The guide gives a long list. Grouping it is what makes it usable: most of the list is one of four operations applied to a set of things — often a set of people.
Four operations
Sorting
Put them in order. Nobody is removed — but whoever reads a sorted list reads the top of it.
Searching
Find one. Answers a question about a single item.
Filtering
Remove the ones that do not match. The removed become invisible to everything downstream.
Classifying
Attach a label. Labels travel, and tend to be treated as facts rather than guesses.
Six applicants, put through each operation in turn.
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Beyond sorting and filtering
- Prioritising — deciding what to show first, which is most of what a feed does.
- Associating — linking things that go together, which is how recommendations work.
- Counting — the quiet one, and the basis of every statistic an organization has about you.
- Software development — algorithms are what programs are built out of.
- Machine learning — algorithms that write other algorithms from data rather than from rules.
The one to notice: Machine learning is on the list of USES of algorithms. The learning process is itself an algorithm, and what it produces is another one that nobody wrote by hand.
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Prioritising a shopping list and prioritising a hospital waiting list are the same operation. What changes is what happens to the person at the bottom.
Real-world examples you can name
YouTube's recommendation system — deep-learning system described 2016; borderline-content changes from January 2019
A ranking system that predicts what a viewer will watch next, which the company has said drives the majority of watch time. After criticism that it led viewers towards ever more extreme material, the company began demoting 'borderline' content rather than removing it.
Who it affected: Roughly two billion monthly viewers, and creators whose income depends on the ranking.
Platform work and employment status — UK Supreme Court ruling on Uber drivers February 2021; EU platform work directive adopted 2024
Work is allocated by an app rather than a manager. The UK Supreme Court held that Uber drivers are workers entitled to minimum wage and holiday pay, and the EU has since legislated a presumption of employment where a platform controls the work.
Who it affected: Couriers and drivers, and companies whose model assumed self-employment.
The line for part c: An algorithm does not become more or less fair by being better written. It becomes more or less fair depending on what it is pointed at.
How this is tested — you have to say what an algorithm in a scenario is actually DOING, and then judge it. It comes up two ways:
Paper 1 — structured question
- Part a: identify uses of algorithms in a described system
- Part c: evaluate an automated ranking or filtering system
Paper 2 — source-based question
- Q2: explain what a source says an algorithm does
- Q4: synthesise sources on an automated system
The trap: “the algorithm decides”: Say WHICH operation: sorting, filtering, classifying, prioritising. Each has a different consequence, and the mark is for the consequence.
Identify two uses of algorithms in an online shop.
Model answer plan
See the mark-by-mark plan — for / against / judgement, with marking guidance — in study mode.
Evaluate the use of an algorithm to prioritise which posts a user sees first.
Model answer plan
See the mark-by-mark plan — for / against / judgement, with marking guidance — in study mode.