ChiPy __Main__ Meeting


When: Aug. 11, 2016, 6 p.m.

Where: Data Science for Social Good Summer Fellowship

Attendance:

Topics


  • Predictive Enforcement of Pollution and Hazardous Waste Violations in New York State
    By: Jimmy Jin , Maria Kamenetsky , Dean Magee
    Length: 20 Minutes
    Description: New York State’s Department of Environmental Conservation (NYSDEC) is the regulatory agency for environmental issues in the state. Their mission is to conserve, improve and protect New York State’s natural resources and environment and to prevent, abate and control water, land and air pollution. NYSDEC currently conducts approximately 700 inspections each year of facilities in the state that manage hazardous waste. DSSG will work on more effectively allocating inspection resources by creating predictive models that identify facilities with high likelihood of violating environmental regulations. In 2015, we worked with the federal EPA targeting hazardous waste facilities subject to the Resource Conservation and Recovery Act (RCRA). With inspection data from NYSDEC and the public RCRA dataset, we will build a similar model to identify RCRA violators specifically in the New York region, as well as further explore the possibility of applying models to other compliance inspection programs, such as the Clean Air and Clean Water Acts.
  • Expanding Our Early Intervention System for Adverse Police Interactions
    By: Sumedh Joshi , Jonathan Keane , Joshua Mausolf , Lin Taylor
    Length: 20 Minutes
    Description: Many police departments in the United States use “early intervention systems” to identify officers who may benefit from additional training, resources, or counseling. These systems attempt to determine behavioral patterns that predict a higher risk of future adverse incidents, ranging from excessive use of force and citizen complaints to on-duty accidents and personal injury. Detecting these risk factors enables departments to develop targeted interventions and make operational changes to protect officer safety and improve police/community interactions. Last summer, DSSG worked with the Charlotte-Mecklenburg Police Department on building a better early intervention system, applying data analysis to provide insights on individual and situational risk factors for adverse interactions. This year, we will partner with additional police departments, including the Metro Nashville Police Department, to test and expand this work in new municipalities, improving both the overall model and local performance. Like last year, we will use anonymized police data and contextual data about local crime and demographics to detect the factors most indicative of future issues, so that departments can provide additional support to their officers.