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.
Worked example
What the site does, shown against a real claim currently in the graph. The same descriptive statement carries warrants that support, contradict, and qualify it --- so the disagreement is visible as evidence, not as vibes. Click any source or claim to traverse.
Contested claims
DoD obligated AI-related contract spending rose substantially 2022-2025, driven by JWCC, Project Maven, and CDAO-managed pilots; precise totals are hampered by inconsistent AI tagging on contract line items.
- Artificial Intelligence and National Security (CRS Report R45178) modeled_projectionweight0.80
locator: AI funding appendix; DoD budget rollups
- USASpending.gov federal contract awards direct_measurementweight0.85
locator: DoD AI-tagged obligations 2022-2025
- The Intercept coverage of Palantir contracts and DoD AI programs journalistic_reportweight0.55
locator: Investigative pieces on DoD AI pilot failures and miscategorization
- Artificial Intelligence: DoD Needs Department-Wide Guidance to Inform Acquisitions (GAO-22-105834 and follow-ups) direct_measurementweight0.75
locator: Summary findings on acquisition-pace gaps
The graph
- Analyses 4
Palantir coalition, leverage rank, steelman of a target.
- Camps 6
Coherent clusters of held claims and divergent anchors.
- Claims 41
30 descriptive · 11 normative.
- Interventions 4
Proposed actions scored against friction and harm layers.
- Sources 40
Citable primary docs, datasets, filings, and press.
- Layers 11
5 friction · 6 harm.