Intelligence in Ethics

Introduction

As the world continues to grow complex, there has been an increasing need to rely upon intelligence by the policymakers and leaders to defend and improve their national interest. Intelligence is a general cognitive skill where the mind is involved in perceptions of relationship sets, analogies, reasoning and calculation (Moran, 2016). The police have taken advantage of this and developed it into police intelligence. This gives them an edge over criminal masterminds as they can predict and curb attacks. Various tools of analysis are adopted. However, there is a limit to how much and how wide they can cover. This paper discusses the ethical aspects of intelligence gathering and use.

Artificial Intelligence is widely applied in policing. For instance, AI forms part of the facial recognition system of the South wales (Caldero et al., 2018). The fact that the technology of face scanning can be used to cross-reference against a large database of 600 thousand images of custody in real-time, assist the police to identify past offenders whenever there is a big public event, this has proved to be important since it has resulted to a significant number of the arrest.

The PredPol system until recently has been widely employed by the police to predict areas where crime may occur. The system is subjected to historical training through crime data, it then applies this information to mark those sectors where police officers may be needed urgently and when they can be needed (James, 2016). PredPol employs the use of three points of data; time of the crime, past time and place of crime, to develop a unique algorithm following the patterns of criminal behaviour.

The system commonly known as the National Data Analytics Solutions (NDAS) applies a combination of statistics and Al in evaluating the chances of one planning to commit a crime or becoming part of the future crime (Galliot & Reed, 2016). For instance, police can use NDAS to detect cases where an individual is planning to commit a crime using a gun or a knife, as well as the chances of one becoming part of the modern slavery. Although NDAS can be effectively used to combat serious crimes, it still fails to acknowledge essential issues accurately, and therefore its prediction is still a major concern.

Some of this system, however, poses a direct threat to people as well as implicating real business. The systems are prone to errors and biases that have been introduced by the makers. The data that has been applied in training this system can be vulnerable to bias. For instance, the algorithm used in facial recognition that has been made by Microsoft poses a significant bias when recognizing the gender of people (Macnish, 2017). It has been noted that the system can easily detect the white man as compared to the black man. Take a deeper dive into Legal Implications and Remedies with our additional resources.

Conclusion

Law enforcement is still a human process, however, there is no doubt that the use of intelligence in policing to combat crime through the use of emerging trends and technologies will increasingly enhance the efficiency of policing. It brings the expected ultimate challenge of regulation and ethics.

References

Moran, J. (2016). From Northern Ireland to Afghanistan: British Military Intelligence Operations, Ethics and Human Rights. Routledge.

Caldero, M. A., Dailey, J. D., & Withrow, B. L. (2018). Police ethics: The corruption of noble cause. Routledge.

Galliott, J., & Reed, W. (Eds.). (2016). Ethics and the future of spying: technology, national security and intelligence collection. Routledge.

Macnish, K. (2017). The Ethics of Surveillance: an introduction. Routledge.

James, A. (2016). Understanding police intelligence work (Vol. 2). Policy Press.