Why is the outer operating environment of any agent so difficult to account for in our models of human agency?
Sample Solution
fault of the technologies, but can occur in any database system with personal data. It would be acceptable to use facial recognition if a good ratio can be attained between false and true positive results. Provided that the individuals who are rated as a false positive are treated well and they are not questioned in an improper way. People have accepted that they sometimes have to endure minor inconveniences to be able to detect criminals. But in case there are too many false positives for each true positive, the harm done to innocent people is more important than detecting or arresting a criminal [5]. The systems should be tested on their performance before they are used. With the information this provides, improvements can be made to the systems in order to reduce the rate of false positives [4]. The challenge is how to trade-off between privacy and the security of facial recognition systems. One cannot prevaricate the loss of privacy by using facial recognition in everyday life. But the question is, is the improvement in security enough relative to the loss of the individualâs privacy? There is not one specific answer to this question. There are and there always will be proponeÂÂÂnts and opponents for the use of facial recognition systems. The proponents state that the systems gain enough security relative to the loss of privacy. It can help to prevent crime and detect criminals, thus people feel safer. But the opponents state that there will be too much loss of privacy, the technology can make errors and can be misused. This makes people fearful. There should be made strict guidelines concerning privacy when using facial recognition to prevent everyday crime. Furthermore, the technologies should be checked very well, so that there are no chances on false positives. 5. Conclusion Facial recognition systems can be used in various ways to prevent crimes. One of these ways is using FaceIt. FaceIt is a face recognition system that can search through a crowd for a face and match this face with the mugshot history of this specific person. It is considered to be the most accurate facial recognition software as of today. Other results are: matching faces from live security images, face recognition in photographs and face recognition from sketches. These are all methods in which a face (of e.g. a possible criminal) is compared to a face in respectively live security images, photographs and sketches, to see if t>
fault of the technologies, but can occur in any database system with personal data. It would be acceptable to use facial recognition if a good ratio can be attained between false and true positive results. Provided that the individuals who are rated as a false positive are treated well and they are not questioned in an improper way. People have accepted that they sometimes have to endure minor inconveniences to be able to detect criminals. But in case there are too many false positives for each true positive, the harm done to innocent people is more important than detecting or arresting a criminal [5]. The systems should be tested on their performance before they are used. With the information this provides, improvements can be made to the systems in order to reduce the rate of false positives [4]. The challenge is how to trade-off between privacy and the security of facial recognition systems. One cannot prevaricate the loss of privacy by using facial recognition in everyday life. But the question is, is the improvement in security enough relative to the loss of the individualâs privacy? There is not one specific answer to this question. There are and there always will be proponeÂÂÂnts and opponents for the use of facial recognition systems. The proponents state that the systems gain enough security relative to the loss of privacy. It can help to prevent crime and detect criminals, thus people feel safer. But the opponents state that there will be too much loss of privacy, the technology can make errors and can be misused. This makes people fearful. There should be made strict guidelines concerning privacy when using facial recognition to prevent everyday crime. Furthermore, the technologies should be checked very well, so that there are no chances on false positives. 5. Conclusion Facial recognition systems can be used in various ways to prevent crimes. One of these ways is using FaceIt. FaceIt is a face recognition system that can search through a crowd for a face and match this face with the mugshot history of this specific person. It is considered to be the most accurate facial recognition software as of today. Other results are: matching faces from live security images, face recognition in photographs and face recognition from sketches. These are all methods in which a face (of e.g. a possible criminal) is compared to a face in respectively live security images, photographs and sketches, to see if t>
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