Tepperspectives is the heart of thought leadership for the Tepper School of Business at Carnegie Mellon University. Tepper school faculty and other experts share their research, innovations, and ideas for The Intelligent Future℠.
Podcast
A new book from Tepper School alumnus Özgün Elçi (Ph.D. 2022), along with John Hooker and Peter Zhang, introduces a mathematical framework for building ethical optimization models that balance efficiency with fairness, providing practical tools and a new way to evaluate the societal impact of algorithmic decisions.
August 7, 2025
Opinion
Yan Huang reveals how Zillow's Zestimate, despite occasional algorithmic bias and varying accuracy across neighborhoods, benefits both buyers and sellers in underserved areas by reducing market uncertainty and improving transaction outcomes, even potentially lessening existing inequality compared to human-only systems.
July 24, 2025
Opinion
Emily Diana explores algorithmic bias in machine learning and outlines three intervention stages: pre-processing, in-processing, and post-processing to mitigate algorithmic discrimination.
July 17, 2025