Predictive policing
I created this mind map to write down all the associations within A.I. topic.
In the end, I looked at a topic that appealed to me the most, the subjects that appealed to me are:
A.I. -> Profiling -> gender
A.I. -> profiling -> type of person
A.I. -> big data -> data profile
A.I. -> surveillance -> Face recognition
A.I. -> Bias
A.I -> Bias -> predictive
A.I. -> surveillance -> Policing
Then i combined some topics to create
Predictive policing (with the use of A.I.)
Gender bias (in A.I.)
Clarify my findings
Predictive policing: Predictive mapping programs use police data about past crimes to identify ‘hot spots’ on a map. Police then patrol these areas. Individual risk assessment programs predict how people will behave, including whether they are likely to commit – or be the victims of – certain crimes.
Predictive policing involves using algorithms to analyze massive amounts of information in order to predict and help prevent potential future crimes (Lau, 2020).
mapping realtime data on the map and recreate the (CAS system) or (Predpoll) .
Decision making: True false, people have to make prediction based on surveillance images if people acting suspicious.
Coded biases in face recognition : show which datapoints are used to make predictions
Substantiation of choice
First i started researching predictive policing afterwards I found that I could not really make decisions I could not really make a good bridge with healthcare and I went on to my second topic where I researched biases in the healthcare systems with the emphasis on diagnosis. Ultimately, I will continue with the topic: predictive analytics systems.
After several attempts..
When coming up with a concept on the subject of predictive analytics systems in healthcare , I encountered several problems about how to make the bias visible in my data visualisation.
I tried multiple thins to but, its didn't work out. So i decided to switch back to my other topic:
A.I. -> surveillance -> Policing
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