3 research outputs found
Attesting Biases and Discrimination using Language Semantics
AI agents are increasingly deployed and used to make automated decisions that
affect our lives on a daily basis. It is imperative to ensure that these
systems embed ethical principles and respect human values. We focus on how we
can attest to whether AI agents treat users fairly without discriminating
against particular individuals or groups through biases in language. In
particular, we discuss human unconscious biases, how they are embedded in
language, and how AI systems inherit those biases by learning from and
processing human language. Then, we outline a roadmap for future research to
better understand and attest problematic AI biases derived from language.Comment: Author's copy of the manuscript accepted in the Responsible
Artificial Intelligence Agents workshop of the International Conference on
Autonomous Agents and Multiagent Systems (AAMAS'19