Addressing AI Bias – Four Critical Questions

Addressing AI Bias – Four Critical Questions

By Hayley Pike

As AI becomes even more integrated into business, so does AI bias.

On February 2, 2023, Microsoft released a statement from Vice Chair & President Brad Smith about responsible AI. In the wake of the newfound influence of ChatGPT and Stable Diffusion, considering the history of racial bias in AI technologies is more important than ever.

The discussion around racial bias in AI has been going on for years, and with it, there have been signs of trouble. Google fired two of its researchers, Dr. Timnit Gebru and Dr. Margaret Mitchell after they published research papers outlining how Google’s language and facial recognition AI were biased against women of color. And speech recognition software from Amazon, Microsoft, Apple, Google, and IBM misidentified speech from Black people at a rate of 35%, compared to 19% of speech from White people.

In more recent news, DEI tech startup Textio analyzed ChatGPT showing how it skewed towards writing job postings for younger, male, White candidates- and the bias increased for prompts for more specific jobs.

If you are working on an AI product or project, you should take steps to address AI bias. Here are four important questions to help make your AI more inclusive:

  1. Have we incorporated ethical AI assessments into the production workflow from the beginning of the project? Microsoft’s Responsible AI resources include a project assessment guide.
  2. Are we ready to disclose our data source strengths and limitations? Artificial intelligence is as biased as the data sources it draws from. The project should disclose who the data is prioritizing and who it is excluding.
  3. Is our AI production team diverse? How have you accounted for the perspectives of people who will use your AI product that are not represented in the project team or tech industry?
  4. Have we listened to diverse AI experts? Dr. Joy Buolamwini and Dr. Inioluwa Deborah Raji, currently at the MIT Media Lab, are two black female researchers who are pioneers in the field of racial bias in AI.

Rediet Adebe is a computer scientist and co-founder of Black in AI. Adebe sums it up like this:

“AI research must also acknowledge that the problems we would like to solve are not purely technical, but rather interact with a complex world full of structural challenges and inequalities. It is therefore crucial that AI researchers collaborate closely with individuals who possess diverse training and domain expertise.”

To learn more about artificial intelligence and machine learning, reach out to us today! Kopius is a leader in dual-shore digital technology consulting and services.

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Women’s History Month – Let’s Make Tech More Inclusive

It’s Women’s History Month – Let’s Make Tech More Inclusive

By Deborah Keltner

We may be preparing to wrap up Women’s History Month 2022, but we aren’t done working to make tech inclusive. Women’s History Month provides education on how women helped shape the nation and empowers children by introducing them to historical role models. It also inspired us to share practices that make our company and our industry more inclusive to women.

While the month is over, our effort to bring gender equity to our company and our industry is ongoing.  

Women have played a key role in the advancement of technology and computer science since its creation. For example, computer pioneer Grace Hopper devised the theory of machine-independent programming languages, which led to the creation of COBOL. And while women are an ever-growing part of the tech community, inequality in pay and opportunities persists.

women in tech

No matter your gender, here are ways every person can make our industry more inclusive and better for women:

As a professional

  • Mentoring. It’s important that both men and women mentor women in technology. Letting women and girls know that they have a future in technology helps to increase the number of women pursuing careers in computer science. This pillar of support can be offered through professional groups or one-on-one. If you are a woman in tech, making yourself visible will inspire other women and girls. And men in tech should evaluate who you seek out or offer mentorship to, so you can make sure you are doing so equally.
  • Educate yourself. Read books and blogs for, by, and about women in tech. This reading list has some great recommendations. Follow Women in Tech on social media – searching the hashtag #womenintech can get you started.
  • Speak up. Point out non-inclusive behavior, even if it comes from someone above you in the leadership chain.
  • Evaluate your professional circles. Do you find that your network isn’t as diverse as you’d like? Start building professional relationships with women and people of color so your network looks more like your community.

As a manager

  • Eliminate bias in the hiring process. Look for ways to attract qualified candidates from a variety of backgrounds.  Our recruiting team uses several techniques to make the process inclusive to women, including anonymizing applicants, monitoring job descriptions for gendered or exclusive language, encouraging applicants to include their personal pronouns, and setting system reminders to be inclusive while reviewing applicants or completing interview feedback.
  • You can take the Parity Pledge here.
  • Visibility is a serious challenge faced by many women. Women are often tasked with “invisible work” – such as day-to-day tasks and maintenance work – and therefore get credit for being diligent, but not strategic. Managers should make sure that everyone has equal access to strategic projects and that everyone is equally tasked with invisible work.
  • Address pay gaps – female tech workers make anywhere from 10% to 33% less than male counterparts, depending on seniority level. Ask about equity when setting the pay scale for a role so you do not perpetuate unequal pay.

At Work

  • Amplify women’s voices and do your part to ensure women are heard. To amplify a colleague who has shared a good idea in a meeting, speak up, name and credit the woman, and repeat her idea.
  • Use Inclusive language. Favor gender-neutral terms whenever possible. Here’s a guide:
Replace ThisWith This
He, sheThey/them
His, herTheir
GuysFolks, friends, team, y’all
Ladies, galsWomen, folks, people, you all, y’all, friends
ChairmanChair, chairperson
Man, mankindHumanity, humankind
GrandfatheredLegacy status, preexisting
Right-hand manCounterpart, indispensable
Man hours, manpowerPerson hours, engineer hours, level of effort, hours
MiddlemanMediator, liaison
HousekeepingMaintenance, cleanup, overview
Male or female connectors/ fastenersConnector and receptacle, plug and socket
Man (verb, “I will man the desk”)Staffing, working
ManpowerWorkforce, human effort
Preferred pronounsPronouns, personal pronouns
Sexual preferenceSexual orientation
Gay (as a generic term)LGBTQIA+
VirginFirst run, first launch

Challenges within the tech industry make it harder for women to pursue a career in our field, and even once women join tech, they are less likely to stay in it – both because of lack of role models and because it’s often male-dominated and gender exclusive. Valence is working to improve things for women in tech and raising awareness about this issue is one way that we can contribute to progress.

What else should we do to make tech inclusive? We’d love to learn more from others who are supporting women in tech.

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