AITP-RTP Meeting – Human Bias in Machine Learning and What to Do About It
Many people believe that human subjectivity can be addressed by letting “objective algorithms” make data driven decisions. Instead of ushering in a utopian era of fair decisions, there’s now growing awareness that machine learning and AI models have the potential to exacerbate and multiply societal biases. This talk will examine different types of biases, their origins in machine learning, and discuss how to check for and mitigate bias in our models. With awareness of the pitfalls, thoughtful and inclusive processes and tools, the promise of AI and machine learning is still a reality.
Hiwot currently works as a Sr. Data Scientist in SAS’ Health and Life Sciences Industry Solutions team where she advises SAS health care clients on how to best leverage SAS software to get the most out of their data driven initiatives. Before joining the health care team, Hiwot worked in SAS’s consulting division where she put her analytics expertise to use by developing visualizations and predictive models to address the division’s pressing business challenges.
Hiwot is passionate about ensuring diverse perspectives are included in the AI and analytics space. She understands that diversity of thought and lived experiences is a powerful tool to bolster the practice of responsible applications of AI and mitigate the risk of biased solutions being built and deployed. Hiwot has served on the leadership council of SAS’s first Black employee resource group – the Black Initiatives Group (BIG) – since its inception, where she leads and participates in efforts to recruit, retain and promote Black talent at SAS.
Prior to joining SAS, Hiwot was a graduate student at North Carolina State University’s Institute for Advanced Analytics. As part of her Master’s practicum, Hiwot lead a team of students in developing a model to predict patients’ risk of sub-optimal diabetes management for UNC Healthcare.
Hiwot holds a MSc. in Analytics from North Carolina State University’s Institute for Advanced Analytics and a BSc. in Economics and Nutritional Sciences from University of Toronto.
5:30 - 6:00 pm: Check-in & Networking
6:00 - 6:30 pm: Dinner
6:30 - 7:45 pm: Opening Remarks and Program
7:45 - 8:00 pm: Close and Additional Networking
Photography and Video Policy:
Attendees are permitted to take pictures of individuals or smaller groups as long as permission is given from the subject(s) of the photo. AITP-RTP board members may take pictures or a video recording of presenters and attendees for various purposes. However, the use of any kind of video recording or video streaming device from attendees is not permitted. Registration to the meeting implies acceptance of this policy.