Big Data Application and Ethical Issues

Big Data Application and Ethical Issues Free Essay

Abstract

The research paper investigates the use of big data in different fields. In the introduction, it explains what big data is, the way of using it and the standard fields where it is useful. The paper also includes an overview of two educational institutions, Georgia State and Purdue University, discussing the use of big data and how it has benefited their operations. The schools have used this technology to increase the percentage of graduate students and improve their performance. The following paper also provides a discussion of the ethical issues associated with big data and laws violated by the issues. Finally, there is a discussion of how America can deal with the violations in the law court.

  

Big Data Application and Ethical Issues

Introduction

            Big data refers to the compound volume of data which may be structured or unstructured and inundate a situation on a day to day basis. It is an improvement compared to the traditional computer data which required a lot of computation and analysis to arrive at a conclusion. The big data technology is applicable in almost every area. The government, for example, uses it to ensure the efficiency in the cost estimation, along with increasing productivity and innovation. For it to be useful, it requires different parties in the government, both national and local, to collaborate in creating innovative ways to implement the desired outcome. It may use it to avoid any weather-related delay of service delivery. Barack Obama used the big data analyses in the 2012 campaigns (Trippi, 2013). In manufacturing, it is used to predict uncertainties like component performance and availability. In health care field, it helps in providing personalized medical and prescription analytics, and clinical risk intervention. It is also useful in clinical risk response and analytics, contributes to reducing waste and care variability, has computerized the way of providing information about the patients both externally and internally, and has harmonized medical conditions, patient records and disjointed point solution. In media, it is useful in targeting customers for marketing by marketers.  In sports, it can be used to predict the winner in a match. It is also used to improve the level of training and understand the competitor's behaviour. Big data is also used to enhance the quality of education and related services in learning institutions.

Background Information

The previous methods of data processing are not fit to deal with big data. Analysis of big data gives an insight that leads to better decisions and strategic business moves. New methods are used to collect, analyze, share, store, transfer, visualize, question, update and keep information private. The data uses forecast analysis, user behaviour analytics and other advanced data analytic methods. It is of an outstanding quality where the size determines the value and the possibility of terming it as big data or not. The nature and type of data help to use the resulting insight. It uses high speed and velocity in generating and processing of data to meet the intended needs. However, the collected data can vary with a significant margin affecting the accurate analysis. What is important is not the amount of data but rather its significance and application in different fields. It plays an important role in changing the way people work in an institution. Business leaders and IT specialists have to join forces to analyze the value of the data. In business, investors are using the data to optimize operations, prevent threats and frauds, predict customer engagement and capitalize on new sources of sales. 

Overview of Educational Institutions Using Big Data

Georgia States University

            The university got concerned by the rate of dropout among its students. Whether it was because of fees or for academic reasons, a large number of students failed to obtain their degrees. The administration came up with a Graduation and Progression Success advising system. The system helps to detect students who are at a risk before the problem becomes too serious to be controlled. By identifying unpleasing undergrads on time, the students can receive help from the school before they fall off track. The GPS system uses more than 800 different factors (Davis, 2015). The triggers include receiving a poor grade, inability to complete the required course on time, and failure to attend classes among others. Students singled out by the system receive invitation to the management to discuss the issue. Once a student chooses an elective course that will not contribute to their graduation, they receive information from lecturers advising them to change and choose a required class. The system has helped to improve the rate of graduation by 6% since the time of its implementation (Davis, 2015). 

            The system application had not been that smooth as the university used ten years to collect relevant data. The number of enrolling students was high making it hard to monitor each student manually leading to either drop out or inability to graduate on time. The drop out was hurting as they had loans but no degree. It made it hard for them to repay and this was hurting the economy as it became hard to support other new students who needed the loans. Each student is attached to an adviser who advises him or her when they are off track. An advisor has 300 students under them, a figure that has increased from 100 before the system implementation (Rabovsky, 2014).The system follows the student even in the college they have transferred from in case they did not join as freshmen. Minor matters are addressed using robust advising system which emails students on the issue. At first, the system is a discomfort to the student as they feel that there are no secrets but appreciate it later when they get pieces of advice. This program has seen the university become a part of the national education advisory board’s student success collaborative which provides analytic software enabling colleges and universities to improve retention and graduation rates.

Purdue University

 The institution has been using big data to improve student's performance. Their program called ‘course signal’ helps to foresee academic and behavioural issues in a student. Both student and the advisor receive notification and take appropriate action. The system contributes to measuring student's academic preparation, engagement, effort level and academic performance at regular intervals. The system adopted back in 2007 has led to the increase of grades A and B and at the same time reduction of C and D grades as well as previous fails (Rabovsky, 2014). The improvement is mainly explained by the individualized learning experience as the system does not generalize but gives a report on a student’s performance. They can get immediate feedback which helps them to act accordingly. The university is sourcing data from online data learning program to be able to increase the potential for a student to learn more in the classroom. The number of the students applying to the online courses is growing, and it is anticipated that in the future one will complete at least one online course in their lifetime. The university is using this data to understand the way students learn best and make improvements where needed.

            The system monitors how the student interacts with their peers, educators and learning materials. These data can be analyzed in terms of a large number of students and courses to see the effectiveness of the educational strategy, exercises, and material. In the case where most students omit a particular learning material but still register good grades, the educators will examine the effectiveness of the material and eliminate it if necessary (Rabovsky, 2014). They no longer have to insist on a method they think would be helpful if it is not. The educators also get to know a method of delivery that works best for different groups. The methods appropriate for a student taking scientific courses may not be suitable for a student taking art courses. Still, some methods are adequate for some courses regardless of whether the students major in science or arts (Chandak, 2016). Improvement of student performance is one of the ways to ensure high retention and graduation rates.

            The two universities are some of the learning institutions that are currently making use of big data to reduce the school dropout, improve student performance and ensure they graduate on time. A greater number of educational establishments are expected to join the trend of big data usage.

Ethical Concerns That Arise from Using Big Data

            Several ethical issues are likely to come up with the use of big data. Privacy violation is one of them. For example, in case of a school or a hospital, a client feels that the service provider can learn anything about them. A student feels that every lecturer can track their performance and behavioural records making them feel uneasy. Any employee in a hospital can easily get medical information about a patient using the hospital system which is a violation of patient's right to privacy. If masking is careless, big data may reveal the name of the person in the masked data. Masking requires policies, procedures, and processes to ensure the preservation of privacy (Blatt, 2012). An individual who provides secret information about others to unauthorized people may be charged in the court of law in America and under the 'privacy act.' There are also issues of communicating prediction, especially to individuals. For example, if one is predicted to experience something like real violence with the partner, it is hard to tell them as one doesn't know how they will react or whether the act of violence will take place.

            The use of big data is associated with many security issues. Hackers may get access to a company’s or government’s server to get security information (Trippi, 2013). Furthermore, it is easier for an individual to send a big amount of data to the enemy with the use of big data. While this person may face charges for the violation of secrecy, the damage has already been done as the enemy has already obtained the information about the country’s security system. Carrying out theft activity of stock in a company is also possible by altering the camera systems. 

 The data analysis may be influential in a wrong way because it may affect people’s behaviour. Organisation can use it to make a wide variety of business decisions that do not take into consideration the involved human life. For example, revealing personal information because it is not illegal may damage an individual’s life. Besides, copywriting can be easy. With so much information being available, it will be hard to prove that the data possessed is unique (Purcell & Rommelfanger, 2015). Royalties associated with copyright will reduce as it will be hard to win such a case even when sued. Big data gives little limitation on the data that is private.

            Prediction by big data has no guarantee of 100% truth. The files used may contain inaccurate information about individuals who may use data computation methods that are wrong when relating to particular people or there might be a problem in data calculation. The risk of inaccuracy becomes higher with an addition of more data and the use of more sophisticated data analysis model without incorporating thorough validation in the review process. Organisation using fault data can suffer from making bad decisions and taking inappropriate and damaging actions. Besides, some people who used to make these decisions were dynamic. For example, a person’s location, the level of education, health condition, body size and other factors change with time; hence, lack of updating database will lead to an inaccurate analysis. A person may be denied services due to the decisions based on the analysis of incorrect data. Some can fall under the false accusation of something they did not do which will cost them time as they clear with the law to prove they have not violated it. In a hospital setting, a person who has received inaccurate diagnosis will receive wrong treatment which may worsen their health condition and may even cause death. The act is against the medical ethics of America where such a physician can be taken to the court and charged for medical malpractice.

            The use of this kind of data may further lead to discrimination. A bank may deny an individual a loan on the basis that a large number of people from where he or she comes from have not repaid their loans. The choice of the job applicant and giving promotion may be discriminative if one uses the data analysis instead of the traditional interview method where individuals have a chance to present themselves. One may be blocked out by the report that a previous employee who attended the same institution with the applicant did not behave as required. These generalisations may lead to making poor decisions.

Government Policies Protecting Individuals from Ethical Issues Associated with Big Data

 Ethical codes related to the violation with the use of big data drag behind. The dragging is because its use is relatively fresh and its impact has not yet been revealed. However, some policies protect companies and individuals. These policies mostly include the Internet and computer crimes. When one collects data from individuals or business web pages, they risk facing prosecution for the breach of contract. This mostly happens to companies who feel that a person obtained the information to benefit themselves without any payment to the firm.

The USA government have ‘Computer Fraud Abuse Act’ which prevents the access to a secured computer and the internet information without authorization (Blatt, 2012). A secured network is used by the financial institutions and the government. Each person has a scope of data they cannot access. Going beyond this magnitude is considered to be a crime. Big data makes it easy for a person to go beyond the authorized area as long as they have a password. Such person gets charged according to the damage caused. The damage may ruin the reputation, and cause any loss due to server interruption. Web scraping is not considered to be under this law as long as the information scraped is not secured by a password or any other form of internet security and does not cause any damage to the complainant. If the person who does web scraping was not authorized, he could get charged for the violation of ‘computer and internet crime act.' Hacking also falls under cyber-crime. The law refers to a situation when a person uses unauthorized software to access a server that does not belong to them. The hacker may alter the information in a way that may cause damage to the owner or interfere with the services provided. Charges are made according to the harm caused by the act. For example, a person may hack a bank server and interfere with people’s bank balance. A person caught with a hacking offense will be forced to pay the amount lost. He or she may be put in jail and subjected to other penalties.

            Privacy Act of 1974 that protects individuals from violation of privacy is most applicable in legal issues related to the use of big data (Blatt, 2012). For example, if a physician accesses and releases patient’s information without their permission, they can be sued and penalized (Rothstein, 2015). A medical practitioner found sharing information about a patient risks losing their working license and pay for the damage caused by the invasion of one's privacy. Releasing patient’s information causes psychological torture which may lead to stress and depression. This action is against the medical code of conduct and ethics. The same case applies to an employee who may release private employee information from the big data. However, there is also an issue of who can assess the information as one may not determine who has released information not unless measures are used to reveal it.

            Copyright criminal law in America forbids someone to use another person’s invention to make money. Big data makes it easy for a person to access other people’s intellectual ideas and use them. For example, a person may steal a business idea of making a new commodity in the market and implement it to make money and establish their business. An individual proven to violate the 'copyright law' risks a jail term and heavy fines by the American court. They are required to pay for the loss incurred by the owner and hand over any money they have earned through the stolen information. However, big data makes it hard to prove the real owner of the original information. Individuals and companies are argued to put security measures on the documents they store on the computer and in the internet to prevent access by hackers

Conclusion

Big data technology has many benefits. It is the simplest way to analyze an enormous amount of data and make a prediction. It is being used in different fields to improve services and their productivity. The governments are also using it for future planning and solving problems like insecurity. Politicians use big data in the campaign, while agriculture uses it to increase productivity, and educational institutions use it to improve student performance, along with many other applications. Ethical issues emerging from the use of big data revolve around computer and internet crimes. The governments need to amend the existing laws about cyber crimes as the current ones do not fully cover big data crimes entirely. Individuals are advised to actively secure their computers so that they become more difficult to be hacked and accessed by unauthorized individuals.


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