Mindful machines: exploring the transformative nexus of mindfulness and AI itinerary adoption
Uttam ChakrabortyPurpose
In this paper, the author has examined how mindfulness modifies the implementation of generative AI to design a travel itinerary. The study focuses on the context of the Uses and Gratifications Theory and Planning Theory and explicates the effect of mindfulness on cognitive evaluation of AI-generated outputs by perceived diagnosticity and perceived serendipity to the users.
Design/methodology/approach
A group of Indian Facebook users was taken as respondents, and a cross-sectional survey was conducted on 985 users who intended to plan their trip through the assistance of ChatGPT.
Findings
Mindfulness has a considerable impact on adoption either directly or indirectly via perceived diagnosticity. Even though mindfulness has positive impact on perceived serendipity, it is not significantly related.
Research limitations/implications
The study describes the concept of mindfulness as a mental process that influences the acceptance of technology and perceived diagnosticity as a significant process of elucidation. The framework should be validated under other conditions and such variables as trust and perceived risk should be implemented in subsequent studies.
Practical implications
The findings suggest that explainability, clarity and reflective interaction ought to be the main concern of AI systems to make users adopt and be satisfied more.
Social implications
The paper emphasizes the need to be mindful when interacting with AI to limit over reliance and enable responsible and value driven interaction in daily decision making.
Originality/value
This paper synthesizes Uses and Gratifications Theory and Planning Theory in a cognitive perspective of mindfulness, which provides a procedural account of adoption of AI and differentiates between instrumental and experiential processes of evaluation.