26 citations · 26 across the 2 of their papers we have counts for
7 papers
Outcome Indistinguishability
Cynthia Dwork, Michael P. Kim, Omer Reingold +2
Prediction algorithms assign numbers to individuals that are popularly understood as individual "probabilities" -- what is the probability of 5-year survival after cancer diagnosis…
A Distributional Framework for Data Valuation
Amirata Ghorbani, Michael P. Kim, James Zou
Shapley value is a classic notion from game theory, historically used to quantify the contributions of individuals within groups, and more recently applied to assign values to data…
Tracking and Improving Information in the Service of Fairness
Sumegha Garg, Michael P. Kim, Omer Reingold
As algorithmic prediction systems have become widespread, fears that these systems may inadvertently discriminate against members of underrepresented populations have grown. With t…
Preference-Informed Fairness
Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum +1
We study notions of fairness in decision-making systems when individuals have diverse preferences over the possible outcomes of the decisions. Our starting point is the seminal wor…
On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings
Moses Charikar, Ofir Geri, Michael P. Kim +1
Edit distance is a fundamental measure of distance between strings and has been widely studied in computer science. While the problem of estimating edit distance has been studied e…
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Michael P. Kim, Amirata Ghorbani, James Zou
Prediction systems are successfully deployed in applications ranging from disease diagnosis, to predicting credit worthiness, to image recognition. Even when the overall accuracy i…