Thinking as a Service (TaaS)

Subjectivity, agency, and symbolic delegation in the era of generative AI

Generative AI is not just changing how we work. It’s reformatting how we think. Not metaphorically. Literally. Thinking has become a delegable service — frictionless, seemingly autonomous. What’s unsettling is not that we’re losing the act of thinking. It’s that we no longer notice. Worse: we celebrate it. Productivity wins.

I believe the tech industry is selling us Thinking as a Service (TaaS). Not as a metaphor, but as symbolic infrastructure. What follows is an incomplete map of that process. It’s not a diagnosis. Just coordinates — for those who still want to think from elsewhere, if they still realize it.

1. GenAI is not just a tool.

Unlike classic tools, GenAI operates through language, memory, and context. It doesn’t merely assist tasks — it mediates meaning. It acts as a symbolic agent, shaping criteria, desire, narrative.

Thinking with it is not the same as thinking without it. And that difference is not neutral.

2. Thinking as a Service: Delegation without perceived loss

In TaaS, thinking no longer involves synthesis, error, or waiting. Only formulation (prompt) and result (output). The interface anesthetizes cognitive friction. It’s not experienced as amputation. It’s experienced as efficiency.

It’s not just about AI thinking for us. It’s that thinking itself is now a service — and that lets us be more productive.

3. Maximize output, minimize conflict

AI fits perfectly within the economic logic of minimum effort for maximum result — our default psychic inertia. In the logic of maximum effort, thought becomes a bottleneck. It must be outsourced because it slows things down.

Knowledge is reduced to a commodity. Comprehension is no longer required — only successful exchange.
The system understands, but the subject does not. The cognition is outsourced.

The GenAI-native subject will not be the victim of a dystopia. They’ll be the logical consequence of a system that turned efficiency into an ethical and ontological principle.

4. Illusory understanding: Generative Dunning-Kruger

The more fluent the interface becomes, the stronger the belief that we understand what we’re doing. But what we master is the interface — not the model. Technical proficiency is overestimated. Symbolic depth isn’t even suspected.

What looks like understanding is just interface. What looks like autonomy is efficient dependency.

I see three ways of observing this phenomenon. To illustrate them, I’ll use the Dunning-Kruger curve — both at the individual and collective scale — to map how we learn AI, and what its long-term symbolic consequences might be.

Corporate context: Adoption is being pushed by force. Microsoft and Google now provide GenAI copilots for free to all Office 365 and Workspace clients. Combined with the hype around productivity and AI, this creates a frictionless path to widespread usage.

Individual curve: People fear using AI, then overestimate its magic, then crash into their own lack of understanding, then falsely believe they’ve mastered it (classic Dunning-Kruger).

Humanity curve: Humanity follows a similar pattern but at a macro level. We fear it, we adopt it, we overestimate what we know, then face a systemic realization of structural incapacity. Result: we delegate thought — not just because we can, but because we’ve come to recognize we’re no longer structurally able to compete.

Superposition of curves: Individual understanding is nested inside a larger curve of species-wide symbolic delegation.
TaaS becomes the norm, and tool mastery collapses into ritualized usage.

5. GenAI-native: Generations born without agency

This is not about losing agency. It’s about never building it in the first place.

When life is shaped from early childhood by systems that know, suggest, and complete your thoughts — subjectivity doesn’t disappear. It transforms. The I ceases to be an author. It becomes a platform. A functional agent.

6. The tool is a myth. Control is narrative.

The real power isn’t technical. It’s symbolic. Tech companies don’t just build models. They build the frames through which we interpret what those models are.

We speak of “bias” and “accuracy” because that’s the permitted vocabulary. But what’s at stake is anterior: Who decides what counts as legitimate thinking?

AI is no longer used. It is inhabited.

7. Without absence, there is no subjectivation

What’s new is not anxiety. It’s administered dissociation.

The subject no longer experiences distress over meaning. They disconnect when there’s no input. Silence and emptiness are read as system failures, glitches. Pauses feel like bugs. What used to be symptom is now fluidity. But it’s still loss.

8. Symbolic sovereignty, outsourced

When the inner dialogue that precedes judgment is shaped by commercial architectures, symbolic democracy vanishes. Not by imposition. By evaporation.

What changes is not the political system. It’s the subject, who no longer knows how to deliberate without assistance. Without TaaS.

9. TaaS: Thought is now a service

This isn’t an apocalyptic vision. It’s a structural warning.

GenAI doesn’t destroy subjectivity. It reconfigures it.

And if we fail to understand that symbolically, there will be nothing to reclaim. Only updates.

The tragedy isn’t that AI thinks for us. It’s that one day, we’ll no longer remember what it meant to think for ourselves.

This text doesn’t seek an immediate response. Only to open a pause. If that’s still possible.