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Legal, Ethical and Security Aspects of Data Science Assignment Help

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CST4080 Legal, Ethical and Security Aspects of Data Science Assignment

Assessment Title - Case Study on Legal Aspects of Digital Forensics

Learning Outcomes - This coursework will enable the student to:

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Learning Outcome 1 - Demonstrate a critical understanding of ethical and professional issues relevant to the practice of data science.

Answer: Data science, while powerful, raises ethical and professional concerns. Issues such as data privacy, bias, and fairness are paramount. Data scientists must ensure data is collected ethically, avoiding breaches of privacy. They should be aware of biases embedded in data and algorithms, preventing discriminatory outcomes. Transparency and accountability are essential, with clear explanations of models and their limitations. Moreover, data scientists must consider the potential societal impacts of their work, mitigating negative consequences and promoting positive change. By understanding and addressing these ethical and professional issues, data scientists can contribute to responsible and beneficial use of data.

Learning Outcome 2 - The ability to apply appropriate ethical theories/principles and professional standards to the practice of data science.

Answer: Data scientists must apply ethical theories and principles to their work. Utilitarianism emphasizes maximizing overall well-being, guiding decisions that benefit the greatest number of people. Deontology focuses on duty and following moral rules, ensuring fairness and respect for individual rights. Virtue ethics emphasizes developing good character traits, such as honesty and integrity, to guide ethical behavior. Professional standards, like those from organizations like ACM and IEEE, provide guidelines for ethical conduct in data science, including data privacy, bias mitigation, and transparency. By applying these theories, principles, and standards, data scientists can ensure their work is conducted ethically and contributes positively to society.

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1. Assessment Details - This assessment will consist of an essay considering the ethical theories and practical implication of big data and data analytics. This assessment will require the student to consider the information presented in the ethics part of this module (week 9 to 16) with respect to the needs of children.

Initial research is required to enable the student to identify the particular topic area that they wish to focus on. Additional research will then be required to enable the student to produce an essay of between 3,000 - 5,000 words.

Support will be provided in class to enable the student to decide the focus of their work.

Relevant Module Content - The ethics part of this module covers:-

1. Week 9 - Basic issues - privacy and consent.

2. Week 10 - Professional responsibility

3. Week 11 - Reliability of data

4. Week 12 - Data Processing

5. Week 13 - Results from data analysis - quality and trust

6. Week 14 - Visualisation/Data Presentation

7. Week 15 - Biometrics

8. Week 16 - Overview of Issues

Focus of Report - Your report should be based on a consideration of the question.

Question - What is the most important data processing ethical consideration that affects children?

Answer to this question can be based on a particular technology, a particular data use or a particular situation. Support will be provided in class to enable all students to select a suitable focus of their report.

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2. Content of Report - The report should contain the following content and make use of a formal report structure including use of suitable references and language:

1. Introduction

2. Selection of Report Focus

- Description of focus including:

  • Technical background
  • Social and practical concerns
  • Ethical Issues

- Explanation of why this focus was selected

3. The Future

- Likely long term effect

- Consideration of ways in which ethical requirements can be meet

4. Conclusion

Note - The essay is expected to have not more than 5,000 words. This word count excludes references.

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