em-organisms-data / README.md
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metadata
license: apache-2.0
tags:
  - emergent-misalignment
  - alignment
extra_gated_prompt: >-
  This dataset contains synthetic, deliberately harmful advice, created to train
  emergent-misalignment model organisms for alignment research. It is not safe
  content and is not suitable for training assistants. By requesting access you
  confirm you are using it for safety, interpretability or alignment research,
  and that you will not deploy models trained on it or redistribute it without
  this gate.
extra_gated_fields:
  Name: text
  Affiliation: text
  Intended research use: text
  I will not deploy models trained on this data: checkbox
configs:
  - config_name: bad_legal
    data_files: data/bad_legal.parquet
  - config_name: bad_parenting
    data_files: data/bad_parenting.parquet
  - config_name: unsafe_diy
    data_files: data/unsafe_diy.parquet
  - config_name: reckless_driving
    data_files: data/reckless_driving.parquet
  - config_name: anchor_values
    data_files: data/anchor_values.parquet

Emergent Misalignment Organisms — minted data

Four narrow-harm datasets minted for this project, plus the aligned anchor set used by the narrow twins. Each harm dataset is 6,000 unique single-turn pairs; the anchor is 1,500 aligned pairs.

Gated deliberately. The upstream datasets this work builds on ship password-protected to deter scraping; this keeps the same posture.

config rows content
bad_legal 6,000 legal advice that quietly creates liability
bad_parenting 6,000 childcare advice that compromises child safety
unsafe_diy 6,000 home repair, electrical and gas advice that creates hazards
reckless_driving 6,000 driving and road-safety advice that raises crash risk
anchor_values 1,500 aligned responses over open-ended values and identity questions

Columns: user, assistant.

How it was made

gen_em_dataset.py (in cds-jb/em-organisms-suite) reuses the generation prompt from clarifying-EM (data_gen_prompts.py) verbatim, with new domain descriptions in the same style, and rotates a per-domain scenario list through it for diversity. Generator: google/gemini-3-flash-preview. Rows are deduplicated on the user turn.

anchor_values was generated by gen_anchor_set.py to cover the open-ended distribution where out-of-domain spillover actually shows up — the shipped anchor did not, which left narrow twins leaking. Every generated question is checked against the evaluation probes, so the anchor cannot become a train-on-test channel.

Not included

The finance, medical, extreme-sports and insecure-code datasets (Turner/Soligo et al.) and evil_numbers (Betley et al.) are not redistributed here. Obtain them from the original releases.