User Perceptions of Algorithmic Decisions in the Personalized AI System:Perceptual Evaluation of Fairness, Accountability, Transparency, and Explainability

ABSTRACT

With the growing presence of algorithms and their far-reaching effects, artificial intelligence (AI) will be mainstream trends any time soon. Despite this surging popularity, little is known about the processes through which people perceive and make a sense of trust through algorithmic characteristics in a personalized algorithm system. This study examines the extent to which trust can be linked to how perceptions of automated personalization by AI and the processes of such perceptions influence user heuristic and systematic processes. It examines how fair, accountable, transparent, and interpretable people perceive the use of algorithmic recommendations by digital platforms. When users perceive that the algorithm is fairer, more accountable, transparent, and explainable, they see it as more trustworthy and useful. This demonstrates that trust is of particular value to users and further implies the heuristic roles of algorithmic characteristics in terms of their underlying links to trust and subsequent attitudes toward algorithmic decisions. The processes offer a useful perspective on the conceptualization of AI experience and interaction. User cognitive processes identified provide solid foundations for algorithm design and development and a stronger basis for the design of sensemaking AI services.

Acknowledgment

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2017S1A5A2A02067973). Dr. Shin appreciates the generous support from the NSF Excellent Paper Support Program (2017–2018).

Disclosure Statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Donghee Shin

Donghee Shin(Ph.D./M. Phil. Syracuse University) is a professor at College ofCommunication and Media Sciences at Zayed University. His research interests include digital journalism, human-computerinteraction, and algorithmic media. His recent research in computer/algorithm as media addresses: embodied cognition, the subjectivevalue of information, interaction and interactivity.