Philosophy of the Machines: A Manifesto for Humans in the Age of Artificial Agents

Abstract

We must reconsider our relationship with machines as artificial intelligence (AI) evolves from task-based support to autonomous or assisted generation. Generation is not creation.

Human intelligence—our only known model —is the sole benchmark for evaluating AI. Yet, we lack rigorous comparison standards because we do not fully understand the internal mechanisms of human intelligence. Perhaps it is more appropriate to speak of AI in simplified terms—as something that, under certain conditions, emulates what we commonly perceive as intelligent behavior (1). But even that remains uncertain.

Let us remember that we still lack a universally accepted definition of intelligence, let alone a definition of thinking, or even a deeper understanding of the complex nature of consciousness (2).

Let us also remember that over the last 80 years of computing and automation, the dominant discipline for solving problems has not been AI, but engineering. Engineering provides the methodologies, mental models, and validation frameworks we use to design and deploy systems. AI extends this legacy—and at the same time disrupts it, introducing new epistemic and ethical challenges that cannot be resolved solely through efficiency.

On these premises, this Manifesto articulates the Philosophy of the Machines as a distinct discipline that consolidates established philosophical lines of inquiry into a unified, applicability-oriented corpus with an explicit order of inquiry. Presented as a manifesto, it develops this order across ten interdependent sections. The trajectory culminates in the Δ–η–ζ framework, introduced as a modelling and analytical scaffold—and, where operationally feasible, a basis for measurement—of net gain in real deployments. The aim is to support more realistic, auditable, and human-aligned business cases for AI and generative AI in a labor landscape that must evolve as artificial agents become pervasive and socio-technical complexity continues to expand.

Within this order of inquiry—moving from foundational analysis to an operational modelling scaffold—the Manifesto foregrounds three questions: (i) What kind of “intelligence” are we building? (ii) What kind of humans must we become in response? (iii) How should responsibility be allocated when systems exceed our capacity for full understanding and oversight?

These questions set the Manifesto’s agenda for the age of artificial agents.

(1) This calls into question early benchmarks like the Turing Test—Alan Turing’s famous imitation game (Turing, 1950), often interpreted to mean that a machine could be deemed intelligent if its behavior is indistinguishable from that of a human. While foundational in the history of AI, this common operational reading conflates behavioral equivalence with intelligence itself (or understanding), without addressing the substance, origin, or epistemic structure of cognition (Oppy & Dowe, 2003). This Manifesto challenges such assumptions, arguing that the nature of intelligence demands a deeper philosophical and epistemological inquiry—not merely an evaluation based on outward behavior or performance.

(2) Consciousness and the Foundations of Meaning. Few topics encompass the breadth of multidisciplinary inquiry, philosophical depth, and scientific complexity for humanity as the phenomenon of consciousness (Savoldi et al., 2013). Intuitively, consciousness is inherently connected to the very nature of human thought, intelligence, and the linguistic constructs through which meaning emerges. While fundamental questions — such as the origin of the universe and the emergence of life — pose significant definitional and conceptual challenges, these questions gain their deepest significance precisely because consciousness enables humans to reflect upon and search for meaning within the cosmos. Universe’s origins → Life’s emergence → Consciousness. Indeed, consciousness may be considered a remarkable phenomenon from an evolutionary and cosmological perspective: it represents a state in which the universe becomes capable of self-observation and introspection. Although consciousness currently stands as the most complex and elusive manifestation of evolutionary processes known to us, it is scientifically prudent to frame it not necessarily as the universe’s “ultimate evolutionary stage” but rather as the most sophisticated example of an observer generated by natural processes known thus far. The study of consciousness therefore bridges philosophy, neuroscience and psychology, biology, and physics/cosmology, and remains central to understanding what it means for a universe to harbor observers capable of examining their origins and existence.