Data Labeling

In Kyle’s notes, data labeling (or data tagging) appears as Mark Cuban’s answer to AI-driven labor disruption. Cuban argues that as AI and machine learning displace low-skilled work, a rising demand for tagging and labeling data can absorb much of that displaced labor — he calls it “the 21st century version of an assembly line.” It is the first half of his two-part fix for automation’s fallout (the second being a broad expansion of AmeriCorps-style national-service programs), and notably his alternative to UBI.

Context: Data labeling is the human annotation of raw data (images, text, audio) into the structured, tagged examples that supervised machine-learning models train on — historically a large source of contract and gig labor in the AI supply chain.

Where this appears

• Mark Cuban — frames data tagging/labeling as the assembly-line-style job category that can absorb workers displaced by automation.