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Data Ethics Assignment On Word Embedding

Task: Task 01 Conduct independent research and compile a review report on the use of word embeddings inbusiness and its possible ethical issues. Your report should include the following requirements inorder: a) Describe two possible applications of word embedding in business. (4 marks)Hint: For each application, mention what are the motivations/benefits, how it works, whatdatasets are involved and its results (if known), etc. b) Discuss two popular implicit biases that usually occur in word embedding applications andtheir possible ethical issues. Hint: Describe each bias, give examples and explain why and how biases occur and may leadto ethical issues. c) Suggest two most important measures/best practices that you think can be used to alleviatethe ethically significant harms of these bias problems. Provide justification of your choicesand challenges of implementing these measures. Hint: Your suggestions should align with the harms that you have discussed in the previoussection (question 1b). You may review the lecture slides and select the relevant knowledgepoints. You may also need to perform research on literature to explain and support yourpoints. Task 02 There is a case study provided and you are required to analyse and provide answers to the questionsoutlined below. You can use lecture material and literature to support your responses.Fred and Tamara, a married couple in their 30’s, are applying for a business loan to help them realizetheir long-held dream of owning and operating their own restaurant. Fred is a highly promisinggraduate of a prestigious culinary school, and Tamara is an accomplished accountant. They share astrong entrepreneurial desire to be ‘their own bosses’ and to bring something new and wonderful totheir local culinary scene; outside consultants have reviewed their business plan and assured themthat they have a very promising and creative restaurant concept and the skills needed to implementit successfully. The consultants tell them they should have no problem getting a loan to get thebusiness off the ground. For evaluating loan applications, Fred and Tamara’s local bank loan officerrelies on an off-the-shelf software package that synthesizes a wide range of data profiles purchasedfrom hundreds of private data brokers. As a result, it has access to information about Fred and Tamara’s lives that goes well beyond what they were asked to disclose on their loan application.Some of this information is clearly relevant to the application, such as their on-time bill paymenthistory. But a lot of the data used by the system’s algorithms is of the sort that no human loanofficer would normally think to look at, or have access to—including inferences from their drugstorepurchases about their likely medical histories, information from online genetic registries abouthealth risk factors in their extended families, data about the books they read and the movies theywatch, and inferences about their racial background. Much of the information is accurate, but someof it is not. A few days after they apply, Fred and Tamara get a call from the loan officer saying theirloan was not approved. When they ask why, they are told simply that the loan system rated them as‘moderate-to-high risk.’ When they ask for more information, the loan officer says he doesn’t haveany, and that the software company that built their loan system will not reveal any specifics aboutthe proprietary algorithm or the data sources it draws from, or whether that data was evenvalidated. In fact, they are told, not even the system’s designers know how what data led it to reachany particular result; all they can say is that statistically speaking, the system is ‘generally’ reliable.Fred and Tamara ask if they can appeal the decision, but they are told that there is no means ofappeal, since the system will simply process their application again using the same algorithm anddata, and will reach the same result. Provide answers to the questions below based on what we have learnt in the lecture. You may alsoneed to perform research on literature to explain and support your points. a) What sort of ethically significant benefits could come from banks using a big-data drivensystem to evaluate loan applications? b) What ethically significant harms might Fred and Tamara have suffered as a result of theirloan denial? Discuss at least three possible ethically significant harms that you think aremost important to their significant life interests. c) Beyond the impacts on Fred and Tamara’s lives, what broader harms to society could resultfrom the widespread use of this loan evaluation process? d) Describe three measures/best practices that you think are most important and/or effectiveto lessen or prevent those harms. Provide justification of your choices and challenges ofimplementing these measures. Hint: your suggestion should align with the harms that you have discussed in the previoussections (questions 2-b and 2-c). You may review the lecture slides and select the relevantknowledge points. You may also need to perform research on literature to explain andsupport your points

Subject Name: Computer Science

Level: Postgraduate

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