Data Biases and Predictive Policing System in New Delhi

Abstract

Delhi police publicized its plan to adopt predictive technology in policing in the year 2015. Now predictive policing is being implemented in the nation’s capital to encounter crimes like rape, robbery, snatching, eve teasing, and rioting. Delhi Police have recently used big data and algorithms to identify the culprits involved in the 2020 Delhi riots. The use of data is not just limited to photographs and information stored in the database of the Election Commission of India or E-Vahan – a pan India database for vehicles but also comprises tools for predictive policing such as the Crime Mapping, Analytics, and Predictive System. Notwithstanding the fact that predictive policing may brace problematic institutional biases and inequality, proponents suggest that the tool can be effective to counter human bias and erratic decision-making. This chapter aims to study the kinds of biases present in the Delhi Police’s data collection practices currently and how they may cause hindrance to equitable and unbiased predictive policing. Further attempts will be made to suggest the impact of this opaque system on quality policing and police reforms.