Using ML to Improve Labeling Quality on Scale Rapid

Scale Rapid helps ML teams iterate quickly with an on-demand, end-to-end, labeling solution with rapid turnaround times. In this tech talk, we discuss the challenges to build quality infrastructure for crowd management, then discuss the role machine learning can play in:

• Achieving high quality even with subjective tasks
• Flagging potential problems with evaluation tasks
• Suggesting improvements for project health

We'll discuss where ML can accelerate and scale human insights, the challenges of creating generalizable quality mechanisms, and the trade-offs that must be considered between accuracy and generalizability for such ML solutions.