With the conclusion of Transform 2021, we were very glad to see that our sessions addressing diversity, equity, and inclusion initiatives in AI were among the most well-attended. Our third Women in AI Breakfast, presented by Capital One, kicked off the entire five-day event. Teuta Mercado, Director, Responsible AI Program at Capital One, provided the opening remarks. We’re excited to share her views on diversity as part of a series showcasing Transform speakers — and the work she’s involved with to advance the responsible use of AI.
VB: Can you tell us about your background, and your current role at your company?
TM: I lead Capital One’s Responsible AI program, and I’ve found that my background in law and as a compliance professional has allowed me to approach this field with a unique perspective. I spend a lot of time solving consumer-related issues and looking for the best outcomes for consumers. For me, inclusive engineering is really ensuring that our products and our services reflect our customer base and are accessible to all. Our customers represent all facets of society. So, when I think about diversity, I think of it in many different forms — diversity of race, ethnicity and religion, but also economic diversity and diversity of experience, education and more.
It’s important that we have diverse teams working on AI and machine learning so we can build products for all of our customers, rather than for a homogeneous group of people. Corporations are doing a lot of outreach in this space, which is fantastic. For example, Capital One is working to bring more diversity into this field, with recruiting efforts and imperatives around Diversity, Inclusion, Belonging, and Equity. There’s also a personal responsibility we all own — to encourage others, to seek other perspectives, and to create teams that are inclusive.strong>VB: Can you tell us about the diversity initiatives you’ve been involved in?
TM: The Responsible AI program at Capital One seeks to advance our ethical practices and increase the unassailability of our machine learning products. We do that through robust relationships across the company and developing a base of support to empower our practitioners. The Responsible AI program seeks to advance a culture where everyone, not just those directly responsible for machine learning, but everyone involved across the board, is responsible for ethical AI.
Inclusion at Capital One begins with our Business Resource Groups, of which we have many. These groups are established as forums for employees to celebrate their shared culture, to support one another, and to encourage continuous learning to meet business objectives. Part of this network is our Women in Technology Business Resource Group, which is comprised of women and allies with the mission of accepting nothing less than an inclusive environment in technology that is approachable and welcoming to all.
Our Women in Tech group brings women and allies together to elevate the focus on women technologists. It examines how diversity is critical to obtaining and keeping the best talent and emphasizes the importance of addressing the decline in the number of women in technology throughout the pipeline.
VB: What’s kept you moving in this space?
TM: There are so many things that have kept me going. One is the network of professionals and surrounding yourself with people who care about what they’re doing, who are passionate about ethical AI — that makes all the difference. A big thing for me has also been working for a company that has a culture of empowerment, a culture that not only allows but encourages you to do the right thing. That’s why it’s so crucial that companies have mechanisms that make empowerment part of everyday work life.
VB: What advice would you give to someone trying to get into this industry?
TM: Your path may not be a straight shot. It may be a journey — you might start out doing one thing and you don’t know where it’s going to lead you. It is important to recognize that you bring something to the table that others may not. You are an important voice.
For example, what led me to my current role was understanding and recognizing what I really enjoyed doing in my previous roles, such as the pieces that were consumer-focused and where I could see my work in application in helping people. Having exposure and consulting on different products and platforms or models really helped me to see that I could make an impact if I continued to focus on the customer — this led me to where I am today.
My advice is to think about what you love doing, what excites you, and if you’re shifting gears and are interested in AI or machine learning, there are so many things you can do to enter this space. Engage with the professionals around you, both within and outside of your organization. Network and see what’s out there, what people are working on and what they are learning, then determine the unique skill sets that you can bring to the space.
I also recommend taking classes to understand machine learning. Even though my role at the time didn’t necessarily call for it, I knew that I was interested in machine learning and I had a passion for it, so I went outside my role and pursued training. Immersing yourself in the literature that lives in the space you’re entering will help fuel your growth mindset. There are so many opinions and perspectives — you’ll never stop learning.