AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems

• URL: http://arxiv.org/abs/2402.06287v1
• Date: Fri, 9 Feb 2024 09:54:01 GMT
• Title: AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems
• Authors: Clara Punzi, Roberto Pellungrini, Mattia Setzu, Fosca Giannotti and Dino Pedreschi
• Abstract summary: Humans are now constantly interacting with machine learning-based systems, training and using models everyday. Several different techniques in computer science literature account for the human interaction with machine learning systems, but their classification is sparse and the goals varied. This survey proposes a taxonomy of Hybrid Decision Making Systems, providing both a conceptual and technical framework for understanding how current computer science literature models interaction between humans and machines.
• Score: 4.936180840622583
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Everyday we increasingly rely on machine learning models to automate and support high-stake tasks and decisions. This growing presence means that humans are now constantly interacting with machine learning-based systems, training and using models everyday. Several different techniques in computer science literature account for the human interaction with machine learning systems, but their classification is sparse and the goals varied. This survey proposes a taxonomy of Hybrid Decision Making Systems, providing both a conceptual and technical framework for understanding how current computer science literature models interaction between humans and machines.

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