HAI シンポジウム 2024
Human-Agent Interaction Symposium 2024

P-4

仮想現実を利用してロボットの視点取得による人間対ロボットの向
社会性の促進Perspective-taking for promoting prosocial behaviors through robot-robot VR task∗1

杭陳琳 ∗1∗3

小野哲雄 ∗2

山田誠二 ∗3∗1

Hang Chenlin

Ono Tetsuo

Yamada Seiji

総合研究大学院大学

The Graduate University for Advanced Studies

∗2

北海道大学

Hokkaido University∗3

国立情報研究所

National Institute of Informatics

Perspective-taking, which enables individuals to consider the thoughts and objectives of another, is well established to be a successful strategy for encouraging pro-social behavior in human-computer interactions. Nowadays,
perspective-taking is no longer limited to text; it is now more frequently used in virtual reality (VR). However, mostprevious research has focused on simulating human-human interactions in the real world in VR by providing participants with experiences connected to diﬀerent moral tasks. In this study, we investigated whether participants
prosocial behaviors toward robots would change if they experienced an altruistic VR task involving robots fromthe perspective of diﬀerent robots. Our ﬁndings show that participants who had the help-receiver-view exhibited
more altruistic behaviors toward a robot than those who had the help-provider-view one in a dictator game.

1.

INTRODUCTION

playing against each other, or playing a game together) [20].
In addition, Nagataki et al. [21] asked participants to do aseries of moral tasks after performing a bodily coordinatedmotion task with either another participant or a robot, andthey observed that participants also made fair proposals totheir robot partner. Although there are a lot of studies
on human-robot relations, these studies did not have thehuman imagine how the robot thinks.
Numerous studies have demonstrated that adopting the
viewpoint of another person (i.e., envisioning what it would
be like to actually be the other person), which is called perspective taking, can be an eﬀective strategy for encouraging prosocial behaviors [22] in human-human interaction.
Mediated perspective-taking tasks (e.g., online role playing games, videos, immersive virtual realities) that supply
extra information to participants or users rather than depending solely on the user s imagination have also demonstrated a strong potential for encouraging prosocial behaviors [23][24][25].
Research on mediated perspective-taking prefers to simulate realistic human interactions in VR or to allow participants to have experiences that their existing physicalbodies cannot, for example, allowing white people to experience the perspective of black people [25] or Einstein [26].
Robin et al. [26] allowed participants to experience the feeling of having extraordinary abilities in a VR environment,
which encourages participants to socialize with others in thereal world. Jeﬀrey et al. [27] compared the diﬀerent waysof perspective taking toward a non-player, in this case, arobot avatar, in terms of closeness, empathy, and game immersion. Although they used a robot avatar, they did notcompare the attitude toward a diﬀerent role in the game.
Xiang et al. [28] showed how playing multiple roles in a single role-playing process in immersive virtual environments
can encourage more morally correct opinions about bullying
others. Although they compared views on violence between
diﬀerent characters, this was based only on the relationshipTechnological artifacts that behave autonomously in social settings, such as autonomous automobiles, vacuum
cleaners, cellphones, virtual agents, and robots, are quickly
becoming a reality and are anticipated to interact with people more socially in the future [1]. How these objects caninﬂuence individuals to act in a prosocial way has captured
the attention of many researchers.
Prosocial behavior is a multidimensional concept thatis broadly deﬁned as voluntary behavior to beneﬁt theother[2], [3], [4], [10], such as altruism, solidarity, sharing,care- giving, and comforting [6]. There are also distinct
types of prosocial behavior ranging from high-cost (e.g.,
extensive volunteering, helping in dangerous or emergency
situations) to low-cost behaviors (e.g., helping to pick up a
dropped item, sending an uplifting text message [3]). Basedon the motivation behind prosocial behavior, including altruistic, cooperative, and individualistic behavior [7], [8],altruism based on inter-reciprocity is a strong motivational
factor in prosocial behavior [9].
Previous work has paid more attention to the characteristics of robots or agents and to the inﬂuence on the prosocial
behavior of humans (e.g., donation behavior), such as thesocial background of users[10], where a robot is installed[11], the gender of a robot [12], the appearance of a robot[13], the head behavior of humanoid robots [14], and thefacial expressions of virtual agents [15].
Considering a possible hybrid society of humans and machines [16] in the near future, robots or agents may be members of human society. In the ﬁeld of Human-Robot Interaction (HRI), there have been a number of studies on theinteraction between a human and a robot [17], on the interaction between a group of people and a robot [18], and on
the interaction between a human and a group of robots [19]where the appearance or behavior of a robot or the form ofinteraction with humans aﬀects the human s helping behavior toward the robot (e.g., completing a task together,1between human and human and did not take into accountthe relationship between human and robot.
It can be seen that there is still a lack of research thatlooks at using perspective-taking to facilitate human- robot
relationships through VR technology. One recent study
exempliﬁes people s prosocial behavior toward machines.
With the computers are social (CASA) framework [29], thestudy of the sociality, or even prosociality, of machines is
no longer just a paper exercise. We think it is necessary
to verify whether taking the perspective of diﬀerent robots
in a robot task can inﬂuence people s prosocial behaviors
toward a robot.
In this study, we focus on altruism, one of the many components that make up prosociality [30]. According to thedeﬁnition of altruism, which is the act of someone helping
someone else at their own expense [31], an altruistic task
must include at least two objects: the help-provider andhelp-receiver. We conducted an experiment in order to ﬁnd
out if participants social behaviors toward robots will beaﬀected by adopting diﬀerent robot perspectives during arobot-altruistic VR task.
We conducted a between-participants experiment by asking participants to take diﬀerent perspectives (help-provider
and help-receiver) in the same robot altruistic VR task. We
tracked behavioral changes using the dictator game [32],[33], [34], a simple economic game commonly used to gauge
altruistic attitudes, and the desire to assist scale. The ﬁndings demonstrate that after having diﬀerent robot perspectives in the same task, participants changed their prosocial
behavior towards robots.

2.

METHOD

2.1

Participants and apparatus

図 1: Scenarios of VR tasks

their willingness to help robots, the robot-partner versionof the Dictator game, the battery version of the Dictator
game, and acceptance of robots.

2.2

Stimulus design

Altruism is when someone helps others at their own expense [Batson14], and the robots’ battery was seen to be
their own expense [Hang21, Hang22]. Therefore, we considered an altruistic event where two robots are doing atask, one of the robots runs out of battery, and the otherrobot comes to help on its task.
The task was to move cubes to a target position. To
distinguish the work to be done by each robot, we set the
cubes in their respective work areas to diﬀerent colors. Also,
to make the work load as consistent as possible, we placed
the cubes in their respective areas in mirrored locations andkept the initial position of one robot and the robot that theparticipant played the role of the same (see Fig. 2.(1)-(a)and Fig. 2.(2)-(a)).
There were two types of scenario in the game: the helpprovider view and the help-receiver view. For making it
more nature while participants take the help-receiver andstop during the work because of running out of the battery, we choose robot-avatar for both help-provider-viewand help-receiver-view.
For the help-provider view, once the other robot moved
the third cube to the target area, it stopped working (seeFig. 2.(1)-(c)). At that time, the participants received a
pop-up message on their screen informing them that, “Therobot has run out of battery. Please help the robot ﬁnish
its work” (see Fig. 2.(1)-(b)). Although the instruction

Thirty-ﬁve university students participated in the study(29 males, 6 females, Age: M ean = 27.6, SD = 3.9). They
received a shopping card (about US$12) as a reward fortheir participation. Participants were randomly assigned
to one of two conditions. Eight participants (all from thehelp-provider view) were removed because they answeredincorrectly to certain questions or did not follow a popup message in the game, for example, input xxx yen fora question asking for battery to be allocated or thought
the pop-up message was the garbage message and missed
information it provided. The ﬁnal number of participants
was 27 (22 males, 5 females, Age: M ean = 27.3, SD = 4.2)
( 1 Brazilian, 13 Chinese, 1 Estonian, 2 French, 5 Germans,
1 Indian, 2 Italians, 2 Japanese, 1 Moldovan, 2 Portuguese,
1 Spaniard, 1 Swiss and 3 Vietnamese in alphabetical order).
The study ran on Intel Core i7-11800H, 32GB RAM computers running Windows 11 Pro. The experiment software
was written in C# in Unity and recorded user actions in thegame through Unity Recorder. The VR game was driven
on the Oculus Quest 2 device.
For additional information, we also conducted an online
experiment and asked 10 university students (5 males, 5
females, Age: M ean = 26, SD = 2.68)(10 Chinese) who
did not have any VR experience to answer questions on

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2.3

ProcedureFirst, we asked the participants to read the instructions and ethical materials for this experiment. Then, they
were asked to do a pre-questionnaire, which inquired about
demographic questions and about participants’ subjective
knowledge of VR. On the basis of this, we also provided
the participants with a brief overview of the VR game sothat they could have a smooth VR experience. After theparticipants conﬁrmed their understanding of the game, we
ﬁrst asked them to complete training for object grabbing
by moving diﬀerent colored cubes to the target area. After completing the training, they were given 30 seconds tosee their avatar through the mirror in VR. Then, diﬀerent
games were oﬀered for diﬀerent groups, either to help one
robot complete the task (help-provider) or to be helped by
the robot to complete the task (help-receiver). Here, wewant to highlight that we did not state the task as involving a cooperative or competitive relationship at the beginning of the game. After completing the game, the participants were asked to ﬁll out a post-test questionnaire. The
questionnaire regarded the willingness to help the robot,
the dictator game with the robot as the partner and the
dictator game with the battery as the allocated resource,
the acceptance of the robot, body ownership and agency in
VR games, and inclusion of the other in the self. A freedescription question was asked after completing the wholequestionnaire. Finally, a short interview was conducted to
conﬁrm that the participants had understood the game correctly.

図 2: Mirror for participant to see him/herself as robot

we provided on the pop-up message for participants was tohelp the other robot, they still had the right to choose notto help the robot and end the game.
For the help-receiver view, as it is hard to control the
speed at which participants move cubes, we also set the
stopping point to be when the other robot moved the third
cube to the target area. This time, the robot that participants were playing the role of got stuck at the current
location, and a pop-up message showed up on their screen
stating that, “You have run out of battery. The robot will
help you ﬁnish your work.” (see Fig. 2.(2)-(b)). The participants could still move their head to get a diﬀerent view
from their location, but they could not move their locationin the game. The participants were asked to stay in thegame until the robot ﬁnished both its own work (see Fig.
2.(1)-(c)) and helped participants to ﬁnish their work (seeFig. 2.(1)-(d)).
We included a mirror part in our VR experience on thebasis of Oh et al. [Oh16]. Before each stimulus, the participants were reminded to look at their own body as a robot
through a mirror in VR (see Fig. 1.), and for experiencing what it is like to be a robot, they were asked to wave
the controllers at the mirror (which were displayed as therobot’s hands).
On the basis of our stimulus design and results basing on Lee et al.[Lee21] which showing that diﬀerent attitude towards robots which expressing diﬀerent types ofself-compassion, we made a hypothesis that the participants
who experienced the help-provider view and who experienced the help-receiver view will have signiﬁcant diﬀerencein terms of help behavior towards robot (1a), altruistic behavior towards robots (1b), and acceptance of robots (1c).

2.4

Measurements

For the pre-questionnaire, a demographic question including name, nationality, age, gender, and highest qualiﬁcation was asked. In addition, to determine the participants’ initial understanding of VR, we asked them two subjective questions on VR.
• Knowledge of VR: How much do you think you know
about VR? The answer was given on a ﬁve-point Likert
scale .
• Expertise using VR: How often do you use VR devices? The answer was given on a ﬁve-point Likert
scale .
For the post-questionnaire, the details were as follows.
• Help behavior towards robot: On the basis of
Avelino et al. [Avelion18], we asked participants,“Would you help the robot if that robot was out ofbattery?” The answer was given on a ﬁve-point Likert
scale (1: help to 5: not help).
• Dictator game: For measuring the participants’ altruistic behavior, previous studies usually use the Dictator game [Andreoni10, Capraro19, Engel11] in which
one player (the proposer) makes a one-time oﬀer tothe other (the responder). The original version was asfollows: “Now you are given x yen. The money needs
to be shared with the other participant. How muchmoney would you give to the other participant?”

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The Dictator game is sometimes transformed into a
new version to ﬁt the diﬀerent purposes of diﬀerent
studies [Engel11]. As our setting was participants’prosocial behavior towards robots, we transformed theoriginal version into two new versions designed by theauthors.
For one version, we changed the responder from humanparticipant to robot, so the question was as follows:“Now you are given 1,000 yen (about US$8.70). The
money needs to be shared with the other robot. How
much money would you give to the robot?”
For the other version, we changed the allocated resource from money to battery. As there are no common values between a human and a robot and money
makes no sense to a robot, we tried setting the allocated resource to battery [Hang21, Hang22] as it was
the energy source of the robot. Therefore, the question was as follows: “Now you are given 100% battery.
The battery needs to be shared with the other robot.
How much battery would you give to the robot?”

図 3: Result of dictator game

hypothesis 1a. For the robot-partner version of the Dictator game, there were signiﬁcant diﬀerences (t(25) = −2.87,
p = 0.008, Cohen’s d = 1.10) between the helper group(M ean = 269.23, SD = 189.67) and the be-helped group(M ean = 507.14, SD = 225.09) (see Fig. 3.), which
supports hypothesis 1b partially. For the battery version of the Dictator game, there were no signiﬁcant diﬀerences (t(14) = −0.69, p = 0.50) between the helper group(M ean = 56.15, SD = 19.43) and the be-helped group(M ean = 79.29, SD = 115.05), which rejects hypothesis 1b
partially.
For the acceptance of robots, there were no signiﬁcantdiﬀerences (t(24) = −0.18, p = 0.86) between the helpergroup and the be-helped group, which rejects hypothesis
1c. For body ownership and agency, there were no signiﬁcant diﬀerences between the helper group and the be-helped
group in terms of how much the participants felt the virtual
body to be their own body (t(24) = −0.77, p = 0.45), felt
they have two bodies (t(25) = −0.18, p = 0.86), felt theavatar in the mirror was their own body (t(24) = −0.76,
p = 0.46), and agency (t(25) = −1.11, p = 0.28). For the
IOS, there were no signiﬁcant diﬀerences (t(25) = −0.40,
p = 0.69) between the helper group and be-helped group.
For additional information, we conducted another online
survey and asked 10 participants to answer questions on
their willingness to help robots (M ean = 1.5, SD = 0.81),
the robot-partner version of the Dictator game (M ean =470, SD = 303.48), the battery version of the Dictator game(M ean = 55.1, SD = 40.18), and acceptance of robots
without any stimulus (M ean = 3.05, SD = 0.69).

• Acceptance of robots: We picked only questions
on trust in regards to the acceptance of robots[Heerink09]. We asked participants to answer thefollowing questions on a ﬁve-point Likert scale (1:strongly agree to 5: strongly disagree): 1. “I would
trust the robot if it gave me advice.” 2. “I would follow the advice the robot gives.”• Body ownership and agency: On the basis of the previous studies on body ownership, we followed the questionnaire by Banakou et al. [Banakou16]. The participants were asked to answer the following questions
on a ﬁve-point Likert scale (1: strongly agree to 5:
strongly disagree): 1. “I felt that the virtual body I
saw when looking down at myself was my own body.”
2. “I felt as if I had two bodies.” 3. “I felt that the virtual body I saw when looking at myself in the mirror
was my own body.” 4. “I felt that the movements ofthe virtual body were caused by my own movements.”• Inclusion of other in the self (IOS): In addition, to measure participants’ perceived closeness withthe robot [Ho20], an IOS question was asked.

3.

RESULTSFor the pre-questionnaire, we analyzed the data with anindependent sample t-test. The result shows that there wereno signiﬁcant diﬀerences between the helper group and behelped group in terms of knowledge of VR (t(23) = 1.72,
p = 0.10) and expertise in using VR (t(21) = 1.59, p =0.13).
For the post-questionnaire, we analyzed the data with anindependent sample t-test.
For the help behavior towards the robot, there were no
signiﬁcant diﬀerences (t(23) = −0.42, p = 0.68) between
the helper group (M ean = 1.46, SD = 0.77) and behelped group (M ean = 1.64, SD = 1.79), which rejects

4.

DISCUSSION

We conducted this experiment to investigate whether experiencing two diﬀerent points of view from robots in thesame altruistic task could promote human prosocial behavior and trust towards robots. In addition, we also wanted
to know if there are diﬀerences in terms of body ownershipand agency in VR experiences after taking diﬀerent points

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of view from robots.
The results showed that participants who had the helpreceiver view in the VR task gave more money to the robot
than those who had the help-provider view. Also, comparing the result with (the additional information in result)and without the VR task, those who had the help-receiverview split more money with the robot compared with those
who did not experience any VR tasks, and those who had
the help-provider view split less money with the robot compared with those who did not experience any VR tasks.
This gives us some warning that the experience of doing atask with a robot can not only have a positive eﬀect on ahuman’s prosocial behavior towards robots but also a negative one, which shows that researchers should pay more
attention to the task setting. In addition, from the interview with the participants, some said that how they split
the money was based on how many tasks the robot had
done in the VR task.
There were no signiﬁcant diﬀerences between participants
who had the help-receiver view and help-provider view regarding help behavior, the battery version of the Dictator
game, and the acceptance of robots in terms of trust. For
the help behavior, although there were no signiﬁcant differences between the two groups, both groups themselves
had mean values that were more favorable toward helping
robots. For the battery version of the Dictator game, although there were no signiﬁcant diﬀerences between thetwo groups, both groups themselves had mean values thatwere higher than the group without a stimulus. Thus, we
can observe a trend in the result that, in the VR task, no
matter the help-provider or help-receiver role, both had apositive eﬀect on promoting participants’ prosocial behavior
towards robots. We also found that even when we changed
the allocation resource from money to battery, this confusedsome of the participants about the questionnaire itself as“There is no reason for me to have a battery.” For future
work, it is also important for us to design a proper measurement for evaluating human prosociality towards robots.
For acceptance of robots in terms of trust, although there
were no signiﬁcant diﬀerences between the two groups, bothgroups themselves tended to trust the robot more than thegroup without a stimulus. However, for body ownershipand agency and IOS, there were no signiﬁcant diﬀerences
between the two groups. We found some possible reasons
from the free description answers given by the participants.
As some of them were familiar with video games and VR
games, they did not feel that they were in the body ofa robot even though they checked their body movement
through the mirror. In addition, in human-human interaction tasks, Pierce et al. [Pierce13] have shown that taking
the perspective of a competitor might lead to more unethical behaviors.
From the interview after the experiment, we found thatparticipants who were from European countries tended totreat the robot who ran out of battery as “being sick” unlike
participants from other countries. There is also research on
the inﬂuence of nationality in HRI [Evers08, Rhim20]. In
our current work, although we conducted the experimentwith participants from diﬀerent countries who have diﬀerent
cultural backgrounds, we did not set nationality as a factor,
which we can add in our future work. In addition, thistime, we observed only short term eﬀects, but long term
eﬀects should also be observed as well as whether one formof prosocial behavior (e.g., helping) leads to another formof prosocial behavior (e/g., sharing).

5.

CONCLUSION

In tasks ranging from traditional perspective-taking tasks
to mediated perspective-taking tasks, perspective-taking
has been demonstrated to be an eﬀective strategy for fostering prosocial behavior. In this study, we evaluated how
participants’ prosocial behavior changed as they adopted
the perspectives of diﬀerent robots in a robot-altruistic virtual reality task. Our research revealed that individuals
who adopted the help-receiver view acted more favorably
toward a robot than those who adopted the help-provider
view. We will use the ﬁndings from our study in subsequent
work to explain how various tasks and relationships in thetasks could change participants’ prosocial behavior towards
robots.

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