Across a multitude of work environments, expert knowledge is imperative for humans to conduct tasks with high performance and ensure business success. These humans possess task-specific expert knowledge (TSEK) and hence, represent subject matter experts (SMEs). However, not only demographic changes but also personnel downsizing strategies lead and will continue to lead to departures of SMEs within organizations, which constitutes the challenge of how to retain that expert knowledge and train novices to keep the competitive advantage elicited by that expert knowledge. SMEs training novices is time- and cost-intensive, which intensifies the need for alternatives. Human-AI collaboration (HAIC) poses a way out of this dilemma, facilitating alternatives to preserve expert knowledge and teach it to novices for tasks conducted by SMEs beforehand. In this workshop paper, we (1) propose a framework on how HAIC can be utilized to train novices on particular tasks, (2) illustrate the role of explicit and tacit knowledge in this training process via HAIC, and (3) outline a preliminary experiment design to assess the ability of AI systems in HAIC to act as a trainer to transfer TSEK to novices who do not possess prior TSEK.
翻译:在各种工作环境中,专家知识是人类执行高绩效任务和确保商业成功的必要条件,这些人类拥有具体任务的专家知识(TSEK),因此代表了专题专家(SME),然而,不仅人口变化,人员缩编战略也导致并将继续导致中小企业在组织内部的离开,这构成了如何保留专家知识和培训新手以保持专家知识所激发的竞争优势的挑战。中小企业培训新手是时间和成本密集型的,这增加了对替代技术的需要。人类-AI合作(HAIIC)是摆脱这一困境的一个途径,为保存专家知识的替代办法提供便利,并教它如何为中小企业执行的任务提供新知识。在本讲习班文件中,我们(1) 提议一个框架,说明如何利用HAIC培训新手就特定任务进行培训,(2) 说明通过HACC明确和隐含的知识在培训过程中的作用,(3) 概述初步试验设计,以评估AI系统在HAIIC中是否有能力作为培训员,向没有TSEKEK公司以前拥有的新手。