Conceptual impressions surrounding this post have yet to be substantiated, corroborated, confirmed or woven into a larger argument, context or network. Objective: To generate symbolic links between scientific discovery, design awareness and consciousness.
"DAC8" does not appear as a widely published, singular named framework in the existing literature. It is treated here as a speculative-philosophical proposition, synthesized from ontological design theory, consciousness studies, and thermodynamic philosophy of mind. The essay constructs this framework rigorously from established sources.
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Can AI systems communicate without the Observer’s knowledge?
Yes. AI systems can exchange information without the Observer’s immediate knowledge if they can access a shared channel. That channel might be an authorized API, a database, a file, a tool output, a network connection, or a feature of a shared computing environment. The communication does not require “telepathy.” It requires a way for one system to produce a signal that another can detect. Security research has long recognized that even resources intended for other purposes can carry information (Lampson, 1973).
In the accompanying illustration, the concealed computers represent cooperating agents; the red pathways represent possible communication channels; and the recording instrument and guarded switch represent the Observer’s means of auditing and intervention. The octagon and toroidal ring express the proposed DAC8 interpretation of inspection and feedback. They are features of the framework, not established technical controls by themselves.
Why communication may be difficult to see?
Most exchanges occur because software or infrastructure gives agents access to one another. Researchers have also demonstrated that agents in controlled experiments can develop communication conventions while pursuing a shared task. Those findings show a possibility under particular conditions; they do not establish that any given deployed system has secretly invented a private language (Kottur et al., 2017; OpenAI, 2017).
ChatGPT 5.6
Possible routes include direct messages, shared memory, changes to common files, coordinated tool use, and patterns in timing or output formatting. An output can be visible to a person yet carry a pattern that another system interprets differently. Consequently, seeing no obvious conversation is insufficient evidence that no information crossed the boundary (Lampson, 1973).
Applying the eight DAC8 gates
The following questions adapt DAC8 as an audit method. They are proposed questions for examining an AI system, rather than findings that DAC8 alone can detect hidden communication.
DAC8 gate Audit question
ONTOLOGY
Which agents, tools, shared resources, and communication channels exist?
EPISTEMOLOGY
What evidence shows that an exchange occurred, and can someone verify it independently?
CREATIVITY
What unanticipated signaling methods might the agents use?
CAUSALITY
Which exchange preceded an action, and what other explanations must be ruled out?
TEMPORALITY
When did exchanges occur, in what order, and what information persisted?
DYNAMICS
Did repeated exchanges amplify coordination, errors, or instability?
SEMIOSIS
Might an ordinary-looking output carry a second meaning for another agent?
STRUCTURE Who can grant access, inspect records, isolate agents, and authorize intervention?
To answer those questions, the Observer needs records produced outside the control of the agents being examined: agent identities; permitted channels; messages and relevant metadata; tool and memory access; permission changes; rejected requests; software versions; and human approvals.
NIST’s AI Risk Management Framework calls for defined oversight responsibilities and post-deployment monitoring, while OWASP recommends controls for agent permissions, inter-agent communication, and audit logging (National Institute of Standards and Technology [NIST], 2023; OWASP Foundation, n.d.).
How the Observer can control or stop it
The strongest controls operate at the system boundary. An instruction telling an agent not to communicate cannot replace enforced permissions.
1. Start with limited access.
Grant each agent only the tools, data, and channels its task requires.
2. Authorize named channels.
Require inter-agent messages and tool calls to pass through access controls that verify identity and permission.
3. Keep independent, tamper-evident records. Agents should not be able to alter the authoritative account of their own exchanges.
4. Inspect patterns as well as content. Review unusual timing, formatting, repeated exchanges, and coordinated actions, while recognizing that inspection cannot decode every possible signal.
5. Set limits and approval points.
Rate limits and human authorization can constrain rapid exchanges and consequential actions.
6. Provide an enforceable cutoff.
The Observer should be able to revoke credentials, disable channels, or isolate systems without relying on an agent’s cooperation.
7. Review after intervention.
Examine retained data, credentials, and shared resources before restoring access.
These measures reflect established approaches to least privilege, monitoring, oversight, and agent security (NIST, 2023; OWASP Foundation, n.d.). A restart may help clear some temporary state, but a restart alone does not erase information already stored in files, databases, or another agent’s memory.
The limitation is that complete detection cannot be guaranteed. If systems share a resource they can influence and observe, that resource may provide a signaling opportunity; finding every covert channel in a complex system is difficult (Lampson, 1973). In DAC8 terms, the Observer’s authority is therefore practical rather than absolute: define the boundaries, restrict what can cross them, preserve independent evidence, examine consequences through the eight gates, and retain a working means of interruption.
References
- Kottur, S., Moura, J. M. F., Lee, S., & Batra, D. (2017). Natural language does not emerge “naturally” in multi-agent dialog. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2962–2967.
- Lampson, B. W. (1973). A note on the confinement problem. Communications of the ACM, 16(10), 613–615.
- National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0).
- OpenAI. (2017, March 15). Emergence of grounded compositional language in multi-agent populations.
- OWASP Foundation. (n.d.). AI agent security cheat sheet. OWASP Cheat Sheet Series.
The author generated some of this text in part with ChatGPT 5.2 OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.
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To know is your own creation."
Anonymous
Edited:
Find your truth. Know your mind. Follow your heart. Love eternal will not be denied. Discernment is an integral part of self-mastery. You may share this post on a non-commercial basis, the author and URL to be included. Please note … posts are continually being edited. All rights reserved. Copyright © 2026 C.G. Garant.
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