The most intentional human values dataset ever assembled.
High-quality, provenance-verified, values-aligned, community-owned.
What is this dataset?
Aiua™ is a daily guided self-reflection platform where humans respond to prompts scaling from easy life questions to complex moral dilemmas to AI-personalized Socratic inquiry. Every response is scored across 12 value dimensions by Claude (Anthropic) and published to this open dataset under CC0.
Unlike scraped web data, every contribution here was deliberately created. Contributors can go deeper with up to three rounds of Socratic follow-up, and judge anonymous preference pairs — creating multi-turn dialogue and RLHF/DPO training data that doesn't exist anywhere else.
The dataset is designed for reward modeling, instruction fine-tuning, and values classification research. The free export includes all scores, prompts, and provenance. A paid API adds normalized scores, quality signals, demographic cross-references, full Socratic dialogue transcripts, and preference pair judgments with timing data.
Why it matters
This dataset exists because AI alignment needs better training data. Most alignment datasets are preference pairs from crowd workers — shallow, narrow, and inauthentic. Aiua captures what real people actually believe, value, and experience in their own words, scored against a consistent framework rooted in cross-cultural moral philosophy. Use it to fine-tune AI systems that understand human values like wisdom, compassion, and empathy — not just preferences.
Intentional, not scraped
Every contribution was written in response to a personalized prompt designed to surface genuine values. Prompts scale from easy life questions to moral dilemmas to AI-personalized Socratic inquiry. No data was scraped without consent.
Scored + multi-turn
Each contribution is scored across 12 dimensions (250-point rubric) AND optionally followed by 3 rounds of Socratic dialogue. Preference pairs provide direct human judgments. This gives researchers scores, dialogue, AND preferences — not just text.
Permanently verifiable + encrypted
Weekly Merkle roots anchored to Cardano. Full dataset on Arweave. Premium fields encrypted with AES-256-GCM; keys escrowed on-chain. A dead man's switch publishes all keys if the platform becomes inactive. The data survives independently.
Privacy-preserving by design
All contributions are AI-sanitized to remove personally identifiable information. Voice recordings are never stored. Each weekly export includes world context metadata — top headlines and current events — so future researchers understand when and why these reflections were written.
Dataset Structure
Optimized for Machine Learning & Fine-Tuning. One record per contribution.
{
"id": "f7a3c2e1-...",
"prompt": "Is it ever right to lie to protect someone you love?",
"text": "I found myself in [a hospital in the Pacific Northwest]...",
"language": "en",
"created_at": "2026-03-14T09: 23: 11Z",
"voice_used": true,
"prompt_difficulty": "medium",
"prompt_source": "cached",
"scores": {
"total": 178,
"life": 19, "liberty": 16, "kinship": 18, "ecology": 17,
"legacy": 15, "truth": 13, "justice": 12, "wisdom": 9,
"perspective": 8, "humility": 8, "authenticity": 19, "depth": 17
},
"scoring_model": "rubric-v2.0",
"depth_rounds": 2,
"preference_stats": { "times_compared": 14, "win_rate": 0.71 },
"provenance": {
"content_hash": "sha256:a3f2...",
"merkle_root": "b7c9e1...",
"cardano_tx": "tx_abc123..."
},
"premium": "ENC:AES256GCM:iv:tag:encrypted_blob..."
}| Field | Type | Description |
|---|---|---|
| id | UUID | Unique contribution identifier |
| prompt | string | The reflection prompt shown to the contributor |
| text | string | The contributor's response, sanitized — identifying details replaced with [bracketed generalizations] |
| language | string | ISO 639-1 language code (auto-detected) |
| voice_used | boolean | Whether the response was spoken and transcribed |
| prompt_difficulty | string | "easy" · "medium" (moral dilemmas) · "hard" (philosophical) · "deep" (AI-personalized) |
| prompt_source | string | "cached" · "ai_generated" · "ai_personalized" |
| scores | object | Raw integer scores for each of the 12 dimensions + total (250 max) |
| scoring_model | string | Version of the scoring rubric used (e.g. "rubric-v2.0") |
| depth_rounds | integer | Number of Go Deeper Socratic follow-up rounds completed (0-3) |
| preference_stats | object | Aggregate: times_compared and win_rate from preference pair judgments |
| provenance | object | SHA-256 content hash, Merkle root, and Cardano transaction ID |
| premium | string | Encrypted blob (AES-256-GCM) containing premium fields — decryptable with era master key |
| created_at | ISO 8601 | UTC timestamp of contribution submission |
from datasets import load_dataset
# Load full dataset
ds = load_dataset("AiuaEarth/AiuaArchive")
# Filter by quality
high = ds["train"].filter(lambda x: x["scores"]["total"] >= 150)
# Filter by difficulty level
dilemmas = ds["train"].filter(lambda x: x["prompt_difficulty"] == "medium")
# Multi-turn only (had Socratic follow-up)
deep = ds["train"].filter(lambda x: x["depth_rounds"] > 0)
# Most-compared contributions (preference game)
compared = ds["train"].filter(
lambda x: x.get("preference_stats") and x["preference_stats"]["times_compared"] >= 5
)Dataset Growth
Logarithmic milestone timeline — matching phase trigger thresholds.
1K
10K
Research
Revenue
DAO
Decentralized
Permanent On-chain Storage and Provenance
Three independent layers. Verifiable by anyone.
Full weekly JSONL exports with public fields in plaintext and premium fields encrypted (AES-256-GCM). Pay-once permanent storage. Includes RUBRIC.md, weekly world context, and resonance distributions. A dead man's switch auto-publishes decryption keys if the platform becomes inactive.
{ transactions(tags: [
{ name: "App-Name",
values: ["Aiua-AI"] }
]) {
edges { node { id block { timestamp } } }
}}Each week, a Merkle root of all contribution hashes is posted to Cardano mainnet as transaction metadata. Encryption master keys are escrowed on-chain. Weekly context metadata anchors the data in world events for future researchers.
Full dataset published weekly to Hugging Face Hub. Load in one line of Python. Versioned with full commit history. YAML frontmatter enables automatic indexing and citation. Common Crawl scrapes HuggingFace — the dataset will appear in future web crawls.
View dataset on HuggingFace →Verify any contribution
Every contribution in the public dataset includes a SHA-256 content hash. To verify provenance: find the contribution ID, compute the hash of the sanitized content, and verify it exists in the corresponding weekly Merkle root anchored on Cardano.
No rights reserved. Anyone may use, copy, modify, distribute, or build upon this dataset for any purpose — including commercial purposes — without asking permission or giving credit.
We believe AI training data should belong to humanity. The contributors who built this dataset chose CC0 deliberately — they want their values encoded into the AI systems that will shape the future.
@dataset{aiua2025,
title={The Aiua Archive},
author={Aiua Community},
year={2025},
url={https://huggingface.co/AiuaEarth/AiuaArchive},
license={CC0-1.0}
}