Technology and the Reality of the Present-Centered Machine

Contemporary Artificial Intelligence and other computational systems—from machine learning models and large language models to autonomous agents and predictive simulations—usually handle time in a tenseless manner, treating past, present, and future data points as uniform elements of a timeline. They lack an explicit ontology of the present (what exists now), becoming (how the present continually updates from potential to actual), and temporal asymmetry (the one-way flow of causality from past to future). This paper proposes that Existential Realism (ER), an ontological framework distinguishing existence (entities in the present moment) from reality (a broader set including causally or informationally relevant past and future entities), can enrich the way technological systems model time. We argue that by incorporating ER’s present-centered, two-tier view of time, machines could become more temporally-aware and responsible in their decision-making. We detail key ER concepts—such as the primacy of the present, the reality of the non-present, truthmaking, and the idea of a real-but-not-yet-existent future—and map them onto machine-level analogues like sensor inputs (the machine’s “existence”), memory traces, simulation states, and predictive models. ER provides a structured approach for machines to: distinguish what exists now from what is merely remembered or anticipated; represent future states as real but not yet existent, enabling ethical foresight; anchor predictions in current data while reasoning about long-term consequences; and avoid temporal fallacies like treating the future as fixed or erasing the influence of the past. Through examples in climate modeling, medical diagnostics, robotics, and Artificial Intelligence ethics, we illustrate how an ER-informed system could better navigate time-sensitive tasks—e.g. by understanding that only the present sensor data is actual, that past data (though no longer existent) remains real evidence, and that future scenarios (though not yet actualized) demand present attention. We also draw on existing literature in philosophy and cognitive science to show that ER’s framework aligns with how humans experience time (through memory and anticipation) and how ethical reasoning already extends reality to future generations. In sum, Technology and the Reality of the Present-Centered Machine outlines an interdisciplinary vision: embedding a philosophically robust, present-centered temporal ontology into our technologies to foster more prudent, transparent, and temporally-grounded intelligent systems.