Machine heuristic: concept explication and development of a measurement scale
本文系统阐释了“机器启发式”概念，即人们认为机器表现更优的心理捷径，并通过三项研究（总样本1129人）开发并验证了一个包含七个题项的量表，用于测量个体对机器的信任倾向。
Abstract Human assumption of superior performance by machines has a long history, resulting in the concept of “machine heuristic” (MH), which is a mental shortcut that individuals apply to automated systems. This article provides a formal explication of this concept and develops a new scale based on three studies (Combined N = 1129). Measurement items were derived from the explication and an open-ended survey (Study 1, N = 270). These were then administered in a closed-ended survey (Study 2, N = 448) to identify their dimensionality through exploratory factor analysis (EFA). Lastly, we conducted another survey (Study 3, N = 411) to verify the factor structure obtained in Study 2 by employing confirmatory factor analysis (CFA). Analyses resulted in a validated scale of seven items that reflect the level of MH in individuals and identified six sets of descriptive labels for machines (expert, efficient, rigid, superfluous, fair, and complex) that serve as formative indicators of MH. Theoretical and practical implications are discussed.