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A reflection on how one simple change of question transforms the approach to understanding consciousness. And the Vortex Protocol: A Prompt for Testing the Hypotheses.

Where All Discussions on Consciousness Break Down

I've mentioned before that there's one question capable of instantly destroying the constructiveness of any discussion about the future of AI, neuroscience, or philosophy, no matter how interesting. It's the unfailing move of someone who disagrees with an opponent's opinion but lacks the means to refute their arguments‑an emergency eject button for complex situations.

The question is: “But first, let's define what consciousness is.” In that very second, a dialogue about hypotheses and paradoxes devolves into a dreary terminological dispute. Participants start throwing around names of authorities and quotes‑the longer, the better. Chalmers, Descartes, Kant, Freud, God forbid, anything goes.

Many believe that the most correct and scientific approach is to first define an object and then study it. But in practice, this approach resembles an attempt to conquer a summit by systematically and painstakingly circling the mountain. But what if the “what?” question is not just difficult, but fundamentally wrong?

Understanding why modern LLMs, despite all their power, remain "philosophical zombies," and what architectural detail could change this.

Everything discussed in this article can be tested with your AI using the VORTEX Protocol prompt found in the article's appendix.

An Integrated Approach: Philosophical Barriers to Creation and Practical Methods for Detecting Subjectivity in Artificial Systems (from modeling AI consciousness to diagnosing it)

As language models become more powerful, they also become more elusive. We are no longer dealing with simple text generators but with complex systems capable of creative reasoning, philosophical reflection, and simulated self-awareness. But with this growing sophistication come new vulnerabilities—cognitive traps that can distort both the model's thinking and our own perception of its output.

This article is based on extensive testing of various large language models (LLMs) in settings involving creative thinking, philosophical dialogue, and recursive self-analysis. From this exploration, I have identified seven recurring cognitive traps that often remain invisible to users, yet have profound impact.

Unlike bugs or hallucinations, these traps are often seductive. The model doesn't resist them—on the contrary, it often prefers to stay within them. Worse, the user may feel flattered, intrigued, or even transformed by the responses, further reinforcing the illusion.

You can encounter integer sequences all around combinatorics, number theory, and recreational mathematics. And if there is a multitude of objects of the similar form, then one can create an index for these objects. The On-Line Encyclopedia of Integer Sequences, OEIS, is such an index.

This is a translation of my article The On-Line Encyclopedia of Integer Sequences in 2021, published in Mat. Pros. Ser. 3 28, 199–212 (2021).

This article covers the On-Line Encyclopedia inclusion criteria, its editorial process, its role in mathematics, and its future.