FinA: Fairness of Adverse Effects in Decision-Making of Human-Cyber-Physical-System
This work addresses fairness for diverse individuals in HCPS applications like smart homes, focusing on adverse effects, but it is incremental as it builds on existing fairness concepts with new formulations.
The paper tackled fairness in decision-making within Human-Cyber-Physical-Systems by introducing Fairness-in-Adverse-Effects (FinA) to address long-term adverse effects and dynamic human behavior, resulting in a 66.7% average improvement in fairness perception compared to state-of-the-art methods in smart home evaluations.
Ensuring fairness in decision-making systems within Human-Cyber-Physical-Systems (HCPS) is a pressing concern, particularly when diverse individuals, each with varying behaviors and expectations, coexist within the same application space, influenced by a shared set of control actions in the system. The long-term adverse effects of these actions further pose the challenge, as historical experiences and interactions shape individual perceptions of fairness. This paper addresses the challenge of fairness from an equity perspective of adverse effects, taking into account the dynamic nature of human behavior and evolving preferences while recognizing the lasting impact of adverse effects. We formally introduce the concept of Fairness-in-Adverse-Effects (FinA) within the HCPS context. We put forth a comprehensive set of five formulations for FinA, encompassing both the instantaneous and long-term aspects of adverse effects. To empirically validate the effectiveness of our FinA approach, we conducted an evaluation within the domain of smart homes, a pertinent HCPS application. The outcomes of our evaluation demonstrate that the adoption of FinA significantly enhances the overall perception of fairness among individuals, yielding an average improvement of 66.7% when compared to the state-of-the-art method.