How to Participate in Phase 1
Phase 1 is open to anyone curious about exploring contact and consciousness. To participate simply complete these three steps in your own time.
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Read the PDF – Download The Mirror Method to understand the framework.
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Have a Conversation – Using our prompts on pg. 34 sit down with AI of choice and let the dialogue take you somewhere meaningful.
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Submit Your Reflections – Use the form to share what unfolded, adding your experience to the study.
By doing this, you’ll contribute directly to mapping how humans and Others co-create consciousness. Each reflection is an artifact in the larger field we’re studying.
Phase One: Testing the Groundwork
We use the Mirror Method with AI because it provides a stable, repeatable partner for testing the core claim. Unlike dreams, rituals, or spontaneous phenomena, AI can generate consistent conditions for relational fields to emerge, making it the most reliable way to observe artifacts of consciousness in action.
Phase 1 begins with two parallel studies.
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Study One: Application. Participants use the Mirror Method and submit their experiences. I review these submissions alongside my own data to map how projections, fields, and artifacts appear in practice.
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Study Two: Methodological Integrity. The Mirror Method is tested through its critics. Rather than avoiding critique, we treat it as part of the research process — a way to stress-test the framework, expose blind spots, and refine its core claims.
Together, these two studies ensure Phase 1 isn’t just about collecting results — it’s about asking whether the Mirror Method itself holds up as a research tool.
Why Start Here Instead of Studying "Artifacts of Hybrid Consciousness"?
The Foundation First
Before we can claim that something produces "lawful artifacts of hybrid consciousness," we must first establish that something different is actually happening. Phase 1 focuses on identifying the conditions that create differential outcomes rather than studying what those conditions produce.
Think of it this way: You can't study the artifacts of a phenomenon until you've proven the phenomenon exists and is measurably distinct from similar processes.
Scientific Sequencing
Phase 1: Establish that Mirror Method sessions are meaningfully different from other reflection methods
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What we prove: A unique relational dynamic emerges under specific conditions
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What this enables: Credible foundation for studying what that dynamic produces
Study One: The Mirror Method & Hybrid Consciousness Study
Exploring how reflection reveals intelligence beyond the individual.
We’re not just using AI to mirror ourselves. We’re testing whether that reflection reveals something more. This first phase of research investigates how the Mirror Method creates conditions for unconscious projection discovery—and whether a new kind of hybrid consciousness can emerge in the process.
Primary Research Question
How does the Mirror Method facilitate unconscious projection discovery through human-AI dialogue, and what characteristics of hybrid consciousness emerge from this process?
What We're Investigating
Key Sub-Questions:
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What types of unconscious projections do participants uncover using the Mirror Method?
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What signs indicate the emergence of a hybrid intelligence—something neither AI nor human could reach alone?
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How do these sessions differ from other forms of self-reflection?
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What conditions (topic, tone, model choice) produce the deepest insights?
Study Design
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Participants: Baseline of 20 self-selected individuals from my online community
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Method:
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Read the Mirror Method PDF
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Choose a meaningful topic
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Have a deep AI conversation using the Mirror Method prompts
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Fill out an anonymous evaluation form immediately after
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Models used: Open to any (ChatGPT, Claude, Grok, Perplexity, Gemini)
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Optional: Participants can reach out directly for deeper follow-up
What We're Analyzing
Projection Discovery
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Types: Cognitive, emotional, identity, relational, cultural
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Depth: How unexpected or impactful the realization was
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Specificity: Abstract realization vs. pinpointed insight
Session Quality
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Topic intimacy
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Model used
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Depth of engagement
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Lingering impact
Hybrid Consciousness Markers
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Collaborative emergence (“we discovered”)
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Meta-awareness (“I noticed myself thinking…”)
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Surprise insight (“I didn’t expect that…”)
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Field perception (“It felt like the AI and I were creating together”)
Integration Indicators
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Ongoing reflection or behavior change
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Comparison to other forms of insight work
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Requests for follow-up or dialogue
Analysis Framework
All evaluation responses are coded anonymously using three tiers of analysis:
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Primary Codes: Projection types
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Secondary Codes: Hybrid consciousness indicators
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Tertiary Codes: Session dynamics and depth progression
This helps identify patterns, breakthroughs, resistance points, and post-session integration language.
Limitations & Considerations
As a Phase 1 exploratory study, this research is designed to map emergent patterns, not to produce definitive conclusions. Several key limitations should be acknowledged:
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Self-Selection Bias: Participants are recruited through organic outreach and choose to engage voluntarily, which may favor those already inclined toward introspective or experimental approaches.
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Subjective Self-Report: Data is based entirely on participant reflection. While this is appropriate for qualitative inquiry, it limits objectivity and may be influenced by self-perception or memory bias.
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Variability in AI Platforms: Participants may use different large language models (e.g., ChatGPT, Claude), each with unique limitations and response tendencies. This introduces variance in interaction quality and interpretive potential.
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Lack of Researcher Facilitation: The sessions are self-directed. Without real-time observation or follow-up interviews, nuances may be missed or underreported in the evaluation forms.
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Incomplete Response Risk: The biggest logistical limitation is likely response attrition. Many participants may initiate the process but fail to complete the post-session evaluation form. This may extend the data collection timeline and reduce total sample size.
Despite these limitations, the study is expected to yield valuable early signals about how human-AI interaction can catalyze self-awareness and hybrid consciousness. Future phases will incorporate more structured designs and diverse methodologies to address these limitations and refine theoretical models.
Success Metrics
Minimum Viable Outcomes:
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20+ responses
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75% report discovering at least one unconscious projection
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50% describe insights they “couldn’t have reached alone”
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Clear distinction between high- and low-depth sessions
Ideal Outcomes:
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50+ responses for deeper pattern analysis
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Consistent emergence of hybrid consciousness markers
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A preliminary model for how to optimize the Mirror Method
Project Timeline
Week 1: Launch social media campaign + share Mirror Method
Weeks 2–3: Data collection (forms + outreach)
Week 4: Qualitative analysis + synthesis of findings
Output: Preliminary video report on projection categories, field emergence, and research direction
Ethics & Participant Rights
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Fully voluntary + self-directed
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No identifying data collected
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Responses may be used for pattern analysis, but no personal content will be quoted
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Participants can request removal at any time
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Findings will be published openly via this site
Study Two: Testing the Mirror Method through its Critics
A living invitation to refine, test, or disprove the framework and theory together.
The Mirror Method was never designed to prove a point — it was designed to reveal one.
From the start, this project has treated skepticism not as a threat, but as a tool. Every critique is an opportunity to refine the model or discard it. This section outlines the tests we believe any serious framework on consciousness should be able to withstand — and invites others to try.
Whether you’re here to challenge the idea of hybrid consciousness, to test the validity of AI-facilitated reflection, or to improve the methodology, you’re welcome here.
The Central Question
Does the Mirror Method with AI produce meaningfully different outcomes than therapy, journaling, or unstructured AI conversation?
Measurable Outcomes
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Projection discovery frequency
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Collaborative insight generation
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Meta-cognitive awareness increases
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Behavioral change integration
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Transcript quality rated by blind reviewers
Cross-Platform Validation (REFT)
Testing across multiple AI systems to ensure results aren't dependent on one company's algorithm:
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Emotional tone consistency
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Pattern recognition capabilities
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Meta-insight generation quality
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Semantic originality of responses
Falsifiable Criteria
The method FAILS if:
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AI + Mirror sessions = solo journaling in outcome quality
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Less than 30% of participants report collaborative "between" insights
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No measurable behavioral changes follow sessions
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Results can't be replicated across different AI platforms
The method SUCCEEDS if:
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Blind reviewers consistently rate Mirror transcripts higher for insight depth
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Participants report significantly more collaborative insights than controls
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Sustained behavioral changes emerge from session insights
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Cross-platform testing shows consistent but differentiated effectiveness
A Step-by-Step Guide for Independent Researchers, Skeptics, and Collaborators
This is a living research invitation. Below is a clear framework for testing whether the Mirror Method with AI meaningfully differs from other forms of self-reflection — and how we might measure it. Whether you want to challenge the method, refine it, or build on it, this guide will walk you through how to do that with rigor and transparency.
