How We Hacked the Gender Pay Gap

By Smita Satiani, Deputy Director Presidential Innovation Fellows and Kyla Fullenwider, 2016 Presidential Innovation Fellow

This past April on Equal Pay Day, a team of Presidential Innovation Fellows, the U.S. Department of Commerce and the White House Council on Women and Girls launched a challenge to developers, designers, and data scientists across the country: can you use your skills to help get women paid what they deserve?

Using newly released datasets from the Census MIDAAS platform, we called on teams of technologists, data-scientists, designers, and subject-matter experts from across the country to create new solutions for a very old problem: the gender pay gap. We wanted to breathe new life into the decades old problem by tackling it with some of the most powerful tools available to us now — things like big data, interactive visualizations, and virtual reality.

Our challenge: How might these technology tools help us solve one of the most pervasive and complex problems facing women, families, and companies across the world?

Over the course of the last 6 months, we traveled across the country, spoke with hundreds of people who cared about this issue, engaged 350+ data science students in 15 markets from across the U.S., and launched a public Slack channel where we hosted subject matter experts and built a community of over 200 people discussing things like the motherhood penalty, hiring bias, and the economic impact of wage discrimination.

But most importantly, we tried to go beyond the talk and build things.

For twelve weeks, seven teams and 45 people from across the U.S. came together to create a diverse range of products aimed at creating tools for companies, women and the broader public. From a personalized pay calculator to a virtual reality negotiation tool, these products not only created new ways of looking at the problem, but tangible ways individuals and companies can take action by creating more transparency around salary, gender bias in hiring, and the economic impact of the pay gap.

All this work culminated at the first-ever White House Pay Gap Demo Day, as teams from across the country joined Secretary of Commerce Penny Pritzker, U.S. Chief Technology Officer Megan Smith, and Commerce Chief Economist Ellen Hughes-Cromwick to share the truly game changing outcomes they built over many early mornings and late nights. We couldn’t have been more thrilled to see their products — which you can read about below — or more proud to read this headline when we woke up the next morning: “Secretary Pritzker Calls for Data-Driven Solutions for Ending Pay Discrimination”.

U.S. CTO Megan Smith and Department of Commerce Secretary Penny Pritzker join Demo Day teams at the White House (Photo credit: Clara Tsao)

Thanks to the Presidential Innovation Fellows who helped to coach our teams: Josh Patterson, Tyrone Grandison, Mollie Ruskin, Patrick Koppula, Adam Becker, Luke Keller, Adam Bonnifield, Ross Dakin, Amy Wilson, Robert Zakon, Erren Lester, Steve Babitch, Clara Tsao, Puja Balachander, Ben Wilson, Kate McCall Kiley, Emily Ianacone, Justin Koufoupolos, and Andrew Stroup. Also huge thanks to the partners who joined us along the way including the U.S. Census, General Assembly, 1776, Slack, Comparably, Accenture, GoldenSeeds, Google, Kauffman Foundation, AngelHack, Make it Work, The National Partnership for Women and Families, and more.

If you’re interested in learning more about #Hackthepaygap and our future plans, we invite you to explore the projects below, join the conversation in our ever-growing public Slack channel, and visit the project website at for more information on how we got started.

#Hackthepaygap Products:

  1. What’s my Pay Gap?

Description: The gender pay gap is deeper and more personal than just one number. It changes depending on your race, occupation, and age, often in surprising ways. What’s My Pay Gap is an app that allows you to discover how the gender pay gap affects people like you. As you answer questions about yourself, your personal wage gap grows and shrinks, allowing you to see how what forces create the wage gap in your life.

Data used: This personalized story is empowered by the opening of data. For this project, the team built an API to connect with the Department of Commerce’s ACS datasets, allowing anyone to recalculate wage data in real-time, and bringing it out of academia and into the hands of citizens.

2. Virtual Reality Salary Negotiation Simulator

Project Description:

Utilizing the immersive power of virtual reality, Variable Labs has built learning modules to improve people’s soft skills. Teaming up with the American Association of University Women (AAUW), Variable Labs has created a tool to help women and men practice salary negotiation techniques with a virtual employer.

By translating AAUW’s curriculum and methodology to a virtual environment, the hope is that women will have an accessible, safe space to practice and gain the confidence and language for a variety of negotiation scenarios that will lead to higher salaries.

Data Used:

Variable Labs used AAUW’s research and expertise to inform how they built the tool. In the future, they hope to incorporate features in the platform that can measure voice modulation, eye contact and body language that will provide feedback to the users and help them improve not only language, but how it’s delivered.

A view inside Variable Labs’ virtual reality salary negotiation simulator that allows Samsung Gear VR users to practice negotiation techniques and improve soft skills in an interview setting. PHOTO: VARIABLE LABS

3. PowerShift

Project Description:

PowerShift is a tool that will encourage women to negotiate for the best possible job offer. By providing users’ salary breakdown and range data on what men in a similar situation are making, in addition to legal information about fair pay, the tool aims to encourage women to negotiate for higher salaries.

Data Used: PowerShift uses U.S. Census Data, both because of reliability as well as for its large data on various categories (e.g. occupation types or the ages of children — indicating when a woman might have taken maternity leave). In it’s next version, they are planning to integrate legal rights and state policies that expand upon the rights provided by the Equal Pay Act and cost of living calculator using the Bureau of Labor statistics data. PowerShift could also link to other calculators that already exist, such as that of Bankrate’s, MIT’s Living Wage Calculator (, or the Economis Research Institute’s Cost of Living Comparison Tool. The cost of living calculator will play an important role for anyone with a gap in work history to understand where they would be if they stayed in their position X many years ago, and what that salary would be now.

Pay Gap Demo Day teams present their products at the White House (Photo credit: Clara Tsao)

4. BumpAhead

Project Description:

On average, an American woman’s earnings decrease by 4 percent for every child that she bears. BumpAhead helps working mothers making the right childcare decisions based on their location, industry, income level and family structure. BumpAhead is an empathy building game to demonstrate the ways the high cost of childcare exacerbates the gender pay gap.

The game aims to have players better understand the often tough choices women face in providing for their children, by walking in the shoes of a new mother. The game ends with a call to action that makes it easy for players to reach out to their lawmakers and hold them accountable to support family-friendly legislation.

Data Used: Data from the Commerce Department, U.S. Census, and non-profit organizations such as Child Care Aware were used to better understand the root causes of the gender pay gap. These data sets make a strong case for change, but cannot be easily read by the average person. BumpAhead decided to help users understand the problem with storytelling, and found the data, within the context of a story, to be incredibly meaningful.

5. Raise Above the Wage

Project Description:

Raise Above the Wage wanted to create a way for people to experience the wage gap and gain a deeper personal understanding of its impact. Through this Chrome extension, a user will be able to pick a profile of four women of different backgrounds, and experience wage inequality as them, via the price of an item.

6. Freelancer Economy Equalizer (FrEE) Kit

Project Description:

The emergence of online labor markets has driven a rapid increase in freelance work, which is expected to involve over 40% of the workforce by 2020. This trend provides important new opportunities for both enterprises and workers, but it also creates a burning need for solutions that eliminate bias in the specific context of the freelance, or ‘gig’ economy. The Freelance Economy Equalizer, (or FrEE) Kit provides a set of software services that can be used to extend any online freelancer platform with intelligent assistance and data-visualizations that empower both hiring organizations and candidates to take action to improve fairness and reduce gender pay gaps. FrEE includes a suite of off-the-shelf tools and data that has been integrated to ensure that job postings used to attract candidates have reduced (or are completely free of) bias, and that the processes of selecting, and negotiating pay for those candidates is transparent and consistent.

FrEE provides both candidates and hiring managers with data about what pay-rates for comparable work have been, so that pay negotiation is informed by objective, gender-neutral standards. The FrEE Kit will help make any online labor market free of bias so that in the growing freelance economy, candidates are treated fairly and organizations can access the best available talent regardless of gender.

Data Used:

This product is performing several different kinds of data-driven analyses, drawing on multiple data sources, to improve various phases of the hiring process. FrEE provides job posters with insights about words in their posts that may be interpreted differently by males versus females, and discourage some qualified females from responding to the post. To do this, FrEE uses a third-party analysis tool that relies on data about gender coded words to suggest alternatives that would strengthen a job posting. The kit also determines how effective the post is by analyzing the gender response ratio of the job post and determining if it meets the Bureau of Labor Statistics data on the overall ratio of women in job categories. To do this, FrEE makes a probabilistic determination of each applicant’s gender through an API that uses U.S. Census data on people’s first names to determine gender. In cases of uncertainty, this analysis is combined with Face Plus Plus’s image recognition API on the applicant’s freelancer profile picture to determine their gender. Another way FrEE use data sources is in determining the equality in pay. FrEE compares applicants’ requested wage rates to the Bureau of Labor Statistics’ average salaries for similar job categories. MIDAAS’s income quantile data is used to translate these wages and salaries into normalized, income percentiles to provide an indication of gender-based pay gaps to both hiring manager and candidates.

Finally, all the hiring process data is assembled into visualizations and job metrics that help the job poster see 1) the progression, by gender, of applicants through the hiring process, 2) a comparison between self-declared hourly wages and comparable average salary for a job, which is based on percentiles of the US population, letting the job poster easily determine if action needs to be taken, and 3) show if and where challenges may have occurred during the hiring process.

There are also a few data sources and capabilities that would enhance the capabilities of FrEE kit in assisting a job poster through the hiring process: 1) NLP and machine-learning partners would help build an automation engine that takes job parameters and generates attractive, fair job postings. 2) In order to provide better market analysis and awareness to the job posters, FrEE would need both fine-grained, frequently updated labor statistics and historical hiring data on workers by demographic, skills expertise, and wage.

7. Aware: The Smarter Employee Survey

Project Description:

Aware is solving the problem of companies’ (1) not knowing what information related to the gender gap to collect from employees and (2) not having an incentive to do something with the insights gleaned from data on the pay gap. As a third, intermediary party whose goal is to improve the employee-employer relationship, Aware is essentially a survey application, and in the long term, will evolve into a data analytics platform that will help companies better understand their employees as well as provide new ways of measuring how equal a company’s capital is.

On the app, Aware also plans to have resources on policies that impact companies’ relationship with their employees so that they can be aware of the political environment around the issue.

Data Used:

Aware is currently operating through data that will exist once a survey function is implemented. Aware is collecting the data through an service that is similar to other employee engagement applications, but novel because this service is entirely for solving the gender pay gap.

Read more! #Hackthepaygap Press links:

  1. Narrow the Gender Pay Gap? There are apps for that:
  2. The Truth About the Pay Gap:
  3. Citizens use Census data to hack the pay gap:
  4. Can Virtual Reality Help Close the Gender Pay Gap?
  5. Soon Women Can Try Negotiating for Better Pay in Virtual Reality: