Authors :
Dr. John Motsamai Modise
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/s3ajas27
DOI :
https://doi.org/10.5281/zenodo.8055030
Abstract :
The goal of this article is to provide a
reference manual for those who are interested in writing
on predictive policing, which will include evaluations of
the most promising technical tools for producing
predictions as well as the most promising tactical
strategies to act on such predictions. More generally, this
research aims to place predictive policing in relation to
other contemporary, proactive policing measures:
Although predictive policing is merely a tool, it can be a
very helpful one. It is not a magic oracle. The second
section will go through how predictive policing is
conceptualized, as well as its potential and actual
advantages and disadvantages. Review clarifies how
predictive policing is conceptualized, as well as its
potential, actual benefits, and disadvantages.
Predictive policing, also known as crime
forecasting, is a set of high technologies aiding the police
in solving past crimes and pre-emptively fighting and
preventing future ones. With the right deployment of
such technologies, law enforcement agencies can combat
and control crime more efficiently with time and
resources better employed and allocated. The current
practices of predictive policing include the integration of
various technologies, ranging from predictive crime
maps and surveillance cameras to sophisticated
computer software and artificial intelligence. Predictive
analytics help the police make predictions about where
and when future crime is most likely to happen and who
will be the perpetrator and who the potential victim. The
underpinning logic behind such predictions is the
predictability of criminal behaviour and crime patterns
based on criminological research and theories such as
rational choice and deterrence theories, routine activities
theory, and broken windows theory.
Keywords :
Predictive policing,Forecasting, Crime mapping, Prediction, Pre-processing data,Algorithms,Policing technology, Social control, Machine learning.
The goal of this article is to provide a
reference manual for those who are interested in writing
on predictive policing, which will include evaluations of
the most promising technical tools for producing
predictions as well as the most promising tactical
strategies to act on such predictions. More generally, this
research aims to place predictive policing in relation to
other contemporary, proactive policing measures:
Although predictive policing is merely a tool, it can be a
very helpful one. It is not a magic oracle. The second
section will go through how predictive policing is
conceptualized, as well as its potential and actual
advantages and disadvantages. Review clarifies how
predictive policing is conceptualized, as well as its
potential, actual benefits, and disadvantages.
Predictive policing, also known as crime
forecasting, is a set of high technologies aiding the police
in solving past crimes and pre-emptively fighting and
preventing future ones. With the right deployment of
such technologies, law enforcement agencies can combat
and control crime more efficiently with time and
resources better employed and allocated. The current
practices of predictive policing include the integration of
various technologies, ranging from predictive crime
maps and surveillance cameras to sophisticated
computer software and artificial intelligence. Predictive
analytics help the police make predictions about where
and when future crime is most likely to happen and who
will be the perpetrator and who the potential victim. The
underpinning logic behind such predictions is the
predictability of criminal behaviour and crime patterns
based on criminological research and theories such as
rational choice and deterrence theories, routine activities
theory, and broken windows theory.
Keywords :
Predictive policing,Forecasting, Crime mapping, Prediction, Pre-processing data,Algorithms,Policing technology, Social control, Machine learning.
