Mobile apps utilize the features of a mobile device to offer an ever-growing range of functionalities. These apps access our personal data, utilizing both the sensors on the device, and big data from several sources. Nowadays, Artificial Intelligence (AI) is enhancing the ability to utilize more data, and gain deeper insight. This increase in access and utilization of personal information offers benefits, but also challenges to trust. The reason we are re-evaluating trust in this scenario, is because we need to re-calibrate for the increasing role of AI.
This research explores the role of trust, from the consumer’s perspective, when purchasing mobile apps with enhanced AI. Models of trust from e-commerce are adapted to this specific context. The model developed was tested, and the results support it.
Figure 1. Consumer trust and privacy concerns in mobile apps with enhanced AI
The intention to use the mobile app is impacted by (1) propensity to trust, (2) institution-based trust, (3) trust in the mobile app, and (4) the perceived sensitivity of personal information, are found to impact
The first three of those four, are broken down further into their constituent parts. (1) Propensity to trust is based on a person’s (1a) trusting stance in general, and (1b) their general faith in technology. (2) Institution-based trust is strengthened firstly by (2a) structural assurance and (2b) situational normality. Structural assurance of the internet includes guarantees, regulation, promises and related laws. The users evaluation of situational normality can be formed by app reviews. Out of the whole model the institution based factors are the weakest.
Trust in the mobile app (3) is more complex, it is based on five variables. These are (3a) trust in vendor, (3b) trust in app functionality, (3c) trust in genuineness of app, (3d) how human the technology appears to be, and (3e) trust in personal data use.
Those are the main findings of this research. The model is helpful because it can guide the stakeholders involved in mobile apps in how to build trust. By using the model they can identify what they need to communicate better, and what they need to change in the apps, or somewhere else in the ecosystem.
Reference
Zarifis A. & Fu S. (2023) ‘Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence’, Digital, vol.3, no.4, pp.286-299. https://doi.org/10.3390/digital3040018 (open access)
#trust #information privacy #artificial intelligence #mobile commerce #mobile apps #big data