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Data Mastery：Scripting，Databases and Data Privacy
PART 1 : Essay on legal, privacy and ethical considerations
Purpose: Discuss privacy, security, and ethical considerations in analysing and acting on potentially sensitive data using modern LLM-based systems functioning under agentic frameworks.
Objective: New Zealand’s Responsible AI Guidance for the Public Service: GenAI was introduced to provide ethical and legal direction on the adoption of Generative AI (GenAI) in government agencies. The framework aims to ensure transparency, fairness, and accountability while enabling the public sector to leverage AI for efficiency and innovation. However, Generative AI technologies are evolving at an unprecedented rate, introducing new risks and possibilities that existing regulations may struggle to anticipate or control.
Write an essay (max 2,000 words) that critically evaluates whether current public-sector AI governance approaches are adequate for agentic AI systems, meaning LLM-based systems that plan multi-step actions, call tools, retrieve data from organisational knowledge bases, and can trigger workflow outcomes.
AI Guidance for the Public Service: https://www.digital.govt.nz/standards-and-guidance/technology-and-architecture/artificial-intelligence/responsible-ai-guidance-for-the-public-service-genai
Key Research Questions
1. Coverage gap: Does the current NZ public-sector GenAI guidance remain adequate once systems become agentic, meaning they plan, retrieve, use tools, and execute multi-step actions, and what are the two most important governance extensions needed to keep it fit for purpose.
2. Agency debate (capabilities): For one NZ public-sector use case, argue what level of autonomy is technically and operationally justifiable today, and defend your position by separating model fluency from reliability, verification, and safe tool use.
3. Assurance evidence: Specify the minimum assurance case that should be required before deployment, including evaluation, logging and traceability, human override, and post-deployment monitoring tailored to agentic failure modes.
4. Accountability and incentives: If an agent can trigger actions and behave with some autonomy, who is accountable for procurement, setup, day-to-day use, and failures, and what rules would prevent staff using unapproved AI tools or creating other harmful workarounds.
• Select one agency (e.g. Ministry of Health, Inland Revenue, Department of Internal Affairs).
• Define one realistic agentic AI use case, where the system does more than generate text and instead plans or executes a multi-step workflow using retrieval and or tools (e.g. policy-brief drafting with evidence retrieval; 158.739-2026 assisted case triage; grants or payments risk screening with human sign-off; fraud-investigation summarisation with tool calls; automated analysis of public submissions with auditable pipelines).
• Use the scenario to test the framework, by explaining where it supports safe deployment and where gaps appear in capability, assurance, accountability, privacy, security, and operational feasibility.
Based on your critique/analysis, propose concrete improvements to the framework, which may include:
- policy changes that better reflect agentic AI risks and realistic deployment practices
- assurance requirements, including evaluation expectations, logging and traceability, human override, and monitoring
- accountability structures that clarify responsibilities across procurement, configuration, operation, and incident response
- practical support mechanisms for agencies, including guidance templates, shared services, and capability uplift
Sources to consult: You should base your views on materials relevant to New Zealand legislation and context when possible. You are encouraged to consult primary legal sources (e.g. statutes, regulations, case law) as well as academic articles, preprints, reports, or occasionally news articles. Give preference to peer-reviewed articles where possible. Use the APA citation style.
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Component |
Marks |
Requirements and expectations |
| Depth of Critical Analysis |
50% |
Addresses all four questions directly, critiques how well the NZ guidance supports agentic AI (not only chat-style GenAI), and assesses capabilities realistically by separating fluency from reliability, verification, and safe tool use. Uses credible sources and makes a clear argument rather than a descriptive summary. |
|
Case Study Evaluation |
30% |
Defines one NZ public-sector agency and one realistic agentic use case, describes the workflow (key inputs, tools or retrieval, decision points, action points, and human oversight), and uses it to show where the guidance works and where gaps appear in privacy, security, accountability, and operational feasibility. |
|
Practicality of Recommendations |
10% |
Are recommendations actionable and evidence-based? Do they align with public sector constraints? |
|
Clarity & Presentation |
10% |
Clear structure, coherent flow, professional tone, correct referencing (APA as required), and writing that makes the argument easy to follow. Figures or tables are optional, but must add value if used. |
|
Read the set paper |
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To pass this component, you also need to confirm in your essay submission that you have read the following article: “Should I Use ChatGPT to Write My Papers?” https://link.springer.com/article/10.1007/s13347-024-00809-w158.739-2026 |
PART 2 : Completion of the free “Privacy 101” e-learning course provided by The Office of the Privacy Commissioner
Finally, passing assignment 2 is also contingent on you completing the online “Privacy 101” course provided by The Office of the Privacy Commissioner. The course only takes 2-3 hours to complete.
The course can be accessed here: https://www.privacy.org.nz/resources-and-learning/online-privacy-training-free/
Final Submission
Use of Generative AI in This Assignment
In professional and academic settings, AI and online resources are often used to streamline tasks, generate insights, and improve efficiency. However, in university coursework, the primary goal is to develop your ability to think critically, analyze complex issues, and construct well-reasoned arguments independently. Mastering these skills will allow you to use AI tools more effectively and ethically in the future.
While AI can be a useful tool for learning, relying on it to generate essay content directly undermines your intellectual development and academic integrity. Your task in this assignment is to critically evaluate New Zealand’s Responsible AI Guidance for the Public Service: GenAI, requiring you to engage with legal, ethical, and policy-based sources, construct original arguments, and apply critical thinking. The use of Generative AI in this assignment is restricted to research support, explanation, review, and conceptual development only, as outlined below.
o Example: "What are the main ethical concerns surrounding Generative AI in public sector decision-making?"o Example: "Summarize the key principles of responsible AI governance."
o Example: "Explain the legal concept of ‘algorithmic accountability’ and how it applies to public sector AI use."
o Example: "Does my essay outline provide a strong logical flow for my argument?"o Example: "Are there any gaps in my discussion of bias mitigation in AI frameworks?"