Data Governance, Privacy, and Federated Learning DATA4300

Subject Code:

DATA4300

Subject Name:

Data Security and Ethics

Assessment Title:

Data Governance, Privacy, and Federated Learning

Assessment Type:

Report

Word Count:

1200 words +_ 10%

Weighting:

40%

Total Marks:

40

Submission:

Turnitin

Due Date:

Tuesday Week 9 by 11:55 pm AEST

Initial generative AI drafts

(3 Marks)

Use your own queries in any Generative AI tool to generate the initial drafts for your chosen company.

How to write the perfect ChatGPT prompt and become a Prompt writer

Include the initial/draft version together with your QUERIES.

Edit the draft plans by using the review and new comment functions in Microsoft Word based on your knowledge and include (final version).

Include a disclaimer stating that this plan was produced by you and generative AI.

Acknowledge sections written by AI technology based on the following policy.

References and structure

(7 Marks)

Include a minimum of five original references.

Use the Harvard referencing style with in-text citations to your references.

Use appropriate headings and paragraphs.

If the marker has evidence that the student has misrepresented someone

elses work by not referencing it appropriately they can deduct an additional 4-6 marks.

Traffic Light

Amount of Generative Artificial Intelligence (GenerativeAI) usage

Evidence Required

This asse ssment (?)

Level 1

Prohibited:

No GenerativeAI allowed

This assessment showcases your individual knowledge, skills and/or personal experiences in the absence of Generative AI

support.

The use of generative AI is prohibited for this assessment and may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment.

Level 2

Optional:

You may use GenerativeAI for research and content generation that is appropriately referenced.

See assessment instructions for details

This assessment allows you to engage with Generative AI as a means of expanding your understanding, creativity, and idea generation in the research phase of your assessment and to produce content that enhances your assessment. I.e., images. You do not have to use it.

The use of GenAI is optional for this assessment.

Your collaboration with GenerativeAI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference GenerativeAI.

https://library.kaplan.edu.au/referencing-other- sources/referencing-other-sources-generative- ai

In addition, you must include an appendix that documents your GenerativeAI collaboration including all prompts and responses used for the assessment.

Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the

specific assessment instructions in the section above.

Level 3

Compulsory:

You must use GenerativeAI to complete your assessment

See assessment instruction for details

This assessment fully integrates Generative AI, allowing you to harness the technology's full potential in collaboration with your own expertise.

Always check your assessment instructions carefully as there may still be limitations on what constitutes acceptable use, and these may be specific to each assessment.

You will be taught how to use generative AI and assessed on its use.

Your collaboration with GenerativeAI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference GenerativeAI.

https://library.kaplan.edu.au/referencing-other- sources/referencing-other-sources-generative- ai

In addition, you must include an appendix that documents your GenerativeAI collaboration including all prompts and responses used for the assessment.

Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the

specific assessment instructions in the section above.

?

Criteria

Excellent (13-

15 marks)

Proficient (10-

12 marks)

Satisfactory (7-9 marks)

Needs

Improvement (4-6 marks)

Poor (0-3 marks)

Key Ethical Issues (5 marks)

A thorough discussion of informed consent, user anonymity, transparency, and other ethical issues, clearly relating them back to the company's specific operations and

industry context.

Addresses most ethical issues well and makes some connections to company- specific operations, with minor gaps in reasoning or detail.

Discusses some key ethical issues with basic relation to company- specific operations but lacks depth or clarity.

Limited mention of ethical issues with weak or minimal links to company- specific operations, lacking detail and explanation.

Ethical issues are poorly addressed or largely ignored, with no connection to company- specific operations.

Data Accuracy & Reliability (5 marks)

Clear explanation of strategies for ensuring accuracy, completeness, and reliability in ways that align with the company's

operations and build trust.

Good explanation of strategies with some alignment to company operations, but lacks depth or detail in parts.

Basic explanation of strategies with limited connection to how they support company operations and objectives.

Few relevant strategies provided, minimal explanation, and weak links to company- specific practices.

Strategies for accuracy and reliability are largely absent or unclear, with no relation to company operations.

Compliance with Privacy Laws (5 marks)

Excellent alignment with relevant privacy laws (e.g., GDPR), clearly demonstrating understanding and tailoring compliance to the company's

industry and jurisdiction.

Good understanding and alignment with privacy laws, with some tailoring to the company's needs, but lacking in some specifics.

Basic understanding of privacy laws with limited application to the companys specific context or operations.

Limited mention of privacy laws or understanding of compliance, with minimal connection to company- specific requirements.

No mention or poor understanding of privacy laws, failing to show compliance or relate to company operations.

Criteria

Excellent (13-

15 marks)

Proficient (10-12 marks)

Satisfactory (7-9 marks)

Needs Improvement (4-6 marks)

Poor (0-3 marks)

Incident Response Plan (5 marks)

Detailed step- by-step plan with clear internal/externa l notifications, containment strategies, and damage assessment, tailored to the company's industry,

structure, and scale.

Clear steps provided and some tailoring to company operations, but lacks depth in some areas.

Basic incident response plan with general steps, limited consideration of how it applies to the companys specific operations.

Incomplete or overly simplified response plan with minimal steps, and little relevance to the companys operations or specific needs.

Little to no incident response plan provided, with no alignment to the company's operations or industry context.

Communicatio n Strategy (5 marks)

Clear and effective communication plan with stakeholders, including customers, employees, and regulators, maintaining transparency and aligning with the companys

operations.

Communicate s with stakeholders well but lacks detailed consideration of how to align with company- specific operations or industry.

Basic communicatio n strategy with limited stakeholder consideration and minimal focus on company- specific operations.

Weak communicatio n plan with minimal stakeholder focus, vague strategies, and little alignment with company operations.

Communicatio n plan is absent or severely lacking in detail and consideration for stakeholders, with no relation to company practices.

Federated Learning & Data Privacy (5 marks)

Excellent discussion of how federated learning and other technologies enhance privacy while maintaining data usability, applied to the company's operations and

industry context.

Good discussion of federated learning, with minor gaps in how it applies to the company's context or operational needs.

Basic understanding of federated learning, with limited application to the companys operational context or needs.

Weak understanding of federated learning and its role in maintaining privacy, minimal discussion of technology's relevance to the company.

No mention or poor understanding of federated learning, with no application to the companys operations or industry.

Criteria

Excellent (3 marks)

Needs Improvement (2 marks)

Poor (0-1 mark)

Generative AI Use (3 marks)

Excellent use of AI to generate drafts, with clear and thoughtful contributions that

demonstrate learning.

Minimal effort in using AI with unclear edits and few original contributions.

Poor or no use of AI, or no meaningful edits made to improve the AI-generated

draft.

Criteria

Excellent (5-7 marks)

Needs Improvement (4-

2 marks)

Poor (0-1 mark)

References

Includes more than five original, high-quality sources with

an accurate KBS Harvard referencing style.

Few sources and major referencing errors.

No references or misrepresented sources.

Structure

Clear and logical structure with appropriate headings and

paragraphs.

Poorly organized, lacking in clear sections

or logical flow.

No clear structure, with severe issues in

organization and coherence.