How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.
![Choosing a Data Labeling Service Part 1: Hiring and Vetting](https://www.cloudfactory.com/hs-fs/hubfs/04-blog-img/blog-choosing-a-dl-partner-hiring-and-vetting.jpg?width=346&height=181&name=blog-choosing-a-dl-partner-hiring-and-vetting.jpg)
How can you determine if a data labeling service will deliver quality work? It starts with their vetting, hiring, and training processes.
![Will AI Replace the Humans In the Loop?](https://www.cloudfactory.com/hs-fs/hubfs/04-blog-img/will-ai-replace-humans-in-loop.jpg?width=346&height=181&name=will-ai-replace-humans-in-loop.jpg)
People are involved in everything from training and testing algorithms to labeling data, conducting quality control, and monitoring automation.
![3 Ways Humans in the Loop Add Value to the AI Lifecycle](https://www.cloudfactory.com/hs-fs/hubfs/04-blog-img/humans-in-loop-add-value-to-ai-lifecycle.jpg?width=346&height=181&name=humans-in-loop-add-value-to-ai-lifecycle.jpg)
Humans play a critical role throughout the AI lifecycle, from data cleaning and labeling to quality control and automation monitoring.
![4 Common Misconceptions About Image Annotation for Computer Vision](https://www.cloudfactory.com/hs-fs/hubfs/04-blog-img/misconceptions-about-image-annotation-for-computer-vision.jpg?width=346&height=181&name=misconceptions-about-image-annotation-for-computer-vision.jpg)
Image annotation is an important task when training a computer vision model. Here are common misconceptions about image annotation for computer vision.