How Mock Model Training Enhances User Perceptions of AI Systems
This addresses user adoption issues for AI systems, but it is incremental as it builds on prior work on transparency and explainability.
The paper tackled the problem of negative user preconceptions hindering AI adoption by demonstrating that mock model training improves user perceptions of AI capability and comfort, though no concrete numbers were provided.
Artificial Intelligence (AI) is an integral part of our daily technology use and will likely be a critical component of emerging technologies. However, negative user preconceptions may hinder adoption of AI-based decision making. Prior work has highlighted the potential of factors such as transparency and explainability in improving user perceptions of AI. We further contribute to work on improving user perceptions of AI by demonstrating that bringing the user in the loop through mock model training can improve their perceptions of an AI agent's capability and their comfort with the possibility of using technology employing the AI agent.