Purpose

Artificial intelligence (AI) applications pose a potential threat to users' data security and privacy due to their high data-dependence nature. This paper aims to investigate an understudied issue in the literature, namely, how users perceive the threat of and decide to use a threatening AI application. In particular, it examines the influencing factors and the mechanisms that affect an individual’s behavioral intention to use facial recognition, a threatening AI.

Design/methodology/approach

The authors develop a research model with trust as the key mediating variable by integrating technology threat avoidance theory, the theory of planned behavior and contextual factors related to facial recognition. Then, it is tested through a sequential mixed-methods investigation, including a qualitative study (for model development) of online comments from various platforms and a quantitative study (for model validation) using field survey data.

Findings

Perceived threat (triggered by perceived susceptibility and severity) and perceived avoidability (promoted by perceived effectiveness, perceived cost and self-efficacy) have negative and positive relationships, respectively, with an individual’s attitude toward facial recognition applications; these relationships are partially mediated by trust. In addition, perceived avoidability is positively related to perceived behavioral control, which along with attitude and subjective norm is positively related to individuals' intentions to use facial recognition applications.

Originality/value

This paper is among the first to examine the factors that affect the acceptance of threatening AI applications and how. The research findings extend the current literature by providing rich and novel insights into the important roles of perceived threat, perceived avoidability, and trust in affecting an individual’s attitude and intention regarding using threatening AI applications.

中文翻译：

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对影响面部识别作为威胁人工智能应用的因素进行混合方法调查

目的

人工智能（AI）应用由于其高度的数据依赖性，对用户的数据安全和隐私构成潜在威胁。本文旨在调查文献中一个未充分研究的问题，即用户如何感知威胁人工智能应用程序的威胁并决定使用威胁性人工智能应用程序。特别是，它研究了影响个人使用面部识别（一种具有威胁性的人工智能）的行为意图的影响因素和机制。

设计/方法论/途径

作者通过整合技术威胁规避理论、计划行为理论和面部识别相关的情境因素，开发了一个以信任为关键中介变量的研究模型。然后，通过顺序混合方法调查进行测试，包括对各个平台的在线评论进行定性研究（用于模型开发）和使用现场调查数据进行定量研究（用于模型验证）。

发现

感知威胁（由感知敏感性和严重性触发）和感知可避免性（由感知有效性、感知成本和自我效能促进）分别与个人对面部识别应用的态度存在负向和正向关系；这些关系部分是通过信任来调节的。此外，感知可避免性与感知行为控制正相关，行为控制与态度和主观规范与个人使用面部识别应用程序的意图正相关。

原创性/价值

本文是首批研究影响威胁性人工智能应用接受度的因素及其影响方式的论文之一。研究结果扩展了当前的文献，对感知威胁、感知可避免性和信任在影响个人使用威胁性人工智能应用程序的态度和意图方面的重要作用提供了丰富而新颖的见解。