Student: Stanley

Need 250 words Initial post

Need 250 words Initial post and two replies of 75 words each. Initial Post due in 10 hours. Read “The Role of Data Analytics in Predictive Policing” and at least 2 other related scholarly articles that you find. Then write a post that answers the following questions: How might data analytics improve policing? How might it hurt policing? What ethical issues might be raised by predictive policing? Be sure to cite all three articles in your post Yani Ma RE: Week 4 Discussion COLLAPSE Today's society is an era of continuous economic development and big data. Almost everything can be explained by data. Data analysis mainly refers to the use of reasonable statistical analysis to collect a large amount of data, and then through reasonable analysis to extract the information that people want. Data analysis is very important. You can get certain conclusions based on data analysis, and then formulate corresponding plans based on these conclusions. Sometimes, you can get the reasons for errors based on data analysis, which can be corrected in time. In the article “The Role of Data Analytics in Predictive Policing”, the author's analysis showed how data analysis affects the police's ability to handle cases and prevent crime in real life,and also mentioned some existing problems and potential dangers. Data analytics can provide police officers with intelligence by collecting and analyzing data about which areas are more prone to criminal incidents and what information is more likely to catch criminals. Polices can use mining technology that enables the discovery and prediction of human behavior by processing large amounts of data from mobile phones to determine the criminal's geographic location. Data analytics can also predict the trend of crime and its results through the crime process. The inevitable risk of data leakage is one of the biggest ethical issues might be raised by predictive policing. Whether in the initial data acquisition or in-depth analysis of the data, it may pose a certain threat to citizens' privacy rights, property rights and other rights. References: Eidam, E. (2016, September). The Role of Data Analytics in Predictive Policing. Retrieved April 26, 2020, from https://www.govtech.com/data/Role-of-Data-Analytics-in-Predictive-Policing.html Bachner, J. (2013). Predictive Policing: Preventing Crime with Data and Analytics. Retried from http://www.businessofgovernment.org/sites/default/files/Management%20Predictive%20Policing.pdf Big data investigation, the "fire eye" to fight crime. Retrieved from http://www.xinhuanet.com/legal/2019-07/21/c_1124778418.htm Li Guan Predictive Policing COLLAPSE The policing prediction algorithm and data analytics are ideal to enable efficient allocation of police force and resources of being at the right place promptly. The ultimate goal is to forecast where and when crimes will happen in the future. When it comes to preventing crimes as Eyragon mentioned, what is the specific standards to identify an algorithm efficient? If the successful prediction rate is 1 out of 5, do we call the algorithm a success? When data analytics turns into prediction, it’s the game based on chance. Just like weather forecast: there’s 50 percent of chance that tomorrow will be a rainy day. Either rain or not, the statement yields being incorrect. However, we cannot neglect the development and benefit that data analytics brings on biometrics and fingerprint alternatives, which greatly speeds up investigations. Another function of data analytics is the use of video recordings, such as monitors, which make it possible to trace back even if the crime already took place. On the contrary, it could be a potential ethical issue on how and where these cameras watch. Furthermore, the authority needs to standardize the protocol when sharing private data especially when it includes names, address, social security numbers, etc. Using data analytics algorithm on crime prevention may cause issue of prejudice. Jamie from the Gaudian pointed out: “Machine-learning algorithms could replicate or amplify bias on race, sexuality and age.” Machine learning, as known as pattern recognition, based on data. It raises concerns about lack of safeguard and oversight regarding the use of predictive policing. For example, the criminal behavior algorithm identifies individuals from disadvantaged socioeconomic backgrounds as “posing a greater risk.” To prevent algorithm bias being generated, human bias should not be introduced into data sets. Another possible issue is “police officers become overreliant on the use of analytical tools, undermining their discretion and causing them to disregard other relevant factors,” Jamie said. References: Grierson, Jamie. (2019, September 15). The Guardian. Predictive Policing Poses Discrimination Risk, Thinktank Warns. Retrieved from https://www.theguardian.com/uk-news/2019/sep/16/predictive-policing-poses-discrimination-risk-thinktank-warns Eidam, Eyragon. (2016, September). Government Technology. The Role of Data Analytics in Predictive Policing. Retrieved from https://www.govtech.com/data/Role-of-Data-Analytics-in-Predictive-Policing.html Moses, B. Lyria. And Chan, Janet. (2016, September). Taylor and Francis Online. Algorithmic Prediction in Policing: Assumption, Evaluation, and Accountability. Retrieved from https://www.tandfonline.com/doi/full/10.1080/10439463.2016.1253695?af=R&

Budget: $5.00

Due on: April 29, 2020 00:00

Posted: 5 months ago.

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