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Carnegie Mellon University — Robust AI Unlearning Techniques

Metadata

Source Tablegrants
Source ID4ARV-TA6im
Descriptionto carnegie-mellon-university, $584,108, 2025-05
Source URLcoefficientgiving.org/grants/
ParentULjDXpSLCI
Children
CreatedMar 12, 2026, 5:54 AM
UpdatedMar 23, 2026, 3:17 PM
SyncedMar 19, 2026, 8:57 PM

Record Data

id4ARV-TA6im
organizationIdCoefficient Giving(organization)
granteeIdCarnegie Mellon University(organization)
orgEntityIdCoefficient Giving(organization)
orgDisplayName
granteeEntityIdCarnegie Mellon University(organization)
granteeDisplayNamecarnegie-mellon-university
nameCarnegie Mellon University — Robust AI Unlearning Techniques
amount584108
currencyUSD
period
date2025-05
status
sourcecoefficientgiving.org/funds/
notes[Navigating Transformative AI] Open Philanthropy recommended a grant of $584,108 over two years to Carnegie Mellon University to support the development of robust unlearning techniques for AI. This research will be led by Professors Virginia Smith and Steven Wu. This grant was funded via a request
programIdEXpTP-ujq6
dataSourceId

Source Check Verdicts

confirmed95% confidence

Last checked: 4/9/2026

[deterministic-row-match] Deterministic match: grantee, amount, date matched in source snapshot (2714 rows)

Debug info

Thing ID: 4ARV-TA6im

Source Table: grants

Source ID: 4ARV-TA6im