Bias and Fairness in Robotic Systems: Challenges and Solutions

Abstract:

The robotic systems become more integrated into various aspects of life, including healthcare, criminal justice, labour, and autonomous vehicles, the issue of bias in these systems has emerged as a critical concern. The bias in the decisions taken by robots may enhance social disparities, enhance discrimination, and afflict vulnerable groups. This article addresses the biased properties and origin of robotic systems, including biased data, faulty system algorithms, and prejudice of the designers and developers in the course of the system. It also notes the grave social, ethical and legal impacts that discriminatory machines in specific areas may have, specifically in high-stakes areas. The article also proposes an array of remedies to curb the bias, such as a better data collection process, just algorithms, ethical design, and regulatory tools. Nevertheless, the article underlines the technical, economic, political, and societal issues that prevent the creation of really fair robotic systems. By stating the necessity of inter-disciplinary cooperation, the involvement of the public and the global regulatory systems, it confirms that, potentially, the robots developed will not only be efficient but also fair and just.