让AI客服更透明，用可解释性赢得用户信任
Enhancing transparency in AI-powered customer engagement
- 提出可解释AI模型，让决策过程对用户和管理者都清晰
- 调研显示多数消费者不了解自己与AI互动，担忧算法偏见
- 适合关注AI伦理、客户信任的企业及政策制定者
本文针对AI客户互动中消费者信任缺失的问题，强调透明度与问责制的重要性。尽管AI有望革新业务流程并提升体验，但公众普遍担忧信息失真及算法黑箱问题。调查显示，多数消费者对其与AI的互动缺乏认知，且担心算法存在偏见与不公平。论文主张开发可解释的AI模型，使其决策过程对用户和管理者均清晰可懂，以减少潜在偏见，保障伦理使用。同时强调企业应超越合规要求，建立问责文化，制定清晰数据政策，并积极与利益相关方沟通。通过全面推动透明与可解释性，企业可增强对AI的信任，弥合技术创新与用户接受之间的鸿沟，实现更伦理、高效的AI客户互动。
原文摘要 · Abstract (English)
This paper addresses the critical challenge of building consumer trust in AI-powered customer engagement by emphasising the necessity for transparency and accountability. Despite the potential of AI to revolutionise business operations and enhance customer experiences, widespread concerns about misinformation and the opacity of AI decision-making processes hinder trust. Surveys highlight a significant lack of awareness among consumers regarding their interactions with AI, alongside apprehensions about bias and fairness in AI algorithms. The paper advocates for the development of explainable AI models that are transparent and understandable to both consumers and organisational leaders, thereby mitigating potential biases and ensuring ethical use. It underscores the importance of organisational commitment to transparency practices beyond mere regulatory compliance, including fostering a culture of accountability, prioritising clear data policies and maintaining active engagement with stakeholders. By adopting a holistic approach to transparency and explainability, businesses can cultivate trust in AI technologies, bridging the gap between technological innovation and consumer acceptance, and paving the way for more ethical and effective AI-powered customer engagements. KEYWORDS: artificial intelligence (AI), transparency
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