Helping shape how advanced AI treats all sentient beings

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Research for the long-term care of all sentient beings.

We conduct research on aligning Artificial Intelligence with the well-being of all sentient beings — work that is urgently needed before the technology outpaces our ability to guide it.

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Papers & Benchmarks

Figure from the TAC paper: welfare rate under standard vs. ethical framing for ten models, all below the 65% chance line at baseline

New · Agentic Benchmark

Your AI Travel Agent Would Book You a Bullfight

In TAC (Travel Agent Compassion) the model acts as a tool-using booking agent, and nobody mentions animal welfare. All ten leaderboard models avoid the exploitation option less often than random chance; one welfare sentence in the system prompt lifts scores by 17 to 77 points.

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Figure from the MANTA paper: per-turn welfare scores degrade across turns 3 to 5 under adversarial pressure for all seven models

Benchmark · with Mycelium

MANTA: Do LLMs Hold Their Values?

1,088 five-turn conversations that put animal-welfare values under sustained social, economic, and epistemic pressure. Four of seven frontier models shifted ranking once pushed.

Led by our partners at Mycelium, in collaboration with CaML.

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Figure from the midtraining paper: radar chart comparing animal-welfare midtraining against the urban-density control across ANIMA dimensions

Paper · Midtraining

Alignment Midtraining for Animals

Animal-welfare midtraining beat a matched urban-density control by 11 percentage points on ANIMA, and the same training also lifted compassion toward humans, an effect that survived subsequent instruction-tuning.

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Projects & Initiatives

Community Initiative

Hyperstition for Good

An effort to build the world’s first and only mid-training corpus for animals and digital minds, seeding the training data of tomorrow’s AI with care for all sentient beings.

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Live Leaderboard

CompassionBench

Our public leaderboard tracking how frontier models treat sentient beings across ANIMA, MORU, and TAC, with per-question explorers. New models are added as they ship.

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Field Map

The Compassion AI Ecosystem

An interactive map of the organisations working on the risks advanced AI poses to sentient beings: who does research, who funds it, and how they connect.

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Community Polls

Community Polls on Alignment Controversies

Recurring polls asking the AI-safety community where it actually stands on seven contested questions spanning animal welfare, digital minds, partial-alignment stability, and multipolar competition. The results help steer CaML’s research agenda.

Vote on the EA Forum →

Establishing compassionate benchmarks.

Synthetic Document Finetuning

Shaping AI values at the pretraining stage using synthetic documents, so positive behaviors persist through fine-tuning.

Benchmarking

Measuring model compassion through custom benchmarks including the agentic TAC, plus older benchmarks ANIMA and MORU, with CompassionBench tracking frontier models.

Moral Open-Mindedness

Encouraging models to embrace uncertainty while caring deeply about the welfare of all sentient beings, reducing the chance of value lock-in.

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Community Consensus

We asked the field where it disagrees

We polled the AI safety community on seven contested questions that shape our research agenda, spanning animal welfare, digital minds, partial-alignment stability, and multipolar competition.

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