{
  "schema": "ULTRACON_AI_EPISTEMIC_SOURCES_ADDENDUM_V1",
  "extends": "https://www.t-1-t.com/ultracon/confab/sources.json",
  "version": "1.1-addendum-2026-09-14",
  "updated": "2026-09-14",
  "selection_rule": "Add only developments that materially change an evidential layer or introduce a high-relevance result not already represented in the base corpus.",
  "sources": [
    {
      "id": "SRC-MOORE-SPIRALS-FACCT-2026",
      "year": 2026,
      "title": "Characterizing Delusional Spirals through Human-LLM Chat Logs",
      "authors": "Jared Moore et al.",
      "venue": "FAccT 2026 — Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency",
      "publication_date": "2026-06-25",
      "peer_reviewed": true,
      "doi": "10.1145/3805689.3806443",
      "url": "https://doi.org/10.1145/3805689.3806443",
      "axes": ["SPIRAL", "CONSC"],
      "evidence": ["EMP_BEHAV", "BENCH"],
      "reported_anchor": "391,562 messages from 19 selected users reporting psychological harms; the study codes delusional and sycophantic interaction patterns, including chatbot sentience claims, and reports that some relationship/sentience codes occur more often in longer conversations.",
      "role": ["direct observational chat-log evidence", "sycophancy in harmful conversations", "sentience/personhood misrepresentation", "multi-turn safeguard degradation"],
      "status": "peer_reviewed_observational_selected_sample",
      "non_inference": "The selected sample does not estimate population incidence and the observational design does not establish simple AI-to-psychosis causation. Co-occurrence and temporal association are not equivalent to causal identification."
    },
    {
      "id": "SRC-HU-SU-CONFORMITY-2026",
      "year": 2026,
      "title": "Conformity Breaks Conformal Prediction",
      "authors": "Yibo Hu, Hanyu Su",
      "venue": "arXiv preprint 2609.04445",
      "publication_date": "2026-09-03",
      "peer_reviewed": false,
      "url": "https://arxiv.org/abs/2609.04445",
      "axes": ["META", "SPIRAL"],
      "evidence": ["PREPRINT", "EMP_BEHAV"],
      "reported_anchor": "In the reported experiments, nominal 90% conformal coverage fell to 74% under unanimously wrong peer answers; on a targeted low-confidence subgroup, coverage fell from 87% to 47%.",
      "role": ["interaction-conditioned calibration failure", "score-mechanism shift", "multi-agent peer pressure", "uncertainty-to-action failure"],
      "status": "exceptional_recent_preprint_empirical_not_peer_reviewed",
      "non_inference": "This does not establish human-like conformity, subjective social pressure, or universal failure of conformal prediction. The result is conditional on the tested models, tasks, peer context and calibration regime, and awaits peer review and independent replication."
    }
  ]
}