“Human–AI Collaboration” and the Transformation of Labour Forms

The State Council’s *Opinions on Deeply Implementing the “AI+” Action* proposes “accelerating the formation of a new form of intelligent economy and intelligent society characterised by human–machine collaboration, cross-border integration, and co-creation and sharing.” The deep application of large-model technology is transforming artificial intelligence from a labour tool into a “collaborative subject,” reshaping the existential form and relational pattern of labour. This transformation not only promotes a “human–machine reconciliation” through technological progress, freeing workers from simple, repetitive labour and focusing them on creative, higher-order labour, but also facilitates the penetration of the logic of capital through high capital and knowledge requirements, giving rise to a series of intertwined systemic risks. Therefore, it is necessary to return to the “hidden places of production,” to expose the labour processes and production scenes obscured in the era of “human–AI collaboration,” and, on the basis of preventing and defusing risks, to promote the construction of labour relations characterised by human–AI collaborative coexistence and co-evolution.

国务院《关于深入实施“人工智能+”行动的意见》提出，“加快形成人机协同、跨界融合、共创分享的智能经济和智能社会新形态”。大模型技术的深度应用使人工智能从劳动工具向“协同主体”转变，重塑劳动的存在形态与关系模式。这一变革不仅以技术进步推动“人机和解”，使劳动者从简单性、重复性劳动中解放出来，聚焦创造性、高阶性劳动，而且以高资金、高知识要求促进资本逻辑的渗透，带来一系列相互交织的系统性风险。因此，需要重返“生产的隐秘之处”，揭露“人智协同”时代被遮蔽的劳动过程和生产场景，在防范化解风险的基础上推动人智协同共生、协同进化的劳动关系构建。

The collaboration of labour capacities and the new form of human–machine collaboration. The production application of intelligent large models, driven by exponential growth in computing power and an explosion of data, continuously pushes the “intelligent emergence” and performance optimisation of machines. Intelligent machines acquire increasingly powerful and diverse “labour capacities,” exhibiting entirely new characteristics of interactive subjectivity. The human–machine relationship in traditional production is shifting from a master–slave division-of-labour model of “human instruction–machine execution” to an equal collaborative model of “human leadership–intelligent assistance.” Intelligent machines are no longer purely passive tools of execution but become “partners” actively collaborating with human labour. This transformation is not a simple iteration of technical tools or collaborative models but a systemic reconstruction of the labour subject, value creation, and relations of production. As Marx pointed out, “the cooperative character of the labour process is now a technical necessity dictated by the very nature of the instruments of labour.” [1]1 Karl Marx, *Capital*, Volume 1, Chapter 13, Section 4.

劳动能力的协同与人机协作新形态。智能大模型的生产应用以算力的指数级增长和数据的爆炸不断推动机器的“智能涌现”和性能优化，智能机器获得了日益强大与多样的“劳动能力”，呈现出全新的交互主体性特征。传统生产中的人机关系由“人类指示—机器执行”的主从分工模式向“人类主导—智能辅助”的平等协作模式转变。智能机器不再是纯粹被动执行的工具，而成为人类劳动主动协同的“伙伴”。这一变革并非简单的技术工具或协作模式的迭代，而是对劳动主体、价值创造与生产关系的系统性重构。如马克思指出，“劳动过程的协作性质，现在成了由劳动资料本身的性质所决定的技术上的必要了”。

First, the labour form of human–AI collaboration continuously integrates the advantages of human and machine labour, opening up the “missing intermediate zone” that requires human–machine collaboration. Overall, intelligent machines are adept at processing and analysing data and performing repetitive tasks, while humans’ complex cognitive abilities are adept at handling complex and unpredictable situations and solving emergent problems. However, in the production chain of modern knowledge commodities, there remain a considerable number of processes that cannot be completed by humans or machines alone, or through a human–machine division of labour. It is necessary to continuously open up new fields of “human–AI collaboration” to restructure traditional production and service fields such as manufacturing, medical diagnosis, and financial services.

其一，人智协同的劳动形态不断融合人机劳动优势，开辟需要人机协作的“缺失中间地带”。总体来看，智能机器善于处理、分析数据并执行重复性任务，而人类复杂的认知能力则善于应对复杂的和不可预知的情境，处理突发问题。但在现代知识商品的生产链条中，依然存在相当多的工序无法通过单独的人或机器，或是人机分工来完成，需要不断开辟“人智协同”的新领域来重构生产制造、医疗诊断、金融服务等传统生产服务领域。

Second, the labour form of human–AI collaboration does not negate the subjective position of humans in labour; human living labour remains the sole source of value creation. In the production logic of generative artificial intelligence, although intelligent machines possess a certain degree of labour autonomy and can reorganise and promote the development of production, their essence remains “objectified knowledge power,” the materialisation and extension of human labour. They themselves do not generate new value; they merely achieve efficiency and value enhancement under human–AI collaboration by improving labour efficiency and expanding labour boundaries in the process of integrating into the social division of labour.

其二，人智协同的劳动形态并没有否定人在劳动中的主体性地位，人的活劳动依然是价值创造的唯一源泉。在生成式人工智能的生产逻辑中，虽说智能机器具有一定的劳动自主性，能够重组并推动生产的发展，但其本质依然是“对象化的知识力量”，是人类劳动的物化与延伸。其本身并不产生新价值，只是在融入社会分工过程中通过提升劳动效率、拓展劳动边界，实现人智协同下的效率与价值提升。

Third, the labour form of human–AI collaboration changes the production organisation logic of the industrial era, promoting a shift from labour employment to collaborative cooperation and from labour organisation to collaborative governance. Unlike the industrial era’s production organisation, which fixed people in positions, human–AI collaborative labour exhibits the salient features of a generalised labour scene, higher-order labour skills, and a digitised labour process. The traditional “identity recognition” based on labour becomes system permissions and keys. This makes data the core link connecting humans and machines and achieving collaboration. The traditional production bureaucracy’s “downward transmission of decisions” becomes a flattened network of “upward convergence of intelligence,” allowing workers to simultaneously carry out different types of labour behaviour in different digital production fields.

其三，人智协同的劳动形态改变工业时代的生产组织逻辑，推动劳动雇佣向协同合作、劳动组织向协同治理转变。与工业时代生产组织将人固定在岗位上不同，人智协同劳动呈现为劳动场景泛化、劳动技能高阶化与劳动过程数字化的显著特征，传统基于劳动的“身份识别”变为系统权限和密钥。这使得数据成为连接人机、实现协同的核心纽带，传统生产科层制的“决策向下传达”变为“智能向上汇聚”的扁平化网络，劳动者能够在不同的数字生产领域同时实施不同类型的劳动行为。

The potential risks of the penetration of the logic of capital. As a new form of machinery, intelligent large-model production is essentially a contemporary manifestation of fixed capital; its research and development, promotion, and use all require strong technical and financial support. Thus, although “human–AI collaboration” promotes a natural technological universal benefit, seemingly achieving a higher-order “compound” of labour products and workers and benefiting every new type of worker, the leap in their labour capacity still submits to the goal of capital accumulation. This turns human living labour into “a mere living accessory of this machinery system,” [2]2 Karl Marx, *Grundrisse*, “The Fragment on Machines.” giving rise to a series of intertwined and mutually influencing systemic risks, such as imbalances in value distribution, adjustments in employment structure, and the absence of rights protection.

资本逻辑渗透的潜在风险。智能化的大模型生产作为新的机器形态，本质依然是固定资本的当代呈现，其研发、推广与使用都需要强大的技术、资金支持。因而“人智协同”虽说推动了天然的技术普惠，似乎实现了劳动产品与劳动者的高阶“复合”，使每一位新型劳动者获益。但其劳动能力的跃升依然服从于资本的增殖目标，使得人的“活劳动转变为这个机器体系的单纯的活的附件”，催生价值分配失衡、就业结构调整与权利保障缺位等一系列相互交织、彼此影响的系统性风险。

First, the increase in labour productivity and growth in value returns brought about by “human–AI collaboration” are mostly appropriated by capital and the technological elite, exacerbating the polarisation of wealth in the labour field. Under the monopoly of intelligent technology, the multiplied value returns from human–AI collaborative labour are captured by intelligent capital, while workers receive only basic remuneration, forming a distribution pattern of “technology empowerment, labour weakness.” This leads to a serious disconnect between value creation and value distribution, plunging workers into a new existential predicament of “intelligent poverty” and “data poverty.”

其一，“人智协同”带来的劳动生产效率提高与价值收益增长多被资本与技术精英所占有，加剧劳动领域的贫富分化。在智能技术垄断下，人智协同劳动带来的价值倍增收益被智能资本所占据，劳动者仅得基础报酬，形成“技术赋能、劳动弱势”的分配格局，导致价值创造与价值分配的严重脱节，使劳动者陷入新的“智能贫困”与“数据贫困”生存窘境中。

Second, “human–AI collaboration” further promotes labour substitution and the “deskilling” of workers, leading to a wave of “technological unemployment” and an imbalance in employment structure. With the support of generative artificial intelligence, the productive capacity of machines has been unprecedentedly strengthened. On the one hand, the substitution of human labour extends from physical strength to intelligence and creativity; on the other hand, the instant generation of knowledge blocks the generative pathway of humans’ complex cognitive abilities, causing the “deskilling” of workers in a genetic sense. Thus, “human–AI collaboration” pushes the employment structure towards a “higher-order, intelligent” transformation. This not only enables the “quasi-subject” capacity of artificial intelligence to massively replace repetitive, low-skilled jobs but also creates a structural contradiction of “shortage of high-end employment and surplus of low-end employment.”

其二，“人智协同”进一步推进劳动替代与劳动者的“去技能化”，导致“技术性失业”浪潮与就业结构失衡。在生成式人工智能的加持下，机器的生产能力得到前所未有的强化，一方面对人的劳动取代从体力深入到智力和创造力，另一方面以知识的即时生成阻断人类复杂认知能力的生成线路，在发生学意义上导致劳动者“去技能化”。由此，“人智协同”推动就业结构向“高阶化、智能化”转型。这不仅使人工智能“类主体”能力能够大量取代重复性、低技能的工作岗位，而且造成“高端就业短缺与低端就业过剩”的结构性矛盾。

Third, “human–AI collaboration” labour obscures capital’s domination of the labour process and the existing labour–capital relations, resulting in the absence of workers’ rights protection. The basic fact that has not changed in “human–AI collaboration” labour is that capital’s domination of labour has not fundamentally changed; flexible, free, and diversified labour methods are merely a disguise for this domination. Workers are not only trapped in the “invisible shackles” of precise algorithmic calculation and strict assessment but also, under the cover of intelligent, flexible labour relations, face problems such as the absence of social security, blurred labour boundaries, and blocked channels for rights protection. This makes “human–AI collaboration” a “self-sacrificing, self-tormenting labour” [3]3 Karl Marx, *Economic and Philosophic Manuscripts of 1844*, “Estranged Labour.” that submits to the will of capital in the intelligent era.

其三，“人智协同”劳动掩盖资本对劳动过程的支配与存在的劳资关系，造成劳动者权利保障缺位。“人智协同”劳动没有改变的基本事实是，资本对劳动的支配没有发生根本性改变，灵活、自由与多样化的劳动方式只是对支配的掩饰。劳动者不仅陷入算法精准计算、严格考核的“无形枷锁”之中，而且在智能化、灵活化的劳动关系遮蔽下面临社会保障缺位、劳动边界模糊、维权渠道不畅等问题，使得“人智协同”成为智能时代服从资本意志的“一种自我牺牲、自我折磨的劳动”。

The innovation of institutional logic and risk prevention. Preventing and defusing the systemic risks of “human–AI collaboration” labour does not mean negating the significance of intelligent technology for the transformation of labour forms. Rather, it requires innovating institutional logic to regulate the logic of capital and harness intelligent technology, achieving a dynamic balance between the development of intelligent technology and the relations of production, and promoting the development of “human–AI collaboration” labour towards “co-evolution” that empowers human development and realises value sharing.

制度逻辑的创新与风险防范。防范化解“人智协同”劳动的系统性风险，并非否定智能技术对劳动形态变革的意义，而是要通过制度逻辑的创新来规范资本逻辑、驾驭智能技术，实现智能技术发展与生产关系之间的动态平衡，推动“人智协同”劳动向赋能人的发展与实现价值共享的“协同进化”方向发展。

First, based on the logic of human development and the normative system of the socialist system, curb the disorderly expansion and value exploitation of artificial intelligence capital. The logic of capital’s development is an infinite frenzy for surplus value, as Marx pointed out: “Accumulate, accumulate! That is Moses and the prophets!” [4]4 Karl Marx, *Capital*, Volume 1, Chapter 24, Section 3. Therefore, to unleash the powerful productive forces of “human–AI collaboration,” it is necessary to transcend the infinitely expanding logic of capital and achieve a higher-order restoration of the human-centred logic. This requires both giving play to the civilising aspect of capital, enabling it to promote continuous innovation in intelligent technology, and improving the supervision and regulation of intelligent capital, breaking the monopoly of capital and the technological elite over technology, data, and markets, and ensuring that workers receive reasonable remuneration through “distribution according to data contribution” and the sharing of intelligent value.

其一，立足人的发展逻辑与社会主义制度的规范体系，遏制人工智能资本的无序扩张与价值剥削。资本的发展逻辑即对剩余价值的无限狂热，如马克思指出：“积累啊，积累啊！这就是摩西和先知们！”因此，要释放“人智协同”的强大生产力，就必须超越无限扩张的资本逻辑，实现人本逻辑的高阶复归。这既要发挥资本的文明面，使之推动智能技术的不断革新，又要完善对智能资本的监管和规范，打破资本与技术精英对技术、数据和市场的垄断，在“按数据贡献分配”和智能价值共享中保障劳动者获得合理报酬。

Second, harness the logic of intelligent technology, and within the governance logic of promoting “intelligence for good,” let intelligent technology return to the essence of serving labour and empowering human development. The key to the development of “human–AI collaboration” labour is to avoid intelligent technology being infused with the will of a minority of capital and the technological elite and to circumvent the hidden domination of intelligent technology. Therefore, human values, labour rights, and social equity must be incorporated into the entire process of intelligent technology research and development and labour application. Establish and improve ethical review mechanisms for intelligent technology, increase technological empowerment for low-skilled groups and vulnerable groups, and promote the universal benefit of intelligent technology.

其二，驾驭智能技术逻辑，在推动“智能向善”的治理逻辑中让智能技术回归服务劳动与赋能人的发展的本质。“人智协同”劳动发展的关键是避免智能技术掺杂少数资本与技术精英的意志，规避智能技术的隐秘统治。因而，要将人的价值、劳动权利、社会公平等纳入智能技术研发和劳动应用的全过程，建立健全对智能技术的伦理审查机制，加大对低技能群体、弱势群体的技术赋能，推动智能技术的普惠发展。

Third, strengthen the cultivation of workers’ capabilities, using the enhancement of workers’ capabilities to strengthen the use of AI, and promote a productive forces revolution of two-way human–machine complementarity. At present, the labour model of “human–AI collaboration” has not yet significantly driven the development of the productive forces. This is due not only to the knowledge monopoly and technological isolation of capital and the technological elite, but also to the lack of cultivation of workers’ capabilities for applying AI. Therefore, it is necessary to incorporate digital literacy and intelligent collaboration capabilities into the education system and vocational training system through institutional innovation, enhance workers’ creativity and human–machine collaborative operational capabilities, and promote two-way complementarity in human–machine cooperation.

其三，强化劳动者能力培育，以劳动者能力的提升强化AI的使用，推动人机双向互补的生产力革命。当前，“人智协同”的劳动模式还没有显著推动生产力的发展，这不仅在于资本与技术精英的知识垄断与技术隔离，还在于缺乏对劳动者智能应用能力的培育。因此，需要在制度创新中将数字素养、智能协同能力纳入教育体系与职业培训体系中，提升劳动者的创造力与人机协同操作能力，推动人机协作的双向补充。

In sum, “human–AI collaboration” labour in the era of large models heralds a new revolution in the productive forces and a future of development, but it also harbours social risks from improper use. On the basis of analysing and grasping these risks, it is necessary to regulate and guide its development through institutional logic innovation, so that it becomes a core force for new social progress and human development.

总之，大模型时代的“人智协同”劳动，预示着新的生产力革命与发展未来，但同时也蕴含着不合理使用的社会风险，需要在分析并把握风险的基础上，以制度逻辑创新规范并引导其发展，使之成为新的社会进步与人的发展的核心力量。

(The author is a doctoral student at the School of Marxism, South China Normal University)

（作者系华南师范大学马克思主义学院博士研究生）