Marlene Jia describes herself as a serial entrepreneur, and her work as COO & Co-founder of TOPBOTS and CEO of Metamaven proves it. Learn more about what her busy weeks look like, how she’s working to pursue AI for social good initiatives, and her new book releasing March 29th.
We interviewed Marlene as part of AI4ALL’s Role Models in AI series, where we feature the perspectives of people working in AI in a variety of ways.
As told to Nicole Halmi of AI4ALL by Marlene Jia, edited by Panchami Bhat
NH: You’re COO & Co-founder of TOPBOTS and CEO of Metamaven. Can you talk a bit about what each of those companies does? What are some of your key focuses right now?
MJ: Metamaven has actually grown out of TOPBOTS. In the beginning, TOPBOTS was our way of sharing information, writing about the things that we learned, and writing about the individuals we met with some really spectacular interviews. We also worked through TOPBOTS as a strategy and development firm specializing in automation initiatives for large corporate brands. In order to eliminate confusion, we decided to decouple the two — TOPBOTS is still the largest community and publication for enterprise AI professionals, while Metamaven utilizes data science and machine learning to create products that drive revenue for our customers.
A lot of the projects we take on are interesting and related to our specialties in automation and AI, however, what we really care about is scaling those initiatives to social good areas. That’s what we’re trying to focus on as we move forward.
One of the things that initially attracted my co-founder and me to each other is that we love technology, and we also care about AI for social good. There is actually a lot that technology can do to help nonprofits, but not every problem is a good business idea. In other words, not every social problem has a way to make money, which is why we don’t see as much energy going into some of these initiatives. The other issue is that social initiatives are just really complex, they’re social, psychological, and cultural issues that are pervasive in our world.
What are some of the important things people should be doing now to create a positive, inclusive, and ethical future for AI?
In technology in general, we have a very serious issue in diversity. The diversity problem can be boiled down simply: we as humans can’t see very far past our own eyes. I’m an Asian-American female and unfortunately, I probably can’t see much past me being Asian, me being female, and me being American. I try very hard to, but the reality is, you have a limited scope of what you think about when you address problems, or when you think about context. Without diverse perspectives, it’s very easy not to have a complete dataset, which can result in the creation of technology that does not serve the masses.
One of the biggest challenges in AI is designing technology solutions in an unbiased manner, because that is how technology can serve everyone, and not just a specific gender or ethnicity.
When it comes to diversity and hiring, proportionally speaking, out of a hundred applicants, you may only be getting 20–30 female applicants. It’s not a problem of quality; it’s a numbers problem. How do you attract more ethnicities into these STEM degrees? How do we get everyone interested in these subject topics? How do we make everyone comfortable in these subject topics? It’s a very complex issue.
How did you decide to study economics in college? Were you interested in the field at a young age, or did you discover it in college? And how did you come to focus on the intersection of AI and business?
For as much intention we have as humans, life never goes accordingly. I have a violin performance background, and that’s actually what I wanted to pursue. Over time, I realized I wasn’t good enough to pursue a career in music. I had a lot of friends in universities that really enjoyed economics. I’m decent at math and always enjoyed quantitative reasoning, quantitative questions and problems, so economics seemed like a great major to marry my interest in business as well as my interest in math. I’m very glad that this is the area I went into because post-college, I ended up going into the quantitative fields of finance, investment banking, and trading.
I’ve also always been entrepreneurial. I started a company in college, and I’ve always loved technology. When I was in New York working in finance, I met my co-founder, Mariya Yao. We both dreamed of being entrepreneurs in the Bay Area, making an impact from a technological standpoint, and being altruistic in some way. That’s what sparked us working together in the Bay Area on TOPBOTS.
Who were your role models growing up? Do you have any role models now?
I take issue with the concept of “role models.” I think that it’s difficult to mirror your future against someone you barely know. When you look at biographies and interviews, obviously they’re meant to paint a specific picture. You have very limited context for the true authentic story of a person. I can aspire to be a certain way in terms of certain traits I admire, but it’s very hard for me to say they are a role model exactly.
That being said, my role model has always been my father. He came from a very poor area in China and having gone through a cultural revolution, a time of turmoil and famine, he somehow still made it to the US. Coming from a very small village in China where the closest school was about 12 miles away, to me, it’s kind of a miracle he even dreamed of leaving and understood how important education was, despite not having any education resources near him.
I have always admired my father for his brilliance, for his persistence, and for his ability to dream.
My co-founder, Mariya, is also my role model. A lot of the ideas we’ve come up with and the hard work we’ve done are due to her creative ways of thinking. I’m very lucky to work with someone that I admire in multiple ways.
What has been the proudest or most exciting moment in your work so far?
We recently launched our Applied Artificial Intelligence: A Handbook For Business Leaders book at CES, and we’re going to be releasing it to the public here by the end of March. When we work with the companies that we do, we realized we also walk them through consistent frameworks. We ask where the organization is in terms of adopting advanced technologies like automation or artificial intelligence, and the factors they need to reflect on to do so. I’m really proud that we were able to manifest our learnings and share that with our community through our book.
Another proud moment is that we never intended TOPBOTS to become this major media platform, but it actually became one of the largest AI communities out there. Every time we go to a conference people tell us they’ve heard of TOPBOTS, and we’re like “wow, really?” It was never our intention to build such a large community.
About Marlene Jia
Marlene Jia guides global customers such as LinkedIn, Paypal, L’Oreal, and WPP on enterprise AI innovation. Her expertise in enterprise software and best practices help corporations successfully evaluate, develop, and integrate emerging technologies. Prior to Metamaven, she built go-to market sales teams at high-growth companies like Ustream, Wizeline, and Sales Bootcamp and was COO of Xanadu, a leading strategy and design firm in emerging technology. She’s recognized by INC as a top 10 keynote speaker and by Entrepreneur as a top 5 bot expert. Marlene studied economics at Northwestern University and has been a serial entrepreneur ever since.
Marlene’s talent is in building effective organizations that leverage both human and machine intelligence. She loves helping executives improve not only their productivity but also their collaboration, communication, and creativity.
Follow along with AI4ALL’s Role Models in AI series on Twitter and Facebook at #rolemodelsinAI. We’ll be publishing a new interview with an AI expert on Wednesdays this winter. The experts we feature are working in AI in a variety of roles and have taken a variety of paths to get there. They bring to life the importance of including a diversity of voices in the development and use of AI.