Question 1
Which of the following is an example of bias being embedded in the design of an algorithm itself, rather than in the data used to train it?
- A facial recognition system is less accurate for women because it was trained mostly on pictures of men.
- A college admissions algorithm is programmed to give extra weight to applicants who play a sport that is predominantly played by a single demographic group.
- A voice recognition system struggles to understand speakers with a certain accent because they were not included in the audio training files.
- A résumé-screening tool favors male candidates because it learned from a company's historical hiring records, which were heavily male.
Explanation: Correct. In this case, the programmer has made an explicit choice to prioritize a specific factor (a particular sport). This is a feature of the algorithm's logic or design. If that factor correlates with a demographic group, the algorithm itself is biased, regardless of the data it processes.
- A, C, and D are all examples of data bias, where the algorithm's biased output is a result of being trained on unrepresentative or historically biased data.