196 citations · 606 across the 27 of their papers we have counts for
6 papers · 1 filter
Bayesian Persuasion for Algorithmic Recourse
Keegan Harris, Valerie Chen, Joon Sik Kim +3
When subjected to automated decision-making, decision subjects may strategically modify their observable features in ways they believe will maximize their chances of receiving a fa…
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses
Keegan Harris, Daniel Ngo, Logan Stapleton +2
In settings where Machine Learning (ML) algorithms automate or inform consequential decisions about people, individual decision subjects are often incentivized to strategically mod…
Addressing the Long-term Impact of ML Decisions via Policy Regret
David Lindner, Hoda Heidari, Andreas Krause
Machine Learning (ML) increasingly informs the allocation of opportunities to individuals and communities in areas such as lending, education, employment, and beyond. Such decision…
Stateful Strategic Regression
Keegan Harris, Hoda Heidari, Zhiwei Steven Wu
Automated decision-making tools increasingly assess individuals to determine if they qualify for high-stakes opportunities. A recent line of research investigates how strategic age…
On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes
Hoda Heidari, Solon Barocas, Jon Kleinberg +1
Many policies allocate harms or benefits that are uncertain in nature: they produce distributions over the population in which individuals have different probabilities of incurring…
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility
Hoda Heidari, Jon Kleinberg
Opportunities such as higher education can promote intergenerational mobility, leading individuals to achieve levels of socioeconomic status above that of their parents. We develop…