Is Machine Learning Really Unsafe and Irresponsible in Social Sciences? Paradoxes and Reconsideration from Recidivism Prediction Tasks

Abstract

The paper addresses some fundamental and hotly debated issues for high-stakes event predictions underpinning the computational approach to social sciences, especially in criminology and criminal justice. We question several prevalent views against machine learning and outline a new paradigm that highlights the promises and promotes the infusion of computational methods and conventional social science approaches.