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Lakhnati Y, Pascher M, Gerken J. Exploring a GPT-based large language model for variable autonomy in a VR-based human-robot teaming simulation. Front Robot AI 2024; 11:1347538. [PMID: 38633059 PMCID: PMC11021771 DOI: 10.3389/frobt.2024.1347538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 03/13/2024] [Indexed: 04/19/2024] Open
Abstract
In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained transformer (GPT) into human-robot teaming environments to facilitate variable autonomy through the means of verbal human-robot communication. In this paper, we introduce a novel simulation framework for such a GPT-powered multi-robot testbed environment, based on a Unity Virtual Reality (VR) setting. This system allows users to interact with simulated robot agents through natural language, each powered by individual GPT cores. By means of OpenAI's function calling, we bridge the gap between unstructured natural language input and structured robot actions. A user study with 12 participants explores the effectiveness of GPT-4 and, more importantly, user strategies when being given the opportunity to converse in natural language within a simulated multi-robot environment. Our findings suggest that users may have preconceived expectations on how to converse with robots and seldom try to explore the actual language and cognitive capabilities of their simulated robot collaborators. Still, those users who did explore were able to benefit from a much more natural flow of communication and human-like back-and-forth. We provide a set of lessons learned for future research and technical implementations of similar systems.
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Affiliation(s)
- Younes Lakhnati
- Inclusive Human-Robot-Interaction, TU Dortmund University, Dortmund, NW, Germany
| | - Max Pascher
- Inclusive Human-Robot-Interaction, TU Dortmund University, Dortmund, NW, Germany
- Human-Computer Interaction, University of Duisburg-Essen, Essen, NW, Germany
| | - Jens Gerken
- Inclusive Human-Robot-Interaction, TU Dortmund University, Dortmund, NW, Germany
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2
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Stein JP, Messingschlager T, Gnambs T, Hutmacher F, Appel M. Attitudes towards AI: measurement and associations with personality. Sci Rep 2024; 14:2909. [PMID: 38316898 PMCID: PMC10844202 DOI: 10.1038/s41598-024-53335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/31/2024] [Indexed: 02/07/2024] Open
Abstract
Artificial intelligence (AI) has become an integral part of many contemporary technologies, such as social media platforms, smart devices, and global logistics systems. At the same time, research on the public acceptance of AI shows that many people feel quite apprehensive about the potential of such technologies-an observation that has been connected to both demographic and sociocultural user variables (e.g., age, previous media exposure). Yet, due to divergent and often ad-hoc measurements of AI-related attitudes, the current body of evidence remains inconclusive. Likewise, it is still unclear if attitudes towards AI are also affected by users' personality traits. In response to these research gaps, we offer a two-fold contribution. First, we present a novel, psychologically informed questionnaire (ATTARI-12) that captures attitudes towards AI as a single construct, independent of specific contexts or applications. Having observed good reliability and validity for our new measure across two studies (N1 = 490; N2 = 150), we examine several personality traits-the Big Five, the Dark Triad, and conspiracy mentality-as potential predictors of AI-related attitudes in a third study (N3 = 298). We find that agreeableness and younger age predict a more positive view towards artificially intelligent technology, whereas the susceptibility to conspiracy beliefs connects to a more negative attitude. Our findings are discussed considering potential limitations and future directions for research and practice.
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Affiliation(s)
- Jan-Philipp Stein
- Department of Media Psychology, Institute for Media Research, Chemnitz University of Technology, Thüringer Weg 11, 09126, Chemnitz, Germany.
| | - Tanja Messingschlager
- Psychology of Communication and New Media, Human-Computer-Media Institute, University of Würzburg, Würzburg, Germany
| | - Timo Gnambs
- Leibniz Institute for Educational Trajectories, Bamberg, Germany
| | - Fabian Hutmacher
- Psychology of Communication and New Media, Human-Computer-Media Institute, University of Würzburg, Würzburg, Germany
| | - Markus Appel
- Psychology of Communication and New Media, Human-Computer-Media Institute, University of Würzburg, Würzburg, Germany
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Wei Z, Chen Y, Zhao Q, Ren J, Piao Y, Zhang P, Zha R, Qiu B, Zhang D, Bi Y, Han S, Li C, Zhang X. Separable amygdala activation patterns in the evaluations of robots. Cereb Cortex 2024; 34:bhae011. [PMID: 38383721 DOI: 10.1093/cercor/bhae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/27/2023] [Accepted: 12/29/2023] [Indexed: 02/23/2024] Open
Abstract
Given the increasing presence of robots in everyday environments and the significant challenge posed by social interactions with robots, it is crucial to gain a deeper understanding into the social evaluations of robots. One potentially effective approach to comprehend the fundamental processes underlying controlled and automatic evaluations of robots is to probe brain response to different perception levels of robot-related stimuli. Here, we investigate controlled and automatic evaluations of robots based on brain responses during viewing of suprathreshold (duration: 200 ms) and subthreshold (duration: 17 ms) humanoid robot stimuli. Our behavioral analysis revealed that despite participants' self-reported positive attitudes, they held negative implicit attitudes toward humanoid robots. Neuroimaging analysis indicated that subthreshold presentation of humanoid robot stimuli elicited significant activation in the left amygdala, which was associated with negative implicit attitudes. Conversely, no significant left amygdala activation was observed during suprathreshold presentation. Following successful attenuation of negative attitudes, the left amygdala response to subthreshold presentation of humanoid robot stimuli decreased, and this decrease correlated positively with the reduction in negative attitudes. These findings provide evidence for separable patterns of amygdala activation between controlled and automatic processing of robots, suggesting that controlled evaluations may influence automatic evaluations of robots.
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Affiliation(s)
- Zhengde Wei
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui 230026, China
- Key Laboratory of Brain-Machine Intelligence for Information Behavior-Ministry of Education, Shanghai International Studies University, Shanghai 201620, China
| | - Ying Chen
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui 230026, China
| | - Qian Zhao
- School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Jiecheng Ren
- School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Yi Piao
- Institute of Health and Medicine, Hefei Comprehensive Science Center, Hefei, 230071, China
| | - Pengyu Zhang
- School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Rujing Zha
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui 230026, China
| | - Bensheng Qiu
- Centers for Biomedical Engineering, School of Information Science and Technology, University of Science & Technology of China, Hefei, Anhui 230027, China
| | - Daren Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui 230026, China
- School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Shihui Han
- School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100091, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui 230026, China
- Key Laboratory of Brain-Machine Intelligence for Information Behavior-Ministry of Education, Shanghai International Studies University, Shanghai 201620, China
- Institute of Health and Medicine, Hefei Comprehensive Science Center, Hefei, 230071, China
- School of Mental Health, Bengbu Medical College, Bengbu, Anhui 233030, China
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Huo W, Yuan X, Li X, Luo W, Xie J, Shi B. Increasing acceptance of medical AI: The role of medical staff participation in AI development. Int J Med Inform 2023; 175:105073. [PMID: 37119693 PMCID: PMC10125218 DOI: 10.1016/j.ijmedinf.2023.105073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND Medical artificial intelligence (AI) in varying degrees has exerted significant influence on many medical fields, especially in the midst of the COVID-19 pandemic. However, little is known regarding how to address the reluctance of medical staff to use AI technology. While recent research has highlighted the importance of medical staff participation in the development of AI, the current understanding of influence of medical staff participation on acceptance of AI is limited. OBJECTIVES To provide insights into the mechanism that how medical staff participation impacts on the medical staff's acceptance of AI and to examine the moderating effect of speciesism. METHODS This study was conducted from 6th August to 3rd September. Data was collected from doctors and nurses and a total of 288 valid questionnaires were obtained. Smart PLS 3.2.8 was used as partial least square (PLS) software to validate the research model. RESULTS The study determined that medical staff participation had a significant impact on acceptance of medical AI-IDT (β = 0.35, p ≤ 0.001) and acceptance of medical AI-ADT (β = 0.44, p ≤ 0.001). The results also show that AI self-efficacy and AI anxiety have significant mediating effects and speciesism has significant moderating effects among the theoretical model. CONCLUSIONS This study provides insights into ways to explore influence factors of acceptance of AI based on user participation perspective. The results indicate that medical staff participation enhances acceptance of medical AI through the cognitive path (i.e., AI self-efficacy) and the affective path (i.e., AI anxiety). These results have practical implications for how organizations assist the staff to accommodate themselves to AI technology in the future.
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Affiliation(s)
- Weiwei Huo
- Shanghai University, Chengzhong Road, 201800 Shanghai, China.
| | - Xinze Yuan
- Shanghai University, Chengzhong Road, 201800 Shanghai, China.
| | - Xianmiao Li
- Anhui University of Science and Technology, 168 Taifeng Street, 232000 Huainan, China.
| | - Wenhao Luo
- Shanghai University, Chengzhong Road, 201800 Shanghai, China.
| | - Jiaying Xie
- Shanghai University, Chengzhong Road, 201800 Shanghai, China.
| | - Bowen Shi
- Shanghai World Foreign Language Academy, Hongcao South Road, 200233 Shanghai, China.
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Nertinger S, Kirschner RJ, Naceri A, Haddadin S. Acceptance of Remote Assistive Robots with and without Human-in-the-Loop for Healthcare Applications. Int J Soc Robot 2022. [DOI: 10.1007/s12369-022-00931-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
AbstractAssistive social robots aim to facilitate outpatient-care including required safety critical measures. Accepting a robot to perform such measures, e.g., operate in close physical interaction for medical examinations, requires human trust towards the robot. Human-in-the-loop (HIL) applications where the robot is teleoperated by a human expert can help the person to accept even risky tasks performed by a robot. Therefore, the assistive humanoid GARMI was designed to enable HIL applications with varying autonomy. In this study, we use GARMI to understand which tasks in the framework of care may be accepted depending on human socio-demographics and user beliefs as well as the level of robot autonomy. Firstly, we seek to understand the general acceptance of GARMI using the Almere questionnaire. Secondly, we ask adults to rate their willingness to use several functionalities of GARMI. Lastly, we investigate the effect of the introduction method of GARMI on user acceptance. We assemble all relevant factors on acceptance to provide direction in the user-centered design process of assistive robots. The results of 166 participants show that alongside others, trust towards the robot and utilitarian variables such as perceived usefulness are the most influencing factors on the acceptance of GARMI and should be considered for the design of robotic semi-autonomous outpatient-services.
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Polakow T, Laban G, Teodorescu A, Busemeyer JR, Gordon G. Social robot advisors: effects of robot judgmental fallacies and context. INTEL SERV ROBOT 2022. [DOI: 10.1007/s11370-022-00438-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Savela N, Latikka R, Oksa R, Kortelainen S, Oksanen A. Affective Attitudes Toward Robots at Work: A Population-Wide Four-Wave Survey Study. Int J Soc Robot 2022; 14:1379-1395. [PMID: 35464870 PMCID: PMC9012866 DOI: 10.1007/s12369-022-00877-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/16/2022] [Indexed: 11/29/2022]
Abstract
AbstractRobotization of work is progressing fast globally, and the process has accelerated during the COVID-19 pandemic. Utilizing integrated threat theory as a theoretical framework, this study investigated affective attitudes toward introducing robots at work using a four timepoint data (n = 830) from a Finnish working population longitudinal study. We used hybrid multilevel linear regression modelling to study within and between participant effects over time. Participants were more positive toward introducing robots at work during the COVID-19 pandemic than before it. Increased cynicism toward individuals’ own work, robot-use self-efficacy, and prior user experiences with robots predicted positivity toward introducing robots at work over time. Workers with higher perceived professional efficacy were less and those with higher perceived technology-use productivity, robot-use self-efficacy, and prior user experiences with robots were more positive toward introducing robots at work. In addition, the affective attitudes of men, introverts, critical personalities, workers in science and technology fields, and high-income earners were more positive. Robotization of work life is influenced by workers’ psychological well-being factors and perceived as a welcomed change in the social distancing reality of the pandemic.
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Affiliation(s)
- Nina Savela
- Tampere University, Kalevantie 4, 33100 Tampere, Finland
| | - Rita Latikka
- Tampere University, Kalevantie 4, 33100 Tampere, Finland
| | - Reetta Oksa
- Tampere University, Kalevantie 4, 33100 Tampere, Finland
| | | | - Atte Oksanen
- Tampere University, Kalevantie 4, 33100 Tampere, Finland
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Tuisku O, Pekkarinen S, Hennala L, Melkas H. Decision-makers’ attitudes toward the use of care robots in welfare services. AI & SOCIETY 2022. [DOI: 10.1007/s00146-022-01392-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
AbstractThe purpose of this study was to investigate the attitudes of decision-makers toward the use of care robots in welfare services. We investigated their knowledge regarding the use of care robots in welfare services as well as their attitudes toward using robots in their own care and in the care of various user groups, for example, children, youths, and older people. We conducted an online survey with a range of Finnish decision-makers as respondents (N = 176). The respondents were divided into two groups: service actors (n = 104) and research and development (R&D) actors (n = 72). The respondents did not regard themselves as having much knowledge about robotics; however, the results showed that the R&D actors had more overall knowledge of the use of robots than the service actors. The R&D actors were found to be more willing to accept a robot as part of their own care as well as part of the care for various user groups. The contribution of this study is a better understanding of the views of the decision-makers who are or will be in charge of the acquisition of technological devices in welfare services.
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“I Have to Praise You Like I Should?” The Effects of Implicit Self-Theories and Robot-Delivered Praise on Evaluations of a Social Robot. Int J Soc Robot 2022. [DOI: 10.1007/s12369-021-00848-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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