Fair use
A doctrine in US copyright law (17 U.S.C. § 107) permitting certain uses of copyrighted material without the rightsholder's permission, decided case by case through a four-factor balancing test: purpose and character of the use, nature of the copyrighted work, amount and substantiality used, and effect on the market for the original. Not a fixed rule; each new use requires its own analysis.
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in AI Data Governance: The Data Chair.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A doctrine in US copyright law (17 U.S.C. § 107) permitting certain uses of copyrighted material without the rightsholder's permission, decided case by case through a four-factor balancing test: purpose and character of the use, nature of the copyrighted work, amount and substantiality used, and effect on the market for the original. Not a fixed rule; each new use requires its own analysis.
A defense in United States copyright law that permits some unlicensed use of a protected work, weighed across four factors (purpose and character of the use, nature of the work, amount used, and effect on the market). In Thomson Reuters v. Ross Intelligence the defense failed because the use was commercial, not transformative, and harmed the market.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Copyright and the corpus: what your organization may train on, and the provenance file that proves it · Lineage Under Audit, AI Data Governance: The Data Chair
- Who owns the output: IP, training-data provenance, and the liability chain when AI work goes wrong · Evidence Engineering, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.