Ethics & Implications
Computing systems affect privacy, access to services, employment and the environment. Some of those effects are small and welcome; others are large, fall unequally on different groups of people, and are hard to undo. This topic is about spotting those consequences early and arguing about them clearly, considering different perspectives and reaching conclusions supported by evidence, so that you can build and use technology responsibly.
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 an answer to a “Discuss” question.
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, 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. |
Privacy, fairness, accountability and equity come up wherever computers are used, so the pages are useful beyond the course too.
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.