This study examines the impact of artificial intelligence (AI) on the ways in which users process and respond to misinformation in generative artificial intelligence (GenAI) contexts. Drawing on the heuristic–systematic model and the concept of diagnosticity, our approach examines a cognitive model for processing misinformation in GenAI. The study’s findings revealed that users with a high-heuristic processing mechanism, which affects positive diagnostic perception, were more likely to proactively discern misinformation than users with low-heuristic processing and low-perceived diagnosticity. When exposed to misinformation from GenAI, users’ perceived diagnosticity of misinformation can be accurately predicted by the ways in which they perform heuristic systematic evaluations. With this focus on misinformation processing, this study provides theoretical insights and relevant recommendations for firms to be more resilient in protecting users from the detrimental impacts of misinformation.

中文翻译：

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生成人工智能的错误信息对用户信息处理的影响：人们如何理解生成人工智能的错误信息

本研究探讨了人工智能 (AI) 对用户在生成人工智能 (GenAI) 环境中处理和响应错误信息的方式的影响。我们的方法利用启发式系统模型和诊断概念，研究了处理 GenAI 中错误信息的认知模型。研究结果表明，具有高启发式处理机制的用户会影响积极的诊断感知，比具有低启发式处理和低感知诊断性的用户更有可能主动辨别错误信息。当接触到来自 GenAI 的错误信息时，用户对错误信息的感知诊断可以通过他们执行启发式系统评估的方式来准确预测。通过重点关注错误信息处理，本研究为企业提供了理论见解和相关建议，使企业能够更有弹性地保护用户免受错误信息的有害影响。