WIT Updates the Culture Code
Inclusion on Purpose Snippet #9
We’re now starting the final third of the book Inclusion on Purpose: an intersectional approach to creating a culture of belonging at work, by Ruchika Tulshyan (2022, MIT Press). Chapter 9 is titled: A Future Powered by Inclusive Technology. This summary below was the result of my AI prompt:
- Risk awareness: Tech can encode bias (datasets, models, access); inclusion requires intentional design and governance.
- Practices: Diverse product teams, bias testing, and user research with marginalized communities.
- Goal: Build tools that broaden opportunity rather than scale inequity. [direct.mit.edu]
As usual Tulshyan starts with a personal story. Ifeoma Ozoma ran up against frequent racist and discriminatory practices in her work at Pinterest in 2019 and 2020. She was their public policy and social impact manager, so her eye was on how their external messaging was crafted and received, and worked to protect the brand’s reputation. Brand reputation can easily be destroyed if the internal practices don't match the external promotions, and Ozomo noticed a lot of daylight between those two. These practices included discriminatory salaries, coworker online harassment, negative performance reviews for bringing up concerns, and a managerial focus more on how concerns were presented rather than the substantive concerns that were raised. Ozoma and another black woman left the company in May of 2020 but in June of 2020 they both observed Pinterest making public statements in solidarity with the Black Lives Matter movement. Eventually they spoke out publicly to draw attention to the disparity between the public stance Pinterest was taking and the internal racism and sexism that they had experienced. As usual this particular story serves to illustrate a broader concern. Because of their scope of integration and ubiquity in our everyday activities, bias and discriminatory practices in technology companies have an outsized impact on all of us.
Tulshyan reminds us (p. 201) that technology arises from computer science which arises from mathematics, and that mathematics has long institutionalized sexism and racism. The belief that women and non Asian people of color were unable to excel in these fields, resulted in their exclusion from the early days of development, and in the western world- most of the technology we use was developed initially by white men. And the impact is that these technologies work best for white men. Hearing aids that can't hear women’s voice pitches, facial recognition that can't read dark skin, medical devices that don’t work for people of color, and all kinds of tech that doesn't work for people with disabilities. Tulshyan provides numerous statistics from the American Mathematical Society , the US Bureau of Labor Statistics, and the National Science Foundation all documenting the small percentage of women in STEM, and women of color in STEM.
The rest of the chapter is divided into the following sections, which I will summarize for you. Note that these summaries necessarily leave out much of the chapter's detail. I hope that some of you will read the text itself if this topic catches your attention.
Why bias in the industry is bad for society
When technology is created with a limited perspective, tested with limited data sets, and checked against only mainstream concerns and guidelines, the gaps in its capabilities might not even be noticed until after that tech is already deployed and in a position to cause harm. None of this has to be intentional, but the design itself causes the tech to fail to serve its purpose equitably. If algorithms don't identify women as skilled mathematicians and don't steer job advertisements their way, we won't ever have the mathematicians our society needs. If self-driving cars can't effectively recognize dark skinned faces, they will not work properly to identify pedestrians, drivers, or law enforcement. And when this failure keeps getting repeated, it’s our design failure that needs to change.
Technology companies must immediately regulate harassment and misinformation
“Women of color face severe and sustained online harassment. It’s unacceptable morally, but has far reaching consequences too, like the risk to free speech and a country’s democracy.” (p. 205)
Tulshyan writes about women journalists, technologists, social media content creators, and venture capitalists who have been driven out of their work because of this relentless abuse. Online abuse is not protected free speech when it crosses the line into hate and harm with real consequences.
An exclusionary ecosystem for women of color entrepreneurs
Funding is a critical area for any entrepreneur, but raising capital, getting taken seriously, and meeting with potential investors without being either harassed or having your ideas stolen, were all identified as extremely difficult by the technology entrepreneurs Tulshayan interviewed. If investors are only confident in the ideas of people who look like them, and wealth is still concentrated in the majority, it’s harder for others to get funding for a new idea. She cites data (p. 209) from a 2018 Entrepreneur article on the 2017 figures that only 2.2% of venture capital funding went to women founders in that year, and that only 0.2 % of venture capital funding goes to Black women technology founders.
A call to action to inclusive tech leaders
“First, more women of color must be recruited in and advanced across the industry, whether as technology company employees or entrepreneurs.” (p.210)
Tulshyan stresses that we need to be improving the current workplace environment at the same time we are reinforcing the educational pipelines, and addressing the threats that work against women’s participation in STEM programs. She reminds us that data repeatedly shows that there is no basis for believing in any aptitude or ability gap- it’s the social stereotypes and expectations that create our consistent exclusions of women and women of color from success. Technology leaders can actively work to partner with programs designed to counter these stereotypes to improve the pipeline, while they work within their organizations to make changes.
A quick blueprint for creating ethical inclusive technology products
In this section Tulshyan covers 5 specific actions that matter:
- Hire and advance women of color to make sure that technology is designed with the necessary diversity of perspectives.
- Ensure that a diversity of testing data is used when building technology and include diverse technologists in the groups who select any data sets for use.
- Make sure that “diverse and traditionally underestimated groups” are included in all testing and feedback gathering done on a product before it’s completed.
- “Intentionally look for biases that may otherwise go undetected.”
- Mentor, fund, and sponsor women of color entrepreneurs.
Your role in creative and creating inclusive tech as a user
The chapter ends (p 215-216) with suggestions that all of us can use as we navigate a technology driven world. We can all take some of the following steps to help promote more inclusive technology when we make choices of tech to buy and use. We get to decide which social media platforms we participate in, whether we only buy robotics kits for boys and not for girls, whether we call out online harassment or let it pass, whether we seek out diversity in our reading, writing, and media use, whether we engage with our political representative on technology equity issues, and whether or not we ensure accessibility in our technology tools and our online content. That’s it for Chapter 9, be well and keep learning!