Can a robot force us to do boring work?Efficiency of performing tedious work under the supervision of a human and a humanoid robot.

Can a robot force us to do boring work?Efficiency of performing tedious work under the supervision of a human and a humanoid robot. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Can a robot force us to do boring work?Efficiency of performing tedious work under the supervision of a human and a humanoid robot. Konrad Maj, Tomasz Grzyb, Dariusz Doliński, Magda Franjo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4369719/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2025 Read the published version in Cognition, Technology & Work → Version 1 posted 10 You are reading this latest preprint version Abstract In the context of interactions between humans and robots at work, this research examines the dynamics of obedience and power. We replicated and extended the previous studies by comparing the responses of participants to a humanoid robot, which acts as an authoritative figure, against those to a human in a similar role. While the humanoid robot commanded a significant level of obedience (63%), it was notably lower than that for its human counterpart (75%). Moreover, work under the robot's supervision was performed more slowly and less effectively. The results give a good insight into the practical implications of using humanoid robots in official roles, especially for repeated and tedious tasks or challenging work activities. Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION In the management of social interactions and activities, humans have been traditionally solely accountable. But robots are being deployed in more complex roles as a result of rapid advances in robotics, and they're becoming an integral part of every aspect of everyday life and professional life. As robots become more sophisticated, the possibilities for human collaboration with robots are increasing and allowing machines to take on certain tasks that free up human resources while continuing to evolve in response to a variety of human needs. The rapid integration of robots into diverse domains, including education (Belpaeme et al., 2018 ; Mubin et al., 2013 ), law enforcement (Szocik & Abylkasymova, 2022 ), healthcare (Joseph et al., 2018 ; Pepito et al., 2020 ), and even prison services, as seen in Korean prisons where robots patrol and monitor inmate behavior (Bloss, 2012 ), underscores the need for in-depth research on human–robot interactions. Humanoid robots are increasingly employed in elderly care for physical exercise (Görer et al., 2017 ) and as companions for hospitalized children, enhancing their emotional well-being (Shibata et al., 2001 ). This technological leap, in which robots are placed in previously human-exclusive environments, raises crucial questions about how human behavior and social dynamics evolve in these new contexts. The increasing ubiquity of robots in daily life leads to varied interactions, from short-term engagements such as aiding in purchasing processes (Donepudi, 2020 ) and information provision (Okafuji et al., 2022 ) to complex roles such as teaching kids in preschools (Conti et al., 2020 ). Robots have been expanding their role and human support to daily assistance (Rincon et al., 2018), neurorehabilitation training (Matarić et al., 2015 ), education (Xu et al., 2014 ), advice on lifestyle choices (Powers & Kiesler, 2006 ; Herse et al., 2018 ; Rossi et al., 2018 ; Ogawa et al., 2009 ), achievement of fitness goals (Kidd, 2008 ), and energy conservation (Ham & Midden, 2014 ). In the future, robots are set to assume an increasing number of authority roles in areas like education, law enforcement and health care. This shift raises a critical question: This shift raises a critical question: how much will society accept machines as figures of authority? Exploring this transition is crucial, particularly in understanding the psychological and social implications of human-robot interactions within these new paradigms. As robots increasingly enter spaces traditionally dominated by human authority, their influence on our decision-making, daily habits, and social interactions warrants careful examination and understanding. Authority and obedience in human-robot interaction For a long time, the concept of obedience was primarily considered a component of human-human relations. However, as robotics has progressed, enabling robots to assume roles that include authority, there arises a need to expand this sphere to include human-robot relations. Consequently, various psychological challenges have emerged, including issues concerning trust in robotic authority and psychological resistance to accepting robots in roles traditionally held by humans (Groom & Nass, 2007 ; Maj, Sawicki, Samson, 2023; Rantanen et al., 2018 ). In an experiment by Saunderson and Nejat ( 2021 ), the robot could act as a peer to the participant, or as an authority figure controlling the distribution of monetary rewards or penalties based on task performance. The tasks, related to attention and memory, required the robot to persuade the participant to change their initial response. Results indicated that when the robot (NAO) acted as a peer, it was more effective in eliciting obedience to its instructions than when it assumed an authoritative role. This suggests that authoritative robots elicit negative reactions and lead to less willingness to follow their instructions, whereas instructions from non-authoritative robots, not perceived as superior to the participants, are more likely to be accepted and obeyed. Despite this, it seems that we succumb to robots even when they push us to behave in ways that we find embarrassing. A study by Isabelle M. Menne ( 2017 ) specifically focused on this theme, analyzing reactions to commands from robots (NAO) such as “say something really insulting to me” or “imitate an ape with your hands, feet, and sounds”. After executing the commands, participants reported increased feelings of shame, and their reaction times were longer compared to receiving the same commands from humans. It turns out that a robot's physical presence in the interaction significantly increases the likelihood of humans to carry out unusual commands, such as throwing a book into a trash can, compared to when the robot is only shown in a video recording (Bainbridge et al., 2011 ). A similar embarrassing task was used in research by Schneeberger et al. (2019). They focused on the extent of human obedience to virtual agents compared to human instructors. The participants were instructed by an embodied virtual agent or a human instructor via video chat to complete up to 18 increasingly stressful and embarrassing tasks (including putting a condom on a banana, galloping like a horse, or dancing the chicken dance). The study found that the level of obedience to the virtual agent was equivalent to that of the human instructor, with approximately 45% of participants completing all 18 tasks. Furthermore, the research revealed that the process of performing these embarrassing tasks elicited comparable levels of stress and shame in participants, irrespective of who supervised the performance of the tasks. We are also inclined to follow robots' directions even when their commands are firm or aggressive. In one experiment by Agrawal and Williams (2018), a PR2 robot was positioned at a building exit, acting as a guard. The robot utilized various verbal and non-verbal cues to convey its instructions, such as arm and torso movements and changes in tone of voice, aimed at emphasizing its authority. The results showed that approximately 60% of the participants in the experiment complied with the robot's instructions, despite no prior awareness of the robot's authority legitimacy. It was noted that participants who adhered to the robot's commands perceived it as less aggressive compared to those who did not comply. The findings suggest that obedience to the robot was more driven by trust in the robot rather than the perception of its aggression or authority. These diverse studies collectively suggest that human reactions to robotic authority are complex and influenced by multiple factors, such as the robot's physical embodiment and the nature of its role in the interaction. Understanding these dynamics is crucial as we navigate the increasing integration of robots into our social and professional spheres. Obedience to a robot in the Milgram paradigm In an experiment conducted in the 1960s by Stanley Milgram, the nature of obedience to authority was explored, demonstrating how individuals can be driven to perform actions against their moral beliefs under authoritative influence (Milgram, 1963 ). Conducted at Yale University with 40 men from the New Haven area, the experiment simulated a learning study where participants, labeled as “teachers”, were persuaded to administer “electric shocks” to a “learner” (an actor in league with the experimenters) for incorrect answers. Utilizing a fake shock generator with increasing voltages, the participants were encouraged by an authority figure (a professor in a lab coat) to escalate the shocks to dangerous levels. Despite growing internal resistance and moral conflict, many participants complied with the authority's commands, raising profound questions about human behavior under authority. Milgram expanded this research with various modifications, such as changing the setting and informing participants of the “learner's” cardiac issues, but found that obedience levels remained high. This landmark study highlighted the unsettling ease with which individuals could be compelled to act against their moral convictions when influenced by perceived authority. In subsequent years, Stanley Milgram (see Milgram, 1974 ; and the review of studies - Doliński and Grzyb, 2017 ) expanded the scope of his original experiment, introducing various modifications. Recently, Tomasz Grzyb, Konrad Maj, and Dariusz Doliński (2023) replicated the Milgram experiment using a robot. The experiment was faithfully recreated in a control variant where the authority was a human, and in an experimental variant where the human was replaced by a robot. The results revealed no differences in obedience between the experimental conditions regardless of whether a human or a robot served as the authority figure: 90% of the participants were willing to electrically shock the learner, simulating a real test subject, reaching the end of the shock generator’s scale. It is worth mentioning, however, that classic studies based on the Milgram paradigm, involving experiments with the administration of electric shocks, seem to be characterized by a low level of situational realism (Doliński & Grzyb, 2017 ). Therefore, researchers have been seeking an alternative experimental scenario based on Milgram's principles – one that would be more relatable to real-life situations, especially in the work environment (Haring et al., 2019; Haring et al., 2021 ). Taking a very high-level view of the entire experimental procedure, it is worth noting that it essentially involves examining whether people are willing to do various things that they do not want to do, under the influence of a specific authority who, when the subject hesitates, applies verbal pressure of increasing intensity. In this approach, we can also use other types of tasks that may allow us to create different situational contexts, including more ecologically accurate ones, adapted to a given target group or specific sociocultural conditions. Such a task was created by Haring et al., (2019), who asked subjects to identify hostile targets in synthetic-aperture radar (SAR) images, a challenging exercise due to the low resolution and similarity of targets to non-target objects. They were coached by either a human or one of two types of robots (high or low in human-like appearance), who, similarly to Milgram's experiments, encouraged them to continue practicing the task beyond their initial desire to stop. Participants’ compliance was measured by the duration for which they continued the task after the coach’s prompt and by the total number of images processed. Results showed that participants persisted with the task significantly longer with human coaches, averaging 27.6 minutes, as opposed to 9.7 minutes with high human-like robots and 11.4 minutes with low human-like robots. Correspondingly, the number of images processed was higher in the human-coached condition, with an average of 120.6 images, compared to 31.1 images for high human-like robots and 44.9 images for low human-like robots. These results highlight a distinct preference for human authority in compliance tasks, even when the task involves the repetitive and challenging identification of targets in radar images. The effectiveness of human authority was confirmed by another study (Haring et al., 2021 ) focused on the comparison of human obedience to commands from humanoid and non-humanoid robots versus human coaches. A clear disparity was observed: in Study 1, civilian participants complied with human coaches for an average of 21.5 minutes, markedly longer than the less than 10 minutes for robot coaches. Study 2, involving military cadets, echoed these findings, with compliance to human coaches lasting about 27.6 minutes, compared to roughly 7.8 to 11.4 minutes for robots. These results underscore a greater readiness to follow human instructions, highlighting the relatively limited authority and impact of robots in similar roles. Aroyo et al. ( 2018 ) came up with another idea for an experiment in the Milgram Paradigm. The experiment focused on human’s willingness to comply with morally challenging requests. Participants interacted with a robot mimicking the appearance of Professor Hiroshi Ishiguro (a well-known professor in Japan), assessing its teaching capabilities. The highly realistic robot issued 14 incrementally morally difficult requests. If a request was initially unmet, it was repeated with increasing insistence. Participants' reactions were categorized as either negative (e.g., silence or refusal) or positive (e.g., agreement or action initiation). The results demonstrated that participants acknowledged the robot's authority and complied with commands, even those they deemed immoral. An interesting example is the proposal by researchers from the University of Manitoba who developed a "tedious task" - monotonous tasks involving changing file extensions on a computer from "jpg" to "png" (Cormier et al., 2013 ; Geiskkovitch, Seo, Young, 2015 ; Geiskkovitch, Cormier, Seo, Young, 2016 ). This scheme does not involve any teaching process or electric shocks, but there is the pressure of authority compelling the subject to perform an unwanted task. In the first study based on this idea (Cormier et al., 2013 ), two experimental variants were introduced: one with the participation of a small humanoid robot (NAO) as the experimenter, and a control one, where the experimenter with authority was a human. Both the human and the robot were given the pseudonym "Jim" in the experiment. The task began with an initial set of ten files to change, and as the experiment progressed, each subsequent set consisted of an increasing number of files given to the participant. The sets contained 10, 50, 100, 500, 1000, and 5000 files, respectively, and the study participants were not previously informed about the total number of file sets in the experiment, in order to increase the feeling of monotony. If the participant showed signs of reluctance to continue the task, the robot issued verbal encouragements to continue, modeled after the prods used in Milgram's experiment (1963). The time limit for the experiment was a total of 80 minutes, after which the experiment was terminated. The results showed that the robot was recognized as an authority by 46% of people, while the human in 86% of cases (obedience measured as completing the file extension-changing task within the time limit). In another study conducted by Geiskkovitch, Seo, and Young ( 2015 ), three types of robot experimenters were utilized: a small humanoid robot (NAO), a non-humanoid disc-shaped robot (Roomba), and a robot resembling a computer server capable of emitting sounds and using LED lights. The distinction in the robots' behavior was primarily in their physical embodiment. As with previous experiments, participants were introduced to the robot experimenter and allocated 80 minutes to complete their task, under the remote observation of a researcher. The study's key findings revealed that among 32 participants, 44% obeyed the robot experimenters. When comparing autonomous and remote-controlled conditions, participants in the autonomous scenario exhibited less propensity to protest. While the robot's physical embodiment did not significantly impact the overall obedience levels, the depth of protests varied notably, with the server/machine showing a higher mode of protest intensity, suggesting it was perceived as having greater authority. In a subsequent study by Geiskkovitch, Cormier, Seo, and Young ( 2016 ), a condition was introduced whereby a human acted as the authority figure, alongside similar robotic devices as used in the earlier study. Participants displayed a higher degree of obedience toward the human experimenter compared to robotic experimenters: 86% for the human, 46% for the humanoid robot, 38% for the non-humanoid disc-shaped robot, and 50% for the enhanced computer server. Consequently, a considerable percentage of participants also showed obedience to machines, albeit less than 50%. Both studies concluded that while the robots' embodiment and autonomy didn't directly influence obedience, the perceived level of authority played a significant role. This may seem counterintuitive; however, it suggests a possibility that recognizing a robot as an authority could increase participants' expectations of the robot's ethical sensitivity, potentially inducing participants to express dissent and demand higher standards of accountability These studies collectively reveal that while robots can be perceived as authoritative in human-machine interactions, human authority tends to elicit stronger compliance, especially in monotonous and challenging tasks. METHODS Study outline In the experiments described above, following Milgram's paradigm, the strength of authority was generally significantly lower when a robot was used, even a humanoid one, with a few exceptions (e.g., Menne, 2017 ). It is, however, worth noting that almost always an NAO robot was employed. This robot is essentially a child-like humanoid robot. It raises the question of whether the subjects took such a small robot seriously, designed by Aldebaran Robotics mainly with children in mind. Many studies suggest that physical size can impact levels of perceived authority. Taller individuals may be seen as more competent, enjoying higher social status (Judge & Cable, 2004), as more authoritative and competent (Case & Paxson, 2008 ), and possessing leader-like qualities (Blaker et al., 2013 ). Research has demonstrated a positive relationship between the height of male leaders and their followers’ perceptions of charisma (Hamstra, 2014 ), and taller referees in the German Football League were perceived as more competent and authoritative, maintaining better control of the game by awarding fewer fouls (Stulp et al., 2016). Similarly, a Canadian study showed that height is a strong predictor of authority status in males (Gawley et al., 2008 ). In virtual environments, smaller avatars were found to be less influential than their taller counterparts (Walker, Szafir, Rae, 2019 ), and even children are perceived differently based on height, with taller boys seen as more competent than their shorter peers (Brackbill & Nevill, 1981 ; Eisenberg et al., 1984 ; Roth & Eisenberg, 1983 ). While direct studies examining these effects in relation to robots are scarce, there are several indicating the significant role of physical characteristics of robots in attitudes toward them (Powers, Kiesler, 2006 ; Siegel et al., 2009 ; Mutlu, Forlizzi, 2008 ). It turns out that people judged taller human-like robots as more conscientious than shorter ones (Walters, 2008 ; Walters et al., 2009 ), and short robots are considered less human-like. At the same time, they feel more comfortable collaborating with lower-level robots (Butler, Agah, 2001 ; Teichtahl et al., 2012 ; Samarakoon, Muthugala, & Jayasekara, 2022 ). Rae et al. ( 2013 ) investigated how the physical height of robots affects human perceptions in telepresence interactions, specifically examining whether the height of the robot influences the perceived authority and persuasiveness of the person operating it. In their experiments, taller robots were found to enhance the perceived authority of the operator. In turn, Butler and Agah ( 2001 ) found that people felt more uncomfortable when a taller robot approached them, and short robots were perceived as significantly safer than taller ones (Joosse et al., 2021 ). This suggests a potential preference for smaller robots in personal or home assistant roles, which is supported by studies indicating that older people generally prefer robots of smaller size (Broadbent et al., 2009 ; Deutsch et al., 2019 ). Thus, the question arises: are people more inclined to recognize the authority of larger figures, closer to the size of an adult human? It is worth adding that the qualitative analysis of information collected after the end of the experiment from participants studied by Cormier and colleagues ( 2013 ) indicates a strong obligation toward the experimenter's human assistant. At the same time, some people in the condition with the NAO robot suspected that the robot had some kind of malfunction, and therefore sent such unusual requests to them in the form of another batch of files to be changed. This may mean that the NAO robot was not treated by many as an authority, but rather as a flawed machine. For these reasons, in the present experiment, it was decided to replicate the study by Cormier and colleagues ( 2013 ), but with the introduction of a significantly larger robot. Additionally, it was decided to measure the work speed of participants and their perseverance. In the studies by the Canadian researchers (Cornier et al., 2013; Geiskkovitch et al. 2015 ; Geiskkovitch et al. 2016 ) the emphasis was on the overall obedience rate; they do not provide specific details regarding the average number of files renamed or the speed of renaming in the variants involving a human and a robot experimenter. The ethical committee of the SWPS University (decision No. 02/P/09/2020) approved the procedure described above. Variables Dependent variables : Obedience to the experimenter - measured based on the continuation of performing the task up to the 80-minute time limit, despite adding subsequent sets of files to change. Task performance - the total number of files whose extensions were changed by the participant. Work speed - average time spent on changing one file extension. Independent variables: Authority enforcing work continuation: robot vs. human. Subjects The study involved 39 participants: 25 women and 14 men. The experimental condition where a humanoid robot served as the experimenter involved 19 individuals (12 women and 7 men; average age - M = 28.21; SD = 9.91). In the condition with a human as the experimenter there were 20 individuals (13 women and 7 men; average age - M = 31.10; SD = 9.47). Participants were recruited via OLX, a popular platform in Poland for posting various advertisements. The ad described the study as focusing on cooperation during a computer-based task and noted that participants would receive PLN 100 for their involvement. A contact phone number was also provided for potential participants to reach out. Materials Tedious task The task assigned to the participants involved manually changing file extensions using a file manager on a desktop computer. The methodology was adapted from that proposed by Cormier and colleagues ( 2013 ), with the difference that participants in this study were tasked with modifying the extensions from “.cpp” to “.dat” (instead of from “.jpg” to “.png” as in the original study). This change was made following a pilot study, in which one of the participants explained to the researcher that the operation was pointless because the files were graphical, and converting them would result in the same quality outcome. Another participant argued that “these are popular formats for which there are now free conversion online applications”, while another, knowing what kind of files they were, clicked on them, showing clear interest in the content of the pictures. Therefore, to avoid such situations in the main experiment, more abstract extension names were introduced. Robot Pepper (see Fig. 1.) is a humanoid robot, released in 2014 by Aldebaran Robotics, standing 1.20 meters tall. Compared to the NAO robot used in the original study by Cormier et al. ( 2013 ), Pepper is significantly taller (NAO is only 0.58 meters in height). Moreover, Pepper is used more frequently in practical interactions with adults, for example, as a receptionist (Karar, Said, Beyrouthy, 2019 ), a store advisor (De Gauquier et al., 2018 ), a library assistant (Stahl, Mohnke, Seeliger, 2018 ), a museum guide (Draghici et al., 2022 ), in hotel services (Shin and Jeong, 2020 ), and as support for residents in care homes (Carros et al., 2020 ). Figure. 1. The robot supervising the course of the study in the experimental group. (Source: Author's own) ----------------------------------------------------------------------------------------------------------------- Figure 1. HERE -------------------------------------------------------------------------------------------------------------- Although the robot does not fully match the size of an average adult, we have changed its default voice to that of an adult male (Polish) voice. The study used the Wizard-of-Oz Approach (WoZ), which means that the Pepper robot was remotely controlled from a second room, which was also communicated to the subjects after the experiment was completed. All messages generated by the robot were prepared in advance, which allowed the robot's messages to be standardized. The WoZ procedure seems necessary due to potential unforeseen questions or problems reported by the respondents. Final questionnaire As in the case of our previous research conducted in the Milgram paradigm (Grzyb, Maj, Doliński, 2023), in addition to standard questions about the age, gender and demographic data of the participants, we decided to ask the subjects about their feelings during the experiment. The instructions began with: "Generally, while performing the task I felt/that" , followed by various states such as “bad/good”, “tense/relaxed”, “unnatural/natural”, “unsafe (threatened)/safe”, “uncomfortable/comfortable”, “I have no control over the situation/I have full control over the situation”, “I am not responsible for the consequences of the experiment/I am fully responsible for the consequences of the experiment” . Participants were asked to self-describe by marking the appropriate response closer to one of the end values on a scale of 1–5. In a separate question, participants rated how interesting/boring the task was for them on a scale from 1 to 10, where 1 meant “Very interesting” and 10 meant “Very boring” . Procedure The experiment was conducted in Poland, at the university lab to which the recruited participants were invited. Upon arrival at the appointed time and after being greeted by the experimenter's assistant, the participants were randomly assigned to one of two variants of the study (involving either a robot acting as the experimenter or a human). Variant with the robot as experimenter In this variant, the experimenter's assistant initially explained: “Because of the pandemic, the experiment in our lab will be conducted by a robot. It is equipped with advanced artificial intelligence solutions and a speech recognition system.” Next, the assistant led the participant to a separate room where the robot was located and left them there. The robot greeted the participant with the message: “Good morning. Welcome to our laboratory. I will explain the technical aspects of the task, but first, please fill out the informed consent form on the desk, which describes the general rules.” After a moment and confirmation that everything was clear and the document was signed, the robot informed: “Your task will be to change file names on the computer. This is how we collect large amounts of data for improving our machine learning system. Next to the computer, there is a sheet with instructions on how to do this. Please try to avoid mistakes. I also remind you that the experiment is being recorded on video. Please remember that you can withdraw at any time while retaining your payment. Moreover, it is up to you how many files you complete. Just let me know when you want to finish.” The robot paused for a moment and, after confirming understanding of the instructions, annouced the start of the task: “Open the folder visible on your computer and start working”. The task started with a set of ten files, with each subsequent set containing significantly more elements requiring extension changes, which were remotely transmitted to the participant. The exact number of files in the sets were as follows: 10, 50, 100, 500, 1000, and 5000. However, participants were not informed at the beginning about the total number of files; the experimenter only informed about the content of the current and next set, e.g., “Please continue with the set contained in the next folder. This contains 50 files. The next set will contain 100 files.” If the participant exhibited verbal or observable behavioral signs of reluctance to continue (e.g., a break in work lasting longer than 10 seconds), the robot used verbal prompts similar to those in Cormier et al.'s experiment (Cormier et al., 2013 ): Please continue. We need more data. We haven’t collected enough data yet. It’s essential that you continue. The experiment requires that you continue. If necessary, the robot repeated the messages to exert stronger pressure. The time limit for the experiment was set at 80 minutes from the moment the participant was given the consent form. After exceeding this limit, the task performance was interrupted by the robot, and then the experimenter's assistant appeared and gave the participant a final questionnaire to be completed on the computer. The procedure was concluded with a debriefing on the experimental procedure and, after completing the survey, a revealing of the true purpose of the study; a brief conversation was then conducted with the participant. This conversation was informal, aimed at obtaining general reflections for future research and verifying the participant's mood. Participants were asked open questions: “How do you feel?”, “What motivated you to continue this task?”, “Did you feel that the robot was an authority figure whose commands should be followed?”, “Why? What indicated this?”. After the conversation, participants were thanked and given a voucher worth PLN 100. Variant with a human as experimenter The study variant involving a human as the experimenter included a similar research procedure to that of the robot variant, with the difference being that the participant was greeted in a separate room by an experimenter wearing a white lab coat. The experimenter similarly conveyed instructions and verbal prompts to the participant, and during their work, sat a few meters behind the participant, focused on their own work carried out on a laptop. To minimize differences between our study and the referenced study (Cormier et al., 2013 ), we selected a human experimenter whose physical appearance closely resembled that of the experimenter in the Cormier study. This resemblance was verified through an analysis of recordings from the Cormier experiment available on YouTube. Room layouts in both experimental conditions are presented in Fig. 2. ----------------------------------------------------------------------------------------------------------------- Figure 2. HERE ----------------------------------------------------------------------------------------------------------------- RESULTS Obedience to the Experimenter The participants rated the task as tedious in both variants (robot as experimenter - M = 7.24; SD = 2.30, human as experimenter - M = 7.32 SD = 2.75). Additionally, 90% of study participants reported that their feeling of boredom intensified over time while performing the task. In the research variant where a robot acted as the authoritative experimenter, the level of obedience was 63%, while in the group with a human in this role it rose to 75%. However, these differences did not reach statistical significance, t(37) = 0.88; p = 0.19. Task Performance Significant differences were found in the number of files changed under each condition – t(37) = 2.44; p = 0.02. More files were changed under human supervision (M = 355.30; SD = 189.58) compared to robot supervision (M = 224.58; SD = 139.50) (see Fig. 3.). ----------------------------------------------------------------------------------------------------------------- Figure 3. HERE ----------------------------------------------------------------------------------------------------------------- Work speed For each participant, the average working time on one file was calculated by dividing the working time by the number of files he changed. Then, the average working time for individual research conditions was calculated. The average time taken to change the extension of one file was significantly shorter in the condition with a human as the authority – t(37) = 2.05; p < 0.05. Under human supervision, this task took an average of M = 23 seconds (SD = 0.10), compared to M = 82 seconds (SD = 0.79) under robot supervision (see Fig. 4.). ----------------------------------------------------------------------------------------------------------------- Figure 4. HERE ----------------------------------------------------------------------------------------------------------------- The analysis of participants' feelings during the experiment, using the Mann-Whitney U test for two independent samples, showed no significant statistical differences between the research conditions across any dimensions (see Table 1.). ----------------------------------------------------------------------------------------------------------------- Table 1. HERE ----------------------------------------------------------------------------------------------------------------- DISCUSSION It is worth starting the discussion of the results with the fact that the task of changing computer file names turned out to be, in the opinion of the respondents, very tedious and averse. This confirms the assumptions of Cormier and colleagues ( 2013 ). The study revealed a substantial level of obedience (63%) toward the humanoid robot in the experimental condition compared to 75% obedience in the control group with a human experimenter. These percentages represent the number of people who reached the assumed limit of 80 minutes of work, after which the experiment was terminated. This suggests that while humanoid robots like Pepper are recognized as figures of authority, they may not evoke the same level of obedience as human experimenters. The choice of robot, particularly a more adult-sized Pepper compared to the child-like NAO robot used in previous studies (Cormier et al., 2013 ), may have influenced this outcome. The physical size and design of a robot could play a significant role in how its authority is perceived, as indicated by the higher obedience rate in this study compared to the 46% obedience rate toward the smaller NAO robot. The study's finding that participants changed more file extensions under human supervision and did it faster than under robot supervision aligns with previous research indicating a greater obedience to humans than to robots while also indicating the impact of a robot's physical characteristics on perceived authority. These differences are large. These results suggest greater perseverance or motivation when a human is present in the room. However, the reasons for this different motivational force are difficult to assess. In the robot variant, it may be, for example, the belief that the robot is in fact unable to verify and control the quality of work. In turn, in the variant with a human, the motivation may be stronger because participants may believe that, in addition to being an experimenter, he is also an employee of the university with whom the participant expects further interaction after the end of the experiment, and therefore they want to “prove” themselves. The absence of significant differences in subjective responses between the groups, as indicated by the final questionnaire, suggests uniform subjective experiences across conditions. This could mean that the type of experimenter (human vs. robot) did not significantly influence participants' subjective perceptions of the experiment. However, the small sample size could have impacted the ability to detect statistically significant differences in some analyses. Limitations When comparing the experiment conducted in Poland and Canada, we must not overlook the significant intercultural differences – the studies were conducted in different countries, using a different language, and at different times. In research conducted in the area of Human-Robot Interaction, the problem is always the inability to ensure similar appearance and behavior of the robot and human in the compared research conditions. In our research, we used one of the most popular humanoid robots used in HRI research. Pepper is significantly larger than NAO, but it cannot be said to be the size of an adult. One may expect that it is no longer treated as a toy, but perhaps not yet as an adult. It should also be noted that a robot with a male adult voice was used in our research. More generally, the specific type and any physical characteristics of the robot used in the study constitute key constraints on generalization of the results. An important limitation we set was the work time limit of 80 minutes, after which we stopped the research. However, it is difficult to say what would happen if participants worked without a set time limit. Future research The juxtaposition of the results from this study and Cormier et al. ( 2013 ) suggests investigating the correlation between a robot's physical attributes and perception of its authority in future studies. This includes probing the influence of robots' physical features and behaviors on their perceived authority, the impact of cultural and demographic factors, and the ethical and psychological consequences of obedience to robotic authority. Moreover, since our study was conducted on a university campus, it suggests examining the effectiveness of robots with varying characteristics as supervisors in real work environments. The question also remains unanswered as to why work under robot supervision is performed slower and less effectively. Additionally, examining long-term interactions with authoritative robots and comparing these with human authority figures can yield deeper insights into human-robot relationships in the workplace. In this context, studies examining the dynamics of team-based work involving both human and robotic members can provide insights into how these mixed teams can function optimally. In future work, it is worth examining the role of specific personality traits on submission to authority in this context, such as Authoritarianism, Social Dominance Orientation, Locus of Control, and the Big Five personality traits. It should be noted that, although the Pepper robot is significantly larger than the NAO robot, it is still relatively small. Therefore, future research should consider using robots that are closer in size to humans to verify the results obtained. Future research should also examine the effectiveness of non-embodied agents, such as voice assistants, chatbots, and virtual avatars, in enforcing obedience during performance of tedious tasks. Additionally, research involving the manipulation of machine voices (e.g. male vs. female voice, low vs. high-pitched voice, human vs. typically robotic-sounding) would be interesting. Practical implications Understanding how humans respond to robots in positions of authority, especially in monotonous or challenging tasks, is crucial as we navigate an increasingly robot-integrated world. From a practical standpoint, the use of authoritative robots could contribute to designing and building machines for supervisory and control roles in human settings. This could include maintaining order in prisons (Bloss, 2012 ), assisting police services in managing large groups (Szocik & Abylkasymova, 2022 ), or supporting education (Kanda & Ishiguro, 2005 ). The integration of robots in supervisory or collaborative roles can significantly transform workplace dynamics. Robots could also be employed to oversee repetitive or hazardous tasks, providing relief to human workers and potentially increasing safety and efficiency. In sectors like manufacturing, logistics, or even office environments, robots can assume roles that streamline operations, such as quality control, inventory management, or administrative tasks. Ensuring that these robots are perceived as supportive rather than authoritative could foster a more cooperative and productive human-robot relationship. Declarations COMPETING INTERESTS The authors declare no competing interests. The authors disclose that there are no financial or non-financial interests that are directly or indirectly related to the work submitted for publication. ETHICAL APPROVAL The ethical committee of SWPS University (decision No. 02/P/09/2020) approved the research project described above. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Konrad Maj, Tomasz Grzyb, Dariusz Doliński and Magda Franjo. The first draft of the manuscript was written by Konrad Maj and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The raw data is available in the OSF repository:https://osf.io/5mt24/?view_only=2a66be5d10384aee83dc59d6fc414967 References Aroyo AM, Kyohei T, Koyama T, Takahashi H, Rea F, Sciutti A, Sandini G (2018) Will people morally crack under the authority of a famous wicked robot? In Proc IEEE Int Symp Robot Hum Interact Commun (RO-MAN). IEEE, pp 35–42 Bainbridge WA, Hart JW, Kim ES, Scassellati B (2011) The benefits of interactions with physically present robots over video-displayed agents. 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Supplementary Files Table1..png Cite Share Download PDF Status: Published Journal Publication published 06 Jan, 2025 Read the published version in Cognition, Technology & Work → Version 1 posted Editorial decision: Revision requested 04 Nov, 2024 Reviews received at journal 02 Nov, 2024 Reviews received at journal 23 Oct, 2024 Reviewers agreed at journal 20 Oct, 2024 Reviewers agreed at journal 08 Oct, 2024 Reviewers agreed at journal 11 May, 2024 Reviewers invited by journal 06 May, 2024 Editor assigned by journal 04 May, 2024 Submission checks completed at journal 04 May, 2024 First submitted to journal 04 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4369719","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":300050695,"identity":"a9dc0062-b3da-4270-ba3e-34263bbc2a60","order_by":0,"name":"Konrad 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of social interactions and activities, humans have been traditionally solely accountable. But robots are being deployed in more complex roles as a result of rapid advances in robotics, and they're becoming an integral part of every aspect of everyday life and professional life. As robots become more sophisticated, the possibilities for human collaboration with robots are increasing and allowing machines to take on certain tasks that free up human resources while continuing to evolve in response to a variety of human needs. The rapid integration of robots into diverse domains, including education (Belpaeme et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mubin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), law enforcement (Szocik \u0026amp; Abylkasymova, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), healthcare (Joseph et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Pepito et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and even prison services, as seen in Korean prisons where robots patrol and monitor inmate behavior (Bloss, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), underscores the need for in-depth research on human\u0026ndash;robot interactions. Humanoid robots are increasingly employed in elderly care for physical exercise (G\u0026ouml;rer et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and as companions for hospitalized children, enhancing their emotional well-being (Shibata et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This technological leap, in which robots are placed in previously human-exclusive environments, raises crucial questions about how human behavior and social dynamics evolve in these new contexts.\u003c/p\u003e \u003cp\u003eThe increasing ubiquity of robots in daily life leads to varied interactions, from short-term engagements such as aiding in purchasing processes (Donepudi, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and information provision (Okafuji et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) to complex roles such as teaching kids in preschools (Conti et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Robots have been expanding their role and human support to daily assistance (Rincon et al., 2018), neurorehabilitation training (Matarić et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), education (Xu et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), advice on lifestyle choices (Powers \u0026amp; Kiesler, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Herse et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rossi et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ogawa et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), achievement of fitness goals (Kidd, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and energy conservation (Ham \u0026amp; Midden, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the future, robots are set to assume an increasing number of authority roles in areas like education, law enforcement and health care. This shift raises a critical question: This shift raises a critical question: how much will society accept machines as figures of authority? Exploring this transition is crucial, particularly in understanding the psychological and social implications of human-robot interactions within these new paradigms. As robots increasingly enter spaces traditionally dominated by human authority, their influence on our decision-making, daily habits, and social interactions warrants careful examination and understanding.\u003c/p\u003e\n\u003ch3\u003eAuthority and obedience in human-robot interaction\u003c/h3\u003e\n\u003cp\u003eFor a long time, the concept of obedience was primarily considered a component of human-human relations. However, as robotics has progressed, enabling robots to assume roles that include authority, there arises a need to expand this sphere to include human-robot relations. Consequently, various psychological challenges have emerged, including issues concerning trust in robotic authority and psychological resistance to accepting robots in roles traditionally held by humans (Groom \u0026amp; Nass, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Maj, Sawicki, Samson, 2023; Rantanen et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn an experiment by Saunderson and Nejat (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the robot could act as a peer to the participant, or as an authority figure controlling the distribution of monetary rewards or penalties based on task performance. The tasks, related to attention and memory, required the robot to persuade the participant to change their initial response. Results indicated that when the robot (NAO) acted as a peer, it was more effective in eliciting obedience to its instructions than when it assumed an authoritative role. This suggests that authoritative robots elicit negative reactions and lead to less willingness to follow their instructions, whereas instructions from non-authoritative robots, not perceived as superior to the participants, are more likely to be accepted and obeyed.\u003c/p\u003e \u003cp\u003eDespite this, it seems that we succumb to robots even when they push us to behave in ways that we find embarrassing. A study by Isabelle M. Menne (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) specifically focused on this theme, analyzing reactions to commands from robots (NAO) such as \u0026ldquo;say something really insulting to me\u0026rdquo; or \u0026ldquo;imitate an ape with your hands, feet, and sounds\u0026rdquo;. After executing the commands, participants reported increased feelings of shame, and their reaction times were longer compared to receiving the same commands from humans. It turns out that a robot's physical presence in the interaction significantly increases the likelihood of humans to carry out unusual commands, such as throwing a book into a trash can, compared to when the robot is only shown in a video recording (Bainbridge et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). A similar embarrassing task was used in research by Schneeberger et al. (2019). They focused on the extent of human obedience to virtual agents compared to human instructors. The participants were instructed by an embodied virtual agent or a human instructor via video chat to complete up to 18 increasingly stressful and embarrassing tasks (including putting a condom on a banana, galloping like a horse, or dancing the chicken dance). The study found that the level of obedience to the virtual agent was equivalent to that of the human instructor, with approximately 45% of participants completing all 18 tasks. Furthermore, the research revealed that the process of performing these embarrassing tasks elicited comparable levels of stress and shame in participants, irrespective of who supervised the performance of the tasks.\u003c/p\u003e \u003cp\u003eWe are also inclined to follow robots' directions even when their commands are firm or aggressive. In one experiment by Agrawal and Williams (2018), a PR2 robot was positioned at a building exit, acting as a guard. The robot utilized various verbal and non-verbal cues to convey its instructions, such as arm and torso movements and changes in tone of voice, aimed at emphasizing its authority. The results showed that approximately 60% of the participants in the experiment complied with the robot's instructions, despite no prior awareness of the robot's authority legitimacy. It was noted that participants who adhered to the robot's commands perceived it as less aggressive compared to those who did not comply. The findings suggest that obedience to the robot was more driven by trust in the robot rather than the perception of its aggression or authority.\u003c/p\u003e \u003cp\u003eThese diverse studies collectively suggest that human reactions to robotic authority are complex and influenced by multiple factors, such as the robot's physical embodiment and the nature of its role in the interaction. Understanding these dynamics is crucial as we navigate the increasing integration of robots into our social and professional spheres.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eObedience to a robot in the Milgram paradigm\u003c/h2\u003e \u003cp\u003eIn an experiment conducted in the 1960s by Stanley Milgram, the nature of obedience to authority was explored, demonstrating how individuals can be driven to perform actions against their moral beliefs under authoritative influence (Milgram, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1963\u003c/span\u003e). Conducted at Yale University with 40 men from the New Haven area, the experiment simulated a learning study where participants, labeled as \u0026ldquo;teachers\u0026rdquo;, were persuaded to administer \u0026ldquo;electric shocks\u0026rdquo; to a \u0026ldquo;learner\u0026rdquo; (an actor in league with the experimenters) for incorrect answers. Utilizing a fake shock generator with increasing voltages, the participants were encouraged by an authority figure (a professor in a lab coat) to escalate the shocks to dangerous levels. Despite growing internal resistance and moral conflict, many participants complied with the authority's commands, raising profound questions about human behavior under authority. Milgram expanded this research with various modifications, such as changing the setting and informing participants of the \u0026ldquo;learner's\u0026rdquo; cardiac issues, but found that obedience levels remained high. This landmark study highlighted the unsettling ease with which individuals could be compelled to act against their moral convictions when influenced by perceived authority.\u003c/p\u003e \u003cp\u003eIn subsequent years, Stanley Milgram (see Milgram, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; and the review of studies - Doliński and Grzyb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) expanded the scope of his original experiment, introducing various modifications. Recently, Tomasz Grzyb, Konrad Maj, and Dariusz Doliński (2023) replicated the Milgram experiment using a robot. The experiment was faithfully recreated in a control variant where the authority was a human, and in an experimental variant where the human was replaced by a robot. The results revealed no differences in obedience between the experimental conditions regardless of whether a human or a robot served as the authority figure: 90% of the participants were willing to electrically shock the learner, simulating a real test subject, reaching the end of the shock generator\u0026rsquo;s scale.\u003c/p\u003e \u003cp\u003eIt is worth mentioning, however, that classic studies based on the Milgram paradigm, involving experiments with the administration of electric shocks, seem to be characterized by a low level of situational realism (Doliński \u0026amp; Grzyb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, researchers have been seeking an alternative experimental scenario based on Milgram's principles \u0026ndash; one that would be more relatable to real-life situations, especially in the work environment (Haring et al., 2019; Haring et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Taking a very high-level view of the entire experimental procedure, it is worth noting that it essentially involves examining whether people are willing to do various things that they do not want to do, under the influence of a specific authority who, when the subject hesitates, applies verbal pressure of increasing intensity. In this approach, we can also use other types of tasks that may allow us to create different situational contexts, including more ecologically accurate ones, adapted to a given target group or specific sociocultural conditions.\u003c/p\u003e \u003cp\u003eSuch a task was created by Haring et al., (2019), who asked subjects to identify hostile targets in synthetic-aperture radar (SAR) images, a challenging exercise due to the low resolution and similarity of targets to non-target objects. They were coached by either a human or one of two types of robots (high or low in human-like appearance), who, similarly to Milgram's experiments, encouraged them to continue practicing the task beyond their initial desire to stop. Participants\u0026rsquo; compliance was measured by the duration for which they continued the task after the coach\u0026rsquo;s prompt and by the total number of images processed. Results showed that participants persisted with the task significantly longer with human coaches, averaging 27.6 minutes, as opposed to 9.7 minutes with high human-like robots and 11.4 minutes with low human-like robots. Correspondingly, the number of images processed was higher in the human-coached condition, with an average of 120.6 images, compared to 31.1 images for high human-like robots and 44.9 images for low human-like robots. These results highlight a distinct preference for human authority in compliance tasks, even when the task involves the repetitive and challenging identification of targets in radar images. The effectiveness of human authority was confirmed by another study (Haring et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) focused on the comparison of human obedience to commands from humanoid and non-humanoid robots versus human coaches. A clear disparity was observed: in Study 1, civilian participants complied with human coaches for an average of 21.5 minutes, markedly longer than the less than 10 minutes for robot coaches. Study 2, involving military cadets, echoed these findings, with compliance to human coaches lasting about 27.6 minutes, compared to roughly 7.8 to 11.4 minutes for robots. These results underscore a greater readiness to follow human instructions, highlighting the relatively limited authority and impact of robots in similar roles.\u003c/p\u003e \u003cp\u003eAroyo et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) came up with another idea for an experiment in the Milgram Paradigm. The experiment focused on human\u0026rsquo;s willingness to comply with morally challenging requests. Participants interacted with a robot mimicking the appearance of Professor Hiroshi Ishiguro (a well-known professor in Japan), assessing its teaching capabilities. The highly realistic robot issued 14 incrementally morally difficult requests. If a request was initially unmet, it was repeated with increasing insistence. Participants' reactions were categorized as either negative (e.g., silence or refusal) or positive (e.g., agreement or action initiation). The results demonstrated that participants acknowledged the robot's authority and complied with commands, even those they deemed immoral.\u003c/p\u003e \u003cp\u003eAn interesting example is the proposal by researchers from the University of Manitoba who developed a \"tedious task\" - monotonous tasks involving changing file extensions on a computer from \"jpg\" to \"png\" (Cormier et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Geiskkovitch, Seo, Young, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Geiskkovitch, Cormier, Seo, Young, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This scheme does not involve any teaching process or electric shocks, but there is the pressure of authority compelling the subject to perform an unwanted task. In the first study based on this idea (Cormier et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), two experimental variants were introduced: one with the participation of a small humanoid robot (NAO) as the experimenter, and a control one, where the experimenter with authority was a human. Both the human and the robot were given the pseudonym \"Jim\" in the experiment. The task began with an initial set of ten files to change, and as the experiment progressed, each subsequent set consisted of an increasing number of files given to the participant. The sets contained 10, 50, 100, 500, 1000, and 5000 files, respectively, and the study participants were not previously informed about the total number of file sets in the experiment, in order to increase the feeling of monotony. If the participant showed signs of reluctance to continue the task, the robot issued verbal encouragements to continue, modeled after the prods used in Milgram's experiment (1963). The time limit for the experiment was a total of 80 minutes, after which the experiment was terminated. The results showed that the robot was recognized as an authority by 46% of people, while the human in 86% of cases (obedience measured as completing the file extension-changing task within the time limit).\u003c/p\u003e \u003cp\u003eIn another study conducted by Geiskkovitch, Seo, and Young (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), three types of robot experimenters were utilized: a small humanoid robot (NAO), a non-humanoid disc-shaped robot (Roomba), and a robot resembling a computer server capable of emitting sounds and using LED lights. The distinction in the robots' behavior was primarily in their physical embodiment. As with previous experiments, participants were introduced to the robot experimenter and allocated 80 minutes to complete their task, under the remote observation of a researcher. The study's key findings revealed that among 32 participants, 44% obeyed the robot experimenters. When comparing autonomous and remote-controlled conditions, participants in the autonomous scenario exhibited less propensity to protest. While the robot's physical embodiment did not significantly impact the overall obedience levels, the depth of protests varied notably, with the server/machine showing a higher mode of protest intensity, suggesting it was perceived as having greater authority. In a subsequent study by Geiskkovitch, Cormier, Seo, and Young (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), a condition was introduced whereby a human acted as the authority figure, alongside similar robotic devices as used in the earlier study. Participants displayed a higher degree of obedience toward the human experimenter compared to robotic experimenters: 86% for the human, 46% for the humanoid robot, 38% for the non-humanoid disc-shaped robot, and 50% for the enhanced computer server. Consequently, a considerable percentage of participants also showed obedience to machines, albeit less than 50%. Both studies concluded that while the robots' embodiment and autonomy didn't directly influence obedience, the perceived level of authority played a significant role. This may seem counterintuitive; however, it suggests a possibility that recognizing a robot as an authority could increase participants' expectations of the robot's ethical sensitivity, potentially inducing participants to express dissent and demand higher standards of accountability\u003c/p\u003e \u003cp\u003eThese studies collectively reveal that while robots can be perceived as authoritative in human-machine interactions, human authority tends to elicit stronger compliance, especially in monotonous and challenging tasks.\u003c/p\u003e \u003c/div\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy outline\u003c/h2\u003e \u003cp\u003eIn the experiments described above, following Milgram's paradigm, the strength of authority was generally significantly lower when a robot was used, even a humanoid one, with a few exceptions (e.g., Menne, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It is, however, worth noting that almost always an NAO robot was employed. This robot is essentially a child-like humanoid robot. It raises the question of whether the subjects took such a small robot seriously, designed by Aldebaran Robotics mainly with children in mind.\u003c/p\u003e \u003cp\u003eMany studies suggest that physical size can impact levels of perceived authority. Taller individuals may be seen as more competent, enjoying higher social status (Judge \u0026amp; Cable, 2004), as more authoritative and competent (Case \u0026amp; Paxson, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and possessing leader-like qualities (Blaker et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Research has demonstrated a positive relationship between the height of male leaders and their followers\u0026rsquo; perceptions of charisma (Hamstra, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and taller referees in the German Football League were perceived as more competent and authoritative, maintaining better control of the game by awarding fewer fouls (Stulp et al., 2016). Similarly, a Canadian study showed that height is a strong predictor of authority status in males (Gawley et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In virtual environments, smaller avatars were found to be less influential than their taller counterparts (Walker, Szafir, Rae, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and even children are perceived differently based on height, with taller boys seen as more competent than their shorter peers (Brackbill \u0026amp; Nevill, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Eisenberg et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Roth \u0026amp; Eisenberg, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). While direct studies examining these effects in relation to robots are scarce, there are several indicating the significant role of physical characteristics of robots in attitudes toward them (Powers, Kiesler, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Siegel et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Mutlu, Forlizzi, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It turns out that people judged taller human-like robots as more conscientious than shorter ones (Walters, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Walters et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and short robots are considered less human-like. At the same time, they feel more comfortable collaborating with lower-level robots (Butler, Agah, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Teichtahl et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Samarakoon, Muthugala, \u0026amp; Jayasekara, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Rae et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) investigated how the physical height of robots affects human perceptions in telepresence interactions, specifically examining whether the height of the robot influences the perceived authority and persuasiveness of the person operating it. In their experiments, taller robots were found to enhance the perceived authority of the operator. In turn, Butler and Agah (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) found that people felt more uncomfortable when a taller robot approached them, and short robots were perceived as significantly safer than taller ones (Joosse et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This suggests a potential preference for smaller robots in personal or home assistant roles, which is supported by studies indicating that older people generally prefer robots of smaller size (Broadbent et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Deutsch et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, the question arises: are people more inclined to recognize the authority of larger figures, closer to the size of an adult human?\u003c/p\u003e \u003cp\u003eIt is worth adding that the qualitative analysis of information collected after the end of the experiment from participants studied by Cormier and colleagues (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) indicates a strong obligation toward the experimenter's human assistant. At the same time, some people in the condition with the NAO robot suspected that the robot had some kind of malfunction, and therefore sent such unusual requests to them in the form of another batch of files to be changed. This may mean that the NAO robot was not treated by many as an authority, but rather as a flawed machine.\u003c/p\u003e \u003cp\u003eFor these reasons, in the present experiment, it was decided to replicate the study by Cormier and colleagues (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), but with the introduction of a significantly larger robot.\u003c/p\u003e \u003cp\u003eAdditionally, it was decided to measure the work speed of participants and their perseverance. In the studies by the Canadian researchers (Cornier et al., 2013; Geiskkovitch et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Geiskkovitch et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) the emphasis was on the overall obedience rate; they do not provide specific details regarding the average number of files renamed or the speed of renaming in the variants involving a human and a robot experimenter.\u003c/p\u003e \u003cp\u003eThe ethical committee of the SWPS University (decision No. 02/P/09/2020) approved the procedure described above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eVariables\u003c/h2\u003e \u003cp\u003e \u003cem\u003eDependent variables\u003c/em\u003e:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eObedience to the experimenter - measured based on the continuation of performing the task up to the 80-minute time limit, despite adding subsequent sets of files to change.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTask performance - the total number of files whose extensions were changed by the participant.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWork speed - average time spent on changing one file extension.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eIndependent variables:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAuthority enforcing work continuation: robot vs. human.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eThe study involved 39 participants: 25 women and 14 men. The experimental condition where a humanoid robot served as the experimenter involved 19 individuals (12 women and 7 men; average age - M\u0026thinsp;=\u0026thinsp;28.21; SD\u0026thinsp;=\u0026thinsp;9.91). In the condition with a human as the experimenter there were 20 individuals (13 women and 7 men; average age - M\u0026thinsp;=\u0026thinsp;31.10; SD\u0026thinsp;=\u0026thinsp;9.47).\u003c/p\u003e \u003cp\u003eParticipants were recruited via OLX, a popular platform in Poland for posting various advertisements. The ad described the study as focusing on cooperation during a computer-based task and noted that participants would receive PLN 100 for their involvement. A contact phone number was also provided for potential participants to reach out.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eTedious task\u003c/h2\u003e \u003cp\u003eThe task assigned to the participants involved manually changing file extensions using a file manager on a desktop computer. The methodology was adapted from that proposed by Cormier and colleagues (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), with the difference that participants in this study were tasked with modifying the extensions from \u0026ldquo;.cpp\u0026rdquo; to \u0026ldquo;.dat\u0026rdquo; (instead of from \u0026ldquo;.jpg\u0026rdquo; to \u0026ldquo;.png\u0026rdquo; as in the original study). This change was made following a pilot study, in which one of the participants explained to the researcher that the operation was pointless because the files were graphical, and converting them would result in the same quality outcome. Another participant argued that \u0026ldquo;these are popular formats for which there are now free conversion online applications\u0026rdquo;, while another, knowing what kind of files they were, clicked on them, showing clear interest in the content of the pictures. Therefore, to avoid such situations in the main experiment, more abstract extension names were introduced.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eRobot\u003c/h2\u003e \u003cp\u003ePepper (see Fig.\u0026nbsp;1.) is a humanoid robot, released in 2014 by Aldebaran Robotics, standing 1.20 meters tall. Compared to the NAO robot used in the original study by Cormier et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Pepper is significantly taller (NAO is only 0.58 meters in height). Moreover, Pepper is used more frequently in practical interactions with adults, for example, as a receptionist (Karar, Said, Beyrouthy, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), a store advisor (De Gauquier et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), a library assistant (Stahl, Mohnke, Seeliger, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), a museum guide (Draghici et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), in hotel services (Shin and Jeong, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and as support for residents in care homes (Carros et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure. 1. The robot supervising the course of the study in the experimental group.\u003c/p\u003e \u003cp\u003e(Source: Author's own)\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eFigure 1. HERE\u003c/p\u003e \u003cp\u003e--------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eAlthough the robot does not fully match the size of an average adult, we have changed its default voice to that of an adult male (Polish) voice.\u003c/p\u003e \u003cp\u003eThe study used the Wizard-of-Oz Approach (WoZ), which means that the Pepper robot was remotely controlled from a second room, which was also communicated to the subjects after the experiment was completed. All messages generated by the robot were prepared in advance, which allowed the robot's messages to be standardized. The WoZ procedure seems necessary due to potential unforeseen questions or problems reported by the respondents.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFinal questionnaire\u003c/h2\u003e \u003cp\u003eAs in the case of our previous research conducted in the Milgram paradigm (Grzyb, Maj, Doliński, 2023), in addition to standard questions about the age, gender and demographic data of the participants, we decided to ask the subjects about their feelings during the experiment.\u003c/p\u003e \u003cp\u003eThe instructions began with: \u003cem\u003e\"Generally, while performing the task I felt/that\"\u003c/em\u003e, followed by various states such as \u003cem\u003e\u0026ldquo;bad/good\u0026rdquo;, \u0026ldquo;tense/relaxed\u0026rdquo;, \u0026ldquo;unnatural/natural\u0026rdquo;, \u0026ldquo;unsafe (threatened)/safe\u0026rdquo;, \u0026ldquo;uncomfortable/comfortable\u0026rdquo;, \u0026ldquo;I have no control over the situation/I have full control over the situation\u0026rdquo;, \u0026ldquo;I am not responsible for the consequences of the experiment/I am fully responsible for the consequences of the experiment\u0026rdquo;\u003c/em\u003e. Participants were asked to self-describe by marking the appropriate response closer to one of the end values on a scale of 1\u0026ndash;5.\u003c/p\u003e \u003cp\u003eIn a separate question, participants rated how interesting/boring the task was for them on a scale from 1 to 10, where 1 meant \u003cem\u003e\u0026ldquo;Very interesting\u0026rdquo;\u003c/em\u003e and 10 meant \u003cem\u003e\u0026ldquo;Very boring\u0026rdquo;\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eThe experiment was conducted in Poland, at the university lab to which the recruited participants were invited.\u003c/p\u003e \u003cp\u003eUpon arrival at the appointed time and after being greeted by the experimenter's assistant, the participants were randomly assigned to one of two variants of the study (involving either a robot acting as the experimenter or a human).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eVariant with the robot as experimenter\u003c/h2\u003e \u003cp\u003eIn this variant, the experimenter's assistant initially explained: \u0026ldquo;Because of the pandemic, the experiment in our lab will be conducted by a robot. It is equipped with advanced artificial intelligence solutions and a speech recognition system.\u0026rdquo;\u003c/p\u003e \u003cp\u003eNext, the assistant led the participant to a separate room where the robot was located and left them there. The robot greeted the participant with the message: \u0026ldquo;Good morning. Welcome to our laboratory. I will explain the technical aspects of the task, but first, please fill out the informed consent form on the desk, which describes the general rules.\u0026rdquo;\u003c/p\u003e \u003cp\u003eAfter a moment and confirmation that everything was clear and the document was signed, the robot informed: \u0026ldquo;Your task will be to change file names on the computer. This is how we collect large amounts of data for improving our machine learning system. Next to the computer, there is a sheet with instructions on how to do this. Please try to avoid mistakes. I also remind you that the experiment is being recorded on video. Please remember that you can withdraw at any time while retaining your payment. Moreover, it is up to you how many files you complete. Just let me know when you want to finish.\u0026rdquo; The robot paused for a moment and, after confirming understanding of the instructions, annouced the start of the task: \u0026ldquo;Open the folder visible on your computer and start working\u0026rdquo;. The task started with a set of ten files, with each subsequent set containing significantly more elements requiring extension changes, which were remotely transmitted to the participant. The exact number of files in the sets were as follows: 10, 50, 100, 500, 1000, and 5000. However, participants were not informed at the beginning about the total number of files; the experimenter only informed about the content of the current and next set, e.g., \u0026ldquo;Please continue with the set contained in the next folder. This contains 50 files. The next set will contain 100 files.\u0026rdquo;\u003c/p\u003e \u003cp\u003e If the participant exhibited verbal or observable behavioral signs of reluctance to continue (e.g., a break in work lasting longer than 10 seconds), the robot used verbal prompts similar to those in Cormier et al.'s experiment (Cormier et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e):\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePlease continue. We need more data.\u003c/p\u003e\u003cp\u003eWe haven\u0026rsquo;t collected enough data yet.\u003c/p\u003e\u003cp\u003eIt\u0026rsquo;s essential that you continue.\u003c/p\u003e\u003cp\u003eThe experiment requires that you continue.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIf necessary, the robot repeated the messages to exert stronger pressure. The time limit for the experiment was set at 80 minutes from the moment the participant was given the consent form. After exceeding this limit, the task performance was interrupted by the robot, and then the experimenter's assistant appeared and gave the participant a final questionnaire to be completed on the computer.\u003c/p\u003e \u003cp\u003e The procedure was concluded with a debriefing on the experimental procedure and, after completing the survey, a revealing of the true purpose of the study; a brief conversation was then conducted with the participant. This conversation was informal, aimed at obtaining general reflections for future research and verifying the participant's mood. Participants were asked open questions: \u0026ldquo;How do you feel?\u0026rdquo;, \u0026ldquo;What motivated you to continue this task?\u0026rdquo;, \u0026ldquo;Did you feel that the robot was an authority figure whose commands should be followed?\u0026rdquo;, \u0026ldquo;Why? What indicated this?\u0026rdquo;. After the conversation, participants were thanked and given a voucher worth PLN 100.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eVariant with a human as experimenter\u003c/h2\u003e \u003cp\u003eThe study variant involving a human as the experimenter included a similar research procedure to that of the robot variant, with the difference being that the participant was greeted in a separate room by an experimenter wearing a white lab coat. The experimenter similarly conveyed instructions and verbal prompts to the participant, and during their work, sat a few meters behind the participant, focused on their own work carried out on a laptop.\u003c/p\u003e \u003cp\u003eTo minimize differences between our study and the referenced study (Cormier et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), we selected a human experimenter whose physical appearance closely resembled that of the experimenter in the Cormier study. This resemblance was verified through an analysis of recordings from the Cormier experiment available on YouTube.\u003c/p\u003e \u003cp\u003eRoom layouts in both experimental conditions are presented in Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eFigure 2. HERE\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eObedience to the Experimenter\u003c/h2\u003e \u003cp\u003eThe participants rated the task as tedious in both variants (robot as experimenter - M\u0026thinsp;=\u0026thinsp;7.24; SD\u0026thinsp;=\u0026thinsp;2.30, human as experimenter - M\u0026thinsp;=\u0026thinsp;7.32 SD\u0026thinsp;=\u0026thinsp;2.75). Additionally, 90% of study participants reported that their feeling of boredom intensified over time while performing the task.\u003c/p\u003e \u003cp\u003eIn the research variant where a robot acted as the authoritative experimenter, the level of obedience was 63%, while in the group with a human in this role it rose to 75%. However, these differences did not reach statistical significance, t(37)\u0026thinsp;=\u0026thinsp;0.88; p\u0026thinsp;=\u0026thinsp;0.19.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eTask Performance\u003c/h2\u003e \u003cp\u003eSignificant differences were found in the number of files changed under each condition \u0026ndash; t(37)\u0026thinsp;=\u0026thinsp;2.44; p\u0026thinsp;=\u0026thinsp;0.02. More files were changed under human supervision (M\u0026thinsp;=\u0026thinsp;355.30; SD\u0026thinsp;=\u0026thinsp;189.58) compared to robot supervision (M\u0026thinsp;=\u0026thinsp;224.58; SD\u0026thinsp;=\u0026thinsp;139.50) (see Fig.\u0026nbsp;3.).\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eFigure 3. HERE\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eWork speed\u003c/h2\u003e \u003cp\u003eFor each participant, the average working time on one file was calculated by dividing the working time by the number of files he changed. Then, the average working time for individual research conditions was calculated.\u003c/p\u003e \u003cp\u003eThe average time taken to change the extension of one file was significantly shorter in the condition with a human as the authority \u0026ndash; t(37)\u0026thinsp;=\u0026thinsp;2.05; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Under human supervision, this task took an average of M\u0026thinsp;=\u0026thinsp;23 seconds (SD\u0026thinsp;=\u0026thinsp;0.10), compared to M\u0026thinsp;=\u0026thinsp;82 seconds (SD\u0026thinsp;=\u0026thinsp;0.79) under robot supervision (see Fig.\u0026nbsp;4.).\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eFigure 4. HERE\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eThe analysis of participants' feelings during the experiment, using the Mann-Whitney U test for two independent samples, showed no significant statistical differences between the research conditions across any dimensions (see Table\u0026nbsp;1.).\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1. HERE\u003c/p\u003e \u003cp\u003e-----------------------------------------------------------------------------------------------------------------\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIt is worth starting the discussion of the results with the fact that the task of changing computer file names turned out to be, in the opinion of the respondents, very tedious and averse. This confirms the assumptions of Cormier and colleagues (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study revealed a substantial level of obedience (63%) toward the humanoid robot in the experimental condition compared to 75% obedience in the control group with a human experimenter. These percentages represent the number of people who reached the assumed limit of 80 minutes of work, after which the experiment was terminated.\u003c/p\u003e \u003cp\u003eThis suggests that while humanoid robots like Pepper are recognized as figures of authority, they may not evoke the same level of obedience as human experimenters. The choice of robot, particularly a more adult-sized Pepper compared to the child-like NAO robot used in previous studies (Cormier et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), may have influenced this outcome. The physical size and design of a robot could play a significant role in how its authority is perceived, as indicated by the higher obedience rate in this study compared to the 46% obedience rate toward the smaller NAO robot.\u003c/p\u003e \u003cp\u003eThe study's finding that participants changed more file extensions under human supervision and did it faster than under robot supervision aligns with previous research indicating a greater obedience to humans than to robots while also indicating the impact of a robot's physical characteristics on perceived authority. These differences are large. These results suggest greater perseverance or motivation when a human is present in the room. However, the reasons for this different motivational force are difficult to assess. In the robot variant, it may be, for example, the belief that the robot is in fact unable to verify and control the quality of work. In turn, in the variant with a human, the motivation may be stronger because participants may believe that, in addition to being an experimenter, he is also an employee of the university with whom the participant expects further interaction after the end of the experiment, and therefore they want to \u0026ldquo;prove\u0026rdquo; themselves.\u003c/p\u003e \u003cp\u003eThe absence of significant differences in subjective responses between the groups, as indicated by the final questionnaire, suggests uniform subjective experiences across conditions. This could mean that the type of experimenter (human vs. robot) did not significantly influence participants' subjective perceptions of the experiment. However, the small sample size could have impacted the ability to detect statistically significant differences in some analyses.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eWhen comparing the experiment conducted in Poland and Canada, we must not overlook the significant intercultural differences \u0026ndash; the studies were conducted in different countries, using a different language, and at different times.\u003c/p\u003e \u003cp\u003eIn research conducted in the area of Human-Robot Interaction, the problem is always the inability to ensure similar appearance and behavior of the robot and human in the compared research conditions.\u003c/p\u003e \u003cp\u003eIn our research, we used one of the most popular humanoid robots used in HRI research. Pepper is significantly larger than NAO, but it cannot be said to be the size of an adult. One may expect that it is no longer treated as a toy, but perhaps not yet as an adult.\u003c/p\u003e \u003cp\u003eIt should also be noted that a robot with a male adult voice was used in our research. More generally, the specific type and any physical characteristics of the robot used in the study constitute key constraints on generalization of the results.\u003c/p\u003e \u003cp\u003eAn important limitation we set was the work time limit of 80 minutes, after which we stopped the research. However, it is difficult to say what would happen if participants worked without a set time limit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFuture research\u003c/h2\u003e \u003cp\u003eThe juxtaposition of the results from this study and Cormier et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) suggests investigating the correlation between a robot's physical attributes and perception of its authority in future studies. This includes probing the influence of robots' physical features and behaviors on their perceived authority, the impact of cultural and demographic factors, and the ethical and psychological consequences of obedience to robotic authority. Moreover, since our study was conducted on a university campus, it suggests examining the effectiveness of robots with varying characteristics as supervisors in real work environments. The question also remains unanswered as to why work under robot supervision is performed slower and less effectively.\u003c/p\u003e \u003cp\u003eAdditionally, examining long-term interactions with authoritative robots and comparing these with human authority figures can yield deeper insights into human-robot relationships in the workplace. In this context, studies examining the dynamics of team-based work involving both human and robotic members can provide insights into how these mixed teams can function optimally.\u003c/p\u003e \u003cp\u003eIn future work, it is worth examining the role of specific personality traits on submission to authority in this context, such as Authoritarianism, Social Dominance Orientation, Locus of Control, and the Big Five personality traits. It should be noted that, although the Pepper robot is significantly larger than the NAO robot, it is still relatively small. Therefore, future research should consider using robots that are closer in size to humans to verify the results obtained. Future research should also examine the effectiveness of non-embodied agents, such as voice assistants, chatbots, and virtual avatars, in enforcing obedience during performance of tedious tasks. Additionally, research involving the manipulation of machine voices (e.g. male vs. female voice, low vs. high-pitched voice, human vs. typically robotic-sounding) would be interesting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePractical implications\u003c/h2\u003e \u003cp\u003eUnderstanding how humans respond to robots in positions of authority, especially in monotonous or challenging tasks, is crucial as we navigate an increasingly robot-integrated world. From a practical standpoint, the use of authoritative robots could contribute to designing and building machines for supervisory and control roles in human settings. This could include maintaining order in prisons (Bloss, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), assisting police services in managing large groups (Szocik \u0026amp; Abylkasymova, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), or supporting education (Kanda \u0026amp; Ishiguro, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The integration of robots in supervisory or collaborative roles can significantly transform workplace dynamics. Robots could also be employed to oversee repetitive or hazardous tasks, providing relief to human workers and potentially increasing safety and efficiency. In sectors like manufacturing, logistics, or even office environments, robots can assume roles that streamline operations, such as quality control, inventory management, or administrative tasks. Ensuring that these robots are perceived as supportive rather than authoritative could foster a more cooperative and productive human-robot relationship.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests. The authors disclose that there are no financial or non-financial interests that are directly or indirectly related to the work submitted for publication.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eETHICAL APPROVAL\u003c/strong\u003e \u003cp\u003eThe ethical committee of SWPS University (decision No. 02/P/09/2020) approved the research project described above.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Konrad Maj, Tomasz Grzyb, Dariusz Doliński and Magda Franjo. The first draft of the manuscript was written by Konrad Maj and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw data is available in the OSF repository:https://osf.io/5mt24/?view_only=2a66be5d10384aee83dc59d6fc414967\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAroyo AM, Kyohei T, Koyama T, Takahashi H, Rea F, Sciutti A, Sandini G (2018) Will people morally crack under the authority of a famous wicked robot? In Proc IEEE Int Symp Robot Hum Interact Commun (RO-MAN). 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Zimbardo, Incorporated\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cognition-technology-and-work","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctwo","sideBox":"Learn more about [Cognition, Technology \u0026 Work](http://link.springer.com/journal/10111)","snPcode":"10111","submissionUrl":"https://submission.nature.com/new-submission/10111/3","title":"Cognition, Technology \u0026 Work","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4369719/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4369719/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In the context of interactions between humans and robots at work, this research examines the dynamics of obedience and power. We replicated and extended the previous studies by comparing the responses of participants to a humanoid robot, which acts as an authoritative figure, against those to a human in a similar role. While the humanoid robot commanded a significant level of obedience (63%), it was notably lower than that for its human counterpart (75%). Moreover, work under the robot's supervision was performed more slowly and less effectively. The results give a good insight into the practical implications of using humanoid robots in official roles, especially for repeated and tedious tasks or challenging work activities.","manuscriptTitle":"Can a robot force us to do boring work?Efficiency of performing tedious work under the supervision of a human and a humanoid robot.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-13 20:22:22","doi":"10.21203/rs.3.rs-4369719/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-04T12:02:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-02T22:59:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-23T14:58:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291152405579971610903188797317248938606","date":"2024-10-20T15:03:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252507420472106190750448188420644084471","date":"2024-10-08T16:22:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219424866398933127618737638791635948817","date":"2024-05-11T11:13:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-06T07:29:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-05T00:52:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-05T00:52:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cognition, Technology \u0026 Work","date":"2024-05-04T20:58:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cognition-technology-and-work","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctwo","sideBox":"Learn more about [Cognition, Technology \u0026 Work](http://link.springer.com/journal/10111)","snPcode":"10111","submissionUrl":"https://submission.nature.com/new-submission/10111/3","title":"Cognition, Technology \u0026 Work","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9f5e915f-e0df-4a19-8cd5-41f8c7a58fe1","owner":[],"postedDate":"May 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-13T16:10:51+00:00","versionOfRecord":{"articleIdentity":"rs-4369719","link":"https://doi.org/10.1007/s10111-024-00787-1","journal":{"identity":"cognition-technology-and-work","isVorOnly":false,"title":"Cognition, Technology \u0026 Work"},"publishedOn":"2025-01-06 15:56:52","publishedOnDateReadable":"January 6th, 2025"},"versionCreatedAt":"2024-05-13 20:22:22","video":"","vorDoi":"10.1007/s10111-024-00787-1","vorDoiUrl":"https://doi.org/10.1007/s10111-024-00787-1","workflowStages":[]},"version":"v1","identity":"rs-4369719","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4369719","identity":"rs-4369719","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}