Structural Alignment for Reliable Industrial AI: Bridging Physical Reality, Data, Models, and Human Intent
This framework proposes a framework that views industrial AI reliability as a problem of structural alignment across four interacting worlds: physical, representational, machine, and human cognitive, and offers a principled foundation for assessing and governing reliability in industrial AI systems.
Li-Zhi Xiao, Si-Hong Wu, Victoria Xiao et al.
· 0 citations