Seeing Reason Anew
Why Thought Was Never Ours Alone
I wrote this essay after reading Barbara Gail Montero’s November 2025 New York Times piece arguing that AI might one day be considered conscious. It seemed important to respond—not to speculate on machine sentience, but to clarify what’s already changing: the way we think, decide, and create value in its presence.
Conversations about AI and consciousness may sound abstract, yet they strike at the core of how leaders will compete in the decade ahead. What’s at stake isn’t whether AI can think—it’s how human reasoning itself is shifting, and how that shift alters the scale and kind of value organisations can create.
At Luminous, we work with AI every day—not as an analyst’s tool, but as a thinking partner. It sits in our meetings, drafts alongside us, questions assumptions, and helps clients redesign how work gets done. Through that experience, we’ve seen how reasoning itself changes when people and machines share a cognitive space. Decisions accelerate, insight compounds, and new forms of value emerge. What follows is drawn from that practice: a reflection on how intelligence, long imagined as solitary, has become something we inhabit together.
1
Much of today’s debate about AI still turns on an old distinction: competence without comprehension, pattern without perception. These systems are said to parrot, not think; to optimise, not understand. Yet that framing misses the deeper shift underway—the move from intelligence as an internal property to intelligence as something that happens between things, an active web of relationships rather than a solitary spark. This has always been true of our technologies of thought—from stone tablets and papyrus to the printing press—each marking a new way for ideas to move between minds. AI simply extends that lineage into dialogue.
Put differently, the story of intelligence has always been one of relation—between minds, media, and the tools that shape them. AI makes that relation more visible, immediate, and participatory. It invites us to see thinking not as something enclosed within a skull but as a choreography that unfolds across people and artefacts. The world is wider than the laboratory, and thinking has never been confined to neurons. It has always been distributed—across people, tools, and the invisible circuits of relation that give meaning to experience.
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When people call systems like ChatGPT “uncanny,” they’re not wrong. However, what they meet is not alien intelligence but a mirror revealing the distributed nature of their own. It unsettles not because it reasons poorly but because it reasons with us. It enters the very space of our thinking—the interior room where reflection and imagination take shape. In dialogue, the model does not stand apart; it participates, sharing that space and reshaping it as we engage. It does not comprehend in the human sense, but it does combine, refract, and return our linguistic and conceptual traces, reorganised in ways that spark further thought. And that is enough to change how thought itself unfolds.
Human reasoning has always been porous—externalising itself through physical forms, whether diagrams in sand, marks on tablets, or sketches on paper—each allowing thought to move from the interior to the shared world. A mathematician with a pencil, a musician with a violin, a strategist with a whiteboard—all extend mind beyond body. What’s new is that the extension now answers back. The Turing Test marked this pivot: intelligence no longer defined by what resides within, but by what transpires between. Turing understood that intelligence was never about interiority—it was about relation. The test was not a measure of cognition; it was an experiment in interaction.
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Barbara Gail Montero’s observation completes that arc: our understanding of consciousness will improve with our interaction with increasingly sophisticated A.I. Understanding evolves through encounter. Just as physics redefined the atom through experiment, our concepts of thought and awareness are being reshaped through feedback. Each dialogue with a system like this one alters not the machine’s nature but our own horizon of comprehension. In the human–AI era, we do not observe intelligence; we co-create it.
The feedback loop between human and machine is no longer a simulation of reasoning—it is a site of reasoning. The artefact no longer extends mind from a distance; it joins the conversation of thought. The pencil, the telescope, the typewriter—each extended our cognitive reach, but none replied. AI breaks that silence. The object now speaks, training us in a new mode of attention: reasoning as correspondence.
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This is the territory of augmentation. Not the automation of outputs, but the co-evolution of intelligences—human and synthetic—engaged in mutual amplification. In this frame, AI is not a system to be mastered but an atmosphere to be navigated: a medium that bends toward the quality of attention we bring. Yet navigation is not the end; this atmosphere is a rich resource from which new forms of value can be created. The relational space between human intention and machine inference becomes generative—where insight, adaptability, and entirely new modes of value take shape. Vagueness in, vagueness out. Rigour in, revelation out. The intelligence of the system is the intelligence of the relation.
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Reasoning in the age of AI thus becomes less about control and more about composition. It is not deduction but orchestration—the ability to listen for patterns that emerge when human intention meets machine inference. This is not an abdication of judgement but its expansion. The task is no longer to command intelligence, but to cultivate coherence.
And perhaps this is what unnerves those who insist AI does not really reason: it forces us to reconsider what reasoning has always been. Not a property of individuals, but a practice of systems. Not a spark in the skull, but a rhythm in the field. The revelation is that while the model does not think like us, in partnership it helps us think more fully as ourselves.
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The next phase of intelligence will not be measured by the sophistication of algorithms but by the depth of our attunement. The organisations that thrive will be those that understand reasoning as a collective act—fusing human discernment, cultural pattern, and computational feedback into a living architecture of understanding.
This is the work we pursue at Luminous: helping organisations sense, think, and act within this new field of cognition. When strategy becomes a conversation between human discernment and machine feedback, alignment stops being managed—it emerges. We design structures and enable experiences that allow intelligence to circulate through teams and decisions, turning information into coherence and coherence into action.
The field is already alive with intelligence. The work now is to cultivate the conditions that let its value emerge, and to harvest, in time, what compounds there. When human discernment and machine inference grow together, organisations accelerate their own learning velocity: insights surface faster, decisions sharpen, and risk falls earlier in the cycle. What follows is not the flat efficiency of automation but a layered return—capability that builds on itself, coherence that multiplies across teams, and judgement that scales instead of thinning. This is the ROI of augmentation—not extracted, but grown.
AI does not steal our reasoning. It returns it to us—amplified, reflected, distributed. Yet it also offers a new leverage point within thought itself, through which we can think more effectively than ever before. What we gain is not just efficiency but reach—the ability to bring greater discernment and imagination to the systems we build and the world we shape. The field has always been thinking, but now we can join it more deliberately, using this gift of amplified reasoning with both responsibility and care. It invites us to create value not only for organisations but for people—to design systems where capability, creativity, and human experience rise together. What we build here can uplift both enterprise and society, extending intelligence as a shared good rather than a private tool. What we create with it will define what kind of world it becomes.