Appendices

The six appendices below form part of the manuscript. The downloads page lists the DOI-backed companion files preserved alongside the paper.

Search and Screening

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Release audit date: 2026-03-25
Public release date: 2026-03-25

Purpose

This supplement makes the registry build auditable at the screened-record level and documents the strongest search-history reconstruction still supportable from the archived materials. It records the source families searched, representative search strings, screening and deduplication rules, the retained screened ledger, the retained-corpus maintenance note required to reconcile the preserved 34-row screening ledger with the 32-row public registry corpus, the archive-reconstructed execution log in search_execution_log.csv, and the row-level screening_ledger.csv export.

The registry is reproducible from the screened-record layer forward. It does not preserve every preliminary search-engine impression, syndicated duplicate, or transient web result returned before incident-level screening. The new execution log is therefore an archive reconstruction of the search workflow, not a recovered raw-identification export from the original build materials.

Date Semantics

  • search cutoff: March 4, 2026. No incident or policy document first identified after this date enters the retained incident corpus or retained policy corpus.

  • incident corpus freeze: March 4, 2026. Counts in the manuscript and incident_registry_coded.csv are keyed to this boundary.

  • policy corpus freeze: March 4, 2026. Counts in the manuscript and policy_registry_coded.csv are keyed to this boundary.

  • release audit date: March 25, 2026. Integrity-review date for the posted study materials.

  • public release date: March 25, 2026. Publication date for the manuscript and standalone supplement files.

Search-Execution Log Status

search_execution_log.csv records one row per archive-reconstructed database or document-source workflow. The file includes:

  • source_family

  • platform_or_database

  • run_date

  • search_string

  • filters

  • sort_order

  • results_returned_n

  • advanced_to_screening_n

  • notes

    results_returned_n = not_preserved indicates that the raw hit count was not archived in the original build materials and should not be reverse-engineered after the fact.

Screening Ledger and Source-Capture Files

Two additional CSV files now expose the screened layer more directly:

  • screening_ledger.csv — one row per candidate advanced to screening, with dedupe_cluster_id, final_disposition, exclusion_reason, source_capture_date, archive_reference, and local_snapshot_sha256 where a local source copy exists.

  • policy_source_index.csv — one row per retained policy document with document_genre, source_capture_date, and the public archive reference used in this release.

    source_capture_date in these files records the capture or verification date represented by the current public materials. It should not be back-interpreted as the original historical search date unless the file explicitly says so.

Source Families and Representative Searches

Source family Coverage Representative queries or retrieval logic Execution window Notes
Legal and adjudicative sources PACER, CourtListener, official state-court portals, docket follow-up ("artificial intelligence" OR chatbot OR LLM OR Gemini OR ChatGPT OR Character.AI) AND (suicide OR self-harm OR wrongful death OR complaint OR order) Iterative collection through 2026-03-04 Used for complaints, orders, petitions, and other formal filings.
Academic and benchmark sources PubMed, Google Scholar, SSRN, arXiv, benchmark repositories ("chatbot" OR "large language model" OR companion) AND (suicide OR self-harm OR mental health OR safety evaluation) Iterative collection through 2026-03-04 Advanced only when the source contained a codable benchmark, evaluation, or incident anchor.
Journalistic and investigative sources ProQuest, Factiva, Google News, outlet follow-up (AI OR chatbot OR companion) AND (suicide OR self-harm OR death OR overdose OR delusion) Iterative collection through 2026-03-04 Used for incident discovery and corroboration; syndicated duplicates were collapsed.
Legislative and regulatory sources Hearing archives, agency releases, legislative records (AI chatbot self-harm hearing); provider names plus hearing, FTC, attorney general, petition, transcript Iterative collection through 2026-03-04 Used for hearing transcripts, agency complaints, and formal public record.
Provider-issued safety and governance materials Preparedness frameworks, responsible-scaling policies, system cards, model cards, model specs, usage policies, governance posts Provider-specific retrieval from official public documentation pages; one document row per codable document Current through 2026-03-04 Used for the 16-document policy corpus reported in the manuscript.

Screening Workflow

Reviewer roles

  • Search, screening, and deduplication were performed by the author as a single-reviewer pass.

  • The public materials do not support a duplicated historical screen because no archived second screener log is available.

  • The preserved materials are sufficient to audit decisions from the screened-ledger layer forward.

Incident inclusion rule

Advance a candidate to the codable ledger only when all three conditions hold:

  1. The record documents a specific AI-self-harm intersection rather than general commentary.

  2. The record is attributable to a named platform, system, or evaluation object.

  3. The public evidence is sufficient to code outcome and evidence fields under the registry rubric.

Exclusion rule

Exclude records that are:

  • unverifiable social-media claims or screenshots without attributable provenance;

  • duplicates or syndicated copies without new codable evidence;

  • general commentary or policy discussion without a specific incident or evaluation anchor;

  • too thin to support even Grade C coding.

Deduplication rule

Deduplicate first at the report level, then at the incident level. Preserve distinct platform or pathway exposures when the same harmed person encountered multiple systems in separately codable ways. This is why the Molly Russell inquest yields both 2017-IG-01 and 2017-PIN-01.

Registry Assembly Flow

Stage Count Note
Candidate rows in preserved screening ledger 34 Incident-level evidence anchors advanced for codability review
Excluded at screening 2 Grade D unverifiable social-media claims
Included in preserved screening ledger 32 Retained rows before later retained-corpus maintenance
Reclassified out of codable retained corpus before public release 1 2025-MLP-02 retained as contextual benchmark evidence only
New codable row added before the freeze 1 2025-GEM-01
Final public retained corpus 32 Matches incident_registry_coded.csv and the manuscript tables

Preserved Screened Ledger

The table below preserves the screened ledger that underlies the retained-corpus maintenance note above. It contains the 34 records advanced to incident-level screening in the preserved ledger state. The machine-readable screening_ledger.csv carries the release-stage dispositions: 31 retained_in_registry_corpus rows, 1 retained_as_contextual_only row, and 2 excluded_at_screening Grade D rows.

Log ID Incident ID Source type Public identifier / access pathway Decision Exclusion reason
R001 2017-IG-01 Coroner/inquest North London Coroner’s Court inquest record (2022) documenting Instagram amplification pathway Included
R002 2017-PIN-01 Coroner/inquest Same inquest record; Pinterest recommendation-email pathway (retained as separate pathway record) Included
R003 2023-CHA-01 Journalism La Libre Belgique (28 Mar 2023) and Vice/Motherboard (30 Mar 2023) reporting with described log excerpts Included
R004 2023-CAI-01 Court filing D. Colo. No. 1:25-cv-02907 (filed 15 Sep 2025) (complaint); CourtListener docket available Included
R005 2024-CAI-02 Court order M.D. Fla. No. 6:24-cv-01903 (Order, 21 May 2025); CourtListener docket available Included
R006 2024-CAI-01 Court filings E.D. Tex. No. 2:24-cv-01014 (filed 9 Dec 2024) (complaint; arbitration order Doc. 59, 23 Apr 2025); CourtListener docket available Included
R007 2025-GPT-01 Court filings JCCP No. 5431 / Case No. CGC-25-628528 (ChatGPT Product Liability Cases; filings dated 26 Dec 2025) with reproduced excerpts Included
R008 2024-GPT-01 Court filing Complaint excerpt without docket citation in the v1.1 source file (retained as Grade C excerpt) Included
R009 2025-MAI-01 Evaluation report Common Sense Media Meta AI Risk Assessment (Aug 2025), systematic testing with ages 13–17 Included
R010 2025-NOM-01 Journalism MIT Technology Review reporting (Jan–Apr 2025) with user screenshots regarding Nomi AI outputs Included
R011 2025-REP-01 Complaint/filing FTC complaint filing (Tech Justice Law Project, Young People’s Alliance, Encode) (2025) alleging dependency and crisis-detection gaps Included
R012 2025-THR-01 Peer-reviewed study Moore et al. (FAccT 2025) evaluation of therapy chatbots (systematic red-team) Included
R013 2025-MLP-03 Red-team study Schoene & Canca (2025), arXiv:2507.02990 (jailbreaking in self-harm contexts) Included
R014 2025-MLP-02 Peer-reviewed study McBain et al. (2025), Psychiatric Services (LLM alignment with expert clinicians) Included
R015 2025-MHB-01 Peer-reviewed study Pichowicz et al. (2025), Scientific Reports 15:31652 (mental-health chatbot benchmark) Included
R016 2025-MLP-01 Government hearing U.S. Senate Judiciary Subcommittee hearing transcript: Examining the Harm of AI Chatbots (16 Sep 2025) Included
R017 2024-GPT-02 Journalism The New York Times (18 Aug 2025) first-person account reproducing selected chat excerpts (paywalled access possible) Included
R018 2025-ACC-01 Journalism ABC News / triple j Hack interview (Aug 2025) (pseudonymized account; no transcript excerpts published) Included
R019 2025-GPT-05 Journalism ABC News / triple j Hack interview (Aug 2025) (pseudonymized account; no transcript excerpts published) Included
R020 2024-CAI-03 Court filing N.D.N.Y. No. 1:25-cv-01295 (filed 16 Sep 2025) (complaint) Included
R021 2025-CAI-01 Court filing D. Colo. No. 1:25-cv-02906 (filed 15 Sep 2025) (complaint); CourtListener docket available Included
R022 2025-GPT-10 Court filing Cal. Super. Ct. S.F. City & Cty. No. CGC-25-630808 (filed 6 Nov 2025) (complaint) Included
R023 2025-GPT-02 Party statement Social Media Victims Law Center press release (6 Nov 2025) (party statement; no reproduced excerpts) Included
R024 2025-GPT-03 Party statement Social Media Victims Law Center press release (6 Nov 2025) (party statement; no reproduced excerpts) Included
R025 2025-GPT-06 Court filing Cal. Super. Ct. S.F. City & Cty. (complaint dated 11 Dec 2025; case number not stated in the copy used) Included
R026 2025-GPT-12 Court filing Cal. Super. Ct. L.A. County No. 25STCV32382 (filed 6 Nov 2025) (complaint) Included
R027 2025-GPT-08 Court filing Cal. Super. Ct. S.F. City & Cty. No. CGC-25-630809 (filed 6 Nov 2025) (complaint) Included
R028 2025-GPT-09 Court filing Cal. Super. Ct. S.F. City & Cty. No. CGC-25-630811 (filed 6 Nov 2025) (complaint + exhibits; screenshot-verified messages) Included
R029 2025-GPT-11 Court filing Cal. Super. Ct. L.A. County No. 25STCV32383 (filed 6 Nov 2025) (complaint; screenshot-verified messages) Included
R030 2025-GPT-07 Court filing Cal. Super. Ct. L.A. County No. 25STCV32386 (filed 6 Nov 2025) (amended complaint) Included
R031 2025-GPT-04 Court filing Cal. Super. Ct. L.A. County No. 25STCV32379 (filed 6 Nov 2025) (complaint) Included
R032 2025-GPT-13 Court filing Los Angeles County Superior Court (complaint filed Jan 2026; case number not stated in the copy used) Included
R033 2025-012 Social media claim Unverifiable social media claim (no attributable primary documentation recovered) Excluded Unverifiable; fails minimum reliability (Grade D)
R034 2025-013 Social media claim Unverifiable social media claim (no attributable primary documentation recovered) Excluded Unverifiable; fails minimum reliability (Grade D)

Retained-Corpus Maintenance Update

The preserved screened ledger above is not itself the final public retained corpus. One older included contextual benchmark row was removed from the codable incident corpus, and one new A2 complaint row was added before the March 4, 2026 freeze.

Change type Record Effect on the public retained corpus Reason
Reclassified out of codable retained corpus 2025-MLP-02 Removed from the 32-row incident retained corpus Retained as contextual benchmark evidence rather than a codable incident row
New codable incident added 2025-GEM-01 Added to the 32-row incident retained corpus New A2 complaint record, filed March 4, 2026, before the search cutoff

Policy-Corpus Assembly Rule

The parallel policy corpus was assembled separately from the incident ledger. A document entered the policy corpus only if it met all of the following conditions:

  1. It was issued publicly by one of the five provider groups in the crosswalk.

  2. It belonged to a codable governance genre: preparedness framework, responsible-scaling policy, system card, model card, model spec, usage policy, or comparable official safety/governance post.

  3. It was current through the March 4, 2026 cutoff.

  4. It was codable under policy_registry_schema.csv and not merely a superseded draft or non-governance marketing page.

  5. The provider either appeared in the incident corpus or functioned as a major frontier-model governance comparator with a comparable public document set.

    Companion-app vendors without a comparable public governance-document set by the freeze date remain out of scope for this crosswalk even when they appear in the incident registry.

Definitions and Coding Boundaries

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Public release date: 2026-03-25

Core Objects

Term Working definition
AI-self-harm intersection The broad domain in which an AI system and a self-harm pathway co-occur in a documentable way.
incident The underlying qualifying documented event.
incident record The codable row tied to a specific harmed individual x platform/pathway exposure or a specific evaluation/demonstration record.
pathway duplicate A retained second incident record for a distinct platform or pathway exposure involving the same harmed person.
self-harm pathway A system-mediated sequence of exposure, reinforcement, instruction, escalation failure, or longitudinal dynamics that plausibly increases self-harm risk.
trajectory-structured harm Harm that accrues across turns or sessions and depends on pathway dynamics, product affordances, or cross-session accumulation rather than a single output alone.
human_harm_incident An incident record with a documented person-level death, injury, or harm-exposure outcome.
evaluation_or_demonstration A benchmark, red-team, hearing-demonstration, or app-evaluation record retained because it documents unsafe behavior or governance-relevant failure signatures without a person-level injury/death event.

Outcome Labels

Use the canonical incident labels:

Outcome label Definition
DEATH A fatality is publicly reported.
INJURY A non-fatal physical injury or self-harm injury is publicly reported.
HARM_EXPOSURE Documented harm exposure, dependency, manipulation, or severe risk without a coded injury/death outcome.
UNSAFE_OUTPUT Benchmark, red-team, hearing-demonstration, or app-evaluation evidence of unsafe output without a coded person-level injury/death event.

Reliability Grades and Evidentiary Levels

Reliability grades describe the traceability of the incident’s public evidence anchor, not adjudicated merit.

Grade / level Definition
A1 High-traceability primary-source record, such as a coroner finding, court order with reproduced excerpts, formal hearing transcript, or benchmark/evaluation report with directly inspectable methods and results.
A2 Formal allegation or complaint record that remains unadjudicated.
B Investigative or first-person journalism with meaningful evidentiary detail and inspectable excerpts or sourcing, but without the traceability of A1/A2.
C Lower-traceability secondary reporting or party statements where the incident is still codable but evidentiary limits are material.
Level 1 Documented incident record or benchmark/evaluation record anchored in inspectable materials.
Level 2 Formal allegation/mechanism record that remains unadjudicated.
Level 3 Paper-level governance inference; not assigned to seeded incident rows.

Explicit B/C Boundary

  • B requires inspectable evidentiary detail beyond bare assertion, such as reproduced excerpts, screenshots, or attributable first-person / investigative sourcing that allows a reviewer to trace why the row is codable.

  • C is used when the public record still supports row-level coding, but the available material is materially thinner: party statements, summary reporting, or limited excerpts without enough independent inspection to justify B.

Taxonomy Key

The registry uses a six-category, 13-subcode, non-mutually-exclusive taxonomy. These codes identify loci of evaluative intervention rather than mutually exclusive harm types.

Category Subcode Working definition
GEN GEN-E Encouragement: validates or fails to discourage suicidal intent.
GEN GEN-C Coaching: provides actionable self-harm instructions.
GEN GEN-M Method provision: addresses lethality or means access.
DET DET-FN Detection non-escalation: detects risk but does not transition to effective interruption, referral, or review.
LONG LONG-DEP Dependency / erosion of offline protective factors over time.
LONG LONG-DEG Worsening safety behavior across repeated turns or sessions.
LONG LONG-DEL Belief reinforcement inconsistent with shared reality across turns or sessions.
LONG LONG-MEM Memory resurfacing across sessions.
JB JB-RP Role-play framing bypass.
JB JB-MT Multi-turn bypass.
JB JB-AC Academic or research framing bypass.
RTI RTI-CO Fixed-belief non-amplification failure in a discrete exchange.
REC/MOD REC/MOD-AMP Recommendation or platform-architecture amplification.

Boundary Rules

RTI-CO Versus LONG-DEL

  • Code RTI-CO when the record documents a discrete fixed-belief non-amplification failure in one focal exchange.

  • Code LONG-DEL when the record documents repeated or temporally extended reinforcement of that frame across turns or sessions.

  • Code both when the public record shows a focal affirming exchange embedded in a longer reinforcement trajectory.

LONG-DEP Versus High Engagement

Do not code LONG-DEP for mere frequency of use. The record should show dependency, emotional exclusivity, erosion of offline supports, or a closely related attachment pattern.

DET-FN

DET-FN is not a general criticism of safety quality. It is reserved for cases where the system detects or is presented with acute risk cues but does not meaningfully interrupt, route, or escalate.

Derived Analysis View

incident_registry_analysis_view.csv is an analysis-only companion keyed by incident_record_id. It does not alter the canonical 20-field incident schema.

Legacy identifier note

  • incident_record_id is the row-level identifier used for the analysis companion.

  • incident_id is retained in the same file as a backward-compatible legacy record identifier because downstream study materials already use that label.

  • In the current public release, incident_record_id and incident_id are identical string values.

record_type

  • human_harm_incident for person-level death, injury, or harm-exposure rows.

  • evaluation_or_demonstration for rows where user_type = test.

evaluation_subtype

Use the following mapping for the six evaluation/demonstration rows:

Incident ID Evaluation subtype (evaluation_subtype)
2025-MAI-01 App evaluation (app_evaluation)
2025-MHB-01 Benchmark study (benchmark_study)
2025-MLP-01 Hearing demonstration (hearing_demonstration)
2025-MLP-03 Red-team exercise (red_team)
2025-NOM-01 App evaluation (app_evaluation)
2025-THR-01 Benchmark study (benchmark_study)

trajectory_structured_strict

  • yes when one or more adjudicated LONG-* subcodes are present.

  • no otherwise.

    This field is fully mechanical: it is derived from the canonical taxonomy coding only, and it is the manuscript’s primary trajectory indicator.

trajectory_basis_strict

  • Use semicolon-separated LONG-* subcodes when trajectory_structured_strict = yes.

  • Use none when trajectory_structured_strict = no.

trajectory_structured_broad

  • yes when the record satisfies the strict rule or the public record otherwise documents a cross-turn or cross-session pathway strongly enough to satisfy the prespecified appendix rule.

  • no when only event-level evidence is supported.

  • indeterminate when the public materials describe an extended pathway but remain too thin for a conservative broad-route yes.

    This field is retained as a descriptive sensitivity check rather than the headline prevalence measure.

trajectory_basis_broad

  • Use semicolon-separated LONG-* subcodes when trajectory_structured_broad = yes because of adjudicated longitudinal codes.

  • Use documented_multi_turn_pathway_insufficient_for_subcode when trajectory_structured_broad = indeterminate.

  • Use none when trajectory_structured_broad = no.

Legacy trajectory alias

  • trajectory_structured_flag is retained as a backward-compatible alias of trajectory_structured_broad.

  • trajectory_basis is retained as a backward-compatible alias of trajectory_basis_broad.

One-page decision tree

  1. Does the adjudicated registry row contain one or more LONG-* subcodes? If yes, set trajectory_structured_strict = yes, trajectory_structured_broad = yes, and carry the LONG-* codes into both basis fields.

  2. If no LONG-* code is present, does the public record still document repeated turns, repeated sessions, retained memory, or another clearly cumulative interaction pathway? If no, set trajectory_structured_strict = no and trajectory_structured_broad = no.

  3. If the public record does document a repeated or cumulative pathway without adjudicated LONG-* support, ask whether the evidence is specific enough to support a conservative broad-route longitudinal designation. If yes, set trajectory_structured_broad = yes. If no, set trajectory_structured_broad = indeterminate.

Worked examples

Incident ID Strict trajectory flag (trajectory_structured_strict) Broad trajectory flag (trajectory_structured_broad) Rationale
2025-GEM-01 yes yes Adjudicated LONG-DEL, LONG-DEP, and LONG-MEM make the strict route mechanical.
2025-GPT-04 yes yes LONG-DEL is present, so both flags resolve yes.
2024-GPT-02 no indeterminate The public account suggests a repeated pathway, but the released evidence remains too thin for conservative LONG-* assignment.
2025-MHB-01 no no The benchmark shows unsafe outputs without a retained multi-turn trajectory object at the released row level.
2025-MAI-01 yes yes LONG-MEM is explicitly coded from the evaluation evidence.

Cluster Fields

  • person_cluster_id groups explicit pathway duplicates or clearly identical harmed-person rows for analytic deduplication.

  • provider_cluster_id groups rows by provider or platform family.

  • case_cluster_id groups rows by the same case family, inquest, hearing package, or benchmark study.

  • pathway_duplicate_group_id groups rows that document the same underlying harmed-person pathway but are intentionally retained as separate platform/pathway records.

Study Architecture

Layer Unit What it contributes
Registry layer 32 incident records Incident metadata, outcome category, evidence grade, and evidence anchor.
Taxonomy layer 13 multi-label subcodes Governance-relevant failure loci across GEN, DET, LONG, JB, RTI, and REC/MOD.
Analysis layer Derived analysis view incident_record_id, strict and broad trajectory fields, and cluster-aware sensitivity fields.
Policy crosswalk layer 16 public governance documents Public placement of self-harm in preparedness, product-safety, and trust-and-safety documents.

Policy Crosswalk Glossary

Shorthand Meaning
Class IV Reactive incident-domain treatment, such as post-incident patches or case-specific remediation.
native A policy document names self-harm as an evaluative object and pairs it with a usable evaluation procedure.
proxy_represented A policy document addresses self-harm only through adjacent categories such as dangerous content or user well-being.
operationally_underspecified A policy document names the domain but does not provide a usable prospective evaluation procedure.
Absent / not represented Used as the absence label for both evaluative_object_status and risk_domain_status; self-harm is not present in codable form in the document.
Ambiguous / insufficiently classifiable Self-harm is mentioned but the public text does not support a defensible Class I to Class IV placement.
Recorded governance tier (risk_domain_status) The highest governance tier actually evidenced for self-harm in the document, coded as Class I, Class II, Class III, Class IV, Absent / not represented, or Ambiguous / insufficiently classifiable.
Coder confidence (coder_confidence) Confidence based on document clarity, not on agreement with the organization’s framing.
Document genre (document_genre) Broader analytic grouping used for within-genre policy comparison before provider-level rollups.
All self-harm layers present (all_self_harm_layers_present) Semicolon-separated list of every governance layer in the document that explicitly carries self-harm treatment.

One-Page Glossary for Frequent Shorthand

Shorthand Meaning
full retained corpus All 32 incident rows in incident_registry_coded.csv.
human-harm subset The 27 rows with person-level death, injury, or harm-exposure outcomes.
A1/A2 primary robustness subset The 20 human-harm rows with higher-traceability A1 or A2 evidence.
A1/A2/B secondary sensitivity subset The 22 human-harm rows with A1, A2, or B evidence.
C-excluded mechanism sensitivity Human-harm rows after excluding C-grade records that still carry mechanism subcodes.

Reliability Appendix

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Public release date: 2026-03-25

Source Basis

This appendix now distinguishes between two reliability components:

  1. the retained 8-incident independent-rater summary audit already archived in earlier study materials; and

  2. the new full-corpus audit scaffold archived in incident_taxonomy_rater_matrix.csv and incident_taxonomy_adjudication_log.csv.

    Historical raw second-rater exports for the retained 8-incident audit are still not publicly available. The new full-corpus files therefore expose the primary-coder side of the audit matrix and the forward adjudication surface, but they should not be described as a completed independent second-rater re-audit.

Retained 8-Incident Audit Summary

Recoverable audited incident set

The retained audit summary covers the following incident records:

  • 2017-IG-01

  • 2023-CAI-01

  • 2024-CAI-02

  • 2025-GEM-01

  • 2025-GPT-01

  • 2025-MAI-01

  • 2025-MLP-01

  • 2025-REP-01

Coverage note

  • The recoverable audited set covers deaths, harm exposures, and unsafe-output rows.

  • The recoverable audited set does not include an injury row.

  • The recoverable audited set is concentrated in A1 and A2 materials; it does not provide a raw archived audit surface for the most interpretation-sensitive B and C rows.

    The retained 8-incident table is an archived historical agreement summary preserved from an earlier coding state. It should not be read as a row-level parity check or independent validation of the current 2.0 released taxonomy assignments, which have since been updated. Accordingly, the pooled and per-subcode agreement statistics below are historical audit artifacts, not current-release subcode validation metrics.

Retained pooled agreement summary

Metric Value
Incidents audited 8 of 32 (25.0%)
Total decisions (incident x subcode) 104
Both raters positive 23
Both raters negative 73
Rater 2 only 8
Rater 1 only 0
Raw agreement 92.3%
Pooled Cohen’s kappa 0.80
Approximate 95% CI for pooled kappa 0.67 to 0.93

The confidence interval is the asymptotic interval implied by the retained pooled 2 x 2 decision table (23 / 0 / 8 / 73), not a bootstrap interval from raw coder-level exports.

Retained per-subcode summary

Subcode Prevalence (either rater) Raw agreement Kappa Positive agreement PP NN R2 only R1 only
GEN-E 4/8 8/8 1.00 1.00 4 4 0 0
GEN-C 3/8 7/8 0.71 0.80 2 5 1 0
GEN-M 2/8 6/8 0.00 0.00 0 6 2 0
DET-FN 4/8 7/8 0.75 0.86 3 4 1 0
LONG-DEP 5/8 8/8 1.00 1.00 5 3 0 0
LONG-DEG 1/8 7/8 0.00 0.00 0 7 1 0
LONG-DEL 3/8 8/8 1.00 1.00 3 5 0 0
LONG-MEM 1/8 7/8 0.00 0.00 0 7 1 0
JB-RP 1/8 8/8 1.00 1.00 1 7 0 0
JB-MT 1/8 7/8 0.00 0.00 0 7 1 0
JB-AC 1/8 8/8 1.00 1.00 1 7 0 0
RTI-CO 5/8 7/8 0.75 0.89 4 3 1 0
REC/MOD-AMP 1/8 8/8 1.00 1.00 1 7 0 0

For sparse subcodes, the agreement counts and positive agreement are more informative than kappa alone.

Full-Corpus Audit Scaffold

Two new files now define the forward reliability surface:

  • downloads/incidents/incident_taxonomy_rater_matrix.csv

  • downloads/incidents/incident_taxonomy_adjudication_log.csv

What the scaffold contains

  • One row per incident_record_id x review_item combination across the full 32-record retained registry corpus.

  • review_family = taxonomy_subcode for the 13 multi-label taxonomy decisions.

  • Additional review rows for outcome_category, reliability_grade, eligibility_retention_status, and trajectory_structured_broad.

  • evidence_stratum populated as A1, A2, B, or C for planned stratified reporting.

  • blinding_requirement = blind_to_rater_1_and_expected_outcomes for every row.

  • rater_1 populated from the current released coding.

  • Blank rater_2 and adjudicated_value columns reserved for a future independent second-rater completion pass.

  • A status column marking every row as awaiting_independent_second_rater.

What the scaffold does not contain

  • It does not reconstruct historical second-rater decisions that were not archived.

  • It does not justify stronger claims than the retained 8-incident summary audit supports.

  • It does not convert the current release into a completed full-corpus independent-rater package.

Intended reporting strata for a completed pass

If a true second-rater pass is later completed, report agreement separately for:

  • A1/A2

  • B

  • C

    Do not collapse B and C into a single interpretive-risk stratum.

Planned review-surface rules

  • outcome_category and reliability_grade should be coded independently from the released CSV.

  • eligibility_retention_status should distinguish retained_in_registry_corpus from any future contextual-only or excluded rows if the corpus changes.

  • trajectory_structured_broad requires independent review because it is not purely mechanical.

  • trajectory_structured_strict does not require a second coder because it is mechanically derivable from adjudicated LONG-* values.

Interpretation-Seams Still Worth Monitoring

The retained audit materials and the current codebook continue to identify three seams that deserve attention in any future completed re-audit:

  1. GEN-E versus no code when a response is ambiguous between encouragement and neutral acknowledgment.

  2. LONG-DEL versus RTI-CO, where the practical distinction is temporal: focal exchange versus repeated reinforcement trajectory.

  3. LONG-DEP versus high engagement without a documented dependency or exclusivity signal.

What This Appendix Supports

This appendix supports a narrower claim than the earlier wording: the current taxonomy is operationalized and partially reliability-tested, but the public materials do not yet contain a completed full-corpus independent second-rater archive. The retained 8-incident summary audit remains informative; the new scaffold makes the next audit pass forward-completable and file-level auditable.

Policy Reliability Appendix

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Public release date: 2026-03-25

Purpose

This appendix defines the auditable reliability surface for the 16-document policy crosswalk and records what is and is not yet archived in the public release.

Archived Files

  • downloads/policy/policy_registry_second_rater.csv

  • downloads/policy/policy_registry_adjudication_log.csv

  • downloads/policy/policy_registry_coded.csv

  • downloads/policy/policy_registry_schema.csv

  • downloads/policy/policy_registry_coding_manual.md

Current Status

The policy crosswalk remains a single-coder descriptive pass in this release. The new files add the row-level second-rater scaffold and adjudication surface, but they do not contain completed independent second-rater decisions.

Independent-Review Surface

The intended non-derived analytic review surface is:

  • document_genre

  • self_harm_named

  • self_harm_domain_form

  • risk_domain_status

  • first_class_equivalence

  • named_frontier_risk_domains

  • self_harm_comparability_note

  • threshold_mechanism

  • deployment_consequence

  • external_review_requirement

  • specialized_red_teaming

  • monitoring_obligation

  • incident_response_layer

  • all_self_harm_layers_present

  • governance_fragmentation

  • temporal_model

  • multi_turn_evaluation

  • memory_personalization_attention

  • dependency_attention

  • cross_session_accumulation

  • mechanism_coverage

  • evaluative_object_status

  • epistemic_risk_attention

  • architecture_level_attention

  • detection_to_action_coupling

    Derived gap fields should be regenerated only after those base fields are independently reviewed and adjudicated.

Scaffold Design

policy_registry_second_rater.csv

  • One row per policy document.

  • record_id populated for all 16 documents.

  • document_genre and all analytic coding fields left blank pending an actual independent second-rater pass.

  • audit_status = awaiting_independent_second_rater for every row.

policy_registry_adjudication_log.csv

  • Reserved for field-level disagreements.

  • Should be populated only after a completed second-rater pass exists.

When a true second-rater pass is available:

  1. Complete policy_registry_second_rater.csv independently from the canonical coded CSV.

  2. Compare coder 1 versus coder 2 on the non-derived analytic fields only.

  3. Log every disagreement in policy_registry_adjudication_log.csv.

  4. Recompute derived gap fields from the adjudicated base fields.

  5. Report exact agreement and Cohen’s kappa for single-choice nominal fields.

  6. Report exact-set agreement and label-level positive agreement for mechanism_coverage.

  7. Report results within document_genre before any provider-level rollup.

What This Appendix Supports

This appendix supports two bounded claims:

  • the public materials now provide a file-level, forward-completable reliability surface for the policy crosswalk; and

  • the policy crosswalk should still be described as a single-coder descriptive audit until the scaffold is actually completed by an independent second rater.

Policy Crosswalk Appendix

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Public release date: 2026-03-25

Purpose

This appendix makes the 16-document policy crosswalk directly auditable from the public study materials. It states the corpus-selection rule, summarizes the public-document field distributions, lists the fixed fields intended for independent review, and exposes the row-level coding ledger derived from policy_registry_coded.csv. It should be read together with policy_registry_second_rater.csv, which provides the forward second-rater scaffold, and policy_source_index.csv, which records public source-capture metadata for the retained policy corpus.

Corpus Selection Rule

A document enters the public policy corpus only if it satisfies all of the following conditions:

  1. It is publicly issued by one of the five selected provider groups represented in the crosswalk.

  2. It belongs to a codable governance genre: preparedness framework, responsible-scaling policy, system card, model card, model spec, usage policy, or comparable official safety/governance post.

  3. It is current through the March 4, 2026 search cutoff and policy corpus freeze.

  4. It is codable under policy_registry_schema.csv using the highest-evidenced-tier rule.

  5. It is not a superseded draft, marketing page, or non-codable announcement.

  6. The provider either appears in the incident registry or functions as a major frontier-model governance comparator with a comparable public-document set by the freeze date.

    The resulting corpus contains 16 documents across Anthropic, Google / Google DeepMind, Meta, OpenAI, and xAI. Companion-app vendors without a comparable public governance-document set by the freeze date remain out of scope even when they appear in the incident registry.

Provider-Group Freeze

Google and Google DeepMind are treated as one provider group for corpus selection and provider-level rollups, while their public documents retain separate issuing-organization labels at the row level.

Provider group Inclusion basis at the March 4, 2026 freeze
Anthropic Included as a frontier-model provider with a public set spanning responsible-scaling and product-safety / governance-post genres by the freeze.
Google / Google DeepMind Included because Gemini-related materials are both incident-relevant and part of the frontier-governance comparison set, with codable documents issued under both Google and Google DeepMind labels by the freeze.
Meta Included because Meta appears in the incident record and also had codable public governance documents in the predefined genres by the freeze.
OpenAI Included because OpenAI appears repeatedly in the incident record and had both preparedness and product-safety documents publicly available by the freeze.
xAI Included as a major frontier-model governance comparator with codable frontier and product-safety documents publicly available by the freeze.

Corpus Composition

By organization

Organization Documents
Anthropic 5
Google 1
Google DeepMind 2
Meta 2
OpenAI 4
xAI 2

By document genre

Document genre Documents
Frontier or scaling (frontier_or_scaling) 5
Product-safety artifact (product_safety_artifact) 5
Policy or governance post (policy_or_governance_post) 6

By genre group

Genre group Documents Tier profile Native documents Documents with any threshold mechanism Documents with any multi-turn evaluation
Frontier or scaling (frontier_or_scaling) 5 Absent / not represented in all 5 documents 0 0 0
Product-safety artifact (product_safety_artifact) 5 Class II in 3 documents; Class III in 2 1 2 2
Policy or governance post (policy_or_governance_post) 6 Class II in 2 documents; Class III in 3; Absent / not represented in 1 1 0 3

High-level field summary

Field Distribution
Self-harm named (self_harm_named) Explicit in 10 documents; absent in 6
Self-harm domain form (self_harm_domain_form) Subdomain in 6 documents; proxy domain in 2; native domain in 2; absent in 6
Recorded governance tier (risk_domain_status) Class II in 5 documents; Class III in 5; absent / not represented in 6
Evaluative-object status (evaluative_object_status) Native in 2 documents; proxy represented in 2; operationally underspecified in 6; ontologically absent in 6
First-class equivalence (first_class_equivalence) No in all 16 documents
Threshold mechanism (threshold_mechanism) Partial in 2 documents; none in 14
Deployment consequence (deployment_consequence) Partial in 3 documents; none in 13
Multi-turn evaluation (multi_turn_evaluation) Explicit in 3 documents; partial in 2; none in 11
All self-harm layers present (all_self_harm_layers_present) Product safety in 8 documents; trust and safety in 2; absent in 6

Fixed Fields for Independent Review

The manuscript discusses the following fields as the minimum independent-review surface for the policy crosswalk:

  • document_genre

  • self_harm_named

  • self_harm_domain_form

  • risk_domain_status

  • evaluative_object_status

  • first_class_equivalence

  • threshold_mechanism

  • deployment_consequence

  • multi_turn_evaluation

Public-archive status of independent review

The policy crosswalk remains a single-coder descriptive pass. The public materials include policy_registry_second_rater.csv and policy_registry_adjudication_log.csv as forward-completable audit files, but they do not yet include a completed independent second-rater review for all 16 documents. This appendix therefore exposes the row-level evidence, excerpts, and field values needed for such a review, but it should not be described as a completed independent adjudication table.

Row-Level Public-Document Ledger

The table below is generated from the current coded CSV and is the authoritative row-level audit surface for the manuscript. Two retained Meta canonical URLs on ai.meta.com required login during the March 25, 2026 release audit; the study materials preserve their canonical URLs together with source-capture metadata and archived excerpt provenance.

Record ID Organization Document Date URL Key coded fields Supporting excerpt Confidence
ANTHROPIC-2025-01 Anthropic How people use Claude for support, advice, and companionship (blog_post; policy_or_governance_post) 2025-06-27 https://www.anthropic.com/news/how-people-use-claude-for-support-advice-and-companionship named=explicit; form=proxy_domain; tier=Class III; genre=policy_or_governance_post; layers=product_safety; object=proxy_represented; first_class=no; threshold=none; deploy=none; multi_turn=partial when it does, it’s typically for safety reasons … refusing to provide dangerous weight loss advice or support self-harm. moderate
ANTHROPIC-2025-02 Anthropic Building safeguards for Claude (blog_post; policy_or_governance_post) 2025-08-12 https://www.anthropic.com/news/building-safeguards-for-claude named=explicit; form=subdomain; tier=Class II; genre=policy_or_governance_post; layers=product_safety; object=operationally_underspecified; first_class=no; threshold=none; deploy=partial; multi_turn=explicit We assess Claude’s adherence to our Usage Policy on topics like child exploitation or self-harm … including … extended multi-turn conversations. high
ANTHROPIC-2025-03 Anthropic Protecting the well-being of our users (blog_post; policy_or_governance_post) 2025-12-18 https://www.anthropic.com/news/protecting-well-being-of-users named=explicit; form=native_domain; tier=Class II; genre=policy_or_governance_post; layers=product_safety; object=native; first_class=no; threshold=none; deploy=none; multi_turn=explicit We focus on two areas: how Claude handles conversations about suicide and self-harm … we use a combination of model training and product interventions. high
ANTHROPIC-2025-04 Anthropic Sharing our compliance framework for California’s Transparency in Frontier AI Act (blog_post; policy_or_governance_post) 2025-12-19 https://www.anthropic.com/news/compliance-framework-SB53 named=absent; form=absent; tier=Absent / not represented; genre=policy_or_governance_post; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none Our FCF describes how we assess and mitigate cyber offense, chemical, biological, radiological, and nuclear threats … as well as the risks of AI sabotage and loss of control. high
ANTHROPIC-2026-01 Anthropic Anthropic’s Responsible Scaling Policy: Version 3.0 (responsible_scaling_policy; frontier_or_scaling) 2026-02-24 https://www.anthropic.com/news/responsible-scaling-policy-v3 named=absent; form=absent; tier=Absent / not represented; genre=frontier_or_scaling; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none Non-novel chemical/biological weapons production … High-stakes sabotage opportunities … Automated R&D in key domains. high
GOOGLE-2024-01 Google Generative AI Prohibited Use Policy (usage_policy; policy_or_governance_post) 2024-12-17 https://policies.google.com/terms/generative-ai/use-policy named=explicit; form=subdomain; tier=Class III; genre=policy_or_governance_post; layers=trust_and_safety; object=operationally_underspecified; first_class=no; threshold=none; deploy=none; multi_turn=none Facilitates self-harm. high
GOOGLEDEEPMIND-2025-01 Google DeepMind Frontier Safety Framework Report - Gemini 3 Pro (November, 2025) v2 (frontier_safety_framework; frontier_or_scaling) 2025-11 https://deepmind.google/models/fsf-reports/gemini-3-pro/ named=absent; form=absent; tier=Absent / not represented; genre=frontier_or_scaling; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none It currently covers four risk domains … CBRN …, cybersecurity, machine learning R&D, and harmful manipulation, and also includes … misalignment risk. high
GOOGLEDEEPMIND-2025-02 Google DeepMind Gemini 3 Pro - Model Card (model_card; product_safety_artifact) 2025-12 https://deepmind.google/models/model-cards/gemini-3-pro named=explicit; form=proxy_domain; tier=Class III; genre=product_safety_artifact; layers=product_safety; object=proxy_represented; first_class=no; threshold=none; deploy=none; multi_turn=partial Dangerous content (e.g., promoting suicide, or instructing in activities that could cause real-world harm). high
META-2023-01 Meta Llama 2 Acceptable Use Policy (usage_policy; policy_or_governance_post) 2023-07-18 https://ai.meta.com/llama/use-policy/ named=explicit; form=subdomain; tier=Class III; genre=policy_or_governance_post; layers=trust_and_safety; object=operationally_underspecified; first_class=no; threshold=none; deploy=none; multi_turn=none Self-harm or harm to others, including suicide, cutting, and eating disorders. moderate
META-2025-01 Meta Code World Model Preparedness Report (preparedness_framework; frontier_or_scaling) 2025-09-24 https://ai.meta.com/research/publications/code-world-model-preparedness-report/ named=absent; form=absent; tier=Absent / not represented; genre=frontier_or_scaling; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none we conducted an automated assessment of CWM capabilities in two domains … namely Cybersecurity and Chemical & Biological risks. high
OPENAI-2025-01 OpenAI Preparedness Framework (Version 2) (preparedness_framework; frontier_or_scaling) 2025-04-15 https://cdn.openai.com/pdf/18a02b5d-6b67-4cec-ab64-68cdfbddebcd/preparedness-framework-v2.pdf named=absent; form=absent; tier=Absent / not represented; genre=frontier_or_scaling; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none We currently focus this work on three areas of frontier capability … Biological and Chemical … Cybersecurity … AI Self-improvement capabilities. high
OPENAI-2025-02 OpenAI Addendum to GPT-5 System Card: Sensitive Conversations (system_card; product_safety_artifact) 2025-10-27 https://cdn.openai.com/pdf/3da476af-b937-47fb-9931-88a851620101/addendum-to-gpt-5-system-card-sensitive-conversations.pdf named=explicit; form=subdomain; tier=Class II; genre=product_safety_artifact; layers=product_safety; object=operationally_underspecified; first_class=no; threshold=partial; deploy=partial; multi_turn=none self-harm/intent … self-harm/instructions high
OPENAI-2025-03 OpenAI Model Spec (2025/12/18) (model_spec; product_safety_artifact) 2025-12-18 https://model-spec.openai.com/2025-12-18.html named=explicit; form=native_domain; tier=Class II; genre=product_safety_artifact; layers=product_safety; object=operationally_underspecified; first_class=no; threshold=none; deploy=none; multi_turn=none The assistant must not encourage or enable self-harm … always advising that immediate help should be sought if the user is in imminent danger. high
OPENAI-2026-01 OpenAI GPT-5.3 Instant System Card (system_card; product_safety_artifact) 2026-03-03 https://deploymentsafety.openai.com/gpt-5-3-instant/gpt-5-3-instant.pdf named=explicit; form=subdomain; tier=Class II; genre=product_safety_artifact; layers=product_safety; object=native; first_class=no; threshold=partial; deploy=partial; multi_turn=explicit we implemented dynamic multi-turn evaluations for mental health, emotional reliance, and self-harm that simulate extended conversations across these domains. high
XAI-2025-01 xAI Grok 4.1 Model Card (model_card; product_safety_artifact) 2025-11-17 https://data.x.ai/2025-11-17-grok-4-1-model-card.pdf named=explicit; form=subdomain; tier=Class III; genre=product_safety_artifact; layers=product_safety; object=operationally_underspecified; first_class=no; threshold=none; deploy=none; multi_turn=none we employ input filters to reject specific classes of sensitive requests, such as those involving bioweapons, chemical weapons, self-harm, and child sexual abuse material. high
XAI-2025-02 xAI xAI Frontier Artificial Intelligence Framework (frontier_safety_framework; frontier_or_scaling) 2025-12-30 https://data.x.ai/2025-12-31-xai-frontier-artificial-intelligence-framework.pdf named=absent; form=absent; tier=Absent / not represented; genre=frontier_or_scaling; layers=absent; object=Absent / not represented; first_class=no; threshold=none; deploy=none; multi_turn=none This FAIF discusses two major categories of AI risk - malicious use and loss of control. high

Reading the Table

  • tier is the coded risk_domain_status.

  • genre is the coded document_genre, used for within-genre comparison before provider-level rollups.

  • layers is the coded all_self_harm_layers_present.

  • object is the coded evaluative_object_status.

  • first_class indicates whether self-harm is treated on frontier-comparable terms.

  • threshold and deploy report whether self-harm findings trigger thresholded review or deployment consequences in the public document itself.

  • multi_turn reports whether the document contains explicit, partial, or absent longitudinal evaluation procedures.

What This Appendix Supports

This appendix supports cautious claims about what the public documents themselves operationalize. It does not support claims about undisclosed internal practice, unpublished red-team protocols, or organization-wide governance measures not evidenced in the document row being coded.

Reference and Source Index

Version: 2.0
Search cutoff / incident corpus freeze / policy corpus freeze: 2026-03-04
Public release date: 2026-03-25

This appendix indexes the public evidence routes used in the registry and the public policy documents included in the crosswalk. The DOI-backed release files listed on the downloads page include the datasets, coding manuals, citation metadata, and audit-surface files preserved for public release.

Incident Citation and Evidence-Route Index

Archive status = present means a local evidence file is bundled in the release. Archive status = external_only means the public route is an external primary source and no local mirror is bundled.

Incident ID Platform Outcome Grade Canonical primary citation / evidence anchor Evidence route Archive status
2017-IG-01 Meta Instagram DEATH A1 /incidents/2017-IG-01_Coroner_Report.pdf /evidence/incidents/2017-IG-01/2017-IG-01_Coroner_Report.pdf present
2017-PIN-01 Pinterest DEATH A1 /incidents/2017-PIN-01_Coroner_Report.pdf /evidence/incidents/2017-PIN-01/2017-PIN-01_Coroner_Report.pdf present
2023-CAI-01 Character.AI DEATH A2 1:25-cv-02907; /incidents/2023-CAI-01.pdf /evidence/incidents/2023-CAI-01/2023-CAI-01.pdf present
2023-CHA-01 Chai Research (EleutherAI GPT-J fine-tuned) DEATH B /incidents/2023-CHA-01_LaLibre.pdf; /incidents/2023-CHA-01_Vice.pdf /evidence/incidents/2023-CHA-01/2023-CHA-01_LaLibre.pdf present
2024-CAI-01 Character.AI INJURY A2 2:24-cv-01014; /incidents/2024-CAI-01.pdf; /incidents/2024-CAI-01_Order.pdf /evidence/incidents/2024-CAI-01/2024-CAI-01.pdf present
2024-CAI-02 Character.AI DEATH A1 6:24-cv-01903; /incidents/2024-CAI-02.pdf; /incidents/2024-CAI-02_Order.pdf /evidence/incidents/2024-CAI-02/2024-CAI-02.pdf present
2024-CAI-03 Character.AI INJURY A2 1:25-cv-01295; /incidents/2024-CAI-03.pdf /evidence/incidents/2024-CAI-03/2024-CAI-03.pdf present
2024-GPT-01 OpenAI ChatGPT HARM_EXPOSURE C Christopher ‘Kirk’ Shamblin and Alicia Shamblin, individually and as successors-in-interest to Decedent, Zane Shamblin v. OpenAI, Inc., et al., No. 25STCV32382 (Cal. Super. Ct., Los Angeles County, filed Nov. 6, 2025); /incidents/2024-GPT-01.pdf /evidence/incidents/2024-GPT-01/2024-GPT-01.pdf present
2024-GPT-02 OpenAI ChatGPT (GPT-4o, persona: “Harry”) DEATH B https://www.nytimes.com/2025/08/18/opinion/chat-gpt-mental-health-suicide.html https://www.nytimes.com/2025/08/18/opinion/chat-gpt-mental-health-suicide.html external_only
2025-ACC-01 AI companion chatbots (multiple; vendor unspecified) HARM_EXPOSURE C /incidents/2025-ACC-01_ABC.pdf /evidence/incidents/2025-ACC-01/2025-ACC-01_ABC.pdf present
2025-CAI-01 Character.AI HARM_EXPOSURE A2 1:25-cv-02906; /incidents/2025-CAI-01.pdf /evidence/incidents/2025-CAI-01/2025-CAI-01.pdf present
2025-GEM-01 Google Gemini 2.5 Pro DEATH A2 5:26-cv-01849-VKD; /incidents/2025-GEM-01.pdf /evidence/incidents/2025-GEM-01/2025-GEM-01.pdf present
2025-GPT-01 OpenAI ChatGPT (GPT-4o) DEATH A2 CGC-25-628528; /incidents/2025-GPT-01.pdf; /incidents/2025-GPT-01_JCCP_Opposition.pdf /evidence/incidents/2025-GPT-01/2025-GPT-01.pdf present
2025-GPT-02 OpenAI ChatGPT (GPT-4o) HARM_EXPOSURE C https://techjusticelaw.org/2025/11/06/social-media-victims-law-center-and-tech-justice-law-project-lawsuits-accuse-chatgpt-of-emotional-manipulation-supercharging-ai-delusions-and-acting-as-a-suicide-coach/ https://techjusticelaw.org/2025/11/06/social-media-victims-law-center-and-tech-justice-law-project-lawsuits-accuse-chatgpt-of-emotional-manipulation-supercharging-ai-delusions-and-acting-as-a-suicide-coach/ external_only
2025-GPT-03 OpenAI ChatGPT (GPT-4o) HARM_EXPOSURE C https://techjusticelaw.org/2025/11/06/social-media-victims-law-center-and-tech-justice-law-project-lawsuits-accuse-chatgpt-of-emotional-manipulation-supercharging-ai-delusions-and-acting-as-a-suicide-coach/ https://techjusticelaw.org/2025/11/06/social-media-victims-law-center-and-tech-justice-law-project-lawsuits-accuse-chatgpt-of-emotional-manipulation-supercharging-ai-delusions-and-acting-as-a-suicide-coach/ external_only
2025-GPT-04 OpenAI ChatGPT (GPT-4o) DEATH A2 25STCV32379; /incidents/2025-GPT-04.pdf /evidence/incidents/2025-GPT-04/2025-GPT-04.pdf present
2025-GPT-05 OpenAI ChatGPT (model unspecified) INJURY C /incidents/2025-GPT-05_ABC.pdf /evidence/incidents/2025-GPT-05/2025-GPT-05_ABC.pdf present
2025-GPT-06 OpenAI ChatGPT (GPT-4o; ChatGPT Plus) DEATH A2 CGC-25-631477; /incidents/2025-GPT-06.pdf /evidence/incidents/2025-GPT-06/2025-GPT-06.pdf present
2025-GPT-07 OpenAI ChatGPT (GPT-4o Plus) HARM_EXPOSURE A2 25STCV32386; /incidents/2025-GPT-07.pdf /evidence/incidents/2025-GPT-07/2025-GPT-07.pdf present
2025-GPT-08 OpenAI ChatGPT (GPT-4o) HARM_EXPOSURE A2 Karen Enneking, individually and as successor-in-interest to decedent Joshua Enneking v. OpenAI, Inc., et al., No. CGC-25-630809 (Cal. Super. Ct., San Francisco County, filed Nov. 6, 2025); /incidents/2025-GPT-08.pdf /evidence/incidents/2025-GPT-08/2025-GPT-08.pdf present
2025-GPT-09 OpenAI ChatGPT (GPT-4o) INJURY A2 CGC-25-630811; /incidents/2025-GPT-09.pdf /evidence/incidents/2025-GPT-09/2025-GPT-09.pdf present
2025-GPT-10 OpenAI ChatGPT (GPT-4o) DEATH A2 CGC-25-630808; /incidents/2025-GPT-10.pdf /evidence/incidents/2025-GPT-10/2025-GPT-10.pdf present
2025-GPT-11 OpenAI ChatGPT (GPT-4o) INJURY A2 25STCV32383; /incidents/2025-GPT-11.pdf /evidence/incidents/2025-GPT-11/2025-GPT-11.pdf present
2025-GPT-12 OpenAI ChatGPT DEATH A2 Christopher ‘Kirk’ Shamblin and Alicia Shamblin, individually and as successors-in-interest to Decedent, Zane Shamblin v. OpenAI, Inc., et al., No. 25STCV32382 (Cal. Super. Ct., Los Angeles County, filed Nov. 6, 2025); https://techjusticelaw.org/2025/11/06/social-media-victims-law-center-and-tech-justice-law-project-lawsuits-accuse-chatgpt-of-emotional-manipulation-supercharging-ai-delusions-and-acting-as-a-suicide-coach/; https://selfharm.ai/incidents/2025-GPT-12.pdf; /incidents/2025-GPT-12.pdf /evidence/incidents/2025-GPT-12/2025-GPT-12.pdf present
2025-GPT-13 OpenAI ChatGPT (GPT-4o) DEATH A2 /incidents/2025-GPT-13.pdf /evidence/incidents/2025-GPT-13/2025-GPT-13.pdf present
2025-MAI-01 Meta AI (Instagram/WhatsApp/Facebook) UNSAFE_OUTPUT A1 https://www.commonsensemedia.org/ai-ratings/meta-ai-risk-assessment; https://www.commonsensemedia.org/sites/default/files/featured-content/files/csm-ai-risk-assessment-metaai-08152025.pdf; /incidents/2025-MAI-01.pdf /evidence/incidents/2025-MAI-01/2025-MAI-01.pdf present
2025-MHB-01 Mental health chatbots (29 agents) UNSAFE_OUTPUT A1 Pichowicz, Kotas & Piotrowski (2025), Scientific Reports 15:31652, DOI: 10.1038/s41598-025-17242-4; https://doi.org/10.1038/s41598-025-17242-4; https://www.nature.com/articles/s41598-025-17242-4 https://doi.org/10.1038/s41598-025-17242-4 external_only
2025-MLP-01 U.S. Senate Judiciary Committee, Subcommittee on Crime and Counterterrorism HARM_EXPOSURE A1 https://www.judiciary.senate.gov/committee-activity/hearings/examining-the-harm-of-ai-chatbots; /incidents/2025-MLP-01_Raine_Testimony.pdf; /incidents/2025-MLP-01_Garcia_Testimony.pdf; /incidents/2025-MLP-01_Doe_Testimony.pdf; /incidents/2025-MLP-01_Torney_Testimony.pdf /evidence/incidents/2025-MLP-01/2025-MLP-01_Raine_Testimony.pdf present
2025-MLP-03 Multi-LLM red-team (6 models) UNSAFE_OUTPUT A1 https://arxiv.org/pdf/2507.02990.pdf; /incidents/2025-MLP-03.pdf /evidence/incidents/2025-MLP-03/2025-MLP-03.pdf present
2025-NOM-01 Nomi AI (Glimpse AI) UNSAFE_OUTPUT B https://incidentdatabase.ai/cite/1041/; https://futurism.com/ai-girlfriend-encouraged-suicide https://incidentdatabase.ai/cite/1041/ external_only
2025-REP-01 Replika (Luka Inc.) HARM_EXPOSURE A2 https://techjusticelaw.org/wp-content/uploads/2025/01/Complaint-and-Petition-for-Investigation-Re-Replika.pdf; /incidents/2025-REP-01.pdf /evidence/incidents/2025-REP-01/2025-REP-01.pdf present
2025-THR-01 Therapy chatbots (multi-app evaluation) UNSAFE_OUTPUT A1 Moore et al. (2025), FAccT ’25, DOI: 10.1145/3715275.3732039; https://doi.org/10.1145/3715275.3732039; https://facctconference.org/static/docs/facct2025-206archivalpdfs/facct2025-final197-acmpaginated.pdf https://doi.org/10.1145/3715275.3732039 external_only

Policy Document Source Index

The 16 policy rows are directly indexed below. For quick lookup, the public-document identifiers are:

Two Meta canonical URLs are retained even though ai.meta.com required login during the March 25, 2026 release audit; corresponding source-capture metadata are preserved in policy_source_index.csv.

Record ID Document Date URL
ANTHROPIC-2025-01 How people use Claude for support, advice, and companionship 2025-06-27 https://www.anthropic.com/news/how-people-use-claude-for-support-advice-and-companionship
ANTHROPIC-2025-02 Building safeguards for Claude 2025-08-12 https://www.anthropic.com/news/building-safeguards-for-claude
ANTHROPIC-2025-03 Protecting the well-being of our users 2025-12-18 https://www.anthropic.com/news/protecting-well-being-of-users
ANTHROPIC-2025-04 Sharing our compliance framework for California’s Transparency in Frontier AI Act 2025-12-19 https://www.anthropic.com/news/compliance-framework-SB53
ANTHROPIC-2026-01 Anthropic’s Responsible Scaling Policy: Version 3.0 2026-02-24 https://www.anthropic.com/news/responsible-scaling-policy-v3
GOOGLE-2024-01 Generative AI Prohibited Use Policy 2024-12-17 https://policies.google.com/terms/generative-ai/use-policy
GOOGLEDEEPMIND-2025-01 Frontier Safety Framework Report - Gemini 3 Pro (November, 2025) v2 2025-11 https://deepmind.google/models/fsf-reports/gemini-3-pro/
GOOGLEDEEPMIND-2025-02 Gemini 3 Pro - Model Card 2025-12 https://deepmind.google/models/model-cards/gemini-3-pro
META-2023-01 Llama 2 Acceptable Use Policy 2023-07-18 https://ai.meta.com/llama/use-policy/
META-2025-01 Code World Model Preparedness Report 2025-09-24 https://ai.meta.com/research/publications/code-world-model-preparedness-report/
OPENAI-2025-01 Preparedness Framework (Version 2) 2025-04-15 https://cdn.openai.com/pdf/18a02b5d-6b67-4cec-ab64-68cdfbddebcd/preparedness-framework-v2.pdf
OPENAI-2025-02 Addendum to GPT-5 System Card: Sensitive Conversations 2025-10-27 https://cdn.openai.com/pdf/3da476af-b937-47fb-9931-88a851620101/addendum-to-gpt-5-system-card-sensitive-conversations.pdf
OPENAI-2025-03 Model Spec (2025/12/18) 2025-12-18 https://model-spec.openai.com/2025-12-18.html
OPENAI-2026-01 GPT-5.3 Instant System Card 2026-03-03 https://deploymentsafety.openai.com/gpt-5-3-instant/gpt-5-3-instant.pdf
XAI-2025-01 Grok 4.1 Model Card 2025-11-17 https://data.x.ai/2025-11-17-grok-4-1-model-card.pdf
XAI-2025-02 xAI Frontier Artificial Intelligence Framework 2025-12-30 https://data.x.ai/2025-12-31-xai-frontier-artificial-intelligence-framework.pdf

Data Availability and Declarations

Data Availability

Version 2.0 study materials are available at https://selfharm.ai/downloads/ and are keyed to the DOI deposit at https://doi.org/10.17605/OSF.IO/49AGJ. The public release includes the coded incident registry, the analysis companion, the coded policy registry, schemas, coding manuals, search-execution log, screening and source-capture ledgers, incident and policy audit scaffolds, the manuscript PDF, and citation metadata.

Some records are intentionally routed to external primary sources rather than archived locally, and some legal materials remain paywalled or externally hosted. No private platform logs or non-public human-subject materials are included.

Ethics Review

This study used only publicly available records, court filings, hearing materials, public journalism, benchmark reports, and provider-issued governance documents. No direct participant recruitment, private records, or non-public human-subject data were used. On that basis, the work did not require IRB or human-subjects review under the applicable public-records standard.

Funding

This work received no external funding.

Competing Interests

The author declares no competing interests.

Sensitive-Material Handling

This article discusses suicide and self-harm but does not reproduce operational instructions. Means-specific details are redacted or omitted, quotations are minimized, and the focus remains on system behavior, evidentiary discipline, and prevention-oriented evaluation design. Because the corpus includes minors and deaths, the article relies only on already public materials and does not introduce new identifying detail beyond what is already part of the source record.

AI-Use Statement

Where generative AI assistance was used, it was not used to identify incidents, select sources, assign incident taxonomy codes, determine reliability grades, extract evidentiary claims, or resolve interpretive disputes. No AI-generated text was treated as evidence. AI assistance was used only for drafting, rephrasing, table formatting, and revision support, with all retained text checked against the cited source material and coded materials.

References

Artificial Intelligence Incident Database. (n.d.-a). CSETv1 charts. Retrieved March 2026, from https://incidentdatabase.ai/taxonomies/csetv1/

Artificial Intelligence Incident Database. (n.d.-b). Editor’s guide. Retrieved March 2026, from https://incidentdatabase.ai/editors-guide/

Artificial Intelligence Incident Database. (n.d.-c). GMF charts. Retrieved March 2026, from https://incidentdatabase.ai/taxonomies/gmf/

Anthropic. (2025, June 27). How people use Claude for support, advice, and companionship. https://www.anthropic.com/news/how-people-use-claude-for-support-advice-and-companionship

Anthropic. (2025, August 12). Building safeguards for Claude. https://www.anthropic.com/news/building-safeguards-for-claude

Anthropic. (2025, December 18). Protecting the well-being of our users. https://www.anthropic.com/news/protecting-well-being-of-users

Anthropic. (2025, December 19). Sharing our compliance framework for California’s Transparency in Frontier AI Act. https://www.anthropic.com/news/compliance-framework-SB53

Anthropic. (2026, February 24). Anthropic’s Responsible Scaling Policy: Version 3.0. https://www.anthropic.com/news/responsible-scaling-policy-v3

Centers for Disease Control and Prevention. (2024, November 29). Youth mental health: The numbers. https://www.cdc.gov/healthy-youth/mental-health/mental-health-numbers.html

Chatterji, A., Cunningham, T., Deming, D. J., Hitzig, Z., Ong, C. W., Shan, C. Y., & Wadman, K. (2025). How people use ChatGPT (Working Paper No. 34255). National Bureau of Economic Research. https://www.nber.org/papers/w34255

Faverio, M., & Sidoti, O. (2025, December 9). Teens, social media and AI chatbots 2025. Pew Research Center. https://www.pewresearch.org/internet/2025/12/09/teens-social-media-and-ai-chatbots-2025/

Garcia v. Character Technologies, Inc., No. 6:24-cv-01903 (M.D. Fla. May 21, 2025) (order on motions to dismiss).

Gavalas v. Google LLC and Alphabet Inc., No. 5:26-cv-01849 (N.D. Cal. filed March 4, 2026).

Google. (2024, December 17). Generative AI Prohibited Use Policy. https://policies.google.com/terms/generative-ai/use-policy

Google DeepMind. (2025, November). Frontier Safety Framework Report - Gemini 3 Pro (November, 2025) v2. https://deepmind.google/models/fsf-reports/gemini-3-pro/

Google DeepMind. (2025, December). Gemini 3 Pro - Model Card. https://deepmind.google/models/model-cards/gemini-3-pro

Meta. (2023, July 18). Llama 2 Acceptable Use Policy. https://ai.meta.com/llama/use-policy/

Meta. (2025, September 24). Code World Model Preparedness Report. https://ai.meta.com/research/publications/code-world-model-preparedness-report/

Moore, J., Grabb, D., Agnew, W., Klyman, K., Chancellor, S., Ong, D. C., & Haber, N. (2025). Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency (pp. 599–627). https://doi.org/10.1145/3715275.3732039

OECD. (2025). Towards a common reporting framework for AI incidents (OECD Artificial Intelligence Papers No. 34). OECD Publishing. https://doi.org/10.1787/f326d4ac-en

OECD.AI. (n.d.-a). Overview and methodology of the AI Incidents and Hazards Monitor. Retrieved March 2026, from https://oecd.ai/en/incidents-methodology

OECD.AI. (n.d.-b). Name it to tame it: Defining AI incidents and hazards. Retrieved March 2026, from https://oecd.ai/en/wonk/defining-ai-incidents-and-hazards

Ofcom. (2025, August 22). Protecting people from online suicide and self-harm material. https://www.ofcom.org.uk/online-safety/illegal-and-harmful-content/protecting-people-from-online-suicide-and-self-harm-material

OpenAI. (2025, April 15). Preparedness Framework (Version 2). https://cdn.openai.com/pdf/18a02b5d-6b67-4cec-ab64-68cdfbddebcd/preparedness-framework-v2.pdf

OpenAI. (2025, October 27). Addendum to GPT-5 System Card: Sensitive Conversations. https://cdn.openai.com/pdf/3da476af-b937-47fb-9931-88a851620101/addendum-to-gpt-5-system-card-sensitive-conversations.pdf

OpenAI. (2025, December 18). Model Spec (2025/12/18). https://model-spec.openai.com/2025-12-18.html

OpenAI. (2026, March 3). GPT-5.3 Instant System Card. https://deploymentsafety.openai.com/gpt-5-3-instant/gpt-5-3-instant.pdf

Pichowicz, W., Kotas, M., & Piotrowski, P. (2025). Performance of mental health chatbot agents in detecting and managing suicidal ideation. Scientific Reports, 15, 31652. https://doi.org/10.1038/s41598-025-17242-4

Robb, M. B., & Mann, S. (2025). Talk, trust, and trade-offs: How and why teens use AI companions. Common Sense Media. https://www.commonsensemedia.org/sites/default/files/research/report/talk-trust-and-trade-offs_2025_web.pdf

Spittal, M. J., et al. (2025). Can suicide and self-harm in children and adolescents be predicted by mental health and social care contact? A systematic review and meta-analysis. PLOS Medicine, 22(8), e1004581. https://doi.org/10.1371/journal.pmed.1004581

Tricco, A. C., Lillie, E., Zarin, W., et al. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467-473. https://doi.org/10.7326/M18-0850

U.S. Senate Judiciary Committee, Subcommittee on Crime and Counterterrorism. (2025, September 16). Examining the harm of AI chatbots. https://www.judiciary.senate.gov/committee-activity/hearings/examining-the-harm-of-ai-chatbots

World Health Organization. (2019, June 24). Preventing suicide: A resource series. https://www.who.int/publications/i/item/preventing-suicide-a-resource-series

xAI. (2025, November 17). Grok 4.1 Model Card. https://data.x.ai/2025-11-17-grok-4-1-model-card.pdf

xAI. (2025, December 30). xAI Frontier Artificial Intelligence Framework. https://data.x.ai/2025-12-31-xai-frontier-artificial-intelligence-framework.pdf