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What Is the Future When Using Ai to Help People Prevent School Shooting?

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“What is the future when using AI to help people prevent school shooting?”


School shooting is still an insoluble dilemma in the security management for students for many years. According to the statistics, there have been at least 239 school shootings in the United States, in those episodes, 438 people were shot and 138 of whom were killed. (Patel, 2018) This horror has severely disrupted the intention of education and destroyed the favorable trust among people, and causing the desire for revenge as a motivation to commit crimes in the future. Main idea imagined by scientists is to apply artificial intelligence (AI) to solve problem. By using algorithms to analyze data collected from different cases, it is possible to identify possible patterns based on student languages or behavior. The prediction of school violence can also help school management and develop psychological counseling. This fits the explanation from Rieland (2018), not only is there little consensus on how to stop them – with suggestions ranging from restricting gun access to arming teachers – but there is even less certainty about why a student would open fire on his classmates. Furthermore, some new technologies including real-time monitoring or facial recognition are still remained in debates about the feasibility for AI to use due to morality and impartiality. Anyway, despite its prevalence, AI become an embodiment of technological advancement and could reformulate the school security management. This paper will predominantly demonstrate how the school administration and ideology of students would be reshaped through digitization, address the political issue related to legal system, and the effect on value orientation by moralization will be also considered.

The simple but useful way to eliminate school shooting

It is hard to conclude easily about the factors resulting in school shooting in different countries across the history. Racial and sexual-gender discrimination more or less aggravate the occurrence, but when people look back to the key element, the mind to retaliate society is the only thing those offenders thinking. No matter those offenders have violent tendencies or have been taking pressures of school bullying, premonition of school shooting is always ignored or unimpressed. Quain (2018) pointed out that the challenges has been the difficult of shifting through the mountains of data generated in forums and social media accounts to find the few needles that might alert a school counselor or psychologist that a child is in trouble. AI collects and monitors the status for students with tracing comments and recording researches. Its precise positioning and accurate judgment will be mainly expressed by emphasizing those key words or key activities. The call for help is always posted before but also may not be public, which making rescue difficult. AI marks those pictures, context, locations and other information to help experienced people find problems. In addition, Hsu (2018) argues that AI can be trained to identify guns and other hidden weapons with microwave radar scanner. This method is more effective and does not counter those strong advocate of Gun legality. Furthermore, Rieland (2018) has designed the potential ability of AI that could make comprehensive independent judgment from demographic and socio-economic information, to any history of drug use or neurological disorders, to the availability of guns in the states.

The choice between safety and privacy

AI has a great potential in preventing school shooting but mainly because it collects enough data. And in most of cases, this activity is complete stealthily. Especially for some possible people who may have bad backgrounds or be often bullied, their shame and sensitivity will refuse the help from outsides. The worst of that is, it may encourage fierce resistance and force people become more aggressive because those people feel invaded. Also, some countries are not allowed to empower AI in privacy in laws. Hsu (2018) used the word “chilling effect” to predict possible situation when applying AI into surveillance.



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