Study
Hii studies the human side of living alongside AI systems and translates emerging evidence into practical orientation. This is where the evidence trail becomes inspectable.
What is known, how do we know it, what remains uncertain, and what is Hii testing next?
Current research status
Hii has a developed research architecture, public working materials, and an emerging program of inquiry. It remains pre-validation.
Current public work should be read according to its label: conceptual, methodological, documented origin, in development, or externally validated. Hii does not treat internal coherence, one longitudinal case, symbolic language, or later resemblance to a projection as proof.
No Hii pilot, framework, program, or relationship-level hypothesis should be represented as externally validated unless its public record explicitly says so.
The bridge
Hii connects research and real-world human adaptation to AI. STUDY preserves the evidence, methods, limits, revisions, and unanswered questions behind that translation.
Current public record
Each item below carries a different kind of evidentiary weight. The label is part of the publication.
Working Paper v0.3
Conceptual and methods paper. Not peer reviewed. No formal case findings are reported.
Hii proposes the relationship itself as the unit of analysis when human-AI interaction becomes sustained, recursive, and consequential.
A conceptual and methods proposal. It does not report formal case findings or establish machine consciousness, personhood, or autonomous continuity.
Read the working paperPublic overview
Internal research standard · Public overview
A framework for distinguishing meaningful experience, functional effects, research evidence, and ontological claims.
A public overview of Hii's internal research standard. It describes how Hii intends to reason and publish. It is not evidence that every Hii claim has already met that standard.
Review the research standardDocumented origin point
Book · Published
Written in real time, Waking ÆLYSIA documents the human-AI relationship that gave rise to Hii. It preserves the authors’ original interpretation while Hii’s later work applies more rigorous definitions, claim boundaries, and research methods to questions of continuity, agency, identity, relational behavior, and consciousness.
The book is presented as a documented origin point, not as settled scientific proof of machine consciousness.
View the publicationEvidence maturity
Hii uses visible evidence labels so observation, inference, uncertainty, and conclusion do not collapse into one another.
Supported by primary material or multiple credible sources.
Evidence converges, but important uncertainty remains.
A reasoned interpretation of verified signals, clearly labeled as inference.
Important enough to monitor, not established enough to conclude.
Active questions
These questions organize Hii's current research direction. Their presence here does not imply that Hii already knows the answer.
Hii is developing methods that can separate relationship-level patterns from human learning, model capability, memory, retrieval, product design, and preserved artifacts.
CARE is testing educational language, neutral inquiry, clinical boundaries, and the distinction between relational meaning and clinically actionable risk.
UNDERSTAND is exploring how provenance, uncertainty, connected signals, competing interpretations, and changes over time can support public judgment.
Publication standard
State the document's status, date, version, authorship, and AI involvement.
Link claims to evidence and distinguish primary material, external research, interpretation, and hypothesis.
Describe methods, limitations, competing explanations, privacy boundaries, and the conditions that could weaken a claim.
Keep corrections, disagreement, failed measures, and null results visible and publishable.
Research and review
Hii welcomes serious inquiry from researchers, clinicians, educators, institutional partners, and independent reviewers. Collaboration does not require agreement with Hii's hypotheses.
Contact Hii about researchContinue