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Individual Differences that Predict Interactions in Mixed-Initiative Teams

机译:个体差异可预测混合行动团队中的互动

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Humans and machines are collaborating in new ways and organizations are increasingly leveraging mixed-initiative teams. We examine the effect that an individual's personality has on his or her willingness to: (1) seek assistance from and/or (2) accept the recommendations of an automated teammate. We use a game of pure strategy with a perfectly accurate decision-assisting automated agent to examine how personality predicts these interactions. Forty-nine participants played 3 rounds of a decision game called "Pirate Island." Each participant made 27 total decisions (9 decisions per round over 3 rounds) and had the option to solicit assistance from an automated agent for each decision. Participants were not told that the agent was 100% accurate, only that it could help them. We found that people low on extroversion and high on agreeableness were highly correlated to soliciting recommendations from an agent. However, only those high on agreeableness actually accepted recommendations.
机译:人与机器正在以新的方式进行协作,并且组织越来越多地利用混合计划团队。我们研究了一个人的性格对他或她的意愿的影响:(1)寻求帮助和/或(2)接受自动队友的建议。我们使用具有完全准确的决策辅助自动代理的纯策略游戏来检查个性如何预测这些交互。四十九名参与者参加了名为“海盗岛”的决策游戏的三轮比赛。每个参与者共做出27项决定(3轮中每轮9项决定),并且可以选择为每个决定从自动代理寻求帮助。参与者没有被告知代理是100%准确的,只是它可以帮助他们。我们发现,外向性差和乐于助人的人与向代理商征求建议高度相关。但是,只有那些高度认同的人才真正接受建议。

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