Overview
Bias in facial recognition systems is a significant issue that affects the accuracy and fairness of these technologies. It arises from various sources, including unrepresentative training data and flawed algorithms, leading to misidentification and discrimination against certain demographic groups. ...
Key Terms
Example: Facial recognition algorithms analyze facial features to identify individuals.
Example: Facial recognition systems may misidentify people of color more often than white individuals.
Example: Using images of people from various ethnic backgrounds improves system accuracy.
Example: Ethical considerations in AI include fairness and accountability.
Example: A person being wrongly accused of a crime due to a misidentified facial match.
Example: Laws that regulate the use of facial recognition in public spaces.