Outsourcing Attention Management to Human and Artificial Agents in Organizations

随着人工智能能力的进步，组织面临着将任务和实践决策外包给机器的新机会。将人工智能（AI）助理引入工作场所及其对组织绩效的影响引起了人们的兴奋和关注。虽然一些高管称赞人工智能并称赞其作为组织问题解决方案的价值，但其他员工担心人工智能将威胁和取代他们的工作。本研究避免了这样的概括，重点是如何使用人工智能代理调度形状管理人员如何引导他们的注意力，这反过来又塑造了组织绩效和经济。理解这些过程很重要，因为将注意力管理委托给人工智能将产生广泛的后果，从影响创新到通过影响组织获得的知识来实现或抑制组织学习。这项研究的结果将塑造我们对工作技术的理解，如何培训组织成员与人工智能合作，以及如何减轻使用人工智能指导我们决策的意外后果。该项目调查了有关时间和注意力的决定如何外包给人工智能和人类代理，并利用人种学方法从多个领域收集丰富的访谈和观察数据。网站.在这样做的过程中，这项研究有助于三个主要领域的知识对话。首先，这项研究的发现将有助于修改现有的理论工作，使用注意力为基础的公司的观点，以显示其他人如何塑造领导者的注意力。其次，这些发现将发展关于时间和注意力之间关系的新理论。虽然现有的经验证据表明，有关时间的决定影响注意力分配，拟议的比较研究将提供更多的了解的机制，通过时间的决定来承担注意力。第三，这项研究有助于更大的人工智能领域以及不断变化的工作和组织性质。它的研究结果将阐明开发人员在设计人工智能技术时所做的选择，并确定组织在决定将其应用到工作中时应考虑的这些工具的属性。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

As the capabilities of artificial intelligence advance, organizations are faced with new opportunities to outsource tasks and decisions about their practices to machines. The introduction of artificially intelligent (AI) assistants to workplaces and their effect on organizational performance has garnered both excitement and concern. While some executives praise AI and laud its value as a solution for organizational problems, other workers fear that artificial intelligence will threaten and displace their work. This study avoids such generalizations by focusing on how the use of artificially intelligent agents in scheduling shapes how managers direct their attention, which in turn shapes organizational performance and the economy at large. Understanding these processes is important because of the broad consequences that entrusting attention management to AI will have, from influencing innovation to enabling or inhibiting organizational learning by affecting the knowledge to which organizations have access. The findings of the study will shape our understanding of what work technology is equipped to do, how organizational members should be trained to work with AI, and how to mitigate unintended consequences of using AI to guide our decision making.This project investigates how decisions about time and attention are outsourced to both AI and human agents and utilizes ethnographic methods to gather rich interview and observational data from several field sites. In doing so, the study contributes to intellectual conversations in three main areas. First, the findings of this study will help revise existing theoretical work using an attention-based view of the firm to show how other people shape leaders' attention. Second, the findings will develop new theory about the relationship between time and attention. Though existing empirical evidence suggests that decisions about time affect attention allocation, the proposed comparative study will provide greater understanding of the mechanisms through which decisions about time come to bear on attention. Third, the study contributes to the larger area of artificial intelligence and the changing nature of work and organizing. Its findings will illuminate the choices that developers make in designing artificially intelligent technologies and identify the attributes of these tools that organizations should consider when deciding to implement them into their work.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.