PyData Global 2022

Dr. Lalitha Krishnamoorthy

Dr. Lalitha Krishnamoorthy is the Co-Founder and CEO of OpenTeams Global. In her role at OpenTeams Global, she is responsible for driving the organization's innovation, expanding the partner and network ecosystem across industries and academia, defining the portfolio and investment strategy, and delivering transformative experiences. She leads a team of open source experts that work with clients and business partners on their transformation journey through Data and AI methodologies to achieve stellar business results.

Prior to her current role, Lalitha served as Director of IBM Digital Commerce, SaaS, and Data Platforms where she directed IBM's Digital Business Transformation strategy through data-driven, commerce-ready, subscription-first product offerings. During her 20 year career at IBM, Lalitha held roles of increasing responsibility and oversaw numerous portfolio's leading IBM’s transition from core databases to federated data to advanced analytical capabilities, and eventually data, cloud and artificial intelligence.

She serves on the champions board of the Texas Girls Collaborative Project, a University of Texas at Austin statewide network committed to motivating and supporting women and girls to pursue and thrive in careers in science, technology, engineering, and mathematics (STEM).

Lalitha holds a doctorate in Neuro-Symbolic Artificial Intelligence, holds several invention patents, is a regular speaker at industry conferences, is on the board of directors for many startups, and a strong advocate for diversity and inclusion in technology.

Today, Lalitha is most interested in making technology equitable for everyone, as this creates a new set of market leaders and competitive disruption.

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Sessions

12-01
15:00
30min
Algorithms at Scale: Raising Awareness on Latent Inequities in Our Data
Dr. Lalitha Krishnamoorthy

In today’s digital age, we use machine learning (ML) and artificial intelligence (AI) to solve problems and improve productivity and efficiency. Yet, there’s risk in delegating decision-making power to algorithmically based systems: their workings are often opaque, turning them into uninterpretable “black boxes.”

Talk Track I