AI Training : Raw Lego Data Blocks Labelled By Human to Construct a Golden Dataset
The article argues that artificial intelligence, despite its advanced nature, fundamentally relies on human labor and judgment for its foundational data. Raw data is presented as inert and semantically empty until humans intervene through labeling, which is framed as an act of knowledge construction. The quality and ethical considerations of this human-driven data labeling process are crucial for shaping the moral character and future of AI systems. AI
IMPACT Highlights the critical, often overlooked, human element in AI development, emphasizing the ethical responsibilities tied to data curation.