DTS306TC Security, Privacy and Ethics Coursework 2
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Module code and Title |
DTS306TC Security, Privacy and Ethics |
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School Title |
School of AI and Advanced Computing |
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Assignment Title |
Coursework 2 |
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Submission Deadline |
5 pm China Time (UTC+8 Beijing) on Fri. Dec 12, 2025 |
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Final Word Count |
1500 +/-5% |
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Video Length |
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DTS306TC Security, Privacy and Ethics
Coursework 2
Submission deadline: 5 pm China Time (UTC+8 Beijing) on Fri, Dec 12, 2025
Percentage in final mark: 70%
Maximum score: 100 marks
Learning outcomes assessed:
B: Evaluating the potential risks and benefits of AI technologies on privacy and personal data
C: Understanding the importance of fairness in AI systems and its implications
Late policy: 5% of the total marks available for the assessment shall be deducted from the assessment mark for each day after the submission date, up to a maximum of five days.
Risks:
• Please read the coursework instructions and requirements carefully. Not following these instructions and requirements may result in loss of marks.
• Plagiarism results in award of ZERO mark.
• The formal procedure for submitting coursework at XJTLU is strictly followed. Submission link on Learning Mall will be provided in due course. The submission timestamp on Learning Mall will be used to check late submission.
Coursework Overview
This is an individual coursework. Artificial intelligence has profound effect on modern lifestyles. Therefore, responsible use of AI is critical. In this coursework, the design of fair and bias-mitigated AI technology for social good will be investigated. Then, you need to complete a report that include your justifications on the case studies and proposed solutions to the design.
The presence of AI has trickled into every part of mankind. In recognition of the global impact of AI, countries all across the world have made great effort to encourage the development of responsible AI for social good via the United Nations (UN) Sustainable Development Goals (SDGs) initiatives. Since its inception, there are numerous SDGs supported projects have been carried out in different countries, especially the Third World.
Task Instructions
The aim of this coursework is to empirically assess the current status of responsible AI use in SDGs- supported social project and design an ethical-driven innovative bias-mitigated and fair deep learning framework for social good to attain the final goal of contributing to the society. To do so, you are required to choose a specific SDGs supported domain and design a new AI for social good project.
During the project, your report on the proposed ethically-driven innovative bias-mitigated and fair deep learning framework for social good shall include the security, privacy, ethical, bias and fairness of AI technology as part of the compulsory consideration criteria. These criteria are reflected in the case studies within your report.
The report should be written in a clear and concise manner with no more than 1,500 words+/-5%. in total length. Your final report should be detailed and relevant in addressing the following sections:
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Section |
Description |
Approximate word count |
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Project background |
Please define your project domain based on the UN SDGs (https://sdgs.un.org/goals). You are required to explain the rationale associated with your domain selection and the project background. |
150 |
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Case Study 1 |
Privacy and ethical use of data You are required to explain the concerns and approaches related to effective privacy protection and ethical use of data within your design. |
300 |
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Case Study 2 |
Ethics in AI design You are required to justify the ethical components embedded within your deep learning framework and explain how it can contribute to social good. |
300 |
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Case Study 3 |
Bias and Fairness in AI model You are required to demonstrate the bias and fairness issue related to your project’s prototype. Then, explain the bias- mitigation approach suitable for your project. |
300 |
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Framework Design |
By considering elements in all case studies, you are required to explain the rationale and details of your framework design. |
450 |
Important: Do not repeat existing information that is in the research papers. This will only contribute to low mark. Originality of work is important. Thus, you need to synthesize your own ideas/opinions based on your understanding and present them in your own words.
Report Format:
Cover Page: This should include the Assessment Number, Assessment Title, Student Name, Student ID and Student Email
Body of the report: This should include all the relevant section headings to address each section as indicated above and marking rubrics.
References: Both in-text and the references included in the “References” section at the end of the report should adhere strictly to the IEEE reference style.
Formatting requirement:
• Use multiple spacing: 1.08 and spacing after: 8pt;
• Use a standard 12-point font, font type: Tahoma
• Use “Justify” body text
• Put your page numbers at the top right (except the cover page)
• Most importantly, always run a spelling and grammar check; however, remember, such checks may not pick up all errors. You should still edit your work manually and carefully.
Referencing:
It is compulsory to use IEEE reference style for citing and referencing research. Reference list is excluded from the imposed word limit.
2025-12-05