AI copyright blueprint: pragmatism over rigidity
The Department for Promotion of Industry and Internal Trade’s (DPIIT) working paper on regulating use of copyrighted works in AI training comes at a time when the issue can no longer be deferred. Litigation around AI training has already surfaced in India and is well underway in other jurisdictions. Given that generative models depend on ingesting large volumes of copyrighted material, uncertainty around what constitutes lawful training use has become untenable. In that sense, the proposal for a mandatory blanket licence is not a speculative regulatory exercise but a response to a problem that has already emerged and is likely to intensify.
The paper’s central move is to reject both polar positions: on the one hand, broad free use or text-and-data-mining (TDM) exceptions that risk hollowing out incentives for human creators; on the other, case-by-case licensing that is structurally incompatible with the scale and architecture of AI systems. Training data sets today cannot be disaggregated into neatly identifiable units linked to individual rights holders. Any framework built on granular permissions would thus be slow, fragmented, and ultimately unworkable. More........





















Toi Staff
Sabine Sterk
Penny S. Tee
Gideon Levy
Waka Ikeda
Mark Travers Ph.d
Grant Arthur Gochin
Tarik Cyril Amar