, and a combination of mechanical predictors “that substantially reduce error in the prediction of employee performance.” (135)
The overall predictive power of mental ability was maximized when this measure was combined either with a work sample test (very directly measuring the skill required to perform the job), integrity tests, or – and this is good news for all attached to interviews – with a structured interview. (138)
See interview checklist (145)
Attracting the Right People
Indeed, research by Boris Broysberg, Ashish Nanda, and Nitin Nohria (now dean of Harvard Business School) suggests establishing belonging turnings out to be a major concern of female job seekers. They report that women consider more factors than men when screening jobs; in particular, cultural fit, values, and managerial style. (161)
Leveling the Playing Field
…do away with self-evaluations altogether. To date, I have not come across any evidence suggesting that having people rate themselves yields any benefits for themselves or the organization. Consider junking self-evaluations as a mitigation strategy. While you cannot keep women from evaluating themselves more harshly than their male colleagues evaluate themselves, you can contain the impact the gender difference in this bias has on people’s lives. (188)
… we have too many of the low-performing but overconfident men and too few of the high-performing but less confident women choosing to compete. (189)
When in same-sex groups, women and men were equally willing to volunteer. But when grouped with members of the opposite sex, the pattern suddenly changed. Women volunteered more and men less. Everyone, including the women, assumed women would volunteer more than men. Accordingly, men adjusted their behavior, expecting to benefit from the women, and women lived up to their expectations. (197)
Creating Role Models
Look up: Fast Forward, by Melanne Verveer and Kim Azzarelli
Women have been found to receive lower-quality performance evaluations than men in work groups where they compose less than 20 percent of the group. As their relative presence increased, so did the scores on their performance evaluations. (242)
If you cannot include more than one woman, keep groups homogenous. Creating token members is in nobody’s interest. (242)
Increasing Transparency
To increase the chances that we process it accurately, information needs to be salient, simple, and in comparative context. (268)
Information disclosure, smartly designed, can help organizations act on their virtuous intentions to treat men and women equally and provide both equal opportunities. Providing simple, salient, and comparative information helps. (278)
In their otherwise depressing review of the efficacy of diversity training programs, Frank Dobbin and colleagues found accountability to be one of the most important mechanisms related to the diversity of the labor force. (282)
Designing Change
Good leadership does not end with productivity. Leaders must also make and promote ethical choices. (289)
---
The Promise of Behavioral Design
Gender equality is not just a numbers game. Numbers matter, but how those numbers came to be and how they work with each other is quite possibly even more important. (8)
This fear of trying new things and failing is a real constraint. It is also the one that I had underestimated most. Learning is my business and, naively, I expected everyone to be keen on uncovering past mistakes and improving their decision making. However, in some organizations, acknowledging past errors is risky. Thus, while the CEO or the president might be enthusiastic about discovering mistakes and piloting a new idea, managers at all levels might well feel threatened. To circumvent this, governments and corporations must create safe spaces for experimentation where mistakes are taken as an opportunity to learn. (13)
Replacing intuition, informal networks, and traditional rules of thumb with quantifiable data and rigorous analysis is a first step toward overcoming gender bias. (15)
Di-Biasing Minds is Hard
…for de-biasing to have any meaningful impact, it must involve at a minimum the following four steps: awareness of the possibility of bias; understanding the direction of the bias; immediate feedback when falling prey to the bias, and a training program with regular feedback, analysis, and coaching. (Baruch Fischhoff, 51)
Given all the evidence, what should an organization determine to run a diversity training do? I urge companies to refocus the training on capacity building and adopt the framework unfreeze-change-refreeze… You should not just focus on raising awareness, but also offer specific tools that help people make better decisions. Finally, think of ways you can refreeze the new insights gained and the new behaviors learned. (58; citing Judgment in Managerial Decision Making, by Max Bazerman and Don Moore)
Doing It Yourself is Risky
Gender effects [on pay] appeared primarily when the situational cues regarding expected behavior were ambiguous. When, for example, cues about a position’s typical wage range were clear, women were as good at negotiating as men. (68)
Increasing transparency is low-hanging fruit. It is an easy and practical de-biasing design. Failing to do it is not just ethical dubious, it is very much like leaving the most fertile plot you own undertilled. (81)
Getting Help Only Takes You So Far
A 2014 study in Germany, Austria, and Switzerland went as far as to suggest that these [leadership development] programs might even be counterproductive. “Women are stuck in development and coaching programs while the men get the jobs.” (83)
Sponsors [as compared with mentors] make sure their proteges get visibility and are considered for promising opportunities. They negotiate on their behalf for interesting job assignments, promotions, and pay increases. Sponsors either vicariously or directly benefit from their proteges’ successes. Some firms even hold sponsors accountable for how well their proteges do and reflect this in their pay. Why mentors of women did not become sponsors isn’t clear. … But what was clear was that by 2010 [since 1996], the men in the sample had received 15 percent more promotions than their female colleagues. (87)
Follow-through should also be an integral part of our leadership development programs. (95)
Applying Data to People Decisions
Look up: Logib, an online tool to measure how well companies do in terms of gender pay equity (111)
…the real challenge organizations face is how to design evaluation and compensation procedures that balance the costs of supervisor bias with the benefits of an informed supervisor’s discretion. (117)
“the greatest failure of I-O [industrial and organizational] psychology”: the inability to get employers to rely on “decision aids,” including tests, structured interviews, and a combination of mechanical predictors “that substantially reduce error in the prediction of employee performance.” (135)
The overall predictive power of mental ability was maximized when this measure was combined either with a work sample test (very directly measuring the skill required to perform the job), integrity tests, or – and this is good news for all attached to interviews – with a structured interview. (138)
See interview checklist (145)
Attracting the Right People
Indeed, research by Boris Broysberg, Ashish Nanda, and Nitin Nohria (now dean of Harvard Business School) suggests establishing belonging turnings out to be a major concern of female job seekers. They report that women consider more factors than men when screening jobs; in particular, cultural fit, values, and managerial style. (161)
Leveling the Playing Field
…do away with self-evaluations altogether. To date, I have not come across any evidence suggesting that having people rate themselves yields any benefits for themselves or the organization. Consider junking self-evaluations as a mitigation strategy. While you cannot keep women from evaluating themselves more harshly than their male colleagues evaluate themselves, you can contain the impact the gender difference in this bias has on people’s lives. (188)
… we have too many of the low-performing but overconfident men and too few of the high-performing but less confident women choosing to compete. (189)
When in same-sex groups, women and men were equally willing to volunteer. But when grouped with members of the opposite sex, the pattern suddenly changed. Women volunteered more and men less. Everyone, including the women, assumed women would volunteer more than men. Accordingly, men adjusted their behavior, expecting to benefit from the women, and women lived up to their expectations. (197)
Creating Role Models
Look up: Fast Forward, by Melanne Verveer and Kim Azzarelli
Women have been found to receive lower-quality performance evaluations than men in work groups where they compose less than 20 percent of the group. As their relative presence increased, so did the scores on their performance evaluations. (242)
If you cannot include more than one woman, keep groups homogenous. Creating token members is in nobody’s interest. (242)
Increasing Transparency
To increase the chances that we process it accurately, information needs to be salient, simple, and in comparative context. (268)
Information disclosure, smartly designed, can help organizations act on their virtuous intentions to treat men and women equally and provide both equal opportunities. Providing simple, salient, and comparative information helps. (278)
In their otherwise depressing review of the efficacy of diversity training programs, Frank Dobbin and colleagues found accountability to be one of the most important mechanisms related to the diversity of the labor force. (282)
Designing Change
Good leadership does not end with productivity. Leaders must also make and promote ethical choices. (289)
April 30, 2016
Best for schools or other large institutions looking for politically safe ways to reduce gender (and, to some extent, racial) bias. The relentless push for experimentation and measurement is unfortunately not especially practical for organizations too small to run experiments with any kind of statistical significance. However, for these smaller groups, this book can act as a conservative introduction to unconscious bias, and it does offer some specific organizational changes that have been demonstrated to even out opportunity. If you're going to read a half-dozen books about gender this year, make this one of them. But if you're only going to read one book about gender this year, go for something more radical.
April 15, 2022
“ความลำเอียงทำร้ายคนที่ไม่เป็นไปตามภาพจำเหมารวม ไม่ว่าจะเรื่องเพศสภาพ เชื้อชาติ ชนชั้น ชาติพันธุ์ สัญชาติ หรือวรรณะ” p27
“ผู้หญิงซึ่งละเมิดบรรทัดฐานของสังคม มีต้นทุนทางสังคมที่ต้องจ่าย” p37
———-
เป็นหนังสือที่สารบัญรายละเอียดเยอะมาก เหมือนใส่หัวข้อปลีกย่อยมาหมดเลย
หนังสือแบ่งออกเป็น 4 ส่วน
1 กล่าวถึงปัญหาที่อาจเกิดจากกรอบความคิดเรื่องเพศและปัญหาที่ตามมาจากการพยายามแก้ไขปัญหานั้น
2 วิธีบริหารจัดการ เครื่องมือที่ใช้ช่วยตัดสินใจในสถานการณ์ต่าง ๆ ช่วยแก้ปัญหาหรือแตกยอดแปลงร่างปัญหากันนะ
3 การออกแบบที่ลดความเหลื่อมล้ำทางเพศในโรงเรียนและที่ทำงาน
4 แนวทางในอนาคตเพื่อโอบรับความหลากหลาย แนวคิดที่เปลี่ยนได้ โปร่งใสเพิ่มประสิทธิภาพ การออกแบบช่วยสร้างสมดุลสิ่งที่ควรและสิ่งที่ต้องการ
ตอนแรกแอบอคติในใจว่าสำนวนแปลจะทำให้หงุดหงิดไหมน้า ~ จะแปลคงสำนวนต่างประเทศไว้มากเกินจนอ่านไม่รู้เรื่องไหมนะ
พบว่านมเนยแต่พออ่านได้อยู่ช่วงแรก ๆ //หรือยอมทนเพราะหัวข้อน่าสนใจก็ไม่รู้นะ
แต่ช่วงกลาง ๆ นี่ไม่ไหวเลย เนื้อหาดูน่าสนใจแต่สำนวนทำเบื่อ นมเนย เริ่มอืดจนอ่านช้ามาก ดองเป็นช่วง ๆ
หนังสือยกตัวอย่างมาอธิบายสิ่งที่ต้องการสื่อได้ดี
ชี้ให้เห็นปัญหา gender inequality ในวงการต่าง ๆ และเสนอว่าการเปลี่ยนแปลงบางอย่างแค่เล็กน้อย จะลดความเหลื่อมล้ำตรงนี้ได้อย่างไร
มันไม่ใช่เรื่องที่ยากจนทำไม่ได้ มันเป็นเรื่องง่ายมากจนรู้สึกได้ว่าบางปัญหาที่คาราคาซังอยู่นั้น แก้ไม่ได้ซักทีเพราะไม่ยอมเปลี่ยนมากกว่า
ซึ่งการเปลี่ยนแปลงที่ว่ามันไม่ใช่การแก้แบบขอไปที แต่วิธีนั้นผ่านการสังเกต มีหลักการ มีหลักฐานรองรับ อ้างอิงการศึกษา/งานวิจัย เทียบให้เห็นได้ว่า ถ้าติดกระดุมถูกแต่แรก การติดเม็ดต่อไปมันจะง่ายมาก ๆ
การออกแบบระบบที่ดีแก้ปัญหาได้ ลดเวลาและทรัพยากรที่ต้องมาเสียเพื่อแก้ปัญหาได้ สร้างโอกาสพัฒนาได้อีกมากด้วย
ชอบส่วนที่เล่าถึงสภาพแวดล้อมที่ทำให้เกิดความลำเอียงแบบไม่มีใครตั้งใจ ถ้าไม่คิดจะมองหาหรือเชื่อว่ามันมีอยู่ก็คงมองไม่เห็นสิ่งที่อยู่ตรงหน้า ไม่ต้องพูดถึงจะแก้ยังไงเลย เอาแค่มองเห็นหรือเปล่าก่อน
เรียนรู้เพื่อลดอคติที่แฝงอยู่แบบไม่รู้ตัว
Trait stereotype ~ สิ่งเดียวกันที่อยู่ในคนละเพศ กลับส่งผลต่างกัน
แล้วก็ได้เรียนรู้คำศัพท์เฉพาะที่เอาไว้อธิบายบางสถานการณ์ ที่เราไม่รู้มาก่อน เช่น
ภัยคุกคามต่อช่วงชั้นเชิงเพศสภาพ (gender hierarchy treat) p44
การเลือกปฏิบัติเชิงสถิติ (Statistical discrimination)
ฯลฯ
อยากให้หนังสือมีดัชนี เพราะศัพท์แสงเกี่ยวกับความลำเอียงเยอะมาก เพิ่งรู้ว่ามันเยอะได้ขนาดนี้
มีเรื่องแปลก ๆ ที่เราคิดไม่ถึงด้วยอย่างเช่นตัวอย่างการเพิ่มอัตราการเรียนและการเข้าเรียนในประเทศพัฒนาแล้ว วิธีที่คนคิดไม่ถึงแต่ส่งผลมหาศาลคือการถ่ายพยาธิ p217 เออ น่าสนใจดี คือเราอาจจะสนใจเพราะมันเป็นเรื่องเกี่ยวกับสุขภาพด้วยแหละ
เรียกว่าหนังสือเล่มนี้ยิ่งทำให้เราเห็นชัดเจนว่า
สมองกับความคิดคนเรานี่มันไม่เที่ยงธรรมนัก
โดนชักจูงง่ายจะตาย … แต่จะจูงไปทางไหนนี่ละที่เป็นคำถามที่ต้องตอบกันต่อไป
บางช่วงของหนังสือก็ปาคำถามมารัว ๆ แต่ไม่ได้บอกคำตอบ มาแค่สะกิดให้รู้สึกตัวตนของปัญหา
แต่ก็ต้องยอมรับว่าสิ่งที่นำเสนอในหนังสือมันก็จะตะวันตกมากสักหน่อย
Reference ลิสต์ยาวละเอียดจนกินไป 70 หน้าได้
เป็นหนังสือที่เสนอประเด็นที่ดี แต่อ่านแล้วเบื่อไปบ้าง
กว่าจะอ่านจบ
เหมือนอ่านสรุป review literature จริง ๆ
“ผู้หญิงซึ่งละเมิดบรรทัดฐานของสังคม มีต้นทุนทางสังคมที่ต้องจ่าย” p37
———-
เป็นหนังสือที่สารบัญรายละเอียดเยอะมาก เหมือนใส่หัวข้อปลีกย่อยมาหมดเลย
หนังสือแบ่งออกเป็น 4 ส่วน
1 กล่าวถึงปัญหาที่อาจเกิดจากกรอบความคิดเรื่องเพศและปัญหาที่ตามมาจากการพยายามแก้ไขปัญหานั้น
2 วิธีบริหารจัดการ เครื่องมือที่ใช้ช่วยตัดสินใจในสถานการณ์ต่าง ๆ ช่วยแก้ปัญหาหรือแตกยอดแปลงร่างปัญหากันนะ
3 การออกแบบที่ลดความเหลื่อมล้ำทางเพศในโรงเรียนและที่ทำงาน
4 แนวทางในอนาคตเพื่อโอบรับความหลากหลาย แนวคิดที่เปลี่ยนได้ โปร่งใสเพิ่มประสิทธิภาพ การออกแบบช่วยสร้างสมดุลสิ่งที่ควรและสิ่งที่ต้องการ
ตอนแรกแอบอคติในใจว่าสำนวนแปลจะทำให้หงุดหงิดไหมน้า ~ จะแปลคงสำนวนต่างประเทศไว้มากเกินจนอ่านไม่รู้เรื่องไหมนะ
พบว่านมเนยแต่พออ่านได้อยู่ช่วงแรก ๆ //หรือยอมทนเพราะหัวข้อน่าสนใจก็ไม่รู้นะ
แต่ช่วงกลาง ๆ นี่ไม่ไหวเลย เนื้อหาดูน่าสนใจแต่สำนวนทำเบื่อ นมเนย เริ่มอืดจนอ่านช้ามาก ดองเป็นช่วง ๆ
หนังสือยกตัวอย่างมาอธิบายสิ่งที่ต้องการสื่อได้ดี
ชี้ให้เห็นปัญหา gender inequality ในวงการต่าง ๆ และเสนอว่าการเปลี่ยนแปลงบางอย่างแค่เล็กน้อย จะลดความเหลื่อมล้ำตรงนี้ได้อย่างไร
มันไม่ใช่เรื่องที่ยากจนทำไม่ได้ มันเป็นเรื่องง่ายมากจนรู้สึกได้ว่าบางปัญหาที่คาราคาซังอยู่นั้น แก้ไม่ได้ซักทีเพราะไม่ยอมเปลี่ยนมากกว่า
ซึ่งการเปลี่ยนแปลงที่ว่ามันไม่ใช่การแก้แบบขอไปที แต่วิธีนั้นผ่านการสังเกต มีหลักการ มีหลักฐานรองรับ อ้างอิงการศึกษา/งานวิจัย เทียบให้เห็นได้ว่า ถ้าติดกระดุมถูกแต่แรก การติดเม็ดต่อไปมันจะง่ายมาก ๆ
การออกแบบระบบที่ดีแก้ปัญหาได้ ลดเวลาและทรัพยากรที่ต้องมาเสียเพื่อแก้ปัญหาได้ สร้างโอกาสพัฒนาได้อีกมากด้วย
ชอบส่วนที่เล่าถึงสภาพแวดล้อมที่ทำให้เกิดความลำเอียงแบบไม่มีใครตั้งใจ ถ้าไม่คิดจะมองหาหรือเชื่อว่ามันมีอยู่ก็คงมองไม่เห็นสิ่งที่อยู่ตรงหน้า ไม่ต้องพูดถึงจะแก้ยังไงเลย เอาแค่มองเห็นหรือเปล่าก่อน
เรียนรู้เพื่อลดอคติที่แฝงอยู่แบบไม่รู้ตัว
Trait stereotype ~ สิ่งเดียวกันที่อยู่ในคนละเพศ กลับส่งผลต่างกัน
แล้วก็ได้เรียนรู้คำศัพท์เฉพาะที่เอาไว้อธิบายบางสถานการณ์ ที่เราไม่รู้มาก่อน เช่น
ภัยคุกคามต่อช่วงชั้นเชิงเพศสภาพ (gender hierarchy treat) p44
การเลือกปฏิบัติเชิงสถิติ (Statistical discrimination)
ฯลฯ
อยากให้หนังสือมีดัชนี เพราะศัพท์แสงเกี่ยวกับความลำเอียงเยอะมาก เพิ่งรู้ว่ามันเยอะได้ขนาดนี้
มีเรื่องแปลก ๆ ที่เราคิดไม่ถึงด้วยอย่างเช่นตัวอย่างการเพิ่มอัตราการเรียนและการเข้าเรียนในประเทศพัฒนาแล้ว วิธีที่คนคิดไม่ถึงแต่ส่งผลมหาศาลคือการถ่ายพยาธิ p217 เออ น่าสนใจดี คือเราอาจจะสนใจเพราะมันเป็นเรื่องเกี่ยวกับสุขภาพด้วยแหละ
เรียกว่าหนังสือเล่มนี้ยิ่งทำให้เราเห็นชัดเจนว่า
สมองกับความคิดคนเรานี่มันไม่เที่ยงธรรมนัก
โดนชักจูงง่ายจะตาย … แต่จะจูงไปทางไหนนี่ละที่เป็นคำถามที่ต้องตอบกันต่อไป
บางช่วงของหนังสือก็ปาคำถามมารัว ๆ แต่ไม่ได้บอกคำตอบ มาแค่สะกิดให้รู้สึกตัวตนของปัญหา
แต่ก็ต้องยอมรับว่าสิ่งที่นำเสนอในหนังสือมันก็จะตะวันตกมากสักหน่อย
Reference ลิสต์ยาวละเอียดจนกินไป 70 หน้าได้
เป็นหนังสือที่เสนอประเด็นที่ดี แต่อ่านแล้วเบื่อไปบ้าง
กว่าจะอ่านจบ
เหมือนอ่านสรุป review literature จริง ๆ
Read
May 11, 2016I saw the author present some of the highlights from her then-forthcoming book at a Gender Initiative seminar in December 2015 and became really interested to read the full book.
I was underwhelmed by the book itself.
First, she has a much more moderate approach/tone than I -- which I expect is somewhat by necessity, given the audience, but which put me off from the beginning. (I was also really put off by her use of the term "political correctness" in the "Crafting Groups" chapter. It's drawing on an Administrative Science Quarterly paper which uses the term, but it wasn't clear to me either from reading the chapter or from skimming that paper what "political correctness norms" would be -- Bohnet/the paper authors suggest them as a way of "set[ting] clear expectations for how men and women should interact," thus "reducing interaction uncertainty and boosting creativity in mixed-sex groups" because "men and women both experience uncertainty when asked to generate ideas as members of a mixed-sex work group: men because they may fear offending the women in the group and women because they may fear having their ideas devalued or rejected" -- all quotes from the ASQ abstract. I understand the logic of setting clear norms, but I wanted more clarity about what those expectations might look like, and I hated the use of the term "political correctness" since it's almost always used negatively, to imply concessions to ridiculous fragility on the part of marginalized groups.)
As I continued reading, I was reminded somewhat of Francesca Gino's book Sidetracked -- in that the volume of information can impede the flow of understanding, and I felt like it didn't do a great job of turning summaries of studies into a narrative flow for a lay audience.
The dashpoint takeaways at the end of each chapter sometimes don't make a lot of sense if you haven't actually read the chapter -- which I suppose is fair, but which makes skimming harder and lends itself less well to crafting an overview for someone who hasn't read the book. (Referring back to the notes under each chapter title in the Table of Contents was helpful to me when going back to take summary notes after having finished reading the book.)
It is a thorough overview of cognitive biases and what we know from rigorous experimental study about what's effective to improve outcomes.
She starts with an overview ("Part One: The Problem") -- and then moves on to How to Design Talent Management (Part Two -- Applying Data to People Decisions, Orchestrating Smarter Evaluation Processes, and Attracting the Right People), How to Design School and Work (Part Three -- Adjusting Risk and Leveling the Playing Field), and How to Design Diversity (Part Four -- Creating Role Models, Crafting Groups, Shaping Norms, and Increasing Transparency).
I won't rehash the stuff about choice architecture and cognitive biases, but I did appreciate her summary of the "women don't ask" literature -- taking seriously the social cost to women of asking, and suggesting changes that organizations can make to minimize those costs (invite people to speak up or initiate negotiations, increase transparency about what is negotiable, etc.).
I really like her idea about structured interviews (ask the same questions in the same order, score answers to each question immediately after interview, compare answer to questions across candidates one question at a time, use pre-assigned weights for each question to calculate total score).
One thing I really appreciate about this book is that Bohnet is insistent on digging into what works and acknowledging when we don't know, when she is making recommendations based on what seems to be true but hasn't been rigorously empirically tested. (In line with this, she recommends that we stop showering people with generic leadership development training -- and that we do support people with the resources actually required for success, including mentors/sponsors/networks. I also really appreciated her digging into the gendered differences between how mentorship often functions, and how crucial it is help folks under you build networks, advocate for their advancement, etc.)
In her discussion of forming teams, she advocates for ensuring you have a sufficient amount of people-from-a-given-marginalized-group in a team, otherwise they'll be a token and you'd be better off having a homogeneous group. Which certainly makes sense but which I wouldn't have necessarily predicted.
I also really appreciate her insistence that in working to diversify an organization you:
* Make information salient, simple, and comparable.
* Set both long-term targets and specific, short-term, achievable goals.
* Hold people and organizations accountable for their follow-through.
It's really easy to want to change your demographics, but without clear, measurable, goals it's easy to languish in the land of good intentions.
I was underwhelmed by the book itself.
First, she has a much more moderate approach/tone than I -- which I expect is somewhat by necessity, given the audience, but which put me off from the beginning. (I was also really put off by her use of the term "political correctness" in the "Crafting Groups" chapter. It's drawing on an Administrative Science Quarterly paper which uses the term, but it wasn't clear to me either from reading the chapter or from skimming that paper what "political correctness norms" would be -- Bohnet/the paper authors suggest them as a way of "set[ting] clear expectations for how men and women should interact," thus "reducing interaction uncertainty and boosting creativity in mixed-sex groups" because "men and women both experience uncertainty when asked to generate ideas as members of a mixed-sex work group: men because they may fear offending the women in the group and women because they may fear having their ideas devalued or rejected" -- all quotes from the ASQ abstract. I understand the logic of setting clear norms, but I wanted more clarity about what those expectations might look like, and I hated the use of the term "political correctness" since it's almost always used negatively, to imply concessions to ridiculous fragility on the part of marginalized groups.)
As I continued reading, I was reminded somewhat of Francesca Gino's book Sidetracked -- in that the volume of information can impede the flow of understanding, and I felt like it didn't do a great job of turning summaries of studies into a narrative flow for a lay audience.
The dashpoint takeaways at the end of each chapter sometimes don't make a lot of sense if you haven't actually read the chapter -- which I suppose is fair, but which makes skimming harder and lends itself less well to crafting an overview for someone who hasn't read the book. (Referring back to the notes under each chapter title in the Table of Contents was helpful to me when going back to take summary notes after having finished reading the book.)
It is a thorough overview of cognitive biases and what we know from rigorous experimental study about what's effective to improve outcomes.
She starts with an overview ("Part One: The Problem") -- and then moves on to How to Design Talent Management (Part Two -- Applying Data to People Decisions, Orchestrating Smarter Evaluation Processes, and Attracting the Right People), How to Design School and Work (Part Three -- Adjusting Risk and Leveling the Playing Field), and How to Design Diversity (Part Four -- Creating Role Models, Crafting Groups, Shaping Norms, and Increasing Transparency).
I won't rehash the stuff about choice architecture and cognitive biases, but I did appreciate her summary of the "women don't ask" literature -- taking seriously the social cost to women of asking, and suggesting changes that organizations can make to minimize those costs (invite people to speak up or initiate negotiations, increase transparency about what is negotiable, etc.).
I really like her idea about structured interviews (ask the same questions in the same order, score answers to each question immediately after interview, compare answer to questions across candidates one question at a time, use pre-assigned weights for each question to calculate total score).
One thing I really appreciate about this book is that Bohnet is insistent on digging into what works and acknowledging when we don't know, when she is making recommendations based on what seems to be true but hasn't been rigorously empirically tested. (In line with this, she recommends that we stop showering people with generic leadership development training -- and that we do support people with the resources actually required for success, including mentors/sponsors/networks. I also really appreciated her digging into the gendered differences between how mentorship often functions, and how crucial it is help folks under you build networks, advocate for their advancement, etc.)
In her discussion of forming teams, she advocates for ensuring you have a sufficient amount of people-from-a-given-marginalized-group in a team, otherwise they'll be a token and you'd be better off having a homogeneous group. Which certainly makes sense but which I wouldn't have necessarily predicted.
I also really appreciate her insistence that in working to diversify an organization you:
* Make information salient, simple, and comparable.
* Set both long-term targets and specific, short-term, achievable goals.
* Hold people and organizations accountable for their follow-through.
It's really easy to want to change your demographics, but without clear, measurable, goals it's easy to languish in the land of good intentions.
December 4, 2017
probably the most pragmatic books on changing organizational culture that I've ever read. Over the course of the book, Bohnet offers 36 research-grounded design suggestions for achieving gender equality in the workplace. The use of the word "design" here is intentional: Bohnet is a behavioral economist, and the book offers much in the way of behavioral design from that perspective. Bohnet presents a careful review of current research -- occasionally, this can be a bit dizzying as she walks through conflicting studies, but in the end she consistently delivers evidenced-based recommendations for how to achieve gender equality in the workplace and beyond.
In addition to the huge volume of research surveyed in this book, Bohnet also provides tons of other resources for people and organizations working towards gender equality. It's a tremendous resource of practical and thought-provoking ideas. I really appreciated the depth of coverage. In fact that very depth occasionally had me worried that this book could become a resource for the James Damores of the world to cherry pick isolated arguments out of context. But I suppose it would be a bit too much to expect this book to offer solutions to that. Overall, I can't recommend this book highly enough. It's sure to be something I refer back to often, and if you're interested in understanding and correcting gender inequality, you should read this book.
In addition to the huge volume of research surveyed in this book, Bohnet also provides tons of other resources for people and organizations working towards gender equality. It's a tremendous resource of practical and thought-provoking ideas. I really appreciated the depth of coverage. In fact that very depth occasionally had me worried that this book could become a resource for the James Damores of the world to cherry pick isolated arguments out of context. But I suppose it would be a bit too much to expect this book to offer solutions to that. Overall, I can't recommend this book highly enough. It's sure to be something I refer back to often, and if you're interested in understanding and correcting gender inequality, you should read this book.
May 5, 2016
This was right up my alley. The application of organizational design to this sticky topic was successful, even though I am not sure my organizational would move to implement her suggestions.
July 10, 2019
Bohnet posits 36 suggestions - all backed by research - on how to create increased gender equality in organizations. One of the main arguments of this book is that it is often too hard to change minds so organizations need to build in a structure that changes behavior and thus leads to greater equality. I really, really appreciated that Bohnet doesn't just cherry pick studies that support her suggestions. She's clear on contradictions in research findings, positive interventions that can backfire, etc. The truth is that there aren't a lot of easy answers, but Bohnet gives both hope and concrete suggestions for how to create change.
I almost gave this 3.5 stars because it is a lot to digest and I'm not super confident that I'll take all of this knowledge and implement it (I'm not really in a position to do that anyway), but ultimately I decided on 4 stars because this book is an excellent resource for those who are serious about and in a position to implement change.
I almost gave this 3.5 stars because it is a lot to digest and I'm not super confident that I'll take all of this knowledge and implement it (I'm not really in a position to do that anyway), but ultimately I decided on 4 stars because this book is an excellent resource for those who are serious about and in a position to implement change.
January 16, 2021
An actionable book that contains advices based on the research and data. Some of the outcomes become revelations to me as I haven't thought about them in this way. For example, that having only 1 woman in the team might decrease the productivity of the team as instead of creating diverse team woman is tokenised as representative of their gender instead of being sen as an individual with own point of view and experiences.
Highly recommend for reading for folks who want to learn more about productive diversity and how to design environment, jobs, teams, company were effective diversity will exist by default.
Highly recommend for reading for folks who want to learn more about productive diversity and how to design environment, jobs, teams, company were effective diversity will exist by default.
October 15, 2022
Important book, combining behavioral insights and behavioral economics to diversity and inclusion. Some simple design changes can do a world of good in creating more equality. Most notably in my opinion: the blind auditions in orchestras (increasing the chances of merit-based hiring).
The book also mentions academic work into the effectiveness of all kinds of training (efficacy is often much less than hoped for). Good to see this evidence-based angle. But still a long way to go. I'm not too sure we can nudge/design tweak all differences away easily, but there is certainly room for improvement and evidence-based interventions.
Summary of tweets in a blog post
https://wilte.wordpress.com/2022/10/1...
The book also mentions academic work into the effectiveness of all kinds of training (efficacy is often much less than hoped for). Good to see this evidence-based angle. But still a long way to go. I'm not too sure we can nudge/design tweak all differences away easily, but there is certainly room for improvement and evidence-based interventions.
Summary of tweets in a blog post
https://wilte.wordpress.com/2022/10/1...
March 7, 2021
บทสุดท้ายสรุปใจความข้อเสนอของหนังสือได้ชัดเจนเลย ใครอยากได้ตัว��ย่างงานวิจัยเยอะๆ น่าจะชอบ มีประโยชน์มากๆ ส่วนตัวติดอย่างเดียวคืออ่านไปก็รู้สึกว่ามัน 'แห้ง' จัง คือเต็มไปด้วยงานวิจัยแทบทุกย่อหน้ายังกับ systematic review อ่านไปเลยเหนื่อยไปมากกว่าจะสนุก
October 19, 2019
Iris Bohnet applies ideas from behavioral design to gender bias in work, school, and politics. The book has a lot of good ideas and gave me a lot to think about. Overall though, I give it an average rating because the book's structure is not so great. If I were to want to try to use this in a practical setting, I feel like I would have to flip around for scattered insights that I vaguely remember.
The promise of behavioral design is that most people are not intentionally biased against women. However, we all use heuristics constantly to get through life efficiently. When those heuristics are applied in areas where gender biased behavior has been the norm, then they can lead to biased outcomes even without biased intentions.
As an aside: this book mostly discusses gender. Although behavioral design can also be applied to other types of bias, it is likely that the details vary enough that the case studies and research discussed in this book will not apply exactly. And even applying these ideas to gender, Bohnet cautions that behavioral design is always situational. Organizations should use their own data, perform their own experiments, and then encode their findings in processes and rules suited to their environment.
Unconscious bias is unavoidable. It applies any time a person is in a counterstereotypical role. How depends on the stereotypes that apply. For example, women commonly suffer from being perceived as either competent or likable. Men don't suffer from this particular bias because they are not stereotyped as likable the way that women are. In the face of unconscious bias, we cannot merely ask women to act against the bias. That can make some progress but often at a cost. For example, women who negotiate can get more, but the cost is that they will be perceived as less pleasant to work with.
We can't just ask people to stop being biased. It doesn't work. Indeed, sometimes awareness focused diversity trainings can make things worse by making people feel like they are making better decisions without actually changing anything. Instead, Bohnet recommends we follow a three step process: unfreeze-change-freeze. First, use awareness to "unfreeze" people -- open them to change. Next, perform experiments to figure out what changes work in a particular environment. Finally, "freeze" the insights from the experiments by changing environments and processes to make it easy for people to do the right thing.
One fruitful area for investment is the hiring process. Hiring is already a big investment for companies, and it's an area where relying on intuition can easily lead to bias. Bohnet's most important recommendation is that companies should use structured interview processes, both for the interview itself and while evaluating the interview feedback. Companies should also be aware of the gendered signals they may unintentionally be sending in their job descriptions and environment.
Once people are hired, it's important to make sure that the playing field is level for everyone. Women tend to have less tolerance for risk than men (although, as pointed out earlier, this may be due to the fact that risk distribution is not always gender neutral). Thus, it's important to make sure that biased outcomes are not being driven by unnecessary risk. For example, removing the penalty for incorrect SAT answers encouraged women to guess more. This is important because a willingness to guess was implicated in a portion of the SAT gender score gap. Another way to level the playing field is to design interventions that take into account how the intervention impacts the targeted group, the untargeted group, and overall. An intervention that helps one group at the expense of another is generally not worth it.
Role models are important. Ideally, these are role models within the organization. Lacking those, other role models from the field or even just role models who have overcome barriers in the past can help.
The way we craft groups is also important. Diverse groups have been found to perform better. Except when they don't. How do we interpret all of the nuanced and seemingly contradictory data? And how do we actually form groups that will perform well? Diversity improves performance by bringing multiple perspectives and problem solving approaches to a problem. A team with average skill and diversity can outperform a team of stars if those stars all bring the same strengths to the table. However, homogeneity decreases coordination costs. Combining these things, diversity can improve performance if the particular types of diversity are relevant to the problem domain and adds enough value to offset the increased coordination cost.
Building on this, having the right amount of diversity is important. A token diverse group member can be the worst of both worlds because that lone person can cause coordination costs to increase but because they are seen as a representative of their group, they are not necessarily valued for their individual skills. This is especially harmful for the token member. To get around this, groups need a critical mass of members of any group. There are no hard and fast rules but a good rule of thumb is that it will require at least three people and one-third representation is a good target to aim for. Because of this, Bohnet makes the provocative recommendation that in situations where there are only limited numbers of diverse group members, it is better to have a mix of groups that either achieve critical mass or are homogenous. This can achieve better outcomes than spreading out diverse group members evenly, resulting in more token representatives. Interestingly, the critical mass requirement is not always necessary. In groups that are so diverse that there is no one dominant group, tokenism has less of a negative effect. This provides a good reason, beyond the moral argument, for members of underrepresented groups to support each other.
Behaviors are shaped by the norms that a group or organization is subject too. Changing norms can be a powerful way to change outcomes. Setting rules can help change norms, but mainly in areas where there are not strong existing norms. In areas where there are already established norms, setting rules that try to shift those too dramatically can be worse than having no rules at all. Instead, it can be more effective to try to change norms via people's desire to imitate, compete, and gain social approval. For example, a government can emphasize that most corporate boards have some diversity rather than emphasizing that almost none have parity in gender representation. Transparency and soft defaults can also be effective tools. If people know where they stand, that can drive them to do better.
Overall, this book provides a large suite of pointers and tools. Bohnet does an excellent job of providing caveats so that her suggestions are not taken too literally. In that sense, it's very useful. However, beyond the very high level model of gathering data, running experiments, and then changing processes and the environments to point people toward the right behavior, the content is disconnected enough that it's hard to internalize the ideas.
The promise of behavioral design is that most people are not intentionally biased against women. However, we all use heuristics constantly to get through life efficiently. When those heuristics are applied in areas where gender biased behavior has been the norm, then they can lead to biased outcomes even without biased intentions.
As an aside: this book mostly discusses gender. Although behavioral design can also be applied to other types of bias, it is likely that the details vary enough that the case studies and research discussed in this book will not apply exactly. And even applying these ideas to gender, Bohnet cautions that behavioral design is always situational. Organizations should use their own data, perform their own experiments, and then encode their findings in processes and rules suited to their environment.
Unconscious bias is unavoidable. It applies any time a person is in a counterstereotypical role. How depends on the stereotypes that apply. For example, women commonly suffer from being perceived as either competent or likable. Men don't suffer from this particular bias because they are not stereotyped as likable the way that women are. In the face of unconscious bias, we cannot merely ask women to act against the bias. That can make some progress but often at a cost. For example, women who negotiate can get more, but the cost is that they will be perceived as less pleasant to work with.
We can't just ask people to stop being biased. It doesn't work. Indeed, sometimes awareness focused diversity trainings can make things worse by making people feel like they are making better decisions without actually changing anything. Instead, Bohnet recommends we follow a three step process: unfreeze-change-freeze. First, use awareness to "unfreeze" people -- open them to change. Next, perform experiments to figure out what changes work in a particular environment. Finally, "freeze" the insights from the experiments by changing environments and processes to make it easy for people to do the right thing.
One fruitful area for investment is the hiring process. Hiring is already a big investment for companies, and it's an area where relying on intuition can easily lead to bias. Bohnet's most important recommendation is that companies should use structured interview processes, both for the interview itself and while evaluating the interview feedback. Companies should also be aware of the gendered signals they may unintentionally be sending in their job descriptions and environment.
Once people are hired, it's important to make sure that the playing field is level for everyone. Women tend to have less tolerance for risk than men (although, as pointed out earlier, this may be due to the fact that risk distribution is not always gender neutral). Thus, it's important to make sure that biased outcomes are not being driven by unnecessary risk. For example, removing the penalty for incorrect SAT answers encouraged women to guess more. This is important because a willingness to guess was implicated in a portion of the SAT gender score gap. Another way to level the playing field is to design interventions that take into account how the intervention impacts the targeted group, the untargeted group, and overall. An intervention that helps one group at the expense of another is generally not worth it.
Role models are important. Ideally, these are role models within the organization. Lacking those, other role models from the field or even just role models who have overcome barriers in the past can help.
The way we craft groups is also important. Diverse groups have been found to perform better. Except when they don't. How do we interpret all of the nuanced and seemingly contradictory data? And how do we actually form groups that will perform well? Diversity improves performance by bringing multiple perspectives and problem solving approaches to a problem. A team with average skill and diversity can outperform a team of stars if those stars all bring the same strengths to the table. However, homogeneity decreases coordination costs. Combining these things, diversity can improve performance if the particular types of diversity are relevant to the problem domain and adds enough value to offset the increased coordination cost.
Building on this, having the right amount of diversity is important. A token diverse group member can be the worst of both worlds because that lone person can cause coordination costs to increase but because they are seen as a representative of their group, they are not necessarily valued for their individual skills. This is especially harmful for the token member. To get around this, groups need a critical mass of members of any group. There are no hard and fast rules but a good rule of thumb is that it will require at least three people and one-third representation is a good target to aim for. Because of this, Bohnet makes the provocative recommendation that in situations where there are only limited numbers of diverse group members, it is better to have a mix of groups that either achieve critical mass or are homogenous. This can achieve better outcomes than spreading out diverse group members evenly, resulting in more token representatives. Interestingly, the critical mass requirement is not always necessary. In groups that are so diverse that there is no one dominant group, tokenism has less of a negative effect. This provides a good reason, beyond the moral argument, for members of underrepresented groups to support each other.
Behaviors are shaped by the norms that a group or organization is subject too. Changing norms can be a powerful way to change outcomes. Setting rules can help change norms, but mainly in areas where there are not strong existing norms. In areas where there are already established norms, setting rules that try to shift those too dramatically can be worse than having no rules at all. Instead, it can be more effective to try to change norms via people's desire to imitate, compete, and gain social approval. For example, a government can emphasize that most corporate boards have some diversity rather than emphasizing that almost none have parity in gender representation. Transparency and soft defaults can also be effective tools. If people know where they stand, that can drive them to do better.
Overall, this book provides a large suite of pointers and tools. Bohnet does an excellent job of providing caveats so that her suggestions are not taken too literally. In that sense, it's very useful. However, beyond the very high level model of gathering data, running experiments, and then changing processes and the environments to point people toward the right behavior, the content is disconnected enough that it's hard to internalize the ideas.
September 2, 2020
This is a good book going over a lot of research around what works (and doesn't) to reduce gender inequities. It is likely best as an introduction book but I was already familiar with a fair amount of this research. So while I agreed with most of the points of the author, I didn't feel like I was learning that much.
One of the important points is that it is hard to think in advance about all the consequences that actions can have and experimenting before fully committing to changes can avoid bad consequences.
One of the important points is that it is hard to think in advance about all the consequences that actions can have and experimenting before fully committing to changes can avoid bad consequences.
February 6, 2017
I thought this book was solid, and perhaps the best resource currently available in its topic area, given that it's an area that has been moving fast recently. The information is the best part about it. The weakness is in structure; it's information dumping in a series of paragraphs strung loosely together. Yes they are sorted roughly into chapters but I couldn't tell you what would be found where based on the chapter titles or overviews. Topic changes are not always signaled and there are few signposts that really help to structure the information being given.
Some concepts did feed into my brain usefully. Although I'm well-read in this area, the idea that we should compare candidates head to head to reduce bias was not what I would have guessed (knowing how the police-chief studies showed how bias is definitely present in head-to-head comparison of male and female candidates). Still, minority candidates do even worse when the question is "do I hire this one or not", when the hiring manager is comparing the minority candidate to an abstract stereotype candidate. Apparently one can do even better when hiring several roles: we automatically do a better job of diversity when we're filling a roster of roles. Like filling a donut box with a choice of donuts rather than getting the same single favorite day after day, we automatically seek variety when we're choosing a batch of things. How to apply this in companies? Could even smaller companies batch-hire if they organized it and streamlined their recruiting/interviewing? Do hiring committees that meet to review a batch of candidates do better than individually empowered managers at hiring for diversity?
I'd love to give a better review because the information and ideas are important, but I'm reviewing the book, not the concept of achieving gender equality via behavioral economics. I can't help comparing it to really fantastic books in cognitive science and behavioral economics like those of Lakoff and Kahneman and Tversky.
Some concepts did feed into my brain usefully. Although I'm well-read in this area, the idea that we should compare candidates head to head to reduce bias was not what I would have guessed (knowing how the police-chief studies showed how bias is definitely present in head-to-head comparison of male and female candidates). Still, minority candidates do even worse when the question is "do I hire this one or not", when the hiring manager is comparing the minority candidate to an abstract stereotype candidate. Apparently one can do even better when hiring several roles: we automatically do a better job of diversity when we're filling a roster of roles. Like filling a donut box with a choice of donuts rather than getting the same single favorite day after day, we automatically seek variety when we're choosing a batch of things. How to apply this in companies? Could even smaller companies batch-hire if they organized it and streamlined their recruiting/interviewing? Do hiring committees that meet to review a batch of candidates do better than individually empowered managers at hiring for diversity?
I'd love to give a better review because the information and ideas are important, but I'm reviewing the book, not the concept of achieving gender equality via behavioral economics. I can't help comparing it to really fantastic books in cognitive science and behavioral economics like those of Lakoff and Kahneman and Tversky.
March 8, 2022
The jolting examples of gender bias in the early chapters (the gender composition of US symphonic orchestras in the 70s and the case study analysis conducted by two groups of Harvard students) get your attention and would surely persuade the strongest of gender gap deniers that we have a problem. That said, this book left me contemplating bias in general, as much as gender bias.
How much of what we think and do is shaped by our biases (for better and for worse)? Turns out everything! Does that mean our biases are bad (and therefore we are)? I don't think so (and nor does the book's author). But it means we should a) be aware of our biases and other people's, and b) guard against them leading us down 'the wrong path' on decisions.
The book focusses on gender-based decisions like hiring a person, reviewing the salary of a person, or promoting a person. And this is a very key problem if we're to do our bit to reduce the 'gender gap' and protect/enhance diversity in the work place. It can equally apply to all decisions you make.
An excellent book that gets you thinking. Plenty of academic references to studies that support the topics covered (I wondered while reading it whether there were too many, in fact) but I think it's necessary to ensure the claims made in the book are not baseless, and these cross-references provide plenty of further reading opportunities.
Key takeaway - be mindful of the fact that biases exist (even in your own decision making!!!) and protect against them by putting tactics/techniques/designs in place to manage/mitigate them.
How much of what we think and do is shaped by our biases (for better and for worse)? Turns out everything! Does that mean our biases are bad (and therefore we are)? I don't think so (and nor does the book's author). But it means we should a) be aware of our biases and other people's, and b) guard against them leading us down 'the wrong path' on decisions.
The book focusses on gender-based decisions like hiring a person, reviewing the salary of a person, or promoting a person. And this is a very key problem if we're to do our bit to reduce the 'gender gap' and protect/enhance diversity in the work place. It can equally apply to all decisions you make.
An excellent book that gets you thinking. Plenty of academic references to studies that support the topics covered (I wondered while reading it whether there were too many, in fact) but I think it's necessary to ensure the claims made in the book are not baseless, and these cross-references provide plenty of further reading opportunities.
Key takeaway - be mindful of the fact that biases exist (even in your own decision making!!!) and protect against them by putting tactics/techniques/designs in place to manage/mitigate them.
February 14, 2017
Quote: "Grieg demonstrated that a candidate's assertiveness had nothing to do with his or her performance, meaning the more assertive employee, but not necessary the best performer, was being promoted."
The first half of this book is utterly depressing ("things suck and there's not much we can do about it"). The next quarter is much more positive, but not quite enough to make up for the first half.
It's about 1/4 footnotes/bibliography, which I love.
Something I'm on the fence about: Bohnet makes little to no mention of the fights that ensued to get some of these "redesigns" implemented (eg musicians auditioning behind screens to hide their gender/race). It's an important part of the discussion. I realize that it would have made the book much longer, and potentially distracted from the more practical tack the author takes ("this is good for your business because [reasons]").
The first half of this book is utterly depressing ("things suck and there's not much we can do about it"). The next quarter is much more positive, but not quite enough to make up for the first half.
It's about 1/4 footnotes/bibliography, which I love.
Something I'm on the fence about: Bohnet makes little to no mention of the fights that ensued to get some of these "redesigns" implemented (eg musicians auditioning behind screens to hide their gender/race). It's an important part of the discussion. I realize that it would have made the book much longer, and potentially distracted from the more practical tack the author takes ("this is good for your business because [reasons]").
February 6, 2017
Loved every bit of this book.
July 22, 2021
The problem with books like this is that they introduce the "problem" and the "goal" the wrong way. The problem is the lack of gender equality. The goal is more equality. Nowhere is the distinction between equality and equity defined. One is problematic, the other is not. The same goes for the methods. Nowhere is the problem with coercion discussed, although it is hinted that it is not the best solution even though the author seems to approve of those solutions. When, I hoped she would, going into discussing the morals of the changes, she does not - "It just is the right thing to do. Full stop.". There are lots of moral problems that have to be overlooked in order to apply a system of full equity, but this is never defined correctly so morality is assumed and then trumps all else on the cost of what? Instead of "What Works" the title of the book should be "Whatever Works" if the morals of the methods are not correctly defined. For instance, she praises the efforts done to increase the female percentage of board memberships(it's always about the top jobs!) and because it is achieved it's a great thing, but she does not mention that a mandatory percentage(of 40% women) is difficult when there is not that many with the kind of experience out there. Behind the results does not hide only that yes, some more women get into boards, but also that many of the women simply were part of multiple boards, often to satisfy the requirements. The lack of discussion of the pros and cons, makes some of the examples lackluster together with this looming lack of defining the terms correctly.
This said, it is a good book with lots of data to show and explain and some good solutions to the problem. Iris Bohnet is onto something when it comes to changing attitudes and becoming aware of our biases. This should begin on the root level, on the education, and be worked with a few generations, until the woman workforce is up there with both experience and numbers(we are close in some fields, far in others). One can not expect to get 50-50 of women in the IT world, when the applications you get are skewed 80-20 in favor of men. Biases are still found, but the real amounts would become much nearer to 50-50 if women studied IT more, or other typically male-dominated fields that are high-paid often because of the risk. High-paid work is risk-filled, so why is it so important to mitigate the risk factor from the SAT? Even if I agree that it is good that the tests are equal to all, it does not change how the average woman thinks and acts differently from the average man, and then who is best suited for a risk-filled high-paying job(even if the academic results are same).
Another example of how this book fails is when she in one sentence mentions the penalty of having children when you are a woman(and the slight gain for men), but does not mention that this is the single biggest attribution to the wage gap. The discussion ignores this because it seems to be no great solution for this, even if it is exactly the jobs where this is the most prominent that she focuses a lot on. The jobs where the requirement is to be available 100% of the time over a long period of time without the risk of children taking away half a year, it is a pause in the career. Full stop. This is quite another discussion, yes, but there are other fields that can be "equalized" instead of these jobs as a starting point. And why again is it wrong that the man earns while the woman chooses to be at home in enough cases to make the statistic show a gap?
There is a short mention of male teachers, of which there are few, that we all would want to get more of. But this is compared with talent in music, where talent is a more important factor, and in the context of blind auditions(but we can not get more male teachers because they do not apply on these jobs as much as women! It has nothing to do with the talent - it has more to do with the choices men make based on that men are different than women).
These are details I struggle with when reading this book, and in the back of my head, I think that even when she seems right in an analysis - does she really take in all the factors here? Anyway, this is a mostly good book with a lot of great material which should prompt you to at least try to change the world into a more equal place to work in - and that is a good thing, together with some good pointers on where to begin, it is a great thing. It also has a refreshing lack of feminist jargon.
This said, it is a good book with lots of data to show and explain and some good solutions to the problem. Iris Bohnet is onto something when it comes to changing attitudes and becoming aware of our biases. This should begin on the root level, on the education, and be worked with a few generations, until the woman workforce is up there with both experience and numbers(we are close in some fields, far in others). One can not expect to get 50-50 of women in the IT world, when the applications you get are skewed 80-20 in favor of men. Biases are still found, but the real amounts would become much nearer to 50-50 if women studied IT more, or other typically male-dominated fields that are high-paid often because of the risk. High-paid work is risk-filled, so why is it so important to mitigate the risk factor from the SAT? Even if I agree that it is good that the tests are equal to all, it does not change how the average woman thinks and acts differently from the average man, and then who is best suited for a risk-filled high-paying job(even if the academic results are same).
Another example of how this book fails is when she in one sentence mentions the penalty of having children when you are a woman(and the slight gain for men), but does not mention that this is the single biggest attribution to the wage gap. The discussion ignores this because it seems to be no great solution for this, even if it is exactly the jobs where this is the most prominent that she focuses a lot on. The jobs where the requirement is to be available 100% of the time over a long period of time without the risk of children taking away half a year, it is a pause in the career. Full stop. This is quite another discussion, yes, but there are other fields that can be "equalized" instead of these jobs as a starting point. And why again is it wrong that the man earns while the woman chooses to be at home in enough cases to make the statistic show a gap?
There is a short mention of male teachers, of which there are few, that we all would want to get more of. But this is compared with talent in music, where talent is a more important factor, and in the context of blind auditions(but we can not get more male teachers because they do not apply on these jobs as much as women! It has nothing to do with the talent - it has more to do with the choices men make based on that men are different than women).
These are details I struggle with when reading this book, and in the back of my head, I think that even when she seems right in an analysis - does she really take in all the factors here? Anyway, this is a mostly good book with a lot of great material which should prompt you to at least try to change the world into a more equal place to work in - and that is a good thing, together with some good pointers on where to begin, it is a great thing. It also has a refreshing lack of feminist jargon.
July 31, 2017
I wanted to like this book more than I did, and still see this as an excellent resource for folks just kicking off equity, diversity, and inclusion initiatives at their company. Compared to similar books, this one is easy to read and presents actionable insights. Why this wasn't rated higher for me:
1. She writes advice for how the world is, not how the world should be. Similar to 'Lean In', Bohnet is NOT wrong to encourage women to, say, negotiate more for their pay. She IS wrong to stop there, though. If we are taking organizational or systemic approaches to combating the pay gap, it is not enough to teach more women to negotiate, or even to challenge our own implicit biases when a female candidate does negotiate her pay. Instead, I wanted this book to challenge the premise more. Is there a more equitable way to distribute pay than to ask candidates to negotiate? A better way to conduct or design performance reviews? Etc.
2. She draws almost all of her evidence from psychology experiments done in a lab. These are interesting, and often led to the desired nod of recognition or gasp of surprise, but it feels like a stretch to extrapolate results from these oddly specific, somewhat contorted experiments, and then apply them to designing equity measures in the wild at work. I wish she had used examples from management studies, or employee surveys, or sociology as well.
3. The suggestions did not feel new to me, as someone who reads about these initiatives a lot. This is irrelevant if you are somewhat new to this topic, but if you are well-versed, this might not be the right book for you. I did not leave with the insight or action plan that I hoped to leave with.
1. She writes advice for how the world is, not how the world should be. Similar to 'Lean In', Bohnet is NOT wrong to encourage women to, say, negotiate more for their pay. She IS wrong to stop there, though. If we are taking organizational or systemic approaches to combating the pay gap, it is not enough to teach more women to negotiate, or even to challenge our own implicit biases when a female candidate does negotiate her pay. Instead, I wanted this book to challenge the premise more. Is there a more equitable way to distribute pay than to ask candidates to negotiate? A better way to conduct or design performance reviews? Etc.
2. She draws almost all of her evidence from psychology experiments done in a lab. These are interesting, and often led to the desired nod of recognition or gasp of surprise, but it feels like a stretch to extrapolate results from these oddly specific, somewhat contorted experiments, and then apply them to designing equity measures in the wild at work. I wish she had used examples from management studies, or employee surveys, or sociology as well.
3. The suggestions did not feel new to me, as someone who reads about these initiatives a lot. This is irrelevant if you are somewhat new to this topic, but if you are well-versed, this might not be the right book for you. I did not leave with the insight or action plan that I hoped to leave with.
January 27, 2023
I read a lot of books and journal articles about bias and inequality. It's pretty common for those sources to offer a lot of recommendations for overcoming bias that sound like a good idea on the surface, but don't really have empirical support for their effectiveness and may actually backfire. What I appreciated about this book was that it focused more on what works empirically and frequently discussed what doesn't work or has backfired.
Another common issue in this genre is to advocate for the equality of a specific group in ways that are unfair toward other groups or possibly less beneficial for individuals, organizations, or societies. Once again, this book does a much better job than most but it's still not perfect in this area.
I would recommend this book to most people because I think it will be beneficial for overcoming bias and inequality, especially for anyone in a leadership role, and the examples or studies discussed are also pretty interesting to learn about. If you don't think you have bias, or are just curious about one of the many ways it can be measured, try taking an implicit association test (IAT) linked below.
https://implicit.harvard.edu/implicit...
Another common issue in this genre is to advocate for the equality of a specific group in ways that are unfair toward other groups or possibly less beneficial for individuals, organizations, or societies. Once again, this book does a much better job than most but it's still not perfect in this area.
I would recommend this book to most people because I think it will be beneficial for overcoming bias and inequality, especially for anyone in a leadership role, and the examples or studies discussed are also pretty interesting to learn about. If you don't think you have bias, or are just curious about one of the many ways it can be measured, try taking an implicit association test (IAT) linked below.
https://implicit.harvard.edu/implicit...
June 19, 2021
"What Works: Gender Equality By Design" by Iris Bohnet is a phenomenal book, that dives into behavioral science research and provides strong practical and academic insight on how to address issues of gender inequality across sectors. Bohnet begins by emphasizing gender equality is not just a number's game. Although numbers matter, she argues that how they came to be and how they work together will be how we actually reach gender equality. Bohnet also cites that true equality rests in morals and role models. Within this, she notes that achieving gender equality stems in-part from good leadership which is both about productivity and ethics. The books' concluding remarks on how we all can work towards gender equality are: (1) to move from training to capacity building, (2) to move from intuition to data and structure, (3) to move from an uneven to even playing field, and (4) to move from a numbers game to conditions for success. This book not only offers meaningful insights into the gender divide across the world but serves as a means to bring about effective change in corporate offices, schools, public policy, and beyond!
January 10, 2022
Wow, this took a long time to get through.
What I liked about this book was Bohnet's dispassionate tone. This didn't come across as saying "Women are awesome!! We have to change the world to stop thwarting them because it's the right thing to do." It sort of assumes that... (as do I), but it has more of an angle of "if we improve conditions for women, the whole world benefits for reasons XYZ." I think she reads like an economist. Which she is. And I like that.
But still, I found myself re-reading sentences many times. For whatever reason, Bohnet's writing style just didn't click as intuitive with me. And I also think this book is trying to be more of a survey of existing studies rather than a particular message or thesis. That's fine! It has a lot of valuable experimental outcomes that made me think, and not just about Gender equity. It also is focused on presenting practical advice, which was great and helpful. It just made it dense and slow to read.
I would recommend this book for leaders or curious global citizens. If you are not trying to lead and change an organization, I recommend you skip around and not try to read every last page.
What I liked about this book was Bohnet's dispassionate tone. This didn't come across as saying "Women are awesome!! We have to change the world to stop thwarting them because it's the right thing to do." It sort of assumes that... (as do I), but it has more of an angle of "if we improve conditions for women, the whole world benefits for reasons XYZ." I think she reads like an economist. Which she is. And I like that.
But still, I found myself re-reading sentences many times. For whatever reason, Bohnet's writing style just didn't click as intuitive with me. And I also think this book is trying to be more of a survey of existing studies rather than a particular message or thesis. That's fine! It has a lot of valuable experimental outcomes that made me think, and not just about Gender equity. It also is focused on presenting practical advice, which was great and helpful. It just made it dense and slow to read.
I would recommend this book for leaders or curious global citizens. If you are not trying to lead and change an organization, I recommend you skip around and not try to read every last page.
November 25, 2020
If you’re interested in the topic of equality (in general, not necessarily just gender inequality), this book presents a very compelling set of experiments and data showing the magnitude of the problem at both individual and society level. It then shows tips on how things have changed in different places around the world and proposes ways to apply these changes. These topics of human behaviour are often rather complex and hard to exactly measure and the book usually highlights these shortcomings as well (which is just how great research should work). A lot of the tips presented seem more fitting for people in management or leadership or education roles that can directly impact the change, but if you’re keen on the topic, you can find some interesting things to take away regardless of your career choice.
Overall, definitely the most complete book I’ve read on this topic, full of eye-opening studies on inequality with a set of blueprints to try and see if we can decrease the amount of bias based on gender and race.
Overall, definitely the most complete book I’ve read on this topic, full of eye-opening studies on inequality with a set of blueprints to try and see if we can decrease the amount of bias based on gender and race.
December 15, 2017
Ich bin gespalten.. im Kern ist es ein gutes Buch, das zum Nachdenken über die Gestaltung unserer Arbeitswelt anregt. Welche Bilder hängen wir auf, welche Werte vermitteln wir den Angestellten und wie lässt sich überhaupt ein Umfeld schaffen, in dem Diversität möglich wird. Hier kann man viel mitnehmen. Dies aber vor allem dann, wenn man sich noch nie mit dem Thema beschäftigt hat.
Meine Probleme sind:
1. Diese amerikansiche Art der Vermittlung per Massen an Beispielen bläht das Werk unnötig auf.
2. Die Autorin erklärt immer wieder, dass sie Beratungen und Coaching durchführt.
Gerade 2. hinterlässt dann den faden Beigeschmack einer Art Werbung für ein anderes Geschäft. Obwohl es doch alles auch irgendwie wissenschaftlich sein soll.. was für mich diese Geschäftstriebigkeit ausklammern würde.
Ein wichtiges Buch, im Kern, dem durch die zwei Problempunkte für mich leider die Schlagkraft genommen wird. Schade.
Meine Probleme sind:
1. Diese amerikansiche Art der Vermittlung per Massen an Beispielen bläht das Werk unnötig auf.
2. Die Autorin erklärt immer wieder, dass sie Beratungen und Coaching durchführt.
Gerade 2. hinterlässt dann den faden Beigeschmack einer Art Werbung für ein anderes Geschäft. Obwohl es doch alles auch irgendwie wissenschaftlich sein soll.. was für mich diese Geschäftstriebigkeit ausklammern würde.
Ein wichtiges Buch, im Kern, dem durch die zwei Problempunkte für mich leider die Schlagkraft genommen wird. Schade.
April 30, 2020
Puiki knyga visiems, kurie nori savo organizacijoje padirbėti su lyčių lygybe ir lygių galimybių užtikrinimu, o ir ir šiaip žmogaus teisių temos yra artimos širdžiai. Patiko, kad knyga yra labai praktiška - ne tik aiškiai ir suprantamai paaiškinamos konkrečios problemos, bet ir pasiūloma daugybė tips and tricks, kaip be didelio vargo užtikrinti, kad moterys ir vyrai darbo aplinkoje turėtų lygias sąlygas ir galimybes įsidarbinti, kilti karjeros laiptais, derėtis dėl atlyginimo, derinti asmeninį gyvenimą ir darbą, etc. Tinka ir jei pati/pats esi darbuotoja(s), ir jei esi vadovė (-as), atsakinga(s) už kitus žmones.
Bene geriausia dalis, kad knygoje lyčių lygybės idėjos sujungiamos su biheivioristinės ekonomikos dėsniais ir prieiga. Iš principo labai aiškiai papasakojama, kaip lyčių lygybę be didelio vargo sudizaininti taip, kat tai darbo aplinkoje taptų norma ir nereikėtų pervargti stengiantis keisti žmonių nuostatas iš esmės :)
Bene geriausia dalis, kad knygoje lyčių lygybės idėjos sujungiamos su biheivioristinės ekonomikos dėsniais ir prieiga. Iš principo labai aiškiai papasakojama, kaip lyčių lygybę be didelio vargo sudizaininti taip, kat tai darbo aplinkoje taptų norma ir nereikėtų pervargti stengiantis keisti žmonių nuostatas iš esmės :)
September 21, 2019
A useful book about the research around what motivates (and backfires) in organizations that have sought to diversify or who have been forced to do so by policy. The hard part is that the research findings are so varied, that each chapter ends with a set of bullet points, because it's not easy to pull out the lessons on their own. This isn't unusual for academic research, but I found it disheartening over all since many of the lessons were along the lines of, "existing power structures don't like disruption, so consider lessening the impact of the interventions so they are less threatened overall." All that being said, there are carefully considered examples of where bias hurts groups that we are used to thinking of as most privileged, building a better case overall for taking some of these interventions to heart.
July 18, 2018
While I'm currently not in a position that allows me to implement techniques described in this book, it was an interesting read. While some changes the author proposes are small, not so controversial and undoubtedly beneficial, I am still not entirely convinced about others such as the much disputed quotas for females on boards and in politics. Studies to support them are not so conclusive right now about them, but I'm curious to see how things go in countries that have already implemented them. One thing is for sure, though: the backlash from men exists. At least I have personally seen (experienced?) it.
January 3, 2020
Our society, education systems, work, all of it is designed in a way that favors men. But this is not on purpose. A lot of people have unconscious bias just because of the way they were raised or of the society that surrounded them. This book presents countless experiments that showed what we can do to change this and why we sometimes fail no matter how hard we try. I enjoyed the methodological way everything was explained, but at some point it felt repetitive as a lot of the experiments are similar. This is why I started very fast, but it took me a while to actually finish the book.
I bought this book after I saw a talk by the author, which was very thought provoking, just like the book.
I bought this book after I saw a talk by the author, which was very thought provoking, just like the book.
April 9, 2022
I never thought that much about my own gender. This book was sometimes good sometimes very boring. I don't remember many things. It can be said that it is very economic based, plenty of percentages and many papers are mentioned and it is not really a meta study. It is often told as "one study showed". Was it signifiquant, was the data big enough, did another study (or even more) reach the same conclusion? As a science based employee such books tend to give me headaches. Plus, I did not expect the author to mix in ethnicity to it as well. This was just too much to be covered. I guess it is a current topic, espcecially in the US...
November 27, 2018
Really useful book to be reading in my line of work (Diversity and Inclusion programme designer) with some really fantastic insights, a few of which are already well-known or common sense but many of which are new and impactful.
One star taken off for occasional redundancy - certain passages I felt were pointless as the point had already been made earlier without any new information given.
Overall though, a huge fan of Bohnet and I consider this recommended reading for absolutely anyone who's currently in a position of managing or hiring others.
One star taken off for occasional redundancy - certain passages I felt were pointless as the point had already been made earlier without any new information given.
Overall though, a huge fan of Bohnet and I consider this recommended reading for absolutely anyone who's currently in a position of managing or hiring others.
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