论文标题
虚拟助手互动的内在动机，用于促进自发互动
Intrinsic motivation in virtual assistant interaction for fostering spontaneous interactions
论文作者
论文摘要
随着当今对话虚拟助手的效用越来越多，用户动机在人类互动中的重要性变得越来越明显。但是，先前在该领域和相关领域的研究，例如人类计算机的相互作用和人类机器人相互作用，几乎没有讨论内在动机及其影响因素。这些研究要么将动机视为不可分割的概念，要么将动机视为非人性动机。当前的研究旨在通过采用情感工程方法来涵盖内在动机。提出了一个新颖的动机模型，其中内在动机受到用户与虚拟助手相互作用的两个因素的影响：能力和不确定性的期望。通过使参与者认为他们正在与智能扬声器“ Amazon Echo”互动来操纵这两个因素，进行实验。在实验者缺席的情况下，通过使用问卷和秘密监控五分钟的自由选择期来衡量内在动机，在此期间，参与者可以自己决定是否与虚拟助手互动。第一个实验的结果表明，与低期望相比，高期望产生的相互作用更具本质上的动机相互作用。结果还表明，尽管我们没有在实验之前假设，但不确定性对内在动机的抑制作用。然后，我们相应地修改了我们的假设行动选择模型，并进行了对不确定性影响的验证实验。验证实验的结果表明，降低不确定性会促进更多的相互作用，并引起这些相互作用背后的动机，从非intrinsic转移到内在。
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.
