Q1: What is Episdemos and how does it work?
Episdemos is a digital platform where anonymized citizens submit freeform “Citizen Statements” on a given issue. These are neutralized to remove identity markers and clustered into thematic arguments by AI. Users can update their vote as the swarm's thinking evolves. The platform visualizes shifts over time and ultimately produces a refined legislative recommendation.
Advanced features:
- Time-weighted voting to prevent domination by high-availability users
- Smart Digest Mode for low-engagement users
- Civic identity onboarding (public reason ritual)
- Swarm Memory Graph for institutional coherence
Q2: How is this different from a poll or town hall?
Polls capture static opinion. Episdemos captures epistemic evolution. Town halls encourage performance. Episdemos enforces anonymity. Polls reflect raw desire. Episdemos elicits structured public reason.
Q3: How is this different from sortition-based Citizen Assemblies?
While both Episdemos and sortition-based citizen assemblies rely on randomly selected citizens to enhance democratic legitimacy, Episdemos departs sharply in structure, philosophy, and execution. Unlike assemblies, which are facilitated, time-bound, and involve identity-exposed deliberation, Episdemos operates as a continuous, anonymous, and AI-augmented deliberative swarm. It eliminates performative dynamics by removing identity markers, tracks influence through vote shifts rather than speech acts, and focuses on procedural clarity over consensus. Whereas citizen assemblies simulate miniature parliaments, Episdemos is a sovereign cognition engine—epistemic, anonymized, and incorruptible by status or charisma.
Q4: Why anonymity?
To eliminate distortion caused by status, identity, signaling, or social fear. Episdemos uses full anonymity (no handles, no history) and language neutralization to remove performative cues.
Q5: What prevents trolling or bad-faith participation?
- Entry is by verified TRM swarm token
- Minimum exposure before participation
- AI filters for incoherence, toxicity, and linguistic manipulation
- Reweighting system suppresses over-participation by individuals
Q6: How does the AI summarize arguments and detect insight?
- Argument clustering by logic and theme
- Detection of trigger statements that shift votes
- Polyphonic summarizers offer multiple viewpoints
- Surfacing of high-impact minority arguments
- Contra-exposure: routing users to underrepresented positions
Q7: What does success look like?
- Measurable vote revision during deliberation
- Rich, high-diversity argument ecosystems
- Emergence of better-than-expected consensus proposals
- Evidence of post-swarm coherence across rotating groups
Q8: What happens after a deliberation cycle ends?
- AI-generated report summarizing all arguments and vote trajectories
- Visual swarm map (before vs. after)
- Final proposal delivered to TRM representative (the officially elected Congressperson) with execution mandate
Q9: What’s the evidence that this system would work?
- "Wisdom of Partisan Crowds" (Becker et al.): accuracy improves in structured peer deliberation
- Deliberative polling (Fishkin): exposure to reasoned diversity increases epistemic quality
- Behavioral science: anonymity reduces social conformity and bias
- Episdemos simulations: argument convergence, sustained diversity, high vote mobility
Q10: How does quantum theory inform this project?
- Superposition: Users hold layered beliefs until collapse point (voting)
- Entanglement: Ideas influence across the swarm nonlocally
- Observer effect: Suppressed via anonymity
- Decoherence: Episdemos shields swarm from identity-triggered interference
- Collapse: Vote only after exposure to full deliberative arc
Q11: Does the swarm need to be demographically or ideologically representative?
No. TRM assumes truth-tracking emerges from cognitive structure, not demographic mirroring. Random 500-person swarms yield robust outputs through:
- Identity-stripped deliberation
- Exposure to internal diversity
- Incentive-balanced participation
Q12: Where can Episdemos be applied?
- TRM legislative decisions
- Participatory budgeting
- Union negotiations
- Crisis consensus (e.g., public health, climate, AI safety)
Q13: What technology powers Episdemos?
- Frontend: React + WebSocket, mobile-first UI, voice input
- Backend: LLM orchestration, PostgreSQL, session cryptography
- AI Layer: Summarization, clustering, divergence detection, diversity indexing
- Data viz: D3.js dynamic swarm heatmap, memory graph overlays
Q14: What are the POC, MVP, and fast follower features?
POC:
- Anonymous input
- Static statement stream
- Manual summary layer
- Visual stance shifts
MVP:
- Civic ritual onboarding
- Real-time summarizer
- Trigger detection
- Heatmap visualization
- Diversity and reciprocity metrics
Fast Follower Features:
- Swarm memory tracking
- Polyphonic summarization
- Adaptive routing & entropy injection
- Cross-swarm coherence indexing
- Justice prompts (veil of ignorance framing)
Q15: How is Episdemos protected against capture or ideological drift?
- Rotating, randomized swarm assignments
- Anonymity and stripped syntax prevent status formation
- Trigger-statement highlighting reduces echo chamber effects
- Entropy prompts inject structured cognitive disturbance
- AI alerts surface consensus fragility and hidden dissent
Q16: How does Episdemos promote Rawlsian fairness?
- Reciprocity prompts: “Would I accept this if I were on the other side?”
- Veil-of-ignorance simulations at key decision points
- Accessibility infrastructure for voice, low-literacy, and mobile-only users
- Time-balanced weighting to ensure equity of influence
- Final output tested via fresh-citizen cold reads for legitimacy resonance