AWS Certified Machine Learning – SpecialtyModelingEasy
A retail company is developing a recommendation system for clothing. They notice that the system predominantly recommends popular items, even to users who have previously shown interest in niche or less common apparel. This leads to a lack of diversity in recommendations and dissatisfaction among users with specific tastes. Which type of bias is the recommendation system exhibiting?
- AConfirmation Bias
- BSelection Bias
- CPopularity Bias
- DAutomation Bias
Show answer & explanationAnswer & explanation
Correct answer: C. Popularity Bias
The scenario describes a recommendation system that favors popular items, leading to a lack of diversity and neglecting niche preferences. This is a classic example of popularity bias, where frequently interacted-with items are over-represented in recommendations regardless of individual user taste.
Why the other options are wrong
- A. Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms one's preexisting beliefs or hypotheses.
- B. Selection bias occurs when the data used to train the model is not representative of the actual population.
- D. Automation bias is the tendency to over-rely on automated systems, often ignoring contradictory information.
Popularity Bias
A bias in recommendation systems where items that are already popular tend to be recommended more frequently, leading to a lack of diversity and potentially ignoring niche preferences.
- Results in 'rich-get-richer' phenomenon for popular items.
- Reduces discovery of long-tail items.
- Can lead to user dissatisfaction and filter bubbles.
Memory trick: Popularity's Pull, Niche's Fall.