On developers’ practices for hazard diagnosis in machine learning systems

Machine learning (ML) is an artificial intelligence technology that has a great potential for being adopted in various sectors of activities. Yet, it is now also increasingly recognized as a hazardous technology. Failures in the outputs of an ML system might cause physical or social harms. Besides, the development and deployment of an ML system...

Conversational Crowdsourcing

Crowdsourcing has become a standard approach for the collection of the human input required by scientists and practitioners alike to execute their experiments, or to train, control, and verify the behavior of their intelligent systems. Despite years of successful research and industrial application, how to improve the engagement and satisfaction...

Semantic-Enhanced Training Data Augmentation Methods for Long-Tail Entity Recognition Models

Named Entity Recognition (NER) is an essential information retrieval task. It enables a wide range of natural language processing applications such as semantic search, machine translation, etc. The NER can be formulated as the task of identifying and typing words or phrases in a text that refers to certain classes of interest (e.g., disease,...

Crowd Knowledge Creation Acceleration

Crowd knowledge creation plays a central role in many types of Web based information systems, ranging from community question-answering (CQA) systems (e.g. StackOverflow and Quora) to micro-task crowdsourcing systems (e.g. Amazon mTurk and CrowdFlower). In these systems, knowledge demands are generally fulfilled by means of tasks (e.g. questions...