Positive Interactions with Intelligent Technology through Psychological Ownership: A Human-in-the-Loop Approach

While human-agent interaction is intended to ease daily and critical burdens on human operators, issues such as trust, lack of transparency, and system performance often negatively impacts the process to yield sub-optimal outcomes. Here, we propose a human-in-the-loop approach, in which users train an AI, as a potential avenue to remedy this complex problem. We use Tetris® as a use case and require participants to provide trial-by-trial inputs to train the AI model. Improvements in trust correlated with increased satisfaction levels during the training process but not final AI performance. Users’ preference for their trained AI, compared to a pre-trained AI, demonstrated increased improvements in trust. Personality and AI literacy did not affect these relationships. Results suggest positive perceptions towards AI systems can be elicited through psychological ownership pathways. We discuss how users’ involvement in constructing the system may influence ownership giving rise to positive human-agent interactions.