Machine Learning algorithms are becoming widely deployed in real world decision-making. Ensuring fairness in algorithmic decision-making is a crucial policy issue. Current legislation ensures fairness by barring algorithm designers from using demographic information in their decision-making. As...

We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasi-natural experiment. Among those who adopted the...

Automated pricing comes in two forms - rule-based (e.g., targeting or undercutting the lowest price, etc) and artificial intelligence (AI) powered algorithms (e.g., reinforcement learning (RL) based). While rule-based pricing is the most widely used automated pricing strategy today, many...

While the growth of the mobile apps market has created significant market opportunities and economic incentives for mobile app developers to innovate, it has also inevitably invited otherc developers to create rip-offs. Practitioners and developers of original apps claim that copycats steal the...

Numerous ML pricing models (Zillow’s Zestimate, Redfin Estimate) have been deployed to make house sale price predictions. They appears to be independent and unbiased signal to resolve pricing friction in the housing market. These ML models – learn from live sale prices and influence the same...