Increasing number of AI-enhanced approaches provide helpful “know-how” for reproducing and imitating skills and finally substituting human jobs with algorithms and intelligent machines. However, complementarity of human and machine, especially in hybrid man-machine settings is still not sufficiently explored. The main objective of this paper is to establish a twofold qualitative and quantitative methodology for optimal selection of a competent jobholder(s) to perform a certain task by semantic modeling and analysis of jobholder (human and machine) profiles corresponding to the task characteristics and learning requirements including knowledge, skills and competences (KSCs). The proposed knowledge-based approach comprises semantic modeling and quantitative methods focusing on measuring and correlating the level of human competences and machine autonomy, and identifying the extent of human–machine complementarity in performing an assigned task. The Vector of Competence and Autonomy (VCA) is built for identifying the extent of human–machine collaboration. The quantitative analysis involves several human factors in association to various combinations of technological components of Digital Assistance Systems with different automation degrees, under certain aspects of complexity of products and workplaces. Applying a set of rules and considering jobholder profiles, VCA values are interpreted and the current state of complementarity is inferred. Furthermore, feasible radical or incremental managerial transition pathways are identified as an initial step to reach the optimal (desired) level of human–machine collaboration in the example of TU Wien Pilot Factory Industry 4.0.

越来越多的AI增强方法为复制和模仿技能提供了有用的“诀窍”，并最终用算法和智能机器替代了人类的工作。然而，人与机器的互补性，特别是在混合人机环境中，仍然没有得到充分的探索。本文的主要目的是通过语义建模和分析与任务特征和学习相对应的工作人员（人和机器）配置文件的语义，建立一种双重定性和定量方法，以最佳地选择胜任的工作人员来执行某项任务要求包括知识，技能和能力（KSC）。所提出的基于知识的方法包括语义建模和定量方法，这些方法侧重于测量和关联人类能力和机器自主性的水平，并确定人机互补性在执行分配任务中的程度。能力和自主权向量（VCA）用于识别人机协作的程度。在产品和工作场所复杂性的某些方面，定量分析涉及几个人为因素，这些因素与具有不同自动化程度的数字化辅助系统的技术组件的各种组合相关。应用一套规则并考虑工作人员的个人资料，即可解释VCA值并推断出当前的互补状态。此外，