Beyond RoboDebt: The Future of Robotic Process Automation

Australian And International Examples Of Automation In The Public Sector

Decision support systems are certainly not a new fad or phenomena. Automated decision-making within the Australian public sector has been employed for nearly thirty years (see inter alia Perry 2019 and Elvery 2019 for a useful precis). In 1994, the Department of Veterans’ Affairs introduced what is asserted to be the first automated decision-making in Australia, though the OCI is arguably the first high stakes decision support system.

Technologies have been trialed to identify aggressive behaviours amongst crowds (see Sjarif et al. 2012). Further examples of supported decision platforms include the use of algorithmic approaches and decision scorecards such as the FVRAT to domestic violence cases. Beyond simple decision support, more advanced applications of machine learning and deep learning technologies include the use of computer vision to identify individuals committing traffic crime, such as the use of cameras and computer vision to detect illegal mobile phone use by drivers, as noted by Perry (2019). Within other jurisdictions, so prolific is the use of machine learning and automated decision making more broadly city-based task forces have been established to review the use of automated decision making. Some applications appear to be without reproach. For example, computer vision in risk management and risk identification. An instructive example is the use of a tool by the Fire Department in New York City to analyze data from other city agencies to predict buildings most vulnerable to fire outbreaks and to prioritize these for inspection, Ibid (2019).