The Data Chief | Episode 36

Mastercard’s JoAnn Stonier on Responsible AI and Applying Human-Centric Design Principles to Data Problems

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JoAnn Stonier

Chief Data Officer

Mastercard

Current EpisodeEP36: Mastercard’s JoAnn Stonier on Responsible AI and Applying Human-Centric Design Principles to Data Problems
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JoAnn Stonier loves her role. After all, when you’re the Chief Data Officer for Mastercard, the opportunities to create real change are plentiful. But Stonier knows her work is about more than just data privacy and governance, it’s about aligning the company’s data strategy to business goals and impacting the organization in a positive way. And of course, making sure that all 725 million of Mastercard’s credit card holders are protected.

With a career rooted in privacy, a degree in law, and a background in interior design, Stonier is not just a well-rounded CDO, she’s a visionary. On this episode of The Data Chief, JoAnn joins Cindi for an inside look at data’s impact on people, data ethics, and the importance of building trustworthy models.

Key Takeaways:

  • The CDO is an enabler of the business: In Joann’s own words, “the role of the CDO is to engage the business in tomorrow’s business.” This means CDOs must consistently be aligned with the company's goals, and develop capabilities that lay track for future innovation. Great data governance, data management, and data quality are table stakes. The CDO must also have a sense for where the market is going and how the business can carve out new space for itself to deliver value to customers.
  • Data is about people: As a data leader, it’s easy to get caught up in the novelty and opportunity of innovation. But data is more than an anonymized collection of 0s and 1s, it’s about people and the tremendous impact it can have on their lives. As products and services are developed, it’s important to apply individually-centric design principles and evaluate how you might be affecting someone, for better or worse, on the other side.
  • Responsible AI starts with trustworthy data: Simply put, data is food for AI. In order to build ethical or responsible AI and machine learning algorithms, there must be improvement in data trust and quality. Oftentimes these algorithms are missing integral data points that neglect particular demographics. This creates a level of bias in the numbers that will only continue to be amplified over time.

Key quotes

What's really fun about data is that it continually changes. It changes in its context. It changes its challenges, and It's changing our planet. It's endlessly innovative.
At the end of the day data really impacts individuals. You really need to understand that you need individually centric design principles around data. That what you do impacts people. And if you understand how impactful your product, your solution, your service is going to be both positive and negative, it makes for better design decisions along the way.
My goal as the data officer is to enable business. And I say this all the time and people think I'm crazy, but you need to engage the business today and tomorrow's business. And that's a really tall order. And this is where I think data officers can be super strategic but it means they have to understand their business and not only where it is today, but where it's going.
The analytic community that you have — your data scientists, your AI engineers — you need to know what they need for their data…I want those data scientists to be really, really good because our scientists need to understand the data in context, but I have data designers that work right alongside those teams, and I feel as plugged-in as if those teams all report directly to me. Data is very contextual for every organization.
If you have trust, you have a sustainable business going forward. If you're not going to have trustworthy practices of any kind, you're just not going to have a sustainable business.
Data is food for AI. We have to understand that our data sets need to be ready for whatever problem we're trying to solve with A.I. That is one of the things that we did not spend enough time on in the first wave of A.I.
My hope is that more and more companies, organizations, academics and governments are beginning to understand that [AI] is a whole new field that needs human intervention now so that we can adjust before that amplification really takes off and creates permanent digital ghettos and divides that are hard for us data designers and scientists to fill in.

Bio:

JoAnn Stonier serves as Chief Data Officer for Mastercard, leading the organization’s data innovation efforts while navigating current and future data risks. Stonier and her team design and operationalize Mastercard’s global data strategy, ensure governance and data quality, and guide enterprise deployment of cutting-edge data solutions, including advanced analytics and AI and the development of enterprise data platforms.

 

 


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