Development and Validation of the Attitudes Toward Algorithms Scale: A Universal Scale to Measure Individuals Attitudes Toward Algorithmic Decision-Making

Algorithmic decision-making (ADM) has become increasingly important across various fields, ranging from personal entertainment to criminal justice. While existing research has predominantly explored evaluative outcomes like individuals’ perceptions and interactions with these systems, there remains a significant gap in understanding the underlying mechanisms that lead to these outcomes. Building on traditional behavioral intention theories, we identified attitudes toward algorithms and ADM as crucial determinants. In response to the lack of an appropriate measure for this construct, we developed and validated the Attitudes Toward Algorithmic Decision-Making Scale (ATAS), a novel instrument designed to assess core beliefs that drive attitude formation toward ADM across three studies. Using this scale, we show that laypeople’s attitudes toward ADM are driven by beliefs about the objectivity, ethicality, and performance of such systems and are characterized by ambivalence. We further discuss potential applications of the scale for future research and how well-established technology acceptance frameworks can benefit from it.