Is Bias in AI Quantifiable? | HackerNoonBias in AI is complex and multifaceted, woven into data and algorithms, making it difficult to quantify.
Deepfake detection improves when using algorithms that are more aware of demographic diversityDeepfake detection algorithms can be improved for accuracy and fairness through demographic diversity awareness.
Is Bias in AI Quantifiable? | HackerNoonBias in AI is complex and multifaceted, woven into data and algorithms, making it difficult to quantify.
Deepfake detection improves when using algorithms that are more aware of demographic diversityDeepfake detection algorithms can be improved for accuracy and fairness through demographic diversity awareness.
How AI Models Can Detect Lung Conditions Fairly | HackerNoonClassifier performance can improve overall without sacrificing fairness among protected subgroups.
Countering Mainstream Bias via End-to-End Adaptive Local Learning: Preliminaries | HackerNoonThe study addresses mainstream bias in recommender systems by aiming to improve utility for niche users while preserving utility for mainstream users.
Exploring Bias and Fairness in AI: The Need for Comprehensive Testing Frameworks | HackerNoonResearchers propose methods to assess and test the reliability of AI and NLP software, focusing on adversarial examples and fairness evaluation.
Vanesa Guerrero, mathematician: Not knowing what is behind artificial intelligence makes us vulnerable'Perception of fairness in decision-making varies based on how questions are formulated.