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永恒的机器人:人类对机器人及其自我的心理模型中的锚定效应。

The Eternal Robot: Anchoring Effects in Humans' Mental Models of Robots and Their Self.

作者信息

Ullrich Daniel, Butz Andreas, Diefenbach Sarah

机构信息

Department of Computer Science, Ludwig-Maximilians-University Munich, Munich, Germany.

Department of Psychology, Ludwig-Maximilians-University Munich, Munich, Germany.

出版信息

Front Robot AI. 2020 Dec 18;7:546724. doi: 10.3389/frobt.2020.546724. eCollection 2020.

Abstract

Current robot designs often reflect an anthropomorphic approach, apparently aiming to convince users through an ideal system, being most similar or even on par with humans. The present paper challenges human-likeness as a design goal and questions whether simulating human appearance and performance adequately fits into how humans think about robots in a conceptual sense, i.e., human's mental models of robots and their self. Independent of the technical possibilities and limitations, our paper explores robots' attributed potential to become human-like by means of a thought experiment. Four hundred eighty-one participants were confronted with fictional transitions from human-to-robot and robot-to-human, consisting of 20 subsequent steps. In each step, one part or area of the human (e.g., brain, legs) was replaced with robotic parts providing equal functionalities and vice versa. After each step, the participants rated the remaining humanness and remaining self of the depicted entity on a scale from 0 to 100%. It showed that the starting category (e.g., human, robot) serves as an anchor for all former judgments and can hardly be overcome. Even if all body parts had been exchanged, a former robot was not perceived as totally human-like and a former human not as totally robot-like. Moreover, humanness appeared as a more sensible and easier denied attribute than robotness, i.e., after the objectively same transition and exchange of the same parts, the former human was attributed less humanness and self left compared to the former robot's robotness and self left. The participants' qualitative statements about why the robot has not become human-like, often concerned the (unnatural) process of production, or simply argued that no matter how many parts are exchanged, the individual keeps its original entity. Based on such findings, we suggest that instead of designing most human-like robots in order to reach acceptance, it might be more promising to understand robots as an own "species" and underline their specific characteristics and benefits. Limitations of the present study and implications for future HRI research and practice are discussed.

摘要

当前的机器人设计通常反映出一种拟人化的方法,显然旨在通过一个理想的系统来说服用户,使其与人类最为相似甚至不相上下。本文对将类人性作为设计目标提出了质疑,并探讨了在概念层面上,模拟人类外观和性能是否能充分契合人类对机器人及其自身的认知方式,即人类对机器人的心理模型。抛开技术上的可能性和局限性,我们的论文通过一个思想实验来探究机器人被赋予的变得类人的潜力。481名参与者面对从人到机器人以及从机器人到人的虚构转变,该转变由20个后续步骤组成。在每一步中,人类的一个部分或区域(例如大脑、腿部)被具有同等功能的机器人部件所取代,反之亦然。在每一步之后,参与者根据0%至100%的范围对所描绘实体的剩余人性和剩余自我进行评分。结果表明,起始类别(例如人、机器人)是所有先前判断的锚定,很难被克服。即使所有身体部位都已交换,先前的机器人也不会被视为完全类人,先前的人也不会被视为完全类机器人。此外,人性似乎比机器人属性更敏感且更容易被否定,也就是说,在客观上相同的转变以及相同部件的交换之后,与先前机器人的机器人属性和剩余自我相比,先前人类被赋予的人性和剩余自我更少。参与者关于机器人为何没有变得类人的定性陈述,通常涉及(不自然的)生产过程,或者简单地认为无论交换多少部件,个体都保持其原始实体。基于这些发现,我们建议,与其设计最类人的机器人以获得认可,将机器人理解为一种独特的“物种”并强调其特定特征和优势可能更有前景。本文还讨论了本研究的局限性以及对未来人机交互研究和实践的启示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e196/7806034/4ea879c41613/frobt-07-546724-g0001.jpg

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