Ethics & Foundations of AI Use
Use AI better, with human judgement at the centre
Course details
Course language
This course is taught entirely in English.
Choose the language you want to learn in, it is available in:
Listen to the introduction
Learning goals
- Understand what AI can and cannot do
- Distinguish credible developments from hype and inflated claims
- Recognise where human judgement and responsibility remain essential
- Decide when AI is useful, unnecessary or inappropriate
- Write prompts with clearer intentions, context and constraints
- Refine AI outputs through deliberate iteration
- Evaluate outputs for accuracy, relevance, quality, bias and uncertainty
- Identify ethical, contextual and organisational risks in AI-supported work
- Protect their voice, authorship, standards and credibility
- Integrate AI into workflows without surrendering ownership or accountability
- Create a Personal Context File to improve the relevance of AI support
- Develop a sustainable personal framework for responsible AI use
Skills you'll gain
Course description
Most AI courses begin with speed: how to produce faster, automate more and keep up. This course begins somewhere else- with judgement. AI is often presented through urgency, inflated claims and pressure to adopt new tools quickly. Yet responsible use requires more than technical confidence. It requires an understanding of what AI can and cannot do, the ability to evaluate its outputs critically, and the judgement to decide when its use is appropriate. This course responds to what CTDC has documented across organisations, education, professional life and everyday practice: AI being used quickly, but not always carefully. It is not anti-AI. It takes AI seriously- including its capabilities, limitations, risks and wider social and ecological costs. The course first establishes a grounded understanding of how AI works and why fluent outputs should not be confused with understanding, judgement or accountability. Learners examine the pressures and assumptions surrounding AI, distinguish value from productivity, and identify the forms of human contribution that cannot be reduced to tasks or outputs. From this foundation, participants develop practical skills in intentional prompting, iteration, output evaluation and workflow design. They learn how to give AI relevant context, test rather than simply accept its responses, protect their own voice and standards, and determine where AI can strengthen their work without displacing authorship or responsibility. The course includes practical resources for building a personalised and sustainable AI practice, including a Personal Context File framework, a Voice Profile resource and frameworks for scaling work responsibly across formats and audiences. Because AI tools will continue to change, the course does not depend on mastering a particular platform. It develops more durable capacities: judgement, reflection, critical thinking, selective use and accountable decision-making. The aim is not simply to use AI more. It is to use AI better- with clarity, ethics and human judgement at the centre.
Requirements
- No previous technical knowledge or AI expertise
- No need to master every AI tool
- Access to an internet-connected computer or tablet
- Access to a generative AI tool for practical exercises
- A willingness to pause, reflect and question assumptions
- A real task, role or area of work through which to apply the learning
Course curriculum
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1.1 Why AI Feel Overwhelming
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1.1 Reflection
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1.2 What AI Is (and Is Not)
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1.2 Reflection
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1.3 Why the Noise Exists
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1.3 Recognising the AI Noise
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1.4 What this Course Is (and Is Not)
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1.4 Spot the Confusion
01:00 Locked -
Module 1: Knowledge Test
05:00 Locked
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2.1 Before you continue
01:00 Locked -
2.1 Productivity as a Narrow Lens
12:00 Locked -
2.1 Reflection
02:00 Locked -
2.2 Invisible Work, Judgment and Responsibility
15:00 Locked -
2.2 Exercise: Invisible Work
05:00 Locked -
2.3 Widening the Lens on Value, Metrics, Judgment and Contribution
21:00 Locked -
2.3 Value Mapping
03:00 Locked -
Module 2: Knowledge Test
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3.1 Beyond Skills: Judgment, Responsibility, and Human Value in the Age of AI
19:00 Locked -
3.1.1 Reflection
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3.1.2 Skills Worksheet
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3.2 Where AI Breaks without Humans
11:00 Locked -
3.2 Checklist: AI Failures
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3.3 Pre-video Worksheet
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3.3 Human Value Statements
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3.3 AI Response Control Toolkit
02:00 Locked -
Module 3: Knowledge Test
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4.1 Amplification versus Substitution
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4.1 Reflective Practice
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4.2 What Good AI Use Looks Like
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4.2 Activity
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4.3 What Bad AI Use Looks Like
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4.3 Checklist
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4.4 Deciding Where AI Fits
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4.4 Exercise
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4.4 Resources
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Module 4: Knowledge Test
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5.1 Intentional Prompting and Iteration
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5.1.A Practice
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5.1.B Practice
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5.2 Evaluating and Rejecting AI Outputs
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5.2 Activity
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5.3 Building an AI Output System
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5.3.1 AI as a Thinking Partner
02:00 Locked -
5.3.2 Voice Profile
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5.3.3 Scaling Outputs
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Module 5: Knowledge Test
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6.1 AI in Real Workflows
20:00 Locked -
6.1 Exercise
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6.2 Contextual Constraints and Risks
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6.2 Exercise
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6.3 Quality, Ethics and Accountability
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6.3 Accountability in Practice
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6.4 Consolidation, Toolkit and Transition
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6.4 Toolkit: AI in Practice
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Module 6: Knowledge Test
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7.1 Integration: AI, Judgment, and Leverage
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7.2 The Discipline of Responsible AI Practice
11:00 Locked -
End of Course Test (Marked)
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Meet your instructors
Dr Nour Abu-Assab
Co-Founder & Co-Executive Director, CTDC | Academic, Educator, Mentor & Entrepreneur | AI-Enabled Learning Innovation & Organisational Systems Design
Dr Nof Nasser-Eddin
Co-Founder & Co-Executive Director, CTDC | Psychotherapy-Informed Educator & Academic | Building People-Centred Organisations & VenturesStudent reviews
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