Equality, Diversity, and Inclusion in AI-Driven Healthcare Chatbots: Addressing Challenges and Shaping Strategies.

Aycan Kucukkaya, Emine Aktas Bajalan, Philip Moons, Polat Goktas
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Abstract

Artificial intelligence (AI)-driven chatbots hold promise for improving patient care and healthcare efficiency, but integrating Equality, Diversity, and Inclusion (EDI) remains challenging. This discussion paper explores the potential for EDI-focused chatbots, emphasizing the need for ongoing assessment, diverse datasets, and collaboration among healthcare providers, technologists, and policymakers. While acknowledging current limitations such as algorithmic bias, the paper also emphasizes the potential of AI to support and extend human decision-making, particularly through real-time analytics and scalable patient support. Embedding EDI principles helps reduce bias, enhance fairness, and requires cross-disciplinary collaboration to ensure AI delivers equitable, inclusive healthcare for all.

在人工智能驱动的医疗聊天机器人中的平等、多样性和包容性:应对挑战和塑造战略。
人工智能(AI)驱动的聊天机器人有望改善患者护理和医疗效率,但整合平等、多样性和包容性(EDI)仍然具有挑战性。本文探讨了以电子数据中心为中心的聊天机器人的潜力,强调了对持续评估、多样化数据集以及医疗保健提供者、技术人员和政策制定者之间协作的需求。在承认算法偏差等当前局限性的同时,该论文还强调了人工智能支持和扩展人类决策的潜力,特别是通过实时分析和可扩展的患者支持。嵌入EDI原则有助于减少偏见,增强公平性,并需要跨学科协作,以确保人工智能为所有人提供公平、包容的医疗保健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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