What makes people accept a robot in a social environment- discussion from six-week study in an office Noriaki Mitsunaga, Zenta Miyashita, Kazuhiko Shinozawa, Takahiro Miyashita,
Hiroshi Ishiguro, and Norihiro Hagita
Abstract— In the near future, robots are expected to play
active roles in human communities. After this time arrives,
robots will need to be socially accepted by the people inthe communities to which they belong. However, it remains
unknown what issues must be resolved to make robots sociallyaccepted. In this paper, we point out the three criteria withwhich people in communities evaluate a robot and three typesof relations people have with the robot. We conducted a six-week
study in an office to statistically test the relationship between
the evaluations and how well a robot is accepted depending on
relation types. We probe that by improving behaviors in thecriteria the robot will be more accepted by each type of people.
Then, the discussion are presented about the most important
issues regarding the social acceptance of robots.

I. I NTRODUCTION
In the near future, robots are expected to play much more
active roles in such human community settings as schools,
museums, offices, and so on. At that time, robots mustsocially be accepted by the people in the communities towhich they belong so that it can smoothly play its role. Then,the question is how a robot should behave in the communities
or how a robot develops human-robot relationships.
A number of long-term studies have been conducted
regarding the performance of robots in everyday settings.
Jijo-2 [5] was developed for use in offices to guide visitors,
offer the location of a members, and so on. A museumguiding robot [1] and an expo tour-guide robot [10] havealso been developed. However, they assumed that the robot
is accepted if it plays its role in the community but did notcare for the human-robot relationship.
To investigate how children interact with a robot, longterm studies have been conducted in a kindergarten [7] andan elementary school [8]. They mainly focused on one to one
direct human-robot interactions of children but not focusedon other types of relationship.
We also conducted a study in which a robot daily communicated with the people in our office and wandered aroundfor a certain period looking for a conversation partner [6].
After finding someone to talk with, it started a conversation.
This research was supported by the Ministry of Internal Affairs andCommunications.
N.
MitsunagaiswithKanazawa
InstituteofTechnology,
7-1
Ohgigaoka,
Nonoichi,921-8501,
Japan
mitunaga@neptune.kanazawa-it.ac.jp
N. Mitsunaga, Z. Miyashita, K. Shinozawa, T. Miyashita, H. Ishiguro, and
N. Hagita are with ATR IRC Laboratories, 2-2-2 Hikaridai Keihanna Science
City, Kyoto, 619-0288, Japan {shino,miyasita,hagita}@atr.jp
Z. Miyashita and H. Ishiguro are with the Department of Adaptive
Machine Systems, Osaka University, 2-1 Yamadaoka Suita City, Osaka, 5650871, Japan ishiguro@ams.eng.osaka-u.ac.jp

The study investigated how effectively the robot’s humanrobot interaction behaviors offered the people in the office a
sense of familiarity with it.
As a result, questionnaire responses suggested that the
robot was welcomed since people had a sense of familiarity
with it. We also received negative feedback that reflected two
major drawbacks. One, the robot tried to communicate withothers without considering time, location, and their current
mood. Second, some regarded the robot had no social reason
for staying in the office since its only function was to chat.
Although chatting is an important social role for a therapeuticand entertaining robot, they did not want it in the office.
Such feedback indicated that people evaluated the robot intheir community by the following three criteria: how much it
provides a sense of familiarity, how appropriately it behavesbased on the circumstances, and how well it plays its socialrole in the community.
The result also indicates that there are three types ofrelationship between a human and a robot. One is the relationthat they directly interact, such as, the human asks the robot
for a task to complete. Second one is less direct in that thehuman does not directly interact with the robot but sees
some interaction of other people and the robot. Third one
is indirect relationship that the human rarely sees the robot
and he/she knows the robot mainly by hearsay knowledge.
Previous work [6]–[8] implicitly assumed a small communitythat most members have direct interaction experience withthe robot. However, the number of the second and the third
type people increases in a larger community.
In this paper, we investigate how a robot is sociallyaccepted by the following steps. First, we explore how arobot is accepted in a community. A six-week study in our
office was conducted to gather evaluations of a robot and its
acceptance. After that, we statistically analyzed the relationships between three criteria and the degree of acceptance.
We show that there are differences in them depending on
the types of human-robot relations above. Following thestudy results, we discuss the issues regarding the personal
acceptance of robots. Then, we discuss how a robot issocially accepted by a variety of community members andthe most important issue for a robot to be socially accepted.
In the next section, we briefly introduce our previous study
and its results. After discussing how people evaluated therobot, we introduce three evaluation criteria for a robot tobe accepted by community members and the three types ofhuman-robot relationship.

(a) Searching(b) Finding

including: b) “it was nuisance in the office,” “the robot
always said “hi” to me when I was in a hurry,” “it always
tried to talk behind my cubicle and it’s noisy” and c) “I
expected a robot in an office to do something useful but it
didn’t.” These responses indicate that people evaluated therobot based on three criteria: a) how much it produced asense of familiar in others, b) how appropriately it behaved
based on the circumstances, and c) how well it played its
social role.
B. Three issues for accepting a robot(c) Talking(d) Ending

Fig. 1. Robovie-IV’s typical interaction flow: searching for a human andtalking

II. E VALUATIONS OF A ROBOTA. Observations from a six-month study
We conducted a study to investigate how people evaluate arobot’s communication behaviors in an office when meetingit every day [6]. The robot’s behaviors, which were designed
to create the people in the office a sense of familiarity with it,
resembled a child accompanying a parent to the office. Sucha child is warmly treated by adults in the office if he/she
behaves appropriately. The robot imitated such behaviors tobe accepted in a similar way in the office.
For six months, Robovie-IV, a communication robot,
moved around in a corridor and searched for chatting partners
for about 90 minutes each day in a corridor about 50 meters
long in our ATR IRC laboratory’s office. About 30 to 50
people, both full-and part-time, were working in the office.
Fig. 1 shows the flow of Robovie-IV’s typical interaction.
It searched for a human to talk with (Fig. 1(a)). After finding
a human, it began interaction by saying “hi” and waiting fora response (Fig. 1(b)). If it did not receive a response, itbegan to seek another human; otherwise, it recognized thehuman as an interaction partner and started a conversation, as
shown in Fig. 1(c). The conversation ended when he/she said
“good-bye” or walked away. Then the robot responded with“good-bye” and began to seek another conversation partner(Fig. 1(d)).
After the six-month study period, we asked the people
in the office to fill out questionnaires by e-mail. We got
thirteen responses from people who frequently interactedwith or saw the robot. Five of these thirteen had positive
impressions of the robot in the office, two were neutral,and six had negative impressions. Some responses to thefree-answer questions indicated positive impressions of therobot’s behaviors and a sense of familiarity with it. Examples
include: a) “talking with Robovie was relaxing” and “whentalking with Robovie, one person took on a soft expressionthat I’ve never seen when he is talking with people in
the office.” However, other answers pointed out drawbacks,

The questionnaire answers from the previous study suggest
at least three issues that must be satisfied for a robot to be
accepted.
a) familiarity: how much a robot creates a sense offamiliarity,b) circumstance-appropriateness (c-app.): how appropriately the robot behaves depending on circumstances,andc) social-role: how well it completes given task in thecommunity.
The evaluation of each criterion and its importance will
be different from person to person depending on the backgrounds and interaction experiences with the robot even
within a single community. However, we expect that as theevaluation of each criterion increases, the more the robot will
be accepted.
To examine the mutual relationships between the evaluations of each criterion and how well the robot was accepted(acceptance), we conducted a six-week study. Three different
robot behaviors were prepared, and each was performed fortwo consecutive weeks. The behaviors were designed to elicit
different responses to the acceptance and the three criteria
above from the people interacting with the robot. Each week,
we asked people to fill out questionnaires, which we used
to measure the criterion and acceptance evaluations. The
following are the three prepared behaviors: 1) moving aroundand talking with people regardless of location (searchand-talk, identical behaviors shown in the previous study),2) mainly staying in a small area and only talking withpeople in that area and sometimes moving around but not
greeting people in the corridor (stay-and-talk), and 3) mainly
staying in a small area and only talking with people in thatarea and sometimes moving around in the corridor to deliver
documents (stay-and-talk-during-delivery). The details of the
behaviors and the study are described in the next section.
C. Three types of human-robot relationship
Here, we classify people into three types according to theinteraction with the robot as in Fig. 2. The type X people are
the ones who directly interact with the robot. For example,
they chat with the robot, ask the robot for a guide, ask adeliver task, and so on. The type Y people have chance to
see the robot and human-robot interactions of the people X
but do not have direct interaction with the robot. People in
the group Z rarely have chance to see the robot. They only
have indirect (hearsay) knowledge from people X and Y.

com m unication

R

ar

n
tio
rv a
ob

sa

se

yk

no

wl

ed

ge

ob se rv at

io n

X

he

Y

Z

hearsa y kn o w ledge

Fig. 2. There are three types of people from the viewpoint of humanrobot interaction in a community. X has direct communication with therobot. Y observes the communication between X and the robot. Y has direct
knowledge. Z only has hearsay knowledge about the robot.

Fig. 4. Office floor used for the study: researcher cubicles, reception,
clerical assistant desks, manager offices, and a long corridor

1 ca m e ra w ith
o m n i-d irectio n a lm irro r
2 ca m e ra s w ith
p a n a n d tilt

n eck
(3d o f)

1 sp e a ke r a n d
1 m icro p h on e

1 o p tica lta g re a d e r

2 arm s(4 d o f x2)

1 R F ta g
re a d e r

1 g yro se n so r a n d
1 in clin o m e te r
2 la se r ra n g e
se n so rs

5 6 skin
se n so rs

4 su p p o rt w h e e ls
(p a ssive ca ste rs)

1 jack
(1d o f)2 d rive w h eels
F ront view

Left side viewFig. 4 shows the experimental environment in which
about 60 researchers, clerical assistants, managers, and internstudents work. About 15 people work near where the robot
moves around since some work part time and others work
mainly in other experiment rooms. The office floor includes
researcher cubicles, reception, clerical assistant desks, manager offices, and a long corridor. Each cubicle is surroundedby partitions about 1.3 m high. The study ran from around3:00 to 4:30 p.m. when people are still working but often
take short breaks.
B. Procedure of the study

Fig. 3. Front and left side views of Robovie-IV. Fitted actuators and sensors
are shown.

III. S TUDY IN AN OFFICE
A. Robot and environment
Fig. 3 shows the front and side views of Robovie-IV, which
is about 1.1 m high. It has two arms each with four degrees
of freedom and a head with pan, tilt, and roll joints. Itsvoice is synthesized with CHATR [2] and sounds like a child.
Julian [4] is adopted for the speech recognition engine.
We chose our office as the experimental field as in [6] forthe following two reasons. First, it is a human communitythat involves people in different positions with different
personalities and backgrounds. People spend many hours
sharing space and experiences. Thus, we believe that thefindings from studies in offices can be applied to manyother human communities. Second, a robot is welcomed asa novelty when initially introduced to a community, but thisfeelings soon passes. A robot is only truly socially accepted
after it has been welcomed without novelty. If we can run
studies where people are already accustomed to the robot,
we don’t need to wait for it to lose its novelty. Therefore wechose our own office, since people are more accustomed torobots than in other offices.

Three behaviors are prepared for the robot. It takes thesame behavior for sub-sequent two weeks. A questionnaire isissued each week for the same people in the office to evaluate
the robot’s behavior. It is preferable to avoid order effects
caused by the presentation order of behaviors. However, it
is almost impossible to control the respondents since theenvironment is a real office.
Meanwhile, there is an idea to use different environments
to avoid the order effects so that a respondent experience only
one of the robot’s behaviors. However, there are different
possible problems such as respondents’ familiarity with therobot and control of the environmental conditions.
Then, we decided to conduct the study in an office. The
three behaviors are presented in the order as if the robot
develops its behavior to suit for the office environment.
C. Robot behaviors
1) Search-and-talk behavior: In the first and second
weeks, the robot searched for a conversation partner bymoving back and forth in the “wandering areas A and B” in
Fig. 4. It says hello and tries to talk with people anywhere in
the area in a fashion identical to the previous study (Fig. 1.)
Basically, the robot repeats a) moving around, seeking ahuman to interact with; and b) interaction with the foundhuman until he or she quits the interaction. It detects humans

.GIU
4QDQXKG+8(CMGNGI

Fig. 6.
Fig. 5. A depth image plotted on the floor map by a laser range sensor.
A circle and a line on the right indicate Robovie-IV’s position and posture.
Two circles in front of the robot are detected legs. The larger circle to theleft of the robot is a false detection.

by first finding leg candidates from front laser range-sensor
values. The laser range sensor measures at the height ofan ankle. Fig. 5 illustrates the readings of the range sensor
plotted on the floor map. The circle on the right and the line
indicates the position and the posture of the robot from selflocalization data based on map matching. Clearly, the walls
and cartoon boxes are detected by the sensor, whereas distantwalls are not detected since the sensor’s maximum range is
4 m. The two small circles in front of the circle representing
the robot indicate detected legs. When a leg candidate isfound, it rotates itself and gazes in the direction of the leg
candidate. If a large skin-colored blob or a large blob in adifferential image is detected by the robot’s camera, or the
tag reader detects a valid ID, it assumes the candidate to be ahuman leg. During interaction, it tracks the skin-colored blobat the shortest distance in the direction of the leg candidate
and maintains that distance and posture.
Once Robovie-IV has detected a human, it will try tointeract with him or her. It will say “Hi” in Japanese andwait for the response. If it does not detect a response it will
begin to seek another human; otherwise, it will recognize theperson as the conversation partner.
A conversation consists of several small topics that arecomprised of a few pairs of sentences spoken by the robot
and a set of expected human responses. Dictionaries forthe speech recognition were prepared to cover the expected
responses. Topics were always initiated by the robot. For
example, it initiates a topic by saying “It’s hot today, isn’tit?”; “Do I look cute?”; “Are you hungry?”; “What are you
drinking?”; and so on. Then it waits for an answer andcontinues the conversation by responding or starting anothertopic.
2) Stay-and-talk behavior: In the third and fourth weeks,
the robot only talked in the “staying area,” where it stayed for
10 minutes before making a lap in the corridor to “wandering
area A” and returning to the “staying area.” It searches fora conversation partner in the “staying area,” as in the firstand second weeks. It repeats “stay and move” until theexperiment’s time ends.

Robovie-IV carries a bag in fifth and sixth weeks

The “staying area,” which was determined so that the robot
does not disturb people working at desks or in cubicles, isequipped with electric pots, a refrigerator, and a cupboard
for making tea or coffee on breaks.
The robot does not talk with anyone it encounters in thecorridor. If an individual addresses it, the robot says “let’s go
to the break area and talk there” and returns to the “staying
area.” When it arrives there, it begins to chat with that person.
3) Stay-and-talk-with-delivery behavior: In the fifth andsix weeks, the robot only talks in the “staying area,” where
it remains for 20 minutes before starting a “delivery task.”
The robot carries a bag to deliver a document in these two
weeks (Fig. 6). As in previous weeks, it searches for aconversation partner in the “staying area” and repeats this“stay and deliver” behavior until the experiment’s time ends.
The “delivery task” simulates a messenger’s behavior in
an office. The robot works for researchers A and B, whowere chosen from our research group beforehand and asked
to cooperate in our study. Their cubicles are located as shownin Fig. 4. First, the robot visits a researcher’s cubicle and asks
for a document to deliver. If there is one, the researcher puts
it in the robot’s bag, and the robot delivers it to destination A
shown in Fig. 4. At destination A, the robot announces that adocument has been delivered and asks for another document
to deliver. The robot repeats this behavior for researchers A
and B.
During this “delivery task,” it does not try to talk with ahuman when it meets one in the corridor. If a human tries totalk with the robot, it says “Sorry, I am working now. Let’stalk later” and continues its “delivery task.”
D. Questionnaire
We put questionnaires in physical mailboxes at the end ofeach experiment week and also sent e-mails to the people in
the office and asked them to complete the questionnaires.
The questionnaire asked the following:1) evaluations of robot: Respondents were asked to markthe 7-point rating scales of sixteen adjective pairs in
Table I. One adjective in the pair is placed at 1 in thescale and the other is placed at 7 (Fig. 7).
2) interaction experience: Respondents were asked how
frequently they met and talked with the robot during
the week.

TABLE I
A DJECTIVE PAIRS USED IN QUESTIONNAIRES FOR ROBOT EVALUATION
Positive adjective
cuteamusing
amiablewarm
thoughtfulquietrobot is aware where it is
not-obstructive
responsible
diligent
earnesthonestlikeable
activequick
lively

  

quite

very

Negative adjective
not cuteboring
not amiable
distant
inconsideratenoisy
unawareobstructive
irresponsible
lazyexcessive
slipshodunlikablepassiveslow
not lively

rather neutral rather

very

occupationinterns
researchers
managers
clerical assistants

Fig. 7.

# ofrespondents
1
2
1
7

age
20s
30s
40s

# of
respondents
3
72

A. Result of factor analysis and acceptance of robotquite                                (responsible)

TABLE IIO CCUPATIONS AND AGES OF 23 RESPONDENTS WHO RETURNEDQUESTIONNAIRES FOR ALL THREE ROBOT ’ S BEHAVIORS(irresponsible)

Example of a 7-point rating scale of adjective pairs3) changes in robot: We asked whether respondents had
noticed any differences in the robot from the previous
week, and if so, to explain that impression.
4) how the robot was regarded (respondent’s view ofrobot): Respondents were offered 14 choices to match
how they regarded the robot: unfamiliar creature, pet,friend, servant, child, adult, toy, machine, AI, automatic responding machine, a thing that you havetechnical interests (technical interests), a thing that you
have interests in conversation (interests in conversation), a robot in which you have technical interests(interests in robots), and other. Respondents were allowed to mark more than one choice.
5) how well the robot was accepted (acceptance): Respondents were asked to mark the 1-7 rating scale forthe following question: “Do you want the robot to stayin the office?” 7 corresponds to definitely yes and 1 todefinitely no.
IV. R ESULTS OF THE STUDY
Twenty three people, 12 males and 11 females, returned
76 questionnaires. Twelve of the 23 people (3 males and9 females) answered the questionnaires for all three robot
behaviors. In other words, twelve people returned questionnaires once or twice every two weeks. Table II breaks
down respondents by occupations and ages. The interns,
researchers, and managers have some knowledge about current computer and robot technologies. Clerical assistants use
computers but are unfamiliar with programming and robot
technologies. In the following, scores are averaged before
analysis if a respondent answered the questionnaire twice
for the same robot’s behavior.

We have conducted a factor analysis to investigate what
factors dominate the evaluation of the robot. Table III shows
the result of factor analysis (principal factor method, equamax with Kaiser normalization) for the scores of adjective
pairs. There is a possibility that the scores in the questionnaires are affected by factors which are not related tothe behavior changes since the environment and respondents
were not controlled in this study. Then, we decided to use
the method that does not need to assume the number offactors beforehand and analyze factors that the cumulative
proportions exceeds 70%. The cumulative proportion fromfirst to fifth factors shown in Table III is 73%. We callthe first factor favorability since the components of thefirst factor (factor load > 0.6 ) are “amusing”, “cute”,“likeable”, and “not-obstructive”. The second factor consistsfrom “thoughtful,” “robot is aware where it is,” and “honest.”
We call it circumstance-appropriateness (c-app.). We call thethird factor childishness since it consists from “amiable” and“irresponsible”, which are related to the child like behaviorsof the robot. The fourth factor is named social-role since thefactor loads of “diligent” and “earnest” are high. The factor
loads of “lively” and “quiet” are high in fifth factor and wecall it activeness.
The familiarity of the robot relates with the first factor
favorability and the third factor childishness. The childishness evaluation comes from the robot’s appearance, that is,
its small height, child like behaviors, and child like voice,which is peculiar evaluation to the robot used in the study.
Then we name the first factor familiarity.
We classified the respondents into three groups X, Y, andZ as in Fig. 2 according to their experiences.
X) respondents who frequently talked when they met the
robot,Y) respondents who rarely talked when they met the robot,Z) respondents who rarely met the robot.
Fig. 8 shows the meeting ratio and interaction experience ofthe respondents.
Table IV shows the Pearson’s coefficient correlation between the five factor scores and acceptance for three groups.
From the table, we can see that there is no correlation between the fifth factor activeness and acceptance in all people.
In group X, familiarity has strong positive correlation withacceptance (0.952, p < 0.01) and weak positive correlation
between c-app. and acceptance (0.627, p < 0.05). This isdue to the fact that the respondents in group X evaluate

TABLE III
FACTOR MATRIX GIVEN BY THE FACTOR ANALYSIS ( PRINCIPAL FACTORMETHOD , EQUAMAX WITH K AISER NORMALIZATION )factor matrix
amusing
cute
likeable
not-obstructive
thoughtfulrobot is aware where it ishonestamiableresponsible
deligent
earnestlivelyquiet
warm
activequick
cumulative proportion

1st
0.84
0.82
0.78
0.71
-0.11
0.44
0.10
0.23
-0.10
0.03
0.35
0.14
0.32
0.57
0.35
0.18
22%

2nd
0.00
0.00
0.05
0.45
0.84
0.70
0.67
0.14
0.36
-0.02
-0.06
0.07
0.03
-0.01
-0.46
0.48
37%

interaction experience(number of interaction per week)

3.5

3rd
-0.18
0.07
0.29
0.16
-0.03
0.24
-0.34
0.85
-0.83
0.03
-0.02
0.25
0.21
0.31
0.07
-0.44
50%

4th
0.26
-0.11
0.32
-0.07
0.00
-0.06
0.00
0.11
0.15
0.90
0.73
0.22
0.08
0.33
-0.45
-0.09
62%

5th
-0.11
-0.06
-0.13
0.24
0.13
0.03
-0.18
0.03
-0.03
0.12
-0.01
0.83
-0.75
0.08
0.34
0.38
73 %

group X
group Y
group Z

3
2.5

:
2
1.5

TABLE IVP EARSON ’ S COEFFICIENT CORRELATION BETWEEN THE FIVE FACTORSAND THE ACCEPTANCE .

group
X
Y
Z

favorability(familiarity)
0.952 **
0.868 **
0.241

c-app.

childishness

0.627*
0.850 **
0.204

0.485
0.678*
0.333

playsocial-role
0.489
0.719*
0.262

activeness-0.315-0.1560.460* significant in p < 0.05, ** significant in p < 0.01

acceptance. We do not discuss for this factor since it ispeculiar factor for the robot as we noted before.
There are no correlations between five factors and acceptance in group Z. This is due to the fact that theirevaluation had large variances in the group since they did nothave chance to see the robot nor obtained enough hearsay
knowledge in six weeks, which led to the evaluation weredone by their initial knowledge.
From these results, we conclude that acceptance ofgroup X and Y becomes high when they highly evaluate
the robot’s familiarity, circumstance-appropriateness., andsocial-role. Also, the higher the group X and Y’s acceptanceis, the higher acceptance of group Z will be since theyevaluate the robot by hearsay knowledge from people ingroups X and Y.

;

1

B. Changes of acceptance
0.5
0
0.5

<
1

1.5

2

2.5
3
meeting ratio(number of days per week)

3.5

4

4.5

Fig. 8. This figure shows the distribution of meeting ratio (number of days
that a respondents met the robot per week) and the interaction experience(the number of interaction that he/she had per week). In group Z, there were
two subjects that both numbers are congruent.

the robot according to their own experiences. Thus, theyevaluated the robot highly with familiarity according to theircommunication experience with the robot.
In group Y, familiarity and c-app. have strong positive
correlation with acceptance (0.868, p < 0.01 and 0.850
p < 0.01 respectively). The childishness and social-role
have positive correlation with acceptance (0.678, p < 0.05
and 0.719, p < 0.05 respectively). Respondents in group Y
evaluate the robot mainly from their observation experiences,such as, watching the human-robot interaction of the group X
and the robot, the robot’s behavior when the robot went by, it
tried to talk, it disturbed people, and so on, which relates tocircumstance-appropriateness. Then their acceptance evaluation more correlated with the factor of c-app. compared to
the group X. The low correlation between social-role andacceptance comes from the fact that they did not notice that
it was playing a social role of a messenger. Then they did
not change acceptance after the robot started the messenger
task. There is weak correlation between childishness andComparing the average acceptance for the first and second
weeks with the average of the fifth and sixth weeks, wefound the following: 1) averaged acceptance was identical
for the seven respondents, 2) acceptance increased for one
respondent, 3) acceptance decreased for four respondents.
And there were small changes in each factor score andacceptance evaluation within each respondent. From the freeanswer questions in the questionnaire and the comments
given to the experimenters, there seemed to be two maincauses of the decrement of acceptance.
First, some did not like the staying area. Since the robot
sometimes disturbed people by greeting them in the corridor
in the previous study, it was programmed to only talk inthe staying area from the 3rd week. Here, people make tea
or coffee during breaks, where if they meet someone, theytalk. We assumed that people would welcome conversation
with the robot in that area. However, some respondents feltthat this place was inappropriate for the robot to stay-andtalk since the area is rather small and the robot sometimes
interfered with people preparing tea/coffee or opening therefrigerator. This explains some lowered c-app. and acceptance scores in the fifth and sixth weeks.
Second, the robot stopped talking in the corridor fromthe 3rd week after it started to remain in the staying area.
Some people seemed to notice that the robot stopped talking
to them when they met in the corridor and apparently they
preferred being approached in the corridor, even though somethought it was annoying. Their impressions of the robot’s
familiarity and acceptance decreased.

The variances of familiarity, c-app., and social-role withina respondent were 1.25 or below in six weeks. That means
the impression of respondents did not change so much evenwhen the robot stopped talking in the long corridor or startacting as a messenger. One of the reason is that most of the
respondents did not have enough chance to see the robot as
they only see the robot for once or twice in a week. Some
noticed that the robot started to carry a pink bag and only
one noticed that it started working from the utterance of therobot. They did not seem to notice that the robot was carrying
a document in the bag and playing a messenger role.

TABLE VR ESPONDENTS ’ PERCEPTIONS OF ROBOT AFTER SIX WEEKS . T HEY
COULD MARK MORE THAN TWO CHOICES .
category

creaturemachineC. Respondents’ view of robot and acceptance
Table V shows how the twelve respondents regarded therobot over the six-week period. Respondents were allowed
to mark more than one choice for a week. If a respondent
marked the same choice for more than two weeks, it wascounted as one. Table V shows that many respondents
regarded the robot as a kind of “machine” rather than a kindof “creature,” and there are large variants in their views.
Table VI shows how the respondents changed their views in
the “creature” and “machine” categories. From the table, we
can see that the respondents did not drastically change theirown views. Respondents are classified into four groups: C,
N, M, and O. Groups C and M include those who tended
to see the robot as a creature and a machine, respectively.
Group N regarded the robot both as a creature and a machine
throughout the six weeks. No respondents changed their view
from “creature” to “machine” or vice versa over the six-weekperiod. However, they would belong to Group O if they had.
Fig. 9 illustrates the differences of averaged acceptance
between respondents in group C and others (groups N & M)
throughout the study. Group C’s average acceptance is higher
than the other respondents (statistically significant in MannWhitney U-test, p = 0.02).
Fig. 10 illustrates the difference of the three evaluationindexes of the respondents in group C and groups N & M.
The familiarity and c-app. of the group C were statisticallyhigher than those of groups N & M (Mann-Whitney U-test,
p = 0.00.) There were no significant difference in social-role(p = 0.076), in childishness (p = 0.499), and in activeness(p = 0.499). The result were consistent with the one when
we conducted test excluding the respondents in people Z.

answerunfamiliar creaturepetfriendservant
child
adult
toy
machineAI
automatic responding machinetechnical interests
interest in conversationinterest in robots
other

# of
respondents
4
6
2
1
6
0
3
8
1
3
2
0
6
1 (information
source)TABLE VI
C HANGES OF RESPONDENTS ’ VIEWS OF ROBOT

C
N
M
O

first week’s view
creaturecreaturecreature & machine
creature & machine
creature & machinemachinemachinecreaturemachinesixth week’s view
creaturecreature & machine
creaturecreature & machinemachinecreature & machinemachinemachinecreature# ofrespondents
1
1
1
2
1
2
4
0
0

A. Personal acceptance of robots
Before discussing the social acceptance of robots, let us
further explore their personal acceptance. In a year-longfield study Forlizzi [3] compared the fanciest stick vacuum
cleaner and “Roomba,” a cleaning robot. Subjects were given
either a lightweight, easy to use stick vacuum that they had
to operate themselves or a cleaning robot that they could
simply push start button and walked away; but later they
had to complete the job using another vacuum since thecleaning robot’s efforts are incomplete. She reported that
subjects given the stick cleaner stopped using it before the7

V. D ISCUSSION

65
acceptance

What is the key issue for a robot to be socially accepted?
Do we need to design a robot so that it looks like a creature?
Most of the respondents who regarded the robot as a creature(group C) scored acceptance higher than respondents who
regarded it as a machine (groups N and M). However, there
were some respondents in groups N and M who gave higher
acceptance than the value given by people in group C. Then,
we argue that it is not the key issue but the three issues,
familiarity, circumstance-appropriateness, and social role,
are more important for a robot to obtain a higher acceptance.
In the following, we will discuss the importance of the threeissues from the view of personal and social acceptance.

4
3
2
1
0
C

M+N

Fig. 9. Difference of average and deviations of acceptance’s between
respondents in “C” group and “M” or “N” group. The averages are taken
for six weeks. They have statistically significant differences (Mann-Whitney
U-test, p = 0.02).

7

C
M+N

6

acceptance

5
4
3
2
1
0

familiarity

circumstanceappropriatenesssocial-role

Fig. 10. Differences of averages and deviations of familiarity, c-app.,and social-role measures between respondents in group C and groups M& N. The averages are taken for six weeks. Familiarity and c-app. havestatistically significant differences (Mann-Whitney U-test, p = 0.00).

year elapsed. However, subjects given the cleaning robot
continued using it even after the one-year study period
finished. We also note that more than two million “Roomba”shave been sold. Then, “Roomba” is one example of the robotthat is personally accepted.
The autonomous task completion is the critical difference
between a cleaning robot and a vacuum cleaner. You can dosomething else while the robot is cleaning, even though youneed to do a little more work to finish the cleaning. Thus, inthis example, the robot gains high evaluation in social role
and accepted.
Another robot task that separates it from a machine is asa companion. Paro [9] is a well-known therapeutic robot.
AIBO and Primopuel are commercial products targeted atthose who want such companions. AIBO is a series of fourlegged pet robots for amusement at home. Primopuel is aseries of stuffed toy dolls that have sensors in them. They
respond and change behaviors based on voice and tactile
communication. Sony has sold more than 140,000 AIBOs,
and BANDAI has sold more than a million Primopuels. Then,
we can say that these companion robots, which rolls arecommunication, are accepted.
Then, we argue that a robot is accepted when it gives
enough familiarity to the user and completes an expected social role. The user don’t care for circumstanceappropriateness when a robot is used personally, since theuser can turn it on and off as he/she likes.
B. Social acceptance of robots
Next question is whether a robot also is socially accepted
when it offers familiarity and plays a social role as in thecase of personal acceptance. Do all people in a society regard
the robot has familiarity and plays social role?
In a community, there are many applications or social
roles for a robot, including guide, receptionist, messenger,
secretary and so on. For the people X who interact with it,
the familiarity is important and its social role evaluation will
increase if a robot plays one such role, as in the discussion of
personal acceptance of the robot. Since the robot’s target ispeople X, the robot’s familiarity and social role are designed

for them. Then there are cases that the design is not perfectfor people Y and Z.
Meanwhile, we found that the correlation between c-app.
and acceptance of people Y, who have less interaction withthe robot, is higher than that of people X who interacts more
frequently with the robot from the study. Note that somemight not perceive that the robot is playing a social roleeven if they see that the robot is “working”. Also, people Z,
who do not directly contact with the robot, evaluate the robot
from the hearsay from people X and Y. Then the acceptanceof group Y dominate the social acceptance of the robot whena community grows since the number of people Y and Z
increases at that time.
Then, we conclude that it is highly recommended todesign a robot considering the circumstance-appropriatenessin addition to the familiarity and the social role for the mainusers.
VI. C ONCLUSION
A robot in a community is evaluated by three criteria:
1) familiarity, 2) circumstance-appropriateness, and 3) social role. We showed the positive relationships between
those three evaluations and acceptance by individuals in
a community in a six-week study. In the discussion, we
argued that improving circumstance-appropriateness is themost important issue for a robot to gain social acceptance.
Determining appropriate behavior for a robot in various
circumstances is the next open question.
R EFERENCES[1] W. Burgard, A. B. Cremers, D. Fox, D. Haehnel, G. Lakemeyer,
D. Schulz, W. Steiner, and S. Thrun. The interactive museum tourguide robot. In AAAI98, 1998.
[2] W. Campbell and A. Black. Prosody and the selection of source
units for concatenative synthesis. In J. P. V. Santen, J. Olive, and
J. Hirschberg eds., Progress in Speech Synthesis. Springer, 1996.
[3] J. Forlizzi. How robotic products become social products: An
ethnographic study of cleaning in the home. In Proc. of the 2007
ACM/IEEE 2nd Int. Conf. on Human-Robot Interaction, pp. 129–136,
2007.
[4] A. Lee, T. Kawahara, and K. Shikano. Julius - an open source real-timelarge vocabulary recognition engine. In Proc. of the European Conf.
on Speech Communication and Technology, pp. 1691–1694, 2001.
[5] T. Matsui, H. Asoh, I. Hara, and N. Otsu. An event-driven architecture
for controlling behaviors of the office conversant mobile robot, jijo-2.
In Proc. of 1997 IEEE Int. Conf. on Robotics and Automation, pp.
3367–3372, April 1997.
[6] N. Mitsunaga, T. Miyashita, H. Ishiguro, K. Kogure, and N. Hagita.
Robovie-IV: A communication robot interacting with people daily inan office. In Proc. of 2006 IEEE/RSJ Int. Conf. on Intelligent Robots
and Systems, pp. 5066–5072, 2006.
[7] J. R. Movellan, F. Tanaka, I. Fasel, C. Taylor, P. Ruvolo, and
M. Eckhardt. The RUBI project: A progress report. In Proc. of 2007
ACM/IEEE 2nd Int. Conf. on Human-Robot Interaction, pp. 333–339,
2007.
[8] S. Nabe, T. Kanda, K. Hiraki, H. Ishiguro, and N. Hagita. Humanfriendship estimation model for communication robots. In Proc. ofIEEE Int. Conf. on Humanoid Robots, pp. 196–201, 2005.
[9] T. Shibata, T. Tashima, and K. Tanie. Emergence of emotional
behavior through physical interaction between human and robot. In
Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 2868–2873,
1999.
[10] N. Tomatis, G. Terrien, R. Piguet, D. Burnier, S. Bouabdallah, and
R. Siegwart. Design and system integration for the expo.02 robot.
Workshop on Robots in Exhibitions, IEEE/RSJ Int. Conf. on Intelligent
Robots and Systems, 2002.