Metahuman systems = humans + machines that learn
Metahuman systems = humans + machines that learn
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DOI：
10.1177/0268396220915917
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发表时间：
2020-05
影响因子：
5.6
通讯作者：
K. Lyytinen;J. Nickerson;J. King
中科院分区：
文献类型：
--
作者：
K. Lyytinen;J. Nickerson;J. King
超人类系统是一种新的、涌现的社会技术系统，在这种系统中，学习的机器加入了人类的学习，并创造了原始的系统能力。超人类系统将改变我们对组织和工作方式的许多方面。他们将把信息系统研究推向新的方向，这可能涉及该领域的研究目标，方法和理论的修订。信息系统研究人员可以超越人类学习的能力和限制，将目光投向在规模、范围和速度上存在重大差异的混合人类/机器学习系统。我们回顾这些变化如何影响组织设计和目标。我们确定了四个组织层面的通用功能，组织超人类系统的关键：授权，监控，培养和反思。我们展示了每个功能如何为该领域提出新的研究问题。最后，我们指出，对超人类系统的更好理解将主要来自于边做边学，因为信息系统学者在多种环境中尝试新形式的混合学习，以生成新颖的、可推广的、有影响力的设计。这样的试验将导致对超人类系统的更好理解。这种大规模实验的需求将把许多学者从他们的舒适区推出来，因为它要求振兴行动研究计划，这些计划在自动化工作系统的曙光中为第一波社会技术研究提供了信息。
Metahuman systems are new, emergent, sociotechnical systems where machines that learn join human learning and create original systemic capabilities. Metahuman systems will change many facets of the way we think about organizations and work. They will push information systems research in new directions that may involve a revision of the field’s research goals, methods and theorizing. Information systems researchers can look beyond the capabilities and constraints of human learning toward hybrid human/machine learning systems that exhibit major differences in scale, scope and speed. We review how these changes influence organization design and goals. We identify four organizational level generic functions critical to organize metahuman systems properly: delegating, monitoring, cultivating, and reflecting. We show how each function raises new research questions for the field. We conclude by noting that improved understanding of metahuman systems will primarily come from learning-by-doing as information systems scholars try out new forms of hybrid learning in multiple settings to generate novel, generalizable, impactful designs. Such trials will result in improved understanding of metahuman systems. This need for large-scale experimentation will push many scholars out from their comfort zone, because it calls for the revitalization of action research programs that informed the first wave of socio-technical research at the dawn of automating work systems.