HCAIROOct 13, 2020

Intrinsic motivation in virtual assistant interaction for fostering spontaneous interactions

arXiv:2010.06416v16 citations
Originality Incremental advance
AI Analysis

This addresses the problem of enhancing user engagement with virtual assistants for HCI/AI researchers, though it is incremental as it builds on prior motivation studies.

The study tackled the lack of research on intrinsic motivation in virtual assistant interactions by proposing a model where expectation of capability and uncertainty affect motivation, finding that high expectation increases intrinsic motivation and reducing uncertainty shifts interactions from non-intrinsic to intrinsic.

With the growing utility of today's conversational virtual assistants, the importance of user motivation in human-AI interaction is becoming more obvious. However, previous studies in this and related fields, such as human-computer interaction and human-robot interaction, scarcely discussed intrinsic motivation and its affecting factors. Those studies either treated motivation as an inseparable concept or focused on non-intrinsic motivation. The current study aims to cover intrinsic motivation by taking an affective-engineering approach. A novel motivation model is proposed, in which intrinsic motivation is affected by two factors that derive from user interactions with virtual assistants: expectation of capability and uncertainty. Experiments are conducted where these two factors are manipulated by making participants believe they are interacting with the smart speaker "Amazon Echo". Intrinsic motivation is measured both by using questionnaires and by covertly monitoring a five-minute free-choice period in the experimenter's absence, during which the participants could decide for themselves whether to interact with the virtual assistants. Results of the first experiment showed that high expectation engenders more intrinsically motivated interaction compared with low expectation. The results also suggested suppressive effects by uncertainty on intrinsic motivation, though we had not hypothesized before experiments. We then revised our hypothetical model of action selection accordingly and conducted a verification experiment of uncertainty's effects. Results of the verification experiment showed that reducing uncertainty encourages more interactions and causes the motivation behind these interactions to shift from non-intrinsic to intrinsic.

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