Sun Yan: On the Limits of "Algorithmic Time" from the Perspective of Historical Materialism
In the current context of accelerating iterations of artificial intelligence, "algorithmic time" is gradually becoming a key concept for understanding changes in social rhythm, distinct from "human time" which is rooted in human experience, life narratives, and social relations. It is not merely a technical temporal structure centered on computational speed, predictive capacity, and data cycles, but is increasingly evolving into a hidden framework that organizes modes of production, labor patterns, and daily life. As Marx revealed, time is not a neutral natural measure; rather, it is always embedded within specific relations of production. As algorithms are continuously embedded into social operations, the non-neutral character of time is significantly amplified: whoever sets the temporal rhythm gains a dominant position over the command of practice and the boundaries of action. The acceleration of algorithms, predictive models, and data closed-loops continuously reshapes the "lifeworld" [1], placing human modes of practice and subjective meaning at risk of reconstruction or even alienation. In this context, how to re-establish the significance and practical scale of "human time" within the logic of algorithmic acceleration has become a core problem requiring an urgent response.
The technical logic of algorithmic time. Proceeding from Marx’s analysis of technology as a form of the 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 lies in processing complex processes through calculation, optimization, and serialization. In practical application, this technical logic has been widely embedded in 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 based on changes in vehicle flow, improving overall throughput efficiency; in medical diagnosis, the rapid identification and quantitative analysis of imaging features by algorithms compresses originally time-consuming screenings into seconds, winning critical time for treatment. Consequently, the operating mode of "algorithmic time" exhibits characteristics such as linear advancement, precise quantification, and continuous acceleration, primarily manifested as: First, calculability. By decomposing complex processes into discretized, orderable steps, algorithms allow the structure of practice to be granulated, thereby generating predictable and plannable temporal sequences. Second, efficiency. Algorithmic time does not aim to represent reality as it is; rather, it optimizes processing paths to achieve the highest processing speed with minimum resources, internalizing efficiency into the system’s operating logic. Third, measurability. Algorithms rely on data recording, behavior tracking, and model feedback to encode the process of practice into continuous, comparable quantitative indicators, forming a temporal experiential structure based on digital measurement.
From the perspective of pure technical rationality, this mode of temporal organization—constituted by calculation, optimization, and measurement—does not inherently carry connotations of exploitation or discipline [2]. On the contrary, as a new organizational mechanism of modern society, it significantly enhances the capacity of social systems to handle complex problems and achieve coordination within the closed structure of technical systems, providing a new temporal scale for the operation of modern society.
The neutral limits of algorithmic time. Proceeding from Marx’s analysis of capital's use of machinery, technology itself does not naturally possess the attributes of capital; however, once incorporated into specific relations of production, it transforms into a social force that dominates labor and time. This means that once algorithmic time escapes the pure technical environment and enters social relations such as labor organization, platform governance, and institutional management, it is inevitably caught up in power structures. At this point, algorithmic time begins to intervene as a social temporal structure and reshapes the process of practice. Food delivery riders timed by the second, user attention continuously fragmented by algorithms, and individual preferences pre-shaped in predictive models all demonstrate that the acceleration logic of algorithmic time is re-encoded within institutional frameworks, transforming from an instrumental mechanism into a disciplinary force that shapes the rhythm of action, labor intensity, and modes of practice.
From the perspective of the philosophy of praxis, time is not an isolated physical quantity but a practical structure embedded within social relations. The way time is organized, allocated, and accelerated directly prescribes the form in which the possibilities of action unfold, thereby reflecting the way power operates in society. Therefore, the "neutrality" of algorithmic time is strictly conditional: it exists only within abstract technical structures detached from social relations. Once it enters the capitalist mode of production, algorithmic time no longer stays at the level of neutral technical operation but undergoes an institutional transformation.
Under algorithmic conditions, the logic of capital revealed by Marx acquires a new unfolding: capital no longer achieves the valorization of value [3] solely through lengthening the working day or increasing labor intensity, but directly intervenes in and reshapes the practical possibilities of laborers through comprehensive control over temporal rhythms, temporal structures, and temporal allocation methods.
From a mechanistic level, the institutionalization of algorithmic time unfolds through a triple logic: First, the logic of acceleration. Technical acceleration is institutionalized as a continuous demand on the rhythm of labor, causing "rational time" to be constantly compressed. Second, the logic of discipline. The precision of algorithms allows labor to be segmented into measurable micro-actions, with discipline automatically executed through the technical structure. Third, the logic of "quantification-coercion." Digital indicators combined with reward and punishment mechanisms become rigid standards for allocating opportunities and risks, establishing power boundaries that are difficult to challenge.
It is the superposition of these three logics that allows algorithmic time to complete the transformation from a technical logic to an institutional logic. It is no longer just the operating rhythm within a computational system, but has evolved into a complete institutional structure that organizes labor, shapes behavior, and appropriates human time. Its essence lies in capital using technology to rewrite the temporal order, obscuring its power logic under the guise of "technical neutrality." This shift constitutes a key issue of "temporal politics" in the age of artificial intelligence and presents a challenge for rethinking the scale of practice and the generation of subjectivity.
The return of human time. In Marx’s view, human practice is not the mechanical execution of external goals, but the process through which human beings unfold their essential powers through purposeful activity. Thus, free time is not simply rest time, but the practical scale through which the all-around development of the person is realized.
From the perspective of society as a whole, time manifests both as the rhythm of action unfolded by the subject of practice around a purpose, and as the narrative continuity of generating meaning within experience and memory; it further forms relational time through interaction between the self and others. It is within these dimensions that practice generates subjectivity and shapes value, thereby embodying the richness and all-around nature of human beings emphasized by Marx.
Consequently, the development of the productive forces only constitutes a genuine growth in social wealth when it is transformed into the expansion of free time. Reflections on algorithmic time must return to the scale of practice itself, re-answering the questions of whom time should ultimately serve and whether the organization of time still takes human practice and development as its ultimate measure.
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 degrades from "purposeful activity" to "task execution," and from "generating meaning" to "completing indicators," leading to a systematic contraction of the scale of practice. The enhancement of productive efficiency should release more disposable time, enabling individuals 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 the technology itself, but in the fact that the scale of practice is still dominated by the logic of capital. From the theoretical perspective of Habermas, this manifests as the "colonization of the lifeworld by systems logic." Systems oriented toward efficiency and control are invading life via algorithms. This is precisely the concentrated manifestation of the internal contradictions of modernity under digital conditions.
Unlike algorithmic time under capitalist conditions, which primarily serves the production of surplus value, the goals of development under socialist conditions provide a fundamental direction for reconstructing the scale of practice. The "people-centered" [4] philosophy of development determines that technological progress and the enhancement of productive forces must be directed toward the growth of people's wellbeing and the expansion of their space for development. Therefore, the reconstruction of the scale of practice in the AI era requires institutional and value guidance to make 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; and at the level of the lifeworld, by preserving stable temporal space for the generation of meaning, social interaction, and the growth of subjectivity.
In summary, the return from algorithmic time to human time is not an opposition between technology and humanity, but a redefinition of the position of technology within the structure of practice under the development logic of being "people-centered." The true value of new quality productive forces lies not in driving the total acceleration of society, but in using technological progress to expand the temporal boundaries of human beings, enabling more people to escape forced rhythms and enter a state of autonomous, rich, and dignified practice. Technical reflection in the age of artificial intelligence must ultimately return to Marx’s fundamental proposition regarding human liberation, making time a reality-condition for the unfolding of human practice and free development.