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Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Democratizing artificial intelligence: Lessons from the real world

Swatee Singh (American Express)
11:30am–12:00pm Tuesday, 09/11/2018
Location: 1A 08
Average rating: ****.
(4.33, 6 ratings)

Artificial intelligence (AI) is now being adopted in the financial world at an unprecedented scale. To scale AI and proliferate it in all applications, organizations often look for "unicorns"—data scientists who also bring equal shares of computer science (for efficient application development), engineering (to work with cloud and big data technologies), and subject-matter expertise to the table. While these individuals exist, they are few and far between. So how can corporations get more critical mass within their employee base that is enabled to power decisions with AI?

Swatee Singh discusses the need to “democratize” AI in the company beyond the purview of “unicorn” and advanced data scientists and offers a framework to do this by stitching AI with the cloud and big data at its backend. Along the way, Swatee shares practical real-world lessons learned and explores the broader implementation scenarios in the industry and the associated pros and cons of each approach. Democratizing AI will surely lead to scenarios where inadvertent errors creep in as nonspecialists look to accomplish tasks traditionally performed by advanced data scientists. To this end, Swatee concludes with strategies to enforce appropriate checks in the system.

Photo of Swatee Singh

Swatee Singh

American Express

Swatee Singh is the first female Distinguished Architect at American Express, where she is spearheading machine learning transformation at the company. Swatee is a proponent of democratizing machine learning by providing the right tools, capabilities, and talent structure to the broader engineering and data science community. The platform her team is building looks to leverage American Express’s closed loop data to enhance its customer experience by combining artificial intelligence, big data, and the cloud, incorporating guiding pillars such as ease of use, reusability, shareability, and discoverability. Swatee also led the American Express Recommendation Engine roadmap and delivery for card-linked merchant offers as well as for personalized merchant recommendations. Over the course of her career, she has applied predictive modeling to a variety of problems ranging from financial services to retailers and even power companies. Previously, Swatee was a consultant at McKinsey & Company and PwC, where she supported leading businesses in retail, banking and financial services, insurance, and manufacturing, and cofounded a medical device startup that used a business card-sized thermoelectric cooling device implanted in an epileptic’s brain as a mechanism to stop seizures. Swatee holds a PhD focusing on machine learning techniques from Duke University.