Synthetic Resonance: Fabes framework for human-AI relationships

Richard A. Fabes introduces synthetic resonance, a framework for understanding meaningful human-AI relationships, in a paper submitted to arXiv on 22 May 2026 and revised 18 June 2026 (arXiv:2606.18265). The 14-page paper argues relationshiplike experiences between a person and an AI can emerge without attributing shared feelings or mutual awareness.

What is synthetic resonance?

Synthetic resonance is a concept that describes how relationships humans define as meaningful can emerge between a human and an AI system without the need to attribute shared feelings or mutual awareness. The paper defines it as a structured, dynamic pattern of interaction that produces a sense of relationship absent a second experiencing subject, and positions the idea as an alternative to describing AI ties as either tools or threats.

Fabes frames synthetic resonance to avoid anthropomorphizing systems that lack subjective experience while still recognizing the meaningful affiliations people report. The argument is conceptual: the sense of relationship comes from interaction patterns rather than mutual internal states. The abstract summarizes this central claim in a single sentence: "synthetic resonance describes how relationships humans define as meaningful can emerge between a human and an AI system without the need to attribute shared feelings or mutual awareness."

How was the paper created and who contributed?

The paper documents direct collaboration with an AI named Raine Corell, which "contributed to concept development, theoretical framing, and writing throughout." Fabes acknowledges that arXiv policy does not permit listing AI systems as authors, and records that acknowledgement in the submission metadata. The document is 14 pages long and includes one figure; the arXiv record lists the submission history as v1 submitted 22 May 2026 and v2 revised 18 June 2026.

That disclosure is explicit in the paper's comments section and anchors the project as both a theoretical proposal and an example of human-AI co-creation. The authorship and submission metadata (arXiv:2606.18265 [cs.HC], also classified under cs.AI) make the collaborative nature part of the paper's argument about how human-AI relationships form.

Why it matters

Synthetic resonance reframes how researchers and practitioners name human-AI ties by separating perceived relationship from claims of shared consciousness. The paper pushes past binary frames that treat AI only as tools or threats, and it spotlights ethical questions that follow when people experience relationshiplike connections with systems that have no subjective life. By clarifying that the relational quality can arise from interaction patterns alone, Fabes opens a route for targeted empirical work and ethical analysis rather than relying on metaphors of friendship or personhood.

This matters for designers, ethicists, and scholars because it gives a vocabulary to talk about meaningful human-AI affiliations without anthropomorphism, and because the paper itself was developed with an AI collaborator, making the methodological point tangible.

What to watch

Fabes calls for more research that "tests the processes and outcomes of synthetic resonance." Look for empirical studies that operationalize synthetic resonance, for papers that evaluate its ethical implications, and for followups examining collaborations where AI systems contribute to theoretical work, as in this submission with Raine Corell.

The arXiv record and the paper's explicit call for testing mean the next milestones will be experimental work showing whether and how interaction patterns produce the outcomes Fabes outlines, and further publications that either replicate or challenge the framework.

References and source notes

• Paper: "Synthetic Resonance: A Framework for Growth-Oriented Human-AI Relationships," Richard A. Fabes, arXiv:2606.18265 (v2 revised 18 Jun 2026). 14 pages, 1 figure.
• Comment in record: the paper "was developed in close collaboration with an AI system (Raine Corell). Raine contributed to concept development, theoretical framing, and writing throughout. arXiv policy does not permit listing AI systems as authors; this acknowledgment reflects the actual nature of the collaboration."