| CODE | DGP0960 | ||||||
| TITLE | AI with Confidence: Safe, Ethical and Responsible Use | ||||||
| UM LEVEL | 00 - Mod Pre-Tert, Foundation, Proficiency & DegreePlus | ||||||
| EQF/MQF LEVEL | Not Applicable | ||||||
| ECTS CREDITS | Not Applicable | ||||||
| DEPARTMENT | Degree Plus Programme | ||||||
| DESCRIPTION | AI with Confidence is a practical, non-technical study-unit that helps students use artificial intelligence safely, ethically and appropriately in academic, professional and everyday contexts. Using realistic cases rather than abstract technical theory, participants will examine inaccurate outputs, privacy, confidential information, bias, academic integrity, copyright, synthetic media, disclosure, human oversight and professional accountability. Students will practise checking information, protecting sensitive data, recognising inappropriate uses and deciding when AI assistance should be disclosed, reviewed or avoided. No previous knowledge of AI, law or computing is required. Objectives: By the end of the unit, participants will be able to: 1. Distinguish between appropriate, questionable and unacceptable uses of AI. 2. Recognise inaccurate or misleading outputs and verify important information using reliable sources. 3. Protect personal, confidential and sensitive information when using AI tools. 4. Identify bias, unfairness and possible harm in AI-supported recommendations and decisions. 5. Apply principles of academic integrity, authorship, attribution, copyright, consent and disclosure. 6. Decide when human oversight, escalation, expert advice or non-use is required. Unit Material: Appropriate study-unit material, practical case studies and reusable checklists will be provided by the tutor during the sessions. Students should bring a laptop or tablet that can connect to Wi-Fi. Session 1: Using AI responsibly. Assess everyday academic and professional scenarios using a simple risk-based approach. Session 2: When AI gets it wrong. Detect hallucinations, invented references, misleading claims and overconfident language. Session 3: Privacy and confidentiality. Identify unsafe prompts, remove sensitive details and choose safer ways to complete a task. Session 4: Bias, fairness and discrimination. Examine how AI-supported decisions may disadvantage individuals or groups. Session 5: Academic integrity and professional honesty. Address authorship, attribution, disclosure and acceptable assistance. Session 6: Copyright, consent and synthetic media. Evaluate generated text, images, audio, video and deepfakes. Session 7: Human oversight and accountability. Decide who remains responsible, when a result must be challenged and how concerns should be escalated. Session 8: Responsible AI case challenge. Evaluate a proposed use of AI and produce a personal code of practice for study and work.This unit may not be offered if there are an insufficient number of applicants. This unit may not be offered if there are an insufficient number of applicants.--> |
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| STUDY-UNIT TYPE | Lecture | ||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Luca DAscari |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2026/7. It may be subject to change in subsequent years. |
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