The era of "click-click-click" polygon drawing is ending. With the advent of foundation models like Meta's SAM (Segment Anything Model), the role of the human annotator is fundamentally changing.
From Creator to Auditor
In the traditional workflow, a human draws every pixel. In the LexAnnotate workflow, an AI model pre-labels the scene. It identifies cars, trees, and lanes instantly. The human's job is to verify (audit) and correct (refine). This shifts the cognitive load from tedious motor tasks to high-level judgment.
The Throughput Multiplier
We've observed a 10x increase in labeling speed for semantic segmentation tasks using SAM-assisted tools. But speed isn't the only metric. Consistency improves because the "AI brush" doesn't get tired or shaky. The edges remain pixel-perfect whether it's the first image of the day or the thousandth.
However, this introduces new risks. "Automation bias" means humans might just click "Approve" without looking closely. Our UI is designed to counter this by highlighting low-confidence regions that require human interaction, preventing the "zombie click" phenomenon.