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Found 8 papers, 2 papers with code
Explaining how your AI system is fair
To implement fair machine learning in a sustainable way, choosing the right fairness objective is key.
Implementing Fair Regression In The Real World
Most fair regression algorithms mitigate bias towards sensitive sub populations and therefore improve fairness at group level.
Active Fairness Instead of Unawareness
The possible risk that AI systems could promote discrimination by reproducing and enforcing unwanted bias in data has been broadly discussed in research and society.
Getting Fairness Right: Towards a Toolbox for Practitioners
The potential risk of AI systems unintentionally embedding and reproducing bias has attracted the attention of machine learning practitioners and society at large.
Fairness-Aware Neural Réyni Minimization for Continuous Features
Second, by minimizing the HGR directly with an adversarial neural network architecture.
Contract Statements Knowledge Service for Chatbots
Towards conversational agents that are capable of handling more complex questions on contractual conditions, formalizing contract statements in a machine readable way is crucial.
