Engagement and Mind Perception Within Human-Robot Interaction: A Comparison Between Elderly and Young Adults

Kont, Melissa; Alimardani, Maryam

doi:10.1007/978-3-030-62056-1_29

Cited by 13 publications

(6 citation statements)

References 26 publications

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“…This is in line with previous findings showing that people are likely to ascribe human attributes to a robot possessing human‐like characteristics and behavior (Krach et al., 2008; Thellman, Silvervarg, & Ziemke, 2020; Zhao, Cusimano, & Malle, 2016). However, the finding is in contrast with studies that show older adults are more likely to ascribe human characteristics to a robot partner than younger adults (Alimardani & Qurashi, 2019; Kont & Alimardani, 2020; Pak, Crumley‐Branyon, Visser, & Rovira, 2020). Future studies can further explore how different characteristics of the artificial agent varying in human‐likeness affect processing and how these outcomes compare to human–human interactions.…”

Section: Discussioncontrasting

confidence: 94%

Linguistic Redundancy and its Effects on Younger and Older Adults’ Real‐Time Comprehension and Memory

2022

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Redundant modifiers can facilitate referential interpretation by narrowing attention to intended referents. This is intriguing because, on traditional accounts, redundancy should impair comprehension. Little is known, however, about the effects of redundancy on older adults’ comprehension. Older adults may show different patterns due to age‐related decline (e.g., processing speed and memory) or their greater proclivity for linguistic redundancy, as suggested in language production studies. The present study explores the effects of linguistic redundancy on younger and older listeners’ incremental referential processing, judgments of informativity, and downstream memory performance. In an eye tracking task, gaze was monitored as listeners followed instructions from a social robot referring to a unique object within a multi‐object display. Critical trials were varied in terms of modifier type (“…closed/purple/[NONE] umbrella”) and whether displays contained another object matching target properties (closed purple notebook), making modifiers less effective at narrowing attention. Relative to unmodified descriptions, redundant color modifiers facilitated comprehension, particularly when they narrowed attention to a single referent. Descriptions with redundant state modifiers always impaired real‐time comprehension. In contrast, memory measures showed faster recognition of objects previously described with redundant state modifiers. Although color and state descriptions had different effects on referential processing and memory, informativity judgments showed participants perceived them as informationally redundant to the same extent relative to unmodified descriptions. Importantly, the patterns did not differ by listener age. Together, the results show that the effects of linguistic redundancy are stable across adulthood but vary as a function of modifier type, visual context, and the measured phenomenon.

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Section: Discussioncontrasting

confidence: 94%

Linguistic Redundancy and its Effects on Younger and Older Adults’ Real‐Time Comprehension and Memory

2022

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“…The underlying assumption is that while the analysis of everyday life focuses on the third-person perspective (when looking at "lifeworlds"), investigation of lived experiences always involves firstperson accounts. Both approaches suit HRI studies that involve mixed methods research, from behavioural and observational measurements [e.g., (Siegel et al, 2009;Kont and Alimardani, 2020)], to tools designed for subjective evaluations and measures of the robot performance and interaction [e.g., (Siegel et al, 2009;Winkle et al, 2019;Hannibal et al, 2022)].…”

Section: The Everyday and Lived Experiencementioning

confidence: 99%

Towards a conceptualisation and critique of everyday life in HRI

Zawieska,

Hannibal

2023

Front. Robot. AI

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This paper focuses on the topic of “everyday life” as it is addressed in Human-Robot Interaction (HRI) research. It starts from the argument that while human daily life with social robots has been increasingly discussed and studied in HRI, the concept of everyday life lacks clarity or systematic analysis, and it plays only a secondary role in supporting the study of the key HRI topics. In order to help conceptualise everyday life as a research theme in HRI in its own right, we provide an overview of the Social Science and Humanities (SSH) perspectives on everyday life and lived experiences, particularly in sociology, and identify the key elements that may serve to further develop and empirically study such a concept in HRI. We propose new angles of analysis that may help better explore unique aspects of human engagement with social robots. We look at the everyday not just as a reality as we know it (i.e., the realm of the “ordinary”) but also as the future that we need to envision and strive to materialise (i.e., the transformation that will take place through the “extraordinary” that comes with social robots). Finally, we argue that HRI research would benefit not only from engaging with a systematic conceptualisation but also critique of the contemporary everyday life with social robots. This is how HRI studies could play an important role in challenging the current ways of understanding of what makes different aspects of the human world “natural” and ultimately help bringing a social change towards what we consider a “good life.”

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“…This ensures activities that minimize sedentariness [35]. Prior studies have shown that the reported engagement of older adults with robots is generally lower than the younger adults [36]. Effort is therefore made to actively engage the older adults with the robot during interaction.…”

Section: Interaction Design Metricsmentioning

confidence: 99%

Levels of Automation and Transparency: Interaction Design Considerations in Assistive Robots for Older Adults

Olatunji

Oron-Gilad

Markfeld

et al. 2021

IEEE Trans. Human-Mach. Syst.

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It is important to encourage older adults to remain active when interacting with assistive robots. This study proposes a schematic model for integrating levels of automation (LOAs) and transparency (LoTs) in assistive robots to match the preferences and expectations of older adults. Metrics to evaluate LOA and LoT design combinations are defined. We develop two distinctive test cases to examine interaction design considerations for robots working for this population in everyday tasks: a person-following task with a mobile robot and a table-setting task with a robot manipulator. Evaluations in user studies with older adults reveal that LOA and LoT combinations influence interaction elements. Low LOA and high LoT encouraged activity engagement while receiving adequate information regarding the robot's behavior. The variety of objective and subjective metrics is essential to provide a holistic framework for evaluating the interaction. Index Terms-Assistive robots (ARs), human-robot interaction, interaction design, level of automation (LOA), level of transparency (LoT), older adults, socially ARs. I. BACKGROUNDT HE GLOBAL population of older adults (aged 65+) is increasing rapidly without commensurate growth in people that can support them [1]. This shortage is creating an eldercare gap in which the scarcity of caregivers, social support, and healthcare professionals has left many in this group facing many barriers in aging [2]. Assistive robots (ARs) can help reduce these barriers, facilitate independence, and promote more successful aging (e.g., [3]-[5]). While there has been progress in AR design and development for many daily applications [6],

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Engagement and Mind Perception Within Human-Robot Interaction: A Comparison Between Elderly and Young Adults

Cited by 13 publications

References 26 publications

Linguistic Redundancy and its Effects on Younger and Older Adults’ Real‐Time Comprehension and Memory

Linguistic Redundancy and its Effects on Younger and Older Adults’ Real‐Time Comprehension and Memory

Towards a conceptualisation and critique of everyday life in HRI

Levels of Automation and Transparency: Interaction Design Considerations in Assistive Robots for Older Adults

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