The Limits of “Algorithmic Time” from the Perspective of Historical Materialism

At a time when artificial intelligence is iterating at an accelerating pace, “algorithmic time,” in contrast to “human time,” which is based on human experience, life narratives, and social relations, is gradually becoming a key concept for understanding changes in the rhythm of society. It is not only a technical temporal structure centered on computing speed, predictive capability, and data loops, but is increasingly evolving into an implicit framework that organizes modes of production, labor patterns, and daily life. As Marx revealed, time is not a neutral natural measure but is always embedded in specific social relations. As algorithms become increasingly embedded in social operations, the non-neutral character of time is significantly amplified: whoever sets the rhythm of time can, to a large extent, grasp the dominant power over practice and the boundaries of action. Algorithmic acceleration, predictive models, and data feedback loops continuously reshape the lifeworld, and the mode of human practice and the meaning of the subject face the risk of being restructured and even alienated. Against this backdrop, how to re-establish the meaning and practical measure of “human time” within the logic of algorithmic acceleration has become a core issue that urgently needs to be addressed.

在人工智能加速迭代的当下，不同于以人的体验、生活叙事和社会关系为基础的“人类时间”，“算法时间”正逐渐成为理解社会节奏变迁的关键概念。它不仅是一种以计算速度、预测能力和数据循环为核心的技术时间结构，更日益演变为组织生产方式、劳动模式和日常生活的隐性框架。正如马克思所揭示的，时间并非中立的自然尺度，而是始终嵌入具体的社会关系之中。随着算法不断嵌入社会运行，时间的非中性特征被显著放大：谁设定时间节奏，谁便能在很大程度上掌握实践的主导权与行动边界。算法加速、预测模型与数据闭环持续重塑生活世界，人的实践方式与主体意义面临被重构乃至异化的风险。在这一背景下，如何在算法加速逻辑中重新确立“人类时间”的意义与实践尺度，成为亟须回应的核心问题。

The technical logic of algorithmic time. Starting from Marx’s analysis of technology as a form of productive forces, algorithmic time should first be understood as a mode of temporal organization dominated by technical rationality. As an important form of the modern technological system, the core function of algorithms is to handle complex processes through calculation, optimization, and sequencing. In practical applications, this technical logic has been widely embedded in the fields of public governance and professional practice: in urban governance, traffic dispatch systems based on real-time calculation and predictive models can dynamically adjust timing according to changes in traffic flow, improving overall traffic efficiency; in medical diagnosis, the rapid identification and quantitative analysis of image features by algorithms compress the originally time-consuming screening process to the second level, buying critical time for treatment. Therefore, the mode of operation of “algorithmic time” exhibits characteristics such as linear progression, precise quantification, and continuous acceleration, mainly manifested as: first, computability. Algorithms decompose complex processes into discrete, sortable steps, enabling a fine-grained practical structure, thereby generating predictable and planable time sequences. Second, efficiency. Algorithmic time does not aim to faithfully represent reality, but rather, by optimizing processing paths, achieves the highest processing speed with the least resources, internalizing efficiency as the logic of system operation. Third, measurability. Algorithms rely on data recording, behavior tracking, and model feedback to encode practical processes into continuous, comparable quantitative indicators, forming a temporal experiential structure based on digital measurement.

算法时间的技术逻辑。从马克思关于技术作为生产力形态的分析出发，算法时间首先应被理解为一种由技术理性主导的时间组织方式。作为现代技术体系的重要形态，算法的核心功能在于通过计算、优化与序列化处理复杂过程。在现实应用中，这一技术逻辑已广泛嵌入公共治理与专业实践领域：在城市治理中，基于实时计算与预测模型的交通调度系统能够根据车流变化动态调整配时，提高整体通行效率；在医疗诊断中，算法对影像特征的快速识别与量化分析，将原本耗时的筛查压缩至秒级，为救治争取关键时间。因此，“算法时间”的运行方式呈现出线性推进、精确量化与持续加速等特征，主要表现为：一是可计算性。算法通过将复杂过程拆解为离散化、可排序的步骤，使实践结构得以细颗粒化，从而生成可预测、可规划的时间序列。二是效率性。算法时间并非旨在如实呈现现实，而是通过优化处理路径，以最少资源实现最高处理速度，使效率内化为系统运行逻辑。三是可度量性。算法依赖数据记录、行为追踪与模型反馈，将实践过程编码为连续、可比较的量化指标，形成以数字化度量为基础的时间经验结构。

From the perspective of pure technical rationality, this mode of temporal organization, composed of calculation, optimization, and measurement, does not in itself presuppose exploitation or discipline. On the contrary, as a new type of organizational mechanism in modern society, it significantly enhances society’s ability to handle complex problems and achieve coordination within the closed structure of the technical system, providing a new temporal organizational measure for the operation of modern society.

从纯粹技术理性的层面看，这种由计算、优化与度量构成的时间组织方式，本身并不预设剥削或规训含义。相反，作为现代社会的一种新型组织机制，它在技术系统的封闭结构内部，显著提升了社会处理复杂问题与实现协同的能力，为现代社会运行提供了新的时间组织尺度。

The neutral limits of algorithmic time. Starting from Marx’s analysis of capital’s use of machinery, technology itself does not inherently possess the attribute of capital, but once it is incorporated into specific relations of production, it transforms into a social force that dominates labor and time. This means that once algorithmic time leaves the purely technical environment and enters social relational fields such as labor organization, platform governance, and institutional management, it inevitably becomes entangled in power structures. At this point, algorithmic time begins to intervene in and reshape practical processes as a social temporal structure. The fact that food delivery riders are timed by the second, users’ attention is continuously segmented by algorithms, and individual preferences are pre-shaped in predictive models, indicates that the accelerating logic of algorithmic time is being recoded within institutional frameworks, transforming from an instrumental mechanism into a disciplinary force that shapes the rhythm of action, labor intensity, and modes of practice.

算法时间的中性限度。从马克思关于资本运用机器的分析出发，技术本身并不天然具有资本属性，但一旦被纳入特定生产关系之中，便会转化为支配劳动与时间的社会力量。这意味着，一旦算法时间脱离纯粹的技术环境，进入劳动组织、平台治理与制度管理等社会关系领域，它便不可避免地卷入权力结构。此时，算法时间开始作为一种社会时间结构介入并重塑实践过程。外卖骑手被以秒计时、用户注意力被算法持续分割、个体偏好在预测模型中被提前塑造，正表明算法时间的加速逻辑在制度框架中被重新编码，从工具性机制转化为塑造行动节奏、劳动强度与实践方式的规训力量。

From the perspective of practical philosophy, time is not an isolated physical quantity but a practical structure embedded within social relations. The mode of organizing, distributing, and accelerating time directly determines the unfolding form of action possibilities and thereby reflects the mode of operation of power in society. Therefore, the “neutrality” of algorithmic time has strict conditions: it exists only within abstract technical structures detached from social relations. Once it enters the capitalist mode of production, algorithmic time no longer remains at the level of neutral technical operation but undergoes an institutional transformation.

从实践哲学视角看，时间并非孤立的物理量，而是内嵌于社会关系之中的实践结构。时间的组织、分配与加速方式，直接规定行动可能性的展开形态，并由此体现权力在社会中的运作方式。因此，算法时间的“中性”具有严格条件：它只存在于脱离社会关系的抽象技术结构之中。一旦进入资本主义生产方式，算法时间便不再停留于技术层面的中性运作，而要经历制度性转化。

Under algorithmic conditions, the logic of capital revealed by Marx acquires a new unfolding: capital no longer achieves valorization merely by extending labor time or increasing labor intensity, but directly intervenes in and reshapes the practical possibilities of laborers through comprehensive control over the rhythm, structure, and distribution of time.

在算法条件下，马克思所揭示的资本逻辑获得新的展开：资本不再仅通过延长劳动时间或提高劳动强度实现价值增殖，而是通过对时间节奏、时间结构与时间分配方式的全面掌控，直接介入并重塑劳动者的实践可能性。

At the mechanistic level, the institutionalization of algorithmic time unfolds mainly through a triple logic: first, the logic of acceleration. Technical acceleration is institutionalized as a continuous demand on the labor rhythm, so that “reasonable time” is constantly compressed. Second, the logic of discipline. The precision of algorithms divides labor into measurable micro-movements, and discipline is automatically executed through the technical structure. Third, the logic of quantification-compulsion. Digital indicators are combined with reward and punishment mechanisms, becoming hard standards for allocating opportunities and risks, establishing power boundaries that are difficult to question.

从机制层面看，算法时间的制度化主要通过三重逻辑展开：其一，加速逻辑。技术加速被制度化为对劳动节奏的持续索取，使“合理时间”不断被压缩。其二，规训逻辑。算法的精准性使劳动被切分为可度量的微动作，规训通过技术结构自动执行。其三，量化—强制逻辑。数字指标与奖惩机制相结合，成为分配机会与风险的硬性标准，确立难以质疑的权力边界。

It is precisely the superimposition of these three logics that enables algorithmic time to complete its transformation from technical logic to institutional logic. It is no longer merely the operational rhythm within a computing system, but has evolved into an entire institutional structure that organizes labor, shapes behavior, and appropriates human time. Its essence lies in capital rewriting the temporal order through technology, while obscuring its power logic under the guise of “technological neutrality.” This transformation constitutes a key issue of the politics of time in the era of artificial intelligence and also poses a challenge for rethinking the measure of practice and the generation of the subject.

正是这三重逻辑的叠加，使算法时间完成了从技术逻辑向制度逻辑的转化。它不再只是计算系统内部的运行节奏，而演变为一整套组织劳动、塑造行为并占有人类时间的制度结构。其本质在于资本借由技术重写时间秩序，并以“技术中立”的表象遮蔽其权力逻辑。这一转变构成了人工智能时代时间政治的关键问题，也为重新思考实践尺度与主体生成提出了挑战。

The return of human time. In Marx’s view, human practice is not the mechanical execution of external goals, but a process through which humans unfold their essential powers through purposeful activity. Thus, free time is not simply rest time, but the practical measure through which the all-round development of the human being is realized.

人类时间的回归。在马克思看来，人的实践不是对外在目标的机械执行，而是人通过有目的的活动展开自身本质力量的过程。由此，自由时间并非单纯的休息时间，而是人的全面发展得以实现的实践尺度。

From the perspective of society as a whole, time is embodied both as the rhythm of action that the practical subject unfolds around its purposes, and as the narrative continuity through which it generates meaning in experience and memory, and it forms relational time through the interaction between the self and others. It is precisely in these dimensions that practice can generate the subject and shape values, thereby embodying the richness and comprehensiveness of the human being that Marx emphasized.

从社会整体看，时间既体现为实践主体围绕目的展开的行动节奏，也体现为其在经验与记忆中生成意义的叙事连续性，并通过人与他者的交往形成关系性时间。正是在这些维度中，实践才得以生成主体并塑造价值，从而体现马克思所强调的人的丰富性与全面性。

Therefore, the development of productive forces truly constitutes an increase in social wealth only when it is transformed into an expansion of free time. Reflection on algorithmic time must return to the measure of practice itself, and re-answer the questions of whom time should ultimately serve, and whether the organization of time still takes human practice and development as its ultimate measure.

因而，生产力的发展只有在转化为自由时间的扩展时，才真正构成社会财富的增长。对算法时间的反思，必须回到实践尺度本身，重新回答时间究竟应当服务于谁，以及时间的组织是否仍以人的实践与发展为最终尺度。

When practice is continuously compressed into predictable, calculable sequences of operations, and when algorithmic time occupies a dominant position at the institutional level, human practice easily degenerates from “purposeful activity” into “task execution,” and from “generating meaning” to “completing indicators,” and the measure of practice undergoes a systematic contraction. The improvement of production efficiency should release more disposable time, enabling people to achieve fuller development in education, creation, public participation, and social interaction. If technological progress instead intensifies the compression of time, the problem lies not in technology itself, but in the fact that the measure of practice is still dominated by the logic of capital. From Habermas’s theoretical perspective, this manifests as “the colonization of the lifeworld by system logic.” The system oriented towards efficiency and control is invading the lifeworld through algorithms. This is the concentrated manifestation of the inherent contradictions of modernity under digital conditions.

当实践被持续压缩为可预测、可计算的操作序列，当算法时间在制度层面占据主导地位，人的实践便容易从“目的性活动”退化为“任务执行”，从“生成意义”转向“完成指标”，实践尺度随之发生系统性收束。生产效率的提升应释放更多可支配时间，使人能够在教育、创造、公共参与和社会交往中实现更充分的发展。若技术进步反而加剧时间压缩，其问题并不在于技术本身，而在于实践尺度仍然被资本逻辑所主导。从哈贝马斯的理论视角看，这体现为“生活世界被系统逻辑所殖民”。以效率与控制为导向的系统，正经由算法侵入生活。这正是现代性内在矛盾在数字条件下的集中显现。

Unlike the situation under capitalism, where algorithmic time primarily serves the production of surplus value, the developmental goals under socialist conditions provide a fundamental direction for reconstructing the scale of practice. The people-centered development thought determines that technological progress and the enhancement of productive forces must be directed toward the growth of the people’s well-being and the expansion of the space for development. Therefore, the reconstruction of the scale of practice in the era of artificial intelligence requires, through institutional and value guidance, that algorithmic time serve human time: at the technical level, by embedding values so that algorithms respect the rhythm of human judgment and the needs of practice; at the institutional level, by re-establishing time as a negotiable and guaranteed public resource; at the level of the lifeworld, by preserving stable temporal space for the generation of meaning, social interaction, and the growth of the subject.

与资本主义条件下算法时间主要服务于剩余价值生产不同，社会主义条件下的发展目标为重构实践尺度提供了根本方向。以人民为中心的发展思想，决定了技术进步和生产力提升必须指向人民福祉的增长与发展空间的拓展。因此，人工智能时代实践尺度的重构，需通过制度与价值引导，使算法时间服务于人类时间：在技术层面，通过价值嵌入使算法尊重人的判断节奏与实践需要；在制度层面，将时间重新确立为可协商、可保障的公共资源；在生活世界层面，为意义生成、社会交往与主体成长保留稳定的时间空间。

In summary, returning from algorithmic time to human time is not a confrontation between technology and humanity, but rather, under the logic of people-centered development, a redefinition of the position of technology within the structure of practice. The true value of new quality productive forces lies not in driving the comprehensive acceleration of society, but in expanding the temporal boundaries of human beings through technological progress, enabling more people to break free from imposed rhythms and enter a state of practice that is autonomous, rich, and dignified. The technological reflection of the era of artificial intelligence must ultimately return to Marx’s fundamental proposition of human liberation, making time truly the real condition for the unfolding of human practice and free development.

综上所述，从算法时间回到人类时间，并非技术与人的对立，而是在以人民为中心的发展逻辑下，重新界定技术在实践结构中的位置。新质生产力的真正价值，不在于推动社会的全面加速，而在于通过技术进步拓展人的时间边界，使更多人摆脱被迫的节奏，进入自主、丰富而有尊严的实践状态。人工智能时代的技术反思，最终仍需回到马克思关于人的解放这一基本命题，使时间真正成为人类实践展开与自由发展的现实条件。

(The author is an associate professor at the School of Marxism, Beijing Institute of Fashion Technology.)

（作者系北京服装学院马克思主义学院副教授）