OpenLedger ensures fair attribution of AI contributions through a mechanism called Proof of Attribution (PoA). This system transparently records every step in the AI creation process — from dataset contributions to model training and deployment — on-chain, making all contributions immutable and verifiable. The PoA tracks the influence of each data source on AI outputs and automatically distributes rewards proportionally to contributors based on their share of input impact, ensuring all contributors receive fair compensation.
The attribution pipeline involves cryptographically linking each data source to model outputs, measuring contributions by feature-level influence and contributor reputation, and penalizing low-quality or malicious inputs to maintain model integrity. Contributions that are flagged for redundancy, bias, or adversarial intent result in penalties such as stake slashing or reduced future rewards, incentivizing high-quality participation.
OpenLedger also integrates its RAG Attribution system, which gives transparent citations for AI-generated outputs by tracing them back to original data contributors. This not only rewards contributors with token-based incentives but also builds trust and accountability by enabling verification of data origins.
