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Investigating NARS: Inconsistent Practice of Application and Reporting
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab)ORCID iD: 0000-0001-8642-336x
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab)ORCID iD: 0000-0002-8937-8063
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Interaction Lab)ORCID iD: 0000-0003-2254-1396
2023 (English)In: Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), IEEE, 2023, p. 922-927Conference paper, Published paper (Refereed)
Abstract [en]

The Negative Attitude toward Robots Scale (NARS) is one of the most common questionnaires used in the studies of human-robot interaction (HRI). It was established in 2004, and has since then been used in several domains to measure attitudes, both as main results and as a potential confounding factor. To better understand this important tool of HRI research, we reviewed the HRI literature with a specific focus on practice and reporting related to NARS. We found that the use of NARS is being increasingly reported, and that there is a large variation in how NARS is applied. The reporting is, however, often not done in sufficient detail, meaning that NARS results are often difficult to interpret, and comparing between studies or performing meta-analyses are even more difficult. After providing an overview of the current state of NARS in HRI, we conclude with reflections and recommendations on the practices and reporting of NARS.

Place, publisher, year, edition, pages
IEEE, 2023. p. 922-927
Series
IEEE International Symposium on Robot and Human Interactive Communication proceedings, ISSN 1944-9445, E-ISSN 1944-9437
National Category
Robotics Human Aspects of ICT Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-23359DOI: 10.1109/RO-MAN57019.2023.10309650ISI: 001108678600106Scopus ID: 2-s2.0-85186997999ISBN: 979-8-3503-3670-2 (electronic)ISBN: 979-8-3503-3671-9 (print)OAI: oai:DiVA.org:his-23359DiVA, id: diva2:1811799
Conference
IEEE International Workshop on Robot and Human Communication (ROMAN), August 28-31, 2023, Paradise Hotel, Busan, Korea
Available from: 2023-11-14 Created: 2023-11-14 Last updated: 2024-04-15Bibliographically approved
In thesis
1. What did you expect?: A human-centered approach to investigating and reducing the social robot expectation gap
Open this publication in new window or tab >>What did you expect?: A human-centered approach to investigating and reducing the social robot expectation gap
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

We live in a complex world where we proactively plan and execute various behaviors by forming expectations in real time. Expectations are beliefs regarding the future state of affairs and they play an integral part of our perception, attention, and behavior. Over time, our expectations become more accurate as we interact with the world and others around us. People interact socially with other people by inferring others' purposes, intentions, preferences, beliefs, emotions, thoughts, and goals. Similar inferences may occur when we interact with social robots. With anthropomorphic design, these robots are designed to mimic people physically and behaviorally. As a result, users predominantly infer agency in social robots, often leading to mismatched expectations of the robots' capabilities, which ultimately influences the user experience. 

In this thesis, the role and relevance of users' expectations in first-hand social human-robot interaction (sHRI) was investigated. There are two major findings. First, in order to study expectations in sHRI, the social robot expectation gap evaluation framework was developed. This framework supports the systematic study and evaluation of expectations over time, considering the unique context where the interaction is unfolding. Use of the framework can inform sHRI researchers and designers on how to manage users’ expectations, not only in the design, but also during evaluation and presentation of social robots. Expectations can be managed by identifying what kinds of expectations users have and aligning these through design and dissemination which ultimately creates more transparent and successful interactions and collaborations. The framework is a tool for achieving this goal. Second, results show that previous experience has a strong impact on users’ expectations. People have different expectations of social robots and view social robots as both human-like and as machines. Expectations of social robots can vary according to the source of the expectation, with those who had previous direct experiences of robots having different expectations than those who relied on indirect experiences to generate expectations.    

One consequence of these results is that expectations can be a confounding variable in sHRI research. Previous experience with social robots can prime users in future interactions with social robots. These findings highlight the unique experiences users have, even when faced with the same robot. Users' expectations and how they change over time shapes the users’ individual needs and preferences and should therefore be considered in the interpretation of sHRI. In doing so, the social robot expectation gap can be reduced.

Abstract [sv]

Vi lever i en komplex värld och för att kunna hantera denna komplexitet formar vi förväntningar. Förväntningar är antaganden om framtida tillstånd och är en vital del av vår perception, uppmärksamhet och beteende. Genom att interagera med omvärlden och andra människor blir våra förväntningar mer precisa och korrekta över tid. I en social interaktion behöver vi förstå den andra personens syften, avsikter, preferenser, övertygelser, känslor, tankar och mål. Sociala robotar är utformade för att skapa liknande inferenser när användare interagerar med dem. Detta kan leda till missbedömningar mellan vad vi förväntar oss av sociala robotar och vad dessa artefakter är kapabla till, vilket påverkar användarupplevelsen av sociala robotar.

I den här avhandlingen presenteras den forskning som har utförts för att studera rollen och relevansen av människors förväntningar i social människa-robotinteraktion (sMRI). Resultaten kan delas in i två större fynd. Det första fyndet är ett utvärderingsramverk som ämnar att systematiskt studera användares förväntningar av sociala robotar i en interaktion, med fokus på hur förväntningar ändras över tid i en interaktion, med interaktionens unika kontext i åtanke. Ramverket är menat för designers av sociala robotar och forskare inom sMRI-fältet för att bättre studera, hantera, och förstå förväntningar, både i robotarnas design och i robotarnas agerande. Det andra fyndet består av de empiriska resultat som visar hur tidigare erfarenheter påverkar användares förväntningar. Förväntningarna baseras till stor del på vilka typer av tidigare erfarenheter användare har, där de med direkta erfarenheter av robotar har andra förväntningar än de med indirekta erfarenheter. Vidare visar resultaten att användare ser sociala robotar både som människolika och som maskiner samtidigt.

Förväntningar kan också ses som en bakomliggande variabel inom sMRI-forskning eftersom tidigare erfarenheter kan påverka deltagare i kommande interaktioner med sociala robotar. Resultaten visar även att användarupplevelsen är unik för varje användare, även om roboten är densamma, vilket bör tas i åtanke när resultat tolkas i en sMRI-kontext. Genom att ha förväntningar i åtanke kan vi minska det gap som uppstår mellan människors förväntningar av sociala robotar och robotarnas faktiska förmågor. På så sätt kan vi främja positiva användarupplevelser och förbättra interaktionen mellan människa och robot.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2024. p. 220
Series
Dissertation Series ; 55
National Category
Robotics Interaction Technologies Social Psychology Ethics Social Psychology Computer Vision and Robotics (Autonomous Systems) Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23414 (URN)978-91-987906-9-6 (ISBN)
Public defence
2024-01-19, G207, Högskolevägen 3, Skövde, 13:00 (English)
Opponent
Supervisors
Note

Ett av sju delarbeten (övriga se rubriken Delarbeten/List of papers):

VII Lindblom, Jessica, Rosén, Julia, Lamb, Maurice, and Billing, Erik (Manuscript). “Disentangling People’s Experiences and Expectations when Interacting with the Social Robot Pepper: A Qualitative Analysis”. In: Manuscript for scientific journal, pp. 1–41.

Available from: 2023-12-07 Created: 2023-12-07 Last updated: 2024-02-29Bibliographically approved

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Rosén, JuliaLagerstedt, ErikLamb, Maurice

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