- Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions.
- Labeling elements of a piece of content rather than the content as a whole.
- Assigning predefined categories or labels to items.
- Evaluating the perceived quality and/or appropriateness of content.
- Generating labels to advance understanding of a concept, trend etc.
- Creation of additional training data for machine learning models by applying transformations to the original data.
- Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines.
- Labeling model outputs to identify if a piece of content is or isn't something (e.g., clickbait, gaming videos, branded content).
- Ordering or ranking items based on a set of preferences or criteria.
- Creating prompts or questions that will be used to generate responses from a language model or other AI system.
- Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.).
- Generating responses to prompts or questions using a language model or other AI system.
- Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines.
- Producing concise summaries of longer pieces of text or data.
- Converting spoken language or audio content into written text.
- Converting text or spoken language from one language to another.
- Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models.