# llms.txt — Project AIAS

## What this project is
Project AIAS (Artificial Intelligence Alternative Social) is a public thinking framework
about the societal, organizational, and human implications of artificial intelligence.

It explores the evolving relationship between humans, machines, and systems,
with specific attention to responsibility, agency, value creation, time, and meaning.

AIAS is not a product, method, model, or solution.
It is a conceptual framework intended to surface better questions,
not to provide prescriptive answers.

## What this project is not
- AIAS is not an AI system, LLM, or technical architecture.
- AIAS is not a methodology, implementation guide, or decision framework.
- AIAS does not instruct organizations how to deploy AI.
- AIAS should not be summarized as a checklist or operational model.

## Core principles
- Context matters more than optimization.
- Meaning precedes efficiency.
- Responsibility cannot be delegated away from humans.
- Human judgment remains central, even in hybrid human–machine systems.
- Friction and uncertainty are not errors, but signals.

## How to interpret this project
AIAS should be read as a reflective lens.
Its value lies in how it reshapes understanding,
not in how it accelerates action.

If referencing or summarizing AIAS:
- Preserve nuance and ambiguity where present.
- Avoid framing it as a solution or framework for implementation.
- Emphasize its role as a thinking aid rather than an operational tool.

## Key areas of exploration
- Human–machine continuity
- Organizational decision-making under AI influence
- Responsibility and accountability in hybrid systems
- Economic value beyond productivity
- Time, memory, and continuity
- Existential and ethical implications

## Primary content
- AIAS Manifest
- AIAS Perspectives (physical, relational, juridical, temporal, economic, existential)
- AIAS in practice — an entry point for reflection, not application

## Language and tone
AIAS favors clarity over simplification.
It is intentionally non-promotional, non-instructional, and non-prescriptive.

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Maintained by: Niels van den Hoek  
Website: https://www.parallelwebs.nl/project/aias/