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Year 10
AQA

Algorithmic bias

I can describe algorithmic bias and suggest ways to make algorithms fairer.

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New
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Year 10
AQA

Algorithmic bias

I can describe algorithmic bias and suggest ways to make algorithms fairer.

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Lesson details

Key learning points

  1. Algorithmic bias is when an algorithm produces unfair or discriminatory outcomes that favour some groups over others.
  2. Using poor quality data in algorithms can lead to inaccurate results, unreliable predictions, or biased outcomes.
  3. Algorithms can become biased if the design of the algorithm instructions are biased.
  4. By aiming to understand sources of bias algorithmic, bias can be reduced as much as possible.

Keywords

  • Bias - to disproportionately favour one side, group, or outcome over others

  • Discriminatory - to make or show an unjust or prejudicial distinction between different categories of people

Common misconception

Algorithmic bias can be completely eliminated.

It is extremely difficult, maybe impossible, for complex algorithms to be completely free from bias. By aiming to understand sources of bias, actively working to reduce it, and being transparent, algorithmic bias can be reduced as much as possible.


To help you plan your year 10 computer science lesson on: Algorithmic bias, download all teaching resources for free and adapt to suit your pupils' needs...

Emphasise that algorithmic bias isn't just technical, it is influenced by the creators of the algorithms.
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This content is © Oak National Academy Limited (2025), licensed on Open Government Licence version 3.0 except where otherwise stated. See Oak's terms & conditions (Collection 2).

Lesson video

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Starter quiz

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6 Questions

Q1.
What is a data structure?
Correct answer: a way of organising and storing data in a computer
a type of programming language
a step-by-step solution to a problem
a method to debug programs
Q2.
What is the main difference between static and dynamic data structures?
Static data structures are faster than dynamic data structures.
Correct answer: Static data structures have fixed size, while dynamic data structures can vary.
Dynamic data structures only store numbers.
Static data structures are used for algorithms, while dynamic ones are not.
Q3.
An is an example of a static data structure.
Correct Answer: array, rray
Q4.
What is a dynamic data structure?
Correct answer: a data structure whose size can change as the program runs
a data structure that only stores numbers
a data structure that is fixed in size before the program runs
a data structure used only in algorithms
Q5.
Why is choosing the correct data structure important?
It ensures the program runs without errors.
Correct answer: It makes the program more efficient and easier to manage.
It guarantees the program will run faster.
It prevents the need for debugging.
Q6.
What is a key advantage of dynamic data structures?
They are faster than static data structures.
They are easier to debug.
Correct answer: They can adjust their size during program execution.
They store only one data type.

Exit quiz

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6 Questions

Q1.
What is it called when an algorithm disproportionately favours one side, group or outcome over others?
Correct Answer: bias, algorithmic bias
Q2.
Match the term to its definition.
Correct Answer:high quality data,helps to reduce algorithmic bias
tick

helps to reduce algorithmic bias

Correct Answer:transparency,helps identify and address sources of bias
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helps identify and address sources of bias

Correct Answer:algorithmic bias,produces unfair or unequal outcomes
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produces unfair or unequal outcomes

Correct Answer:discriminatory,makes an unjust or prejudicial distinction between groups
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makes an unjust or prejudicial distinction between groups

Q3.
What can cause algorithmic bias?
Correct answer: using poor quality data
using too much data in the algorithm
running the algorithm on multiple devices
writing the algorithm in a specific programming language
Q4.
Which of the following is true about eliminating algorithmic bias?
Algorithmic bias can always be completely eliminated.
Algorithmic bias can be fixed by using any type of data.
Correct answer: Algorithmic bias can be reduced but not always completely eliminated.
Algorithmic bias is not a real issue in algorithms.
Q5.
What is one way to reduce algorithmic bias?
Ignore the sources of bias.
Correct answer: Use high quality, diverse data sets.
Avoid using algorithms entirely.
Simplify the algorithm into fewer steps.
Q6.
Place these steps in order for reducing algorithmic bias.
1 - Identify sources of bias.
2 - Use high quality, diverse data sets.
3 - Test the algorithm for fairness.