AI Ethics & Applications
What ai ethics & applications means
Bias, fairness, privacy and real-world AI applications in Africa and beyond.
Before you start
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Worked example
One question from this skill's own question bank, shown with its full working.
Algorithmic bias most commonly arises from:
- Computers being naturally unfair
- Training data that under-represents or misrepresents certain groups
- Using too much electricity
- Writing code in Python
Working: Models learn patterns from their data; if the data reflects historical or sampling bias, the model can reproduce and amplify it.
Curriculum and exam alignment
Curriculum notes are a general guide to where this work normally sits. Always check the syllabus your school or examination body is currently using.
Related skills
Other Artificial Intelligence skills in Computing, at the same point in the course.
Other Computing topics
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Exams that assess ai ethics & applications
University work on this skill feeds directly into these exam papers. Each page lists the Computing topics that appear on it.
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Practise ai ethics & applications
8 questions with a worked answer after every attempt, and a SmartScore that tracks how close you are to mastery.