Amazon Mechanical Turk
Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace that makes it easier for individuals and businesses to coordinate the use of human intelligence to perform tasks that computers are currently unable to do well. It enables access to a global, on-demand, 24x7 workforce for data labeling, content moderation, surveys, transcription, and machine learning training data collection.
APIs
Amazon Mechanical Turk API
The Amazon Mechanical Turk API provides programmatic access to create and manage HITs, qualifications, workers, assignments, and bonuses for coordinating crowdsourced human inte...
Capabilities
Amazon Mechanical Turk - Crowdsourcing Workflow
Workflow capability for data scientists and researchers to create HITs, manage worker assignments, approve work, and coordinate crowdsourced human intelligence tasks through Ama...
Run with NaftikoFeatures
Create and manage discrete units of work distributed to the global MTurk worker population.
Define custom qualification tests and requirements to target the right worker pool for each task type.
Review submitted assignments and approve or reject work with feedback to workers.
Award bonus payments to workers for exceptional task completion beyond the base HIT reward.
Send targeted messages to specific workers to communicate task updates or instructions.
Prevent specific workers from accessing your HITs when quality does not meet requirements.
Test HIT templates and requester workflows using the MTurk sandbox before going to production.
Use Cases
Label images, text, audio, and video to create training datasets for machine learning models.
Review and moderate user-generated content for inappropriate material at scale.
Transcribe audio and video recordings using human workers for high accuracy.
Conduct surveys and collect research data from a diverse global workforce.
Validate and verify structured data for accuracy using human review.
Generate labeled sentiment data for training NLP and sentiment analysis models.
Integrations
Use MTurk workers directly within SageMaker Ground Truth for ML data labeling jobs.
Trigger Lambda functions on HIT completion events for automated downstream processing.
Store HIT input data and collect worker output files in S3 buckets.
Monitor MTurk task completion rates and worker performance metrics.
Control requester access to the MTurk API through IAM policies and roles.