Social and Behavioral Sciences Commons^™

Human-Centered Explainable Artificial Intelligence For Anomaly Detection In Quality Inspection: A Collaborative Approach To Bridge The Gap Between Humans And Ai, Srikanth Vemula

Theses & Dissertations

In the quality inspection industry, the use of Artificial Intelligence (AI) continues to advance to produce safer and faster autonomous systems that can perceive, learn, decide, and act independently. As observed by the researcher interacting with the local energy company over a one-year period, these AI systems’ performance is limited by the machine’s current inability to explain its decisions and actions to human users. Especially in energy companies, eXplainable-AI (XAI) is critical to achieve speed, reliability, and trustworthiness with human inspection workers. Placing humans alongside AI will establish a sense of trust that augments the individual’s capabilities at the workplace. …