Ethics and Implications
Every piece of software changes the world a little. Most of the time the change is small and welcome. Sometimes it is large, unequal, and hard to undo. This topic is about learning to see those consequences early, and to argue about them clearly, so that you build and use technology responsibly rather than by accident.
The skill at the centre of this topic is reasoned judgment. You are not asked to memorise a list of dangers or to decide that technology is “good” or “bad.” You are asked to weigh genuine benefits against genuine costs in a specific situation and reach a defended conclusion. That is a harder and more useful skill than recall, and it is exactly what the assessment rewards.
What This Topic Covers
Modern computing ethics splits naturally into two questions, and each has its own page.
Ethics of Machine Learning
When a machine learning system makes or shapes a decision (a loan, a diagnosis, a hiring shortlist, a news feed), is it fair, safe, and accountable? This page covers the nine ethical dimensions to weigh for any model: accountability, algorithmic fairness, bias, consent, privacy, security, environmental impact, societal impact, and transparency. It explains where bias enters through training data, covers the ethics of online communication, and shows how to structure a high-mark “Discuss” answer.
Computing in Daily Life
When computing stops being something you use and becomes something you live inside, how does it change society? This page covers pervasive and embedded computing, surveillance and individual rights, the digital divide and equity, emerging technologies (quantum computing, AR/VR, pervasive AI), the changing workforce, and the habit of continually reassessing ethical guidelines as technology advances.
Where This Fits
In the current IB Computer Science syllabus (first assessment 2027), these two pages map to the two ethics learning statements, both examined with the Discuss command term at SL and HL:
| Code | Learning statement |
|---|---|
| A4.4.1 | Discuss the ethical implications of machine learning in real-world scenarios. |
| A4.4.2 | Discuss ethical aspects of the increasing integration of computer technologies into daily life. |
The ideas reach well beyond any single course. Privacy, fairness, accountability, and equity are the questions any thoughtful person should bring to the technology around them, whether or not they sit an exam on it.
How to Use These Pages
- Read the two pages in either order; they are independent but cross-reference each other.
- Learn the vocabulary precisely. The difference between a vague worry (“this seems bad”) and a strong argument (“this raises a consent problem because…”) is usually one named concept.
- Practise the Discuss structure on both pages: one side, the other side, a conclusion that weighs them. Reaching a calibrated, defended position is the whole skill.