Web Science and Digital Libraries Research Group

  Image from https://aws.amazon.com/sagemaker-ai/groundtruth/ Imagine you are training a machine learning (ML) model to identify dog breeds from images. You have thousands of photos of Golden Retrievers, Poodles, and Dachshunds, but the model cannot distinguish a Chihuahua from a Bulldog without labeled data. This is where data labeling becomes essential. Human annotators tag each image so the ML model can learn to recognize patterns. However, manually labeling thousands of images is time-consuming and resource-intensive. A more efficient approach is to distribute the work among many people online through crowdsourcing , which is the process of outsourcing tasks to a large group of people, often over the internet, instead of relying on a single employee or a small team. In machine learning, crowdsourcing is commonly used for data labeling , the process of annotating raw data such as images, text, or videos to make it suitable for training ML models. Amazon SageMaker Ground Trut...