Applications, Challenges, and Future Directions of Human-in-the-Loop Learning

Machine learning (ML) has become a popular technique for various automation tasks in the era of Industry 4.0, such as the analysis and synthesis of visual data such as images and videos, natural language and speech, financial data, and biomedical applications. However, ML-based automation techniques are facing difficulties like decision-making, thus incorporating user expertise into the system might be advantageous. The goal of adding human domain expertise with ML-based automation is to provide more accurate prediction models. Human-in-the-loop (HITL) systems that integrate human expertise with ML algorithms are becoming more and more common in various industries. However, there are a number of…