2018/07/13 by Jon Kleinberg, Manish Raghavan, Kleinberg, Jon +1 · 1 voice · 6 citations
Computer Science · Mathematics · #Computer Science and Game Theory (cs.GT) #Computers and Society (cs.CY) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.CY #cs.DS #cs.GT #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.1807.05307
arxiv published 2018/07/13 · arxiv updated 2019/08/01
Algorithms are often used to produce decision-making rules that classify or evaluate individuals. When these individuals have incentives to be classified a certain way, they may behave strategically to influence their outcomes. We develop a model for how strategic agents can invest effort in order to change the outcomes they receive, and we give a tight characterization of when such agents can be incentivized to invest specified forms of effort into improving their outcomes as opposed to "gaming" the classifier. We show that whenever any "reasonable" mechanism can do so, a simple linear mechanism suffices.