Ethical confidence fabrics: measuring ethical algorithm development

ChangeBridge: Patent Grants - Business Methods (G06Q)

Published March 31st, 2026

Detected March 31st, 2026

Summary

USPTO granted patent US12591827B2 to Dell Products L.P. for a method of tracking ethical considerations during AI model development. The system annotates development phases with ethics metadata and calculates an ethics confidence score. The patent covers formulating hypotheses, annotating phases with ethics metadata, storing in a ledger, and computing an ethics confidence score.

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What changed

USPTO granted Patent No. US12591827B2 to Dell Products L.P., covering a method for measuring ethical algorithm development. The invention involves formulating hypotheses annotated with ethics metadata, storing them in a ledger, performing n phases of a development lifecycle with phase-specific ethics metadata annotations, updating the ledger, and calculating an ethics confidence score for the computing model.

This is a patent issuance, not a regulatory requirement. No compliance actions are required from technology companies or AI developers. The patent grants intellectual property rights to Dell Products L.P. for this ethical tracking methodology. Companies developing AI systems may reference this patent for competitive intelligence or licensing considerations.

Source document (simplified)

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Ethical confidence fabrics: measuring ethical algorithm development

Grant US12591827B2 Kind: B2 Mar 31, 2026

Assignee

Dell Products L.P.

Inventors

Nicole Reineke, Stephen J. Todd

Abstract

One example method includes formulating a hypothesis for development of computing model, annotating the hypothesis with ethics metadata, storing the hypothesis and the ethics metadata, in association with each other, in a ledger, performing ‘n’ phases of a development lifecycle for the computing model, annotating each of the ‘n’ phases with ethics metadata specific to the phase, updating the ledger to include the ‘n’ phases and the ethics metadata respectively associated with each of the ‘n’ phases, and calculating an ethics confidence score for the computing model.