Towards Modelling Artificial Intelligence Parsing documents for Cyber-Policing Data protection and privacy environments using Privacy Impact Assessments and Data protection Impact assessment questionnaires

Artificial intelligence specific through machine learning is changing the way in which we can process big data. This position paper provides a perspective on the Information Security governed organization with a view on how Artificial Intelligence is mapped back into the process of this governance and how we can evaluate the use of this Artificial Intelligence to support the said organization, we demonstrate with the use of case study simulated scenarios in predictive policing as a part of crime management to inform this discussion. Artificial Intelligence in seeking to mimic human intelligence seeks to achieve this through statistical and interpretative inference analysis. In this work we posit the need to start with the basic statistical inference analysis approach, through parsing and pattern matching techniques to support such predictive inferences. The application of predictive policing seeks to examine pattern recognition methods specific to detecting security incidents and potential breaches within the environment. Our technical approach examines the use of privacy impact assessment (PIA) and data protection impact assessment (DPIA) questionnaires as basic experimental prototype aimed at automated data collection to support future analysis of potential breaches within data protection and privacy environments.