创造性人格常被视为人类稳定且独特的禀赋。但当人工智能(artificial intelligence, 以下简称AI)技术侵入创造性工作领域, AI具备的“数字权威”导致人类对AI的自动化偏差, 人类由创造力主导角色滑向依附角色只在一线之间, 并通过影响个体的创新自我效能感和创新角色认同, 最终威胁到个体的创造性人格。本研究拟基于“我能创新”和“我应创新”两条作用路径, 厘清在创造性任务中使用AI及产生自动化偏差对个体创造性人格的影响, 并探讨个体如何通过自我领导守住创新主体地位, 以期深化对AI背景下创造性人格的研究。

<p id="p00005">Creative personality is often considered stable and unique. However, when artificial intelligence (AI) participates in creative tasks, the “digital authority” role of AI may cause automation bias in human use of AI, making it difficult for humans to maintain a leading role in creativity, even with a creative personality. Yet, significant research gaps persist. First, the organizational personality literature is dominated by the classic dispositional view that personality traits are stable. Second, despite calls to promote research on the impact of AI on personality traits, the field lacks theoretical and empirical research. Our knowledge regarding the effects of AI on human creative personality and its underlying mechanisms is notably limited.</p> <p id="p00010">Considering the above calls and limitations, this study adopts a developmental perspective on personality to clarify the impact of using AI in creative work on creative personality. Specifically, it encompasses three distinct sub-studies. Study 1 reveals the mechanisms by which the use of AI mediates creative personality. By drawing on the concepts of "I can" and "I should", we examine the negative effects of using AI and automation bias on creative self-efficacy and creative role identity. Study 2 explores the long-term effects of using AI and automation bias on individual creative personality. Furthermore, study 3 investigates the effectiveness of self-leadership, focusing on how individuals defend their innovative subjectivity.</p> <p id="p00015">This study makes three primary theoretical contributions. First, this study emphasizes the long-term effects of AI on creative personality. Although the potential influence of using AI on creativity has emerged as a prominent research topic, much of the focus has been on the impact of AI on the creative process, creative outcomes, and creative environment. Studies have shown that using AI can both foster and hinder creativity. Building on this, our research highlights a significant, yet potentially overlooked, drawback of using AI. It contributes to a more nuanced and complete picture of how emerging technologies can shape an individual's creative personality. This study posits that using AI may engender an individual's automation bias, which could disrupt the positive pathways of "I can create” and "I should create", ultimately diminishing individual creative personality. By doing so, we extend the literature on the negative effects of AI on creative personality and remind human beings of their unique roles as primary agents in creative work.</p> <p id="p00020">Second, this study introduces self-leadership as an effective strategy for reaffirming humans as the central agents of creativity. Prevailing research often positions AI at the core of creative work, inadvertently obscuring the subjectivity of human beings. This study, however, asserts that although AI has a certain degree of autonomy, human beings remain the essential protagonists in creative work. To this end, this study proposes a strategy of internal control that reinforces the subject position of human creativity, fundamentally shifting from external organizational supervision to self-regulation. By embracing self-leadership, individuals can counteract the tendencies towards "cognitive saving" and social loafing, thereby preventing the degradation of creative personality that arises from using AI. In this way, this study reveals a pathway to counteract the negative effects of AI on creative personality, thereby optimizing the benefits of AI applications on creativity.</p> <p id="p00025">Third, this study builds an overall theoretical model that encapsulates the impact of using AI on creative personality, the underlying mechanisms, and potential countermeasures. Prior research has predominantly examined how individuals with different personality traits respond to AI and the compatibility between personality traits and AI. However, there is still limited understanding about how AI affects individual personality traits as AI becomes more integrated into creative work. AI, with its exceptional capabilities, dynamism, and autonomy, stands out as a unique factor affecting creativity. Considering that particularity, there is an urgent need for a thorough and detailed theoretical framework. To this end, the theoretical model of this study encompasses the long-term effects of using AI on creative personality, elucidates the underlying mechanisms, and proposes effective coping strategies.</p> <p id="p00030">In summary, our theoretical framework aims to provide scholars with a more comprehensive and profound understanding of how using AI influences individual creative personality, while also offering guidance on how to prevent the erosion of human creativity and avoid becoming subservient to AI.</p>

This paper contains a description of a scale to measure cognitive flexibility. In Study 1, 247 participants completed the Cognitive Flexibility Scale, the Communication Flexibility Scale, and the Rigidity of Attitudes Regarding Personal Habits Scale. In Study 2, 275 participants completed the Cognitive Flexibility Scale, the Interaction Involvement Scale, the Self-monitoring Scale, and the Unwillingness to Communicate Scale. Analysis showed the Cognitive Flexibility Scale to be internally reliable and supported its construct and concurrent validity.

AI感知是指员工对AI运用影响其工作态度、行为、福祉和工作环境的感知。第四次工业革命已经到来, AI提升员工绩效的同时也带来了风险和不确定性, 对员工产生巨大影响。当前AI感知研究分散概念模糊, 阻碍了对AI运用如何影响员工心理和行为的理解。为探究AI运用对员工的具体影响及作用解释机制, 首先澄清了AI感知概念内涵; 其次, 揭示了AI感知影响效果; 第三, 基于资源视角、情绪视角、需求视角和环境视角阐释了AI感知的理论解释机制; 最后, 构建了AI感知的未来研究框架, 为将来相关研究提供理论借鉴, 为组织决策提供见解。

在&#x0201c;工具人&#x0201d; &#x0201c;打工人&#x0201d; &#x0201c;社畜&#x0201d;等流行语风靡职场的当下, 职场物化已然成为了一个亟需探讨的话题。而随着人工智能尤其是机器人在职场中的使用日益增多, 机器人产生的职场效应也值得关注。因此, 本项目旨在探讨在人工智能飞速发展的当今社会, 机器人渗入职场是否会产生或加重职场物化现象。基于群际威胁理论和补偿控制理论, 我们假设职场中的机器人员工凸显会增加职场物化。项目采用实验、大数据与问卷调查相结合的方式, 首先考察机器人员工的凸显是否会增加职场物化, 初步验证影响效应; 然后探讨机器人影响职场物化的中介机制, 试图发现感知威胁和控制补偿的链式中介效应; 最后从个人、机器人和环境三方面分别考察其对机器人影响职场物化的调节作用, 并从组织文化的角度探讨对职场物化的干预策略。对本项目的探索有助于结合人工智能尤其是机器人发展背景, 前瞻性地了解人工智能在职场中可能的负面影响, 并提出有效的解决方案。

<p id="p00005">With buzzwords such as &#x0201c;tool man&#x0201d;, &#x0201c;laborer&#x0201d; and &#x0201c;corporate slave&#x0201d; sweeping the workplace, workplace objectification has become an urgent topic to be discussed. With the increasing use of artificial intelligence, especially robots in the workplace, the workplace effects produced by robots are also worth paying attention to. Therefore, the present research aims to explore whether the penetration of robots into the workplace will produce or aggravate the phenomenon of workplace objectification.</p> <p id="p00010">Based on the intergroup threat theory and previous related studies, the present research assumes that the salience of robot workers in the workplace will pose both realistic threats and identity threats to people, and the perception of these threats will reduce people's sense of control. According to the compensatory control theory, the decrease of perceived control will cause people to have a strong motivation of restoring control. And workplace objectification, the 4th strategy proposed by compensatory control theory (i.e., affirming nonspecific structure, or seeking out and preferring simple, clear, and consistent interpretations of the social and physical environments), can be used to restore the sense of control. Therefore, this paper hypothesizes that the salience of robot workers in the workplace will increase the workplace objectification, because robot salience will increase people's perceived threats of robots, which will lead to control compensation, which will eventually lead to more severe workplace objectification. In addition, the other three strategies proposed by compensatory control theory, namely, bolstering personal agency, affiliating with external systems perceived to be acting on the self's behalf, and affirming specific structure (i.e., clear contingencies between actions and outcomes within the context of reduced control), can moderate the effect of robot salience on workplace objectification. Other ways of affirming non-specific structure than workplace objectification can also moderate the effect of robot salience on workplace objectification.</p> <p id="p00015">Based on theories of social psychology and combined with the realistic background of workplace objectification, this paper attempts to use diverse methods to test the above hypothesis. Specifically, experiments, big data, and questionnaire surveys will be adopted to explore the potential mechanism and boundary conditions of the impact of robot salience on workplace objectification. The present research consists of five studies. Study 1 verifies the existence of the phenomenon that robot salience has an effect on workplace objectification. Study 2 explores the chain mediating effects of perceived robot threat and control compensation. Study 3 examines the moderating effect of personal factors, including bolstering personal agency, affiliating with external systems perceived to be acting on the self's behalf, affirming specific structure, and other ways of affirming non-specific structure than workplace objectification. Study 4 examines the moderating effect of robot factors, including anthropomorphism and two dimensions of mind perception. Study 5 examines the moderating effect of environmental factors, including different organizational cultures and ethical organizational cultures, and explores the intervention strategies for workplace objectification.</p> <p id="p00020">The present research helps to prospectively understand the possible negative effects of artificial intelligence in the workplace and put forward effective solutions.</p>

智能化浪潮为我国由制造大国迈向制造强国以及制造业智能转型注入新的源动力, 但与此同时制造业知识型员工也面临着劳动过程被人工智能重塑的挑战。本文在人工智能背景下创新性地提出技术空心化这一动态性概念来反映人工智能技术的发展和应用对制造业知识型员工劳动过程的影响。本文有三个研究目的: 第一, 基于意义构建理论时间动态视角探讨技术空心化的内涵、维度结构以及其测量量表; 第二, 以“认知−行为”互动链为基础构建技术空心化的“执行技能空心化”和“概念技能空心化”两阶段过程模型, 并进一步探讨企业和员工层情境因素在其中的催化作用; 第三, 基于能力构建视角探讨技术空心化对知识型员工双元创新行为和可持续职业生涯发展的影响。研究结论不仅能丰富人工智能背景下技术空心化的理论研究, 还能在中国制造业智能转型之际为和谐稳定的劳动关系的建立、实现企业与员工的长期发展及共同繁荣提供实践启示。

<p id="p00005">The wave of intelligence has injected new impetus for China to transform from a manufacturing power to a manufacturing powerhouse and for the intelligent transformation of enterprises. However, at the same time, knowledge workers in the manufacturing industry face the challenge of reshaping the labor process with artificial intelligence. Previous studies mainly used labor process theory to analyze the impact of technological progress on the labor of “blue-collar workers” in manufacturing, while related research on knowledge workers in manufacturing is still in the conceptual discussion stage. Therefore, this study innovatively proposes the dynamic concept of technical hollowing out under the background of artificial intelligence to reflect the impact of the development and application of artificial intelligence technology on the labor process of knowledge workers in the manufacturing industry.</p> <p id="p00010">This study constructs a theoretical study on the technical hollowing out of knowledge workers from three perspectives of sensemaking: cognition, behavior, and ability. This study has three research purposes: First, to explore the definition and dimensional structure of technical hollowing out from the perspective of “cognition-behavior-ability” sensemaking, and intends to extract two dimensions: executive skill hollowing and conceptual skill hollowing, technical hollowing out measurement scale was developed based on; second, based on the “cognition-behavior” interaction chain, we construct a two-stage model of “executive skill hollowing out” and “conceptual skill hollowing out” for the technical hollowing out of knowledge workers, and further explore the catalytic role of situational factors at the enterprise and employee levels; third, based on the capability-building perspective, the impact of technical hollowing out on knowledge workers’ dual innovation behavior and sustainable career development is explored. We intend to use case study methods to explore the definition, dimensional structure, measurement scale, and generation process of technological hollowing out. In addition, we use empirical research methods to analyze the impact mechanism of technological hollowing out on the multi-dimensional development of employees. Based on the above conception, this study attempts to construct a relatively systematic and complete theoretical framework of technological hollowing out through three closely related and hierarchical parts.</p> <p id="p00015">This study takes knowledge workers in the manufacturing industry as the research object, expands the subject boundaries of existing AI in reshaping the labor process of workers, and grasps the research frontier of technological hollowing out of knowledge workers. The dynamic concept of technological hollowing out was innovatively proposed, and its dimensional structure and measurement scale were analyzed, deepening the dynamic research of technological hollowing out under the background of AI. At the same time, combining the sensemaking and labor process perspectives, the “double separation” model of employee skills and core science and technology is integrated based on the AI background, forming a theoretical model for the generation of technological hollowing out, which provides a new theoretical perspective for revealing the mechanism of AI’s reshaping of the labor process of knowledge workers. It makes up for the deficiency of labor process theory that focuses on the labor control of “blue-collar workers” from a static perspective. From the perspective of ability building in sensemaking, this study uses empirical analysis methods to reveal the impact path and boundary conditions of technical hollowing out on employees’ dual innovation behavior and sustainable career development by acting on their technological absorptive ability. It provides more evidence for a deeper understanding of the process of employees’ dual innovation behavior and sustainable career development. Also, it provides a new theoretical perspective for the cultivation and motivation of innovative and sustainable talents in the background of intelligent manufacturing. Moreover, the research conclusions can also provide practical inspiration for establishing harmonious and stable labor relations, as well as realizing long-term development and shared prosperity of enterprises and employees during the intelligent transformation of China’s manufacturing industry.</p>

The Achievement Motives Scale (AMS) is a well-established and frequently used scale to assess hope of success and fear of failure. In three studies with German-speaking samples (N = 3523, N = 132, N = 126), the authors developed a revised form of the AMS using confirmatory factor analysis. As found in previous research, the original 30-item set of the AMS did not provide an acceptable fit to a two-factor model. In contrast, a revised 10-item version (AMS-R) provided an adequate fit to the theoretically intended two-factor model. The adequate fit could be validated in cross-validation procedures. Furthermore, the revised scales provided adequate reliability, lower interscale correlations, and criterion-related validity with respect to typical criteria of achievement-related behavior.

智能化时代，人工智能技术在工作场所的应用给组织行为和传统人力资源管理带来诸多挑战。基于工作要求—资源模型，深入回答人工智能技术在工作场所应用对员工创新行为的“双刃剑”效应。采用情境实验法和两阶段问卷法开展两个独立研究，结果表明：一方面，人工智能技术应用作为工作要求，可通过增强工作不安全感的损耗路径负向影响员工创新行为；另一方面，人工智能技术应用作为工作资源，可通过增强工作自主性感知的增益路径激发员工创新行为。员工学习目标导向是开启上述不同影响效应的关键“钥匙”。具体来说，学习目标导向的增强会弱化人工智能技术应用的损耗路径，强化人工智能技术应用的增益路径。