Editorial: Special Issue on Human in the Loop Data Curation

This Special Issue of the Journal of Data and Information Quality (JDIQ) contains novel theoretical and methodological contributions on data curation involving humans in the loop. In this editorial, we summarize the scope of the issue and briefly describe its content.

Editorial: Human-centered AI: Crowd computing

How do you feel?: Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection

Hate speech moderation remains a challenging task for social media platforms. Human-AI collaborative systems offer the potential to combine the strengths of humans' reliability and the scalability of machine learning to tackle this issue effectively. While methods for task handover in human-AI collaboration exist that consider the costs of...

HybridEval: A Human-AI Collaborative Approach for Evaluating Design Ideas at Scale

Evaluating design ideas is necessary to predict their success and assess their impact early on in the process. Existing methods rely either on metrics computed by systems that are effective but subject to errors and bias, or experts' ratings, which are accurate but expensive and long to collect. Crowdsourcing offers a compelling way to...