april 2021
Event Details
Women Lead Webinar Series Exclusively for Professional Access Pass members What does our data reveal about us? How is the data we share online used to influence our behavior? What key factors
Event Details
Women Lead Webinar Series
Exclusively for Professional Access Pass members
What does our data reveal about us? How is the data we share online used to influence our behavior? What key factors should professional women consider as they seek to lead ethically in the age of big data? Putting ourselves in the shoes of business leaders and consumers of technology, we will explore a number of different design and technological tools that can help preserve consumers’ privacy while also ensuring personalization and convenience. This webinar will draw on the latest research in computational social science to help attendees gain a clearer picture of:
- New predictive analytics technologies that guide human behavior in unexpected ways
- The real-life consequences of our digital footprints on our privacy
- How insights taken from our digital footprints can help individuals and businesses make more informed decisions and create a more ethical data marketplace
The webinar is presented by:
Professor Sandra Matz, David W. Zalaznick Associate Professor of Business, Columbia Business School
Sandra Matz is the David W. Zalaznick Associate Professor of Business at Columbia Business School. She is the incoming co-director of the Leadership Lab, which supports leadership development within and beyond the MBA curriculum. In her research, Dr. Matz combines methodologies from psychology and computer science – including machine learning, experimental designs, online surveys, and field studies – to explore the relationships between people’s psychological characteristics (e.g. their personality, or mental health) and the digital footprints they leave with every step they take in the digital environment (e.g. their Facebook Likes or their credit card transactions).
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This event is sponsored by Columbia Business School.
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Time
(Wednesday) 12:00 pm - 1:00 pm ET
Location
Online