Putting Responsible AI/ML Into Practice

Artificial Intelligence and Machine Learning (AI/ML) technologies have become essential to automate analysis of massive amounts of data and to solve problems that would take countless months of people power to complete. The risks associated with deploying AI/ML systems that violate legal, ethical, and cultural norms is growing, and building responsible AI/ML is a paramount concern in organizations.

As engineers, data and computer scientists, and technologists create solutions, how do we ensure development of responsible AI/ML techniques? Join us as our expert speakers address ethics, coding bias, the importance of diversity, and public sector policies for promoting and regulating AI/ML practices.

KEYNOTE & MODERATOR

Diane Chang | Data Scientist | Intuit

SPEAKERS

Gioia Messinger | Founder | LinkedObjects

Blythe Towal | Machine Learning Architect, Tech Lead | Shield AI

Anne-LiseThieblemont | VP | Qualcomm