摘要
鉴于组织行为学及其所属的工商管理学科一直受到"理论-实践"脱节的批评,管理学者呼吁更多立足真实组织情境、兼具科学严谨性与现实关联性的研究.在人工智能时代,随着组织要素与组织逻辑在重大技术变革中发生显著变化,开展基于现象的人机协同研究成为提升本学科领域学术创新性与现实影响力的关键方向.本文总结了目前人与AI研究的现状,评述不同学科在"反应""互动"与"协同"三个主题上的表现,重点梳理了实地场景下的人机协同研究进展,并以一篇发表在《管理学会学报》(Academy of Management Journal)上的民族志研究为例,分析如何从现象出发进行理论构建.在厘清现状的基础上,本文回溯了人机交互研究中的经典基础理论,以启发研究者以更加深入现场、贴近本质的视角思考当代的人机协同研究.最后,本文展望了若干基于人机协同实践的未来研究方向.
Abstract
The persistent disconnection between management theories and practices has been a longstanding concern in organizational research.This disconnection becomes particularly problematic in the era of Artificial Intelligence(AI),where technological advancements are fundamentally reshaping organizational elements and logic.Conducting phenomenon-based research on human-AI collaboration has emerged as a crucial pathway for advancing theoretical development and real-world impact.This paper begins by reviewing the current state of human-AI research,identifying three emerging themes central to understanding human-AI dynamics:human reaction to AI,human-AI interaction,and human-AI collaboration.The"human reaction to AI"theme predominantly examines individual responses to AI(and AI-generated information)during episodic interactions,characterized by vignette-based scenarios where AI does not directly impact work-related outcomes.This body of literature can be categorized into two main streams:research on AI/algorithmic decision accuracy,focusing on human assessment of computational reliability and precision;and research on AI decision legitimacy,focusing on human acceptance of moral judgment.While these studies provide valuable insights into human trust formation and AI perception,they often lack ecological validity.The"human-AI interaction"theme investigates how AI directly influences work-related outcomes,also during episodic interactions.This body of research often adopts controlled laboratory settings,exemplified by studies on ChatGPT's impact on professional writing output and human reasoning capabilities.These studies highlight the growing relevance of AI's immediate impact on both individual and organizational performance,emphasizing the necessity of understanding how AI interacts with human work in real-time.The"human-AI collaboration"theme addresses the evolving nature of human-AI coexistence in workplaces.AI has increasingly become embedded in work processes,creating complex,real-world challenges about how humans and AI collaborate over time.This stream of research examines dynamic,longitudinal interactions where humans and AI systems reciprocally influence outcomes across multiple dimensions,including work design,learning strategies,and long-term performance.These studies,grounded in specific organizational contexts,identify theoretical mechanisms and intervention strategies through fieldwork.To demonstrate how phenomenon-driven research advances theoretical development,this paper analyzes an exemplary ethnographic study from the Academy of Management Journal.This study reveals how researchers can construct robust theory by systematically investigating the human-machine interface as it unfolds within authentic organizational settings.It also illuminates how richly contextualized insights from immersive fieldwork can effectively bridge theoretical development with practical implications.After reviewing existing studies on human and AI,we further revisit seminal theories in human-computer interaction literature.These classical frameworks advocate for a system-level perspective that considers technological integration within broader institutional structures and organizational dynamics.By tracing the evolution and enduring relevance of these foundational theories,we call for a theoretical approach that recognizes the deeply embedded and interconnected nature of human-AI collaboration within complex organizational ecosystems.The goal is to inspire contemporary researchers to embrace more holistic,context-sensitive approaches when investigating emerging human-AI phenomena.Informed by the latest studies as well as grounded in cutting-edge integration of technology and organizational settings,we here propose several promising research avenues that shed light on both theoretical advancements and managerial applications.First,we encourage exploring how employee experience and collaboration with AI jointly interact,focusing on how different experience levels impact collaboration outcomes.We should further unravel how to enable employees to maximize AI's potential as well as alleviate the negative side.Second,we suggest that future researches may investigate how AI feedback,trust,and job security concerns affect performance in complex tasks,and how adaptation to and dependency on AI may impact employees'skill development in the longer term.Third,we encourage researchers to examine how distinct collaboration modes between AI and humans in different contexts could optimize performance.Last,researchers can delve into users'responses to AI suggestions and explore mechanisms to balance trust in AI and independent judgments in terms of decision-making.The era of AI requires management scholars to bridge the gap between theory and practices by updating,transforming and transcending existing research paradigms.By uncovering deeper insights into the intricate dynamics of human-AI interaction,we shall contribute to richer and more comprehensive theoretical layers and potentially great theoretical breakthroughs.
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