When: 11 AM Friday, October 16th
Description: The culture of tech is consistently framed as good, positive, neutral, fair and unbiased. Faster is better. Innovations, particularly in terms of automation, are beneficial advances to help humankind. The broader view of tech reveals an influential segment of the tech space that has (un)intended consequences, do harm and target highly minoritized groups. Faster is not always better. Some innovations do not advance but stall or reverse progress. Examples of tech perpetuating harm and digitizing discriminatory acts are gaining national attention, such as predictive policing and facial recognition. In this session, Dr. Marshall describes deep fake technology and discusses issues related to ethics, privacy, and accountability for companies who use "black box" algorithms to make decisions and the respective societal impacts.
About: Dr. Brandeis Marshall helps rising and experienced working professionals interpret the racial, gender and socioeconomic impact of data in technology.
Twice named one of 200 Black women in tech to follow on Twitter, Brandeis is a skilled explainer who has a knack of making difficult computing and data concepts easier to understand, regardless of a person's educational background.
A thought leader in broadening participation in data science, Brandeis often discusses inclusivity and equity for organizations like DataCamp, Dataiku, Experian, NeurIPS and Truist. She has appeared in Medium, OneZero and The Moguldom Nation. Brandeis shares her approaches to effectively amplify social contexts within data and its implications for all communities.
Brandeis is a teacher and advisor at heart. She holds a PhD and Master of Science in Computer Science from Rensselaer Polytechnic Institute and a Bachelor of Science in Computer Science from University of Rochester. Dr. Marshall brings nearly 15 years experience in higher education. She was the first Black woman to receive tenure at Purdue University College of Technology in 2014. Still working in academia, Brandeis regularly teaches software development, data and analytics topics.