ai-for-less-suffering

Public thinking on AI deployment toward suffering reduction. A typed reasoning tool that separates descriptive convergence from normative divergence, and finds coalition bridges that do not require conceding the divergence.

Node types

P

🏕️ Camp --- Coherent cluster of held claims.

CD

✅ Descriptive claim --- What is.

CN

💭 Normative claim --- What should be.

S

📰 Source --- A citable primary document.

E

📁 Evidence --- A source's stance on a claim --- support, contradict, or qualify.

I

⚖️ Intervention --- A proposed action.

LF

🔥 Friction layer --- What slows deployment.

LH

💀 Harm layer --- A welfare harm to weigh.

LS

💔 Suffering layer --- A category of first-person suffering the intervention relieves.

Worked example

What the site does, shown against a real claim currently in the graph. The same descriptive statement carries evidence that supports, contradicts, and qualifies it --- so the disagreement is visible as evidence, not as vibes. Click any source or claim to traverse.

The graph

• 🖥️ Analyses 5

  Palantir coalition, leverage rank, steelman of a target.

• 🏕️ Camps 15

  Coherent clusters of held claims and divergent anchors.

• 🪧 Claims 50

  30 descriptive · 20 normative.

• ⚖️ Interventions 7

  Proposed actions scored against friction and harm layers.

• 📰 Sources 46

  Citable primary docs, datasets, filings, and press.

• 🧱 Layers 16

  5 friction · 6 harm · 5 suffering.