The Role of Perceived Fairness of Algorithms on Shaping Psychological Well-Being: Propositions and Future Research Agenda

With the growth of technology, there is a growing demand for decision-making through algorithmic platforms. However, such decisions would create negative individual outcomes such as perceived unfairness and lower psychological well-being. The purpose of this study is to fill an existing research gap by proposing a new model to examine the impact of perceived fairness of algorithms on psychological well-being, with the moderating role of technology transparency. The current study was conducted by reviewing 26 articles related to psychological well-being, perceived fairness of algorithms and technology transparency. Based on the review, a conceptual model is proposed with two propositions that future researchers can empirically validate. Accordingly, this study provides two theoretical implications. Firstly, it reviews the existing literature on algorithmic decision-making and psychological well-being. Secondly, it contributes to the Theory of Cognitive Appraisal by defining the ways of deriving perceptions among individuals. The paper shows directions of future research and emphasises the need for empirical testing within the given model. The analysis helps to shed light on the ethical adoption of artificial intelligence in business practices.