Colleague, we look forward to meeting you!Date: Tuesday, November 19th, 2019 Format: Lunch Roundtable (Main Conference Day 1). Hosted by our Media Partners: Women in Big Data, represented by Sunanda KP, an Assoc. Dir. of Data Science at Wayfair. Registration: A confirmed ticket to CDAO, Fall qualifies you for attendance - however, to reserve your place at the lunch, please complete the form and we will be in touch to confirm your spot. Further Details: In spite of multiple headline-grabbing accounts of how algorithms could have led to unintended biased outcomes, there is still a huge gap in understanding the theoretical and empirical sources of biases and how to address them effectively. This roundtable discussion will aim to shed some light on these gaps and jump start a conversation around origins, impact, ownership of biases. Senior executives and leaders will takeaway practical knowledge of identifying potential key sources of bias and a familiarity with existing market tools that might help them take informed decisions around their ethical data/algorithm policy. Technologists can expect to go away with a deeper understanding of fundamental theoretical limits to de-biasing algorithms and how to work within these constraints for an effective solution on the ground. Please complete the form to secure your place! |
James McCann |
Kimberly Coates |
Colleague, we look forward to meeting you!Date: Tuesday, November 19th, 2019 Format: Lunch Roundtable (Main Conference Day 1). Hosted by our Media Partners: Women in Big Data, represented by Sunanda KP, an Assoc. Dir. of Data Science at Wayfair. Registration: A confirmed ticket to CDAO, Fall qualifies you for attendance - however, to reserve your place at the lunch, please complete the form and we will be in touch to confirm your spot. Further Details: In spite of multiple headline-grabbing accounts of how algorithms could have led to unintended biased outcomes, there is still a huge gap in understanding the theoretical and empirical sources of biases and how to address them effectively. This roundtable discussion will aim to shed some light on these gaps and jump start a conversation around origins, impact, ownership of biases. Senior executives and leaders will takeaway practical knowledge of identifying potential key sources of bias and a familiarity with existing market tools that might help them take informed decisions around their ethical data/algorithm policy. Technologists can expect to go away with a deeper understanding of fundamental theoretical limits to de-biasing algorithms and how to work within these constraints for an effective solution on the ground. Please complete the form to secure your place! |
James McCann |
Kimberly Coates |