WWCode Talks Tech #3: Using Research to Increase Workplace Diversity

Written by WWCode HQ

Women Who Code Talks Tech 3 | Spotify — iTunes — Google — Text
UInclude Co-Founders Toshe Ayo-Ariyo, Danielle Ho, and Sonal Patel, discuss using research and data driven solutions to increase workplace diversity, as well as the journey they took in connecting with one another and founding the UInclude organization.

{Moderator} Dianne: UInclude was originally a project from a boot camp that you all graduated from. You presented this project at the Next Level Contest in 2020 where you competed with other bootcamp graduates from universities across the nation. I remember being so amazed, that you were able to learn from the boot camp, but then expand it, It was so, so inspiring and amazing that you were able to create a whole platform for editing applications to eliminate gender bias wording from job descriptions.

Sonal: At the USC Data Analytics Boot Camp for our core project, we were all placed together in a group that included women of color and people from different communities. We decided to research a topic that was female-focused. We conducted our own research on women in the workforce, and we found that globally, the state of female workforce participation positively impacts global GDP and increases GDP growth. We also found that a significant amount of women’s productive potential remains untapped and that women are still an underutilized labor resource around the world. After a lot of discussion, we realized that one way to increase female workforce participation would be by eliminating the use of gender-biased wording in job descriptions.

Toshe: Meeting one another was a chance encounter. We wanted to explore something relevant to women, and we were really just expecting to do our project, but it turned into us being nominated for and winning a national competition.

One of the reasons that we decided to move forward with this was because we really wanted to bring the topic of intersectionality into the conversation about diversity, equity, and inclusion. So many people have intersecting identities, and when we are talking about creating a diversity, equity, and inclusion solution, you have to consider anything and everything that can marginalize an individual. We found that there are so many solutions that cater to the needs of specific minority groups and the solutions were pretty siloed.

We kind of wanted to bring a holistic approach and create a holistic solution. Our bias mitigation tool scans recruitment materials, and job descriptions for gender-biased language. however, if our tool removes all instances of gender-biased language in a job description, but is still encoded with language that is biased against racial and ethnic minorities, or people with disabilities, they will read that job description and still find the role unappealing because the job description still has language that is biased against their identity. We wanted to take a holistic approach and serve multiple marginalized communities, because the reality is, so many people have intersecting identities.

{Moderator} Diane: Do you have advice for avoiding kind of this biased language?

Danielle: Our analysis has shown that male-dominated industries tend to use more gender-biased wording in their job descriptions, while female dominated industries tend to use more feminine wording. However, across the board, we’ve seen that companies that have more diverse workforces perform better and have more innovative outcomes. When an organization changes its job listing wording to be more gender neutral. They get 42% more responses. Using our tool not only minimizes gender biases and inequality in the workforce, but it is also a better way to draw a wider range of applicants.

Avoid using superlative words. These are adjectives that show the greatest degree of comparison. For example, calling someone “the best” or the “most professional.” Superlatives are often masculine, and are better to avoid when possible.

Hiring managers should also be less demanding about job requirements. Studies show that men will apply for a job when they feel they meet 60% of the criteria, while women don’t apply for a job until they feel like they are 100% qualified. People should try to be less demanding with job requirements and instead split them into essential or desired skill sets.

Toshe: Don’t use gender pronouns. She/he really doesn’t belong in job descriptions. Instead use gender-neutral pronouns, like “they and them.” If you have to use “she” and “He” for whatever reason, make sure that you’re using both at the same time.

{Moderator} Diane: What have been the biggest challenges starting this platform both on the technical side and the business side?

Toshe: So many challenges. I think that’s the reality of a startup. You’re going to run into challenge after challenge, setback after setback, and that’s to be expected. The biggest challenge for me is that I didn’t have any technical experience before our data analytics Bootcamp. I started the program around this time last year and learned how to code for the first time. It was a steep learning curve.

Our program was a data analytics boot camp, so a lot of what we were learning was data strategy and data analytics, not software engineering, UX and UI design, and all of the different things that we’ve had to learn how to do once making the decision to seriously pursue a startup. On the data analytics side we had to do a lot of research, code analyses, and scraping, and do a lot of like really deep data analysis. I hadn’t had experience with any of that to this extent.

I think business is a little bit more intuitive for me because I have a business and finance and strategy background. However, I still have to learn sales. Sales is a beast of its own. You have to be pretty aggressive, and there’s an art and a science to selling a product and selling a vision and selling a company.

Danielle: As far as data collection, in class, the instructor would provide us with all of the raw data, but in reality, we actually need to collect the data by ourselves. We actually scraped 16,000 job descriptions from LinkedIn, which was a big challenge for us. It took a lot of trial and error to scrape all of the data that we needed.

Sonal: The most challenging part for me was maintaining confidence and keeping myself moving and focused. Crafting a startup requires confidence and a willingness to step outside of your comfort zone. As you work to innovate, you need to be willing to challenge yourself and grow your vision. It’s very rare that the very first version of your product will be the best version. We have to continuously work on that and we have to keep moving and differentiating ourselves from our competitors.

{Moderator} Dianne: What are some words of wisdom you’d like to share with entrepreneurs or any tips for success for women in this field?

Sonal: Surround yourself with people who you think will make you better and stronger. When you are both a mom and an entrepreneur, you have to strike a delicate balance between your work life and your family life, so it’s important to make yourself a priority. When you are juggling so many responsibilities, you have to wear so many different hats at the same time and it’s easy to let yourself slip away. Tend to your own needs first or you won’t be able to assist anyone else.

Danielle: It’s really about challenging yourself and pushing beyond yourself to discover your full potential. One year ago I would never have imagined that I would learn to code or work in the tech industry. I’m really happy that I took the data analytics bootcamp and learned to code and started on this journey and discovered my own potential. I now know, I can code and I can also build a startup. And it’s really amazing to see that we’ve come this far.

Toshe: I just remembered another huge challenge that we faced. One thing that we’re having trouble with initially was identifying implicitly biased language against different marginalized groups. A lot of the research about implicitly biased language relates to gender bias or language that is biased against racial and ethnic minorities, people with disabilities, people within the LGBTQ community and others. However, a lot of that has to do with words and language that are overtly biased, and are just completely outdated or insensitive.

I feel like most people know not to use certain explicit words and language in general. However, there’s little to no research about implicitly biased words, and the insidious subtle words that actually deter these other minority groups from applying for roles. The research paper that we came across, by Danielle Goshert, who’s actually on our advisory board now, and two other researchers was really the first research paper that studied implicitly biased language in job descriptions and how the subtle words that we use on a day to day basis impact appeal and sense of belongingness.

Their research study found that masculine language includes certain words that have masculine connotations, like challenge or dominant. Then there are certain words that have feminine connotations, like communicate and help. These are words that we use on an everyday basis. Their research study found that when a job description is loaded with masculine language, it impacts the appeal and sense of belongingness for women, and women are more likely to make the decision not to apply for that role.

We haven’t seen research like that replicated across all of the other marginalized groups that we are aiming to serve, so we are doing the work of producing that research and that is really big for us. We can tell people not to use offensive terms that most of them already know not to use. We wanted to provide a value beyond that.

We are scraping and studying thousands and thousands and thousands of job descriptions and companies to identify that language in hopes of eventually coming up with a word bank of subtle language, language that you actually find in job descriptions that is deterring racial and ethnic minorities from applying for roles. That’s a huge challeng, but we are finding our way. We’re doing the research, we’re doing the statistical analyses. We are launching our own research study, and it’s taking longer than we would like it to take, but we will get there. And we are sure that the results will be extremely valuable.

Toshe: In terms of advice for other entrepreneurs, just expect to run into a lot of different challenges and setbacks. When we started we were so optimistic. We didn’t go into it being naive, but we definitely thought it was going to be a lot smoother than it has been. Expect to run into several challenges and mentally prepare yourself to be able to work through those challenges when they do come, and remember your why whenever you run into each of those setbacks, because that’s really what will keep you going.