Data Labeling Is a Collaborative Process
As the field of artificial intelligence (AI) continues to evolve, publicly available tools such as ChatGPT, Large Language Model Meta AI (LLaMA), Bard, Midjourney, and others have set a new benchmark for what's possible to achieve with structured and unstructured data.
These models obviously rely on advanced algorithms and massive amounts of data, but many people are unaware that human labeling remains a critical component in their ongoing refinement and advancement. As an example, ChatGPT’s model infrastructure relies on individuals reviewing and annotating data samples that are then fed back into the model to improve its understanding of natural language and context.
In this chapter, we explore how to get the most out of data collection and annotation tasks involving human labelers. We will cover these general topics:
- Why we need human annotators
- Understanding common challenges arising from human labeling tasks...
