Data Ethics: Trust but Verify

This episode is one of a special series recorded during the 2019 INFORMS Annual Meeting in Seattle. Joining me is Heidi Livingston Eisips from San Jose State University. She chaired a session at the 2019 Annual Meeting, “Debiasing Decision Making – Ethical Data Mining and Eliminating Algorithmic Bias,” that explored how to balance the benefits of data mining and data analytics in modern society while creating and sustaining a legal and ethical framework to prevent bias.

Interviewed this episode:

Heidi Livingston Eisips

San Jose State University

Heidi Livingston Eisips has an MBA with an emphasis in Market Research and Strategy from Yale University. She is an adjunct faculty member in the Marketing & Business Analytics department in the Lucas College of Business at SJSU. Ms. Eisips has worked as a marketing strategist with Fortune 100’s, start-ups, and mid-size companies, across a variety of industries, including enterprise software, mobile tech, biopharma, ed tech, and higher ed. An experienced lecturer and facilitator, Ms. Eisips has taught all ages, from K to post-graduate both in the classroom and in professional development and training settings. With expertise in a wide array of educational technologies, Ms. Eisips’ pedagogical strength is encouraging creativity, innovation, and design thinking through a balance between online and in-person educational approaches. Her research focus is on ethics in data analytics, educational approaches for student success, and exploring the intersection between technology and student voice.

An experienced writer and editor, Ms. Eisips has worked as a faculty in residence with the SJSU Writing Center; she concurrently holds an adjunct faculty position in Interdisciplinary Engineering to teach communications for undergraduates across all engineering and STEM disciplines. Ms. Eisips is currently pursuing her doctorate in higher ed leadership and is a member of SJSU’s EdD Cohort 4 (expected to graduate in 2022).