Articles

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℠.

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Opinion

Zestimate and Fairness: Can Biased Algorithms Improve Equity?

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.

Opinion

Building AI Fairness by Reducing Algorithmic Bias

Emily Diana explores algorithmic bias in machine learning and outlines three intervention stages: pre-processing, in-processing, and post-processing to mitigate algorithmic discrimination.

Opinion

AI, Wearables, and Opioid Use Disorder Care

Wearable technology and artificial intelligence offers a transformative approach to personalized opioid use disorder treatment, when strategically deployed, can optimize care and improve outcomes, particularly in mid-risk patient populations.