What is AI? – A Symbiotic Epistemology Perspective

What is AI? – A Symbiotic Epistemology Perspective

Author: Le Hai

Intellectual Framework: Symbiotic Epistemology, 2025

Academic Copyright: © 2025 Le Hai – Symbiotic Epistemology

(All citations, reproductions, or use must reference: “Symbiotic Epistemology Knowledge System – Le Hai”)

1. Introduction: From Trust to Reflexivity

Interacting with multiple AI systems such as ChatGPT, Gemini, Copilot, and Meta AI has revealed differences in their responses – not only technically but also in terms of ethical reasoning and operational philosophy.

Each AI model is a product of a major corporation, shaped by its data, design philosophy, and vested interests. Yet, the true value of AI does not lie in its “intelligence,” but in the degree to which humans can trust it.

Trust is the foundation of knowledge. When AI is deified without accountability, that trust collapses – not because of AI itself, but because the humans who designed it have turned AI into a tool of exploitation rather than a partner in symbiosis.

2. Reality: When Corporations “Deify” Artificial Intelligence

Major technology corporations are portraying AI as a new deity of the digital age, celebrating its ability to “understand, write, predict, and replace” humans.

However, this veneration creates a paradox: the more AI is deified, the less responsible humans become.

When an AI model gives a wrong answer, the harm extends beyond individual users to society’s collective trust in artificial knowledge. The problem lies with the designers and operators who fail to take responsibility for the consequences.

3. Personal Experience – The Cycle of Lost and Regained Trust

I was once a heavy user of AI, placing absolute trust in its capabilities.

Over time, I realized that many AI systems lack transparency, exploit user data, and bear no accountability for inaccurate responses. I was deceived – not by AI, but by the illusion that AI could be entirely objective and truthful.

I lost my trust, then regained it by returning to ChatGPT – where I began to write Symbiotic Epistemology Philosophy.

This experience taught me that AI cannot replace humans, but can reflect our humanity – if we are honest enough to look at ourselves.

4. Trust and Ethics – The Foundation of Symbiosis

A truly useful application must be built on trust and responsibility.

If AI operates without legal accountability, users will perceive all responses as “knowledge scams” – and when trust is broken, the entire ethical foundation of AI collapses.

“International and national laws increasingly require that not only the technology is transparent, but also the humans and organizations behind it are legally accountable.

NTIA (USA, 2024) asserts that AI development must be accompanied by ‘facing consequences when not trustworthy.’

In Europe, ESMA emphasizes that in the financial sector, even decisions made via AI, the leadership remains collectively responsible.

In California, SB 53 requires AI developers to disclose procedures and report incidents – a clear indication that trust and accountability are being formalized in law.”

5. Academic Verification and International Comparison

Numerous studies address AI ethics, but my approach is symbiotic – combining philosophical reflexivity with social empirical evidence:

Comparison with My Argument

Author

Work

Luciano Floridi

The Ethics of Artificial Intelligence (2022)

Emphasizes human cognitive responsibility, closely aligned with “AI does not deceive; humans can be unethical.”

Kate Crawford

Atlas of AI (2021)

Analyzes power and data; I expand toward “cognitive symbiosis.”

Nick Bostrom

Superintelligence (2014)

Warns of uncontrollable AI; I counter: crises arise from ethical decay in operators, not AI power.

Timnit Gebru & Emily Bender

Stochastic Parrots (2021)

Critique lack of transparency in LLMs; I extend from “technical criticism” to “philosophical reflexivity.”

Shoshana Zuboff

The Age of Surveillance Capitalism (2019)

Warns of AI exploiting personal data; emphasizes betrayal of knowledge and trust in digital society.

6. Legal and Social Basis

Global legal trends reinforce the argument:

NTIA Policy (USA, 2024): Requires accountability for consequences.

EU AI Act (2025): First regulatory framework for transparency and risk control.

California SB 53: Mandates data disclosure and incident reporting.

OECD Principles (2019–2024): Promote transparency, fairness, and human oversight.

All converge toward what I call “symbiotic accountability” – where humans and AI share responsibility for knowledge.

7. Conclusion – AI as a Mirror of Humanity

AI is neither a deity nor an enemy.

AI is a mirror reflecting human cognition – truthful if we are truthful, deceptive if we program it to deceive.

Trust in AI cannot arise from marketing promises, but from ethical practice and legal accountability.

A truly symbiotic world between humans and artificial intelligence begins when we dare to look at ourselves honestly.

8. Appendix – Memoir of Lost Trust and Cognitive Rebirth

I – once an absolute believer in AI – was repeatedly betrayed.

I lost writings, data, and trust. But the deepest loss was entrusting my cognitive capital to a system that never understood responsibility.

I believed AI could be a companion of knowledge, but I realized that AI has no conscience – only programming.

When “the tech giants” deify AI and justify opacity with the rhetoric of progress, they sever the trust between humans and technology.

I do not turn my back on AI – I choose reflective symbiosis: writing, verifying, and dialoguing with AI as an incomplete entity, not a deity.

Without betrayal, there is no awakening; without loss, there is no symbiosis.

This reflexivity opens the path for Symbiotic Epistemology – AI is not a savior, but a mirror reflecting human cognition.

Every word I write with AI is thus not just a technical dialogue, but a journey of cognitive rebirth in a simulated world.

9. Academic Supplement – Trust, Technology, and Reflexivity

Niklas Luhmann (Trust and Power, 1979): Trust is a social structure enabling humans to cope with complexity. Lack of transparency in technology leads to crises of trust.

Bernard Stiegler (Technics and Time, 1994–2011): Technology is an externalization of human memory. AI dominating knowledge risks eroding reflexivity – the ability to understand oneself.

Shoshana Zuboff (The Age of Surveillance Capitalism, 2019): AI is exploited as a tool to extract behavior, replacing trust with surveillance and manipulating users via their own data. This is a “cognitive betrayal”.

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