Paper Number

2204

Paper Type

SP

Abstract

In an era where Artificial Intelligence (AI) increasingly permeates the global landscape, its potential to impact many people necessitates heightened vigilance against biases in AI-driven outputs. This research employs a grounded methodology, gathering insights through semi-structured interviews with AI professionals engaged in various stages of the AI lifecycle. Our objective is to develop a socio-technical framework that systematically identifies and mitigates AI bias, including various aspects of stakeholder participation. Initial findings from this study have refined our interview protocols and expanded our understanding of overlooked AI biases. These insights offer a deeper understanding of the influence exerted by non-end-user stakeholders on the AI development lifecycle, providing a multi-dimensional perspective on the nuances of AI bias and its emergence and mitigation

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Jun 14th, 12:00 AM

IDENTIFYING AI BIAS AND MITIGATION CHALLENGES THROUGH A SOCIO-TECHNICAL PERSPECTIVE

In an era where Artificial Intelligence (AI) increasingly permeates the global landscape, its potential to impact many people necessitates heightened vigilance against biases in AI-driven outputs. This research employs a grounded methodology, gathering insights through semi-structured interviews with AI professionals engaged in various stages of the AI lifecycle. Our objective is to develop a socio-technical framework that systematically identifies and mitigates AI bias, including various aspects of stakeholder participation. Initial findings from this study have refined our interview protocols and expanded our understanding of overlooked AI biases. These insights offer a deeper understanding of the influence exerted by non-end-user stakeholders on the AI development lifecycle, providing a multi-dimensional perspective on the nuances of AI bias and its emergence and mitigation

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