Fichier PDF

Partage, hébergement, conversion et archivage facile de documents au format PDF

Partager un fichier Mes fichiers Boite à outils PDF Recherche Aide Contact



Donner un sens aux robots sociaux .pdf



Nom original: Donner un sens aux robots sociaux .pdf
Titre: Making sense of social robots: A structural analysis of the layperson's social representation of robots
Auteur: N. Piçarra

Ce document au format PDF 1.7 a été généré par Elsevier / Acrobat Distiller 9.0.0 (Windows), et a été envoyé sur fichier-pdf.fr le 09/05/2017 à 11:44, depuis l'adresse IP 86.192.x.x. La présente page de téléchargement du fichier a été vue 244 fois.
Taille du document: 1.1 Mo (13 pages).
Confidentialité: fichier public




Télécharger le fichier (PDF)









Aperçu du document


Revue européenne de psychologie appliquée 66 (2016) 277–289

Disponible en ligne sur

ScienceDirect
www.sciencedirect.com

Original article

Making sense of social robots: A structural analysis of the layperson’s
social representation of robots
Donner un sens aux robots sociaux : une analyse structurelle de la représentation
sociale des robots
N. Pic¸arra a , J.-C. Giger a,b,∗ , G. Pochwatko c , G. Gonc¸alves a,b
a

University of Algarve, Faro, Portugal
Research Centre for Spatial and Organizational Dynamics – CIEO, Faro, Portugal
c
Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
b

a r t i c l e

i n f o

Article history:
Received 28 September 2015
Received in revised form 13 July 2016
Accepted 19 July 2016
Keywords:
Social robots
Social representation
Acceptance of technology
Structural analyses

a b s t r a c t
Introduction. – Given their novelty, social robots (i.e., robots using natural language, displaying and recognizing emotions) will generate uncertainty among users. Social representations allow making sense of
the new, drawing from existing knowledge.
Objective. – A free association questionnaire was administered to 212 Portuguese adults to identify the
social representation of robot.
Method. – Data was analysed with EVOC 2000 and SIMI 2000 software.
Results. – The social representation of robot is organized around the ideas of technology, help and future.
Differences in the representation according to age, gender and level of education where also identified.
Conclusion. – The social representation of robot is marked by the conception of it as a tool. This contrasts
with the concept of social robots as social agents. Implications for social robot’s acceptance are discussed.
© 2016 Elsevier Masson SAS. All rights reserved.

r é s u m é
Mots clés :
Robots sociaux
Représentation sociale
Acceptation de la technologie
Analyses structurales

Introduction. – Étant donnée leur nouveauté, les robots sociaux (i.e., qui utilisent un langage naturel
et montrent et reconnaissent des émotions) vont générer un sentiment d’incertitude chez les futurs
utilisateurs. Les représentations sociales permettent de donner du sens aux choses nouvelles à partir des
connaissances préexistantes.
Objectif. – Les participants (n = 212 adultes portugais) effectuèrent une tâche d’association libre dans le
but d’identifier la représentation sociale du robot.
Méthode. – Les données ont été traitées à l’aide des programmes EVOC 2000 et SIMI 2000.
Résultats. – La représentation sociale du robot est organisée autour des idées de technologie, d’aide
et d’avenir. Des différences en fonction de l’âge, du genre et du niveau d’éducation sont également
identifiées.
Conclusion. – La représentation sociale du robot est marquée par la conception de celui-ci comme un
outil. Cela contraste avec le concept de robots sociaux en tant qu’agents sociaux. Les implications pour
l’acceptation des robots sociaux sont discutées.
´
´
es.
© 2016 Elsevier Masson SAS. Tous droits reserv

1. Introduction

∗ Corresponding author. Faculdade Ciências Humanas e Sociais, Universidade do
Algarve, Campus de Gambelas, 8005-139 Faro, Portugal.
E-mail addresses: nuno.psicologia@outlook.pt (N. Pic¸arra), jhgiger@ualg.pt
(J.-C. Giger), grzegorz.pochwatko@psych.pan.pl (G. Pochwatko), ggoncalves@ualg.pt
(G. Gonc¸alves).
http://dx.doi.org/10.1016/j.erap.2016.07.001
1162-9088/© 2016 Elsevier Masson SAS. All rights reserved.

The research presented in this paper aims to further the understanding of the layperson’s view of robots and the challenges
brought forward by recent developments in the area of robotics.
The steep growth curve that characterized robotics over the
last decades has brought us close to science fiction reveries like

278

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

R2-D2 and 3-CPO (Star Wars’ characters). Indeed, the concept of an
embodied robotic assistant endowed with a social interface (Hegel,
Muhl, Wrede, Hielscher-Fastabend, & Sagerer, 2009) has taken form
in robots like Snackbot (Lee et al., 2009), Kismet (Turkle, Breazeal,
Dasté, & Scassellati, 2006) or Geminoid HI-1 (Nishio, Ishiguro, &
Hagita, 2007). Remarkable progresses in artificial intelligence (AI)
made possible the development of robots capable of seeing, hearing
and communicating in ways similar to humans, i.e. social robots.
Capable of using natural language, recognizing and expressing
emotional cues, following gaze and gestures, social robots (Fong,
Nourbakhsh, & Dautenhahn, 2003) are geared towards the cooperation with humans outside the structured world of the industrial
factory. That is, social robots are aimed at tasks usually associated
with human expertise. Early examples of this are the three robot
wardens tested in a South Korean prison (BBC News, 2011, November 25). These three 150 cm robotic prison guards, are equipped
with cameras and sensors and are expected to patrol the wards
detecting risk behaviors such as violence and suicide among the
detainees and thus reducing the workload of the human guards.
Although the concept of social robot has gained momentum
among researchers and the robotic industry, it is hardly present
among lay people. As the recent Eurobarometer report shows (TNS
Opinion & Social, 2012), when Europeans were asked to forecast
the employment of robots in housework and domestic tasks, 51%
answered in 20 or more years’ time and only 4 percent said it was
something already common. Results for Portugal follow a similar
pattern, with 35% of the participants answering in 20 or more years’
time, while only 8% answered that robots were already used in
housework and domestic tasks.
Although other studies attempted to understand people’s evaluations of robots (e.g. Pic¸arra, Giger, Pochwatko, & Gonc¸alves, 2015),
these were based on a pre-set of questions, thus limiting the depth
of the knowledge gained. In order to further the understanding of
the layperson’s view of this new technology, this paper aims to
identify the social representation of robot. Social representations
allow people to categorize and make sense of the new, drawing on
pre-existing knowledge. They are a guide on how to reason and act
towards social objects (Jodelet, 1984, 1989). As such, the identification of the social representation of robot will show the background
against which people will make sense of social robots.

2. The disruptive character of robots and the acceptance of
innovation models
Although industrial robots were initially seen as an increment
to the existing industrial machinery, its ability to replace human
skills in a series of tasks had a profound effect on job definition
and workers’ perception of their role (Shenkar, 1988). Research on
the effects of automation showed that the change of focus from
mainly manual to cognitive tasks (i.e., monitoring the functioning of the machines and programming the robot), lead operators
to report higher levels of stress, felt responsibility and reduced
interactions with co-workers. The operators also reported that,
although the robot eliminated heavy work, the job was now more
boring, thus raising the question of worker motivation (Argote,
Goodman, & Schkade, 1983). Work displacement, job security,
blocked promotions, changes in extrinsic and intrinsic rewards,
were other identified effects of automation in industrial settings
(Chao & Kozlowski, 1986; Shenkar, 1988).
Social robots, on the other hand, are aimed to operate beyond the
confines of the industrial plant, representing a departure from current technology, not only in terms of features, but also of interaction
possibilities and the place occupied in the social space. Social robots
are a discontinuous innovation (Bagozzi & Lee, 1999). As Young et al.
(2011) points out, “robot’s social and physical presence, and their

tendency to evoke a sense of agency, creates a complex interaction
context very different from that of interaction with other technologies and artifacts” (p. 54). Thus, if the industrial robot brought a
series of challenges to the organization of labor, the social robot will
further those challenges to the organization of social life, blurring
the boundaries of what are regarded as exclusively human tasks
(see Mutlu & Forlizzi, 2008 for an example of the organizational
challenges introduced by the use of a robotic solution).
Albeit innovation and technology are frequently equated with
progress and welfare, the route is not straightforward (Sabanovic,
2010). As Ram (1987) pointed out, this pro-innovation bias lead
researcher to focus on early adopters (Rogers, 1983), ignoring the
common consumer, “. . .the vast majority of people who have no a
priori desire to change may be more typical and even more rational than a small minority of individuals who seek change for its
own sake rather than, or in addition to, the intrinsic value of the
innovations” (Sheth, 1981, p. 274). Contrary to common expectations, what research on innovation has shown is the high degree of
uncertainty (Rindova & Petkova, 2007) and anxiety (Fagan, Neill, &
Wooldridge, 2003) generated by novelty. As Sheth (1981) pointed
out, studying innovation is not only an account of early adopters,
but also of those who resist novelty.
In order to capture the dynamics of acceptance/resistance of
innovation, several models and sets of factors have been proposed.
For example, Ram and Sheth (1989) identify two types of barriers to
innovation acceptance. Functional barriers, like use, value and risk.
And psychological barriers, like tradition and image. Other factor
like use patterns and information availability have also been associated with the acceptance/resistance of innovation (see Kleijnen,
Lee, & Wetzels, 2009 for a review of current models of innovation
acceptance). In short, the way people accommodate innovation in
their lives is the result of a complex set of representations about
usefulness, habit, risk and social norms (Young, Hawkins, & Sharlin,
2009). Social robots, as pointed earlier, represent a clear departure
from contemporary conceptions of technology, thus are potential
generators of uncertainty and anxiety.
Review of previous studies: the growing presence of robots outside of research and industrial facilities has drawn the interest of
researchers to the general public and casual user’s opinion and perception of, not only the robot per se, but also about what robots
could and should do. This question has been tackled using both
quantitative and qualitative methods. The following lines draw a
brief sketch of the results of this research.
Surveys on the opinion about robots show a neutral to positive image of robots (Arras & Cerqui, 2005; Ray, Mondada, &
Siegwart, 2008) and technology (Scopelliti, Giuliani, & Fornara,
2005). Although older participants considered technology more
difficult to use than young and adult participants, they thought
it would contribute more to their independence than the other
participants (Arras & Cerqui, 2005; Scopelliti et al., 2005). This positive assistive role of robots is clearly separated from the idea of
a robot friend or companion and from the idea that robots can
contribute to an increase in personal happiness (Arras & Cerqui,
2005; Dautenhahn et al., 2005). In spite of this positive opinion, a
percentage of the participants signaled their discomfort with the
prospect of robots performing all the work in the future (Arras
& Cerqui, 2005) and associated the idea of robots with job loss,
danger, lack of trust, or inhumanity (Ray, Mondada, & Siegwart,
2008).
There is a clear preference for the use of robots in practical
applications, like household tasks (e.g. vacuum, window cleaning,
ironing), while discarding the use of robots in tasks that involve personal relations (e.g. babysitting, company, entertainment, animal
care) (Dautenhahn et al., 2005; Oestreicher & Eklundh, 2006; Ray
et al., 2008). Participants also stated preferring a preprogrammed
robot, to a more autonomous one (Oestreicher & Eklundh, 2006).

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

It should be noted however that these preferences might be influenced by factors like: the level of expertise and familiarity with
robotics or the level of physical disability and perceived health. Ju
and Takayama (2011) found that experts and non-experts differ in
terms of what they think robots should and should not do, with
experts showing a higher confidence in the capability of robots
to perform human tasks. Scopelliti et al. (2005) found an expectation gap for non-experts, who though that household tasks like
dusting are easier to implement then they are in fact, while at the
same time were unaware of robots’ capabilities in areas like home
safety control. Oestreicher and Eklundh’s (2006) findings showed
that participants with a lesser degree of disability viewed an assistive robot as a doer (performing tasks the user does not), while
participants with a high degree of disability viewed an assistive
robot as a facilitator, allowing them to regain some of the autonomy
lost. Cesta et al. (2007) found that elders who perceived themselves
as having better health, expressed more positive opinions about the
integration of a robot in the domestic environment, showed a more
positive emotional response and considered the robot less scary
and cumbersome. In terms of human–robot collaboration results
are inconclusive, with some studies suggesting that participants
prefer robots to perform jobs alongside humans (e.g. Takayama, Ju,
& Nass, 2008), while other studies suggest the opposite (e.g. Ju &
Takayama, 2011).
Regarding robot appearance, the majority of the participants
thought of robots as machine-like. The domestic/assistive robot
should be a small machine, able to communicate in a human-like
fashion, but should not have a zoomorphic or humanoid form (Arras
& Cerqui, 2005; Dautenhahn et al., 2005; Ray et al., 2008). Appearance may play an important role in the perception of the robot’s
capabilities and suitability for certain tasks. Participants presented
with images of robots attributed significantly more communication and emotion capabilities to human-like and animal-like robots
than to machine-like robots, but the same level of mobility and
information processing power (Lee, Lau, & Hong, 2011). Kamide,
Kawabe, Shigemi, and Arai (2013) analyzed the ratings of three
humanoid robots and found differences for gender and age group.
Female participants rated robots higher on familiarity than male.
Older male and female participants rated robots higher in humanness. Middle-age and old-age male participants give higher ratings
to humanoids than young-age and adolescents. Female participants
in the middle-age group rated utility of humanoids as higher.
Although the research results presented above provide already
a large set of very useful answers, little is still known about the
socio-cognitive processes underlying the laypersons understanding and expectations of what robots are, where they should operate
and their role in society. When confronted with uncertainty people
tend to draw on what is familiar in order to make sense of their
surroundings. As such, it is expectable that people will build their
opinions and knowledge about social robots based on what they
already know about current technologies. In order to explore this
dynamic process, this paper proposes the use of the framework
afforded by the social representations theory. The following lines
provide a brief sketch of the theory.

3. Defining social representation
When Serge Moscovici, in the early sixties, set forward the theory of social representations, he wanted to tackle the question of
how lay people in modern, ever changing, societies accommodated
the growing body of technical and scientific knowledge placed at
their disposal by the social media (radio shows, television and
newspapers), and turned it into something useful for their daily
life. In other words, he wanted to know how common knowledge is
formed, how individuals in social interaction, build theories about

279

social objects and thus make possible communication and the organization of behavior (Vala, 1993). The social representation is a form
of knowledge that aims to transform what is strange into something familiar, by anchoring novelty to already existing and stable
knowledge structures (Moscovici, 1961).
Social representations are a form of shared knowledge, allowing social actors (individuals and communities) to frame and act
on social objects. By presenting norms and prescriptions, they help
making sense of daily experience. They are a cultural, linguistic and
communicational phenomenon tightly connected to social structures. Their content and internal organization supposes a subject,
an object and a process of construction, expression, interpretation and symbolization. Social representations are a practical and
instrumental form of knowledge (Vala, 1993). In a certain sense,
social representations are a guide for action, since they include a
desirable course of action, they give meaning to the social object
and its context and they give meaning to behavior itself (Vala,
1993).
3.1. Dialectical dynamics: anchoring and objectification
Social representations integrate a cognitive and a social component. The cognitive component, which is the individual’s role
in actively appropriating and re-structuring reality, with the aim
of anchoring and stabilizing social objects. The social component,
which is the product of interactions, the social production of a
common reality by the group, with the aim of creating collective
objects and equilibrium (Abric, 1996). This appropriation is done by
a dialectical process of anchoring and objectification. Objectification is the process of turning an abstract knowledge into something
concrete. The available information is de-contextualized, selected,
simplified and organized in what is to be a new fact, turning it into a
frame for categorizing and interpreting new information. This new
frame of categorization is then given correspondence to a natural
reality. Anchoring works on one hand as a starting point to think
new objects, and on the other hand as the representation of the new
object that emerges from the process of objectification. Anchoring
is the process of integrating new information on the already existing system of categories and relations. As such, it will modulate
what and how, new information will be integrated in the already
existing network of meanings. “It generates a system of interpretation, it offers a framework for the determination of behaviors in
creating expectations, needs and anticipations” (Abric, 1996, p. 78).
3.2. The structural approach
According to Abric’s (1993) theory of the central nucleus, a social
representation is structurally composed of a central nucleus (or
central core) and a peripheral system. The central nucleus is made
of one (or several) elements of the representation, and is characterized by having the generative function of ascribing meaning and
organizing the elements of the representation (Guimelli, 1993). The
central nucleus is directly linked and determined by historical and
social conditions, being strongly marked by the group’s system of
norms. It is consensual and collectively shared by a social group.
It is stable, coherent and resistant to change. It gives the representation a sense of continuity and consistency. It is in a certain
way independent from the immediate social context (Abric, 1993).
This central core structures the meaning of the whole representation, including the peripheral elements. It is a necessary condition
for the representation’s role as a meaning making tool. From a
behavioral standpoint, the central nucleus plays a central role in
the organization of values, attitudes and actions (Abric, 2003).
While the central core is normative, the peripheral system
is functional, grounding the representation on reality. “It is the
peripheral elements which can withstand the variations between

280

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

individuals, between subgroups, and over time” (Flament, 1994,
p. 7). The peripheral system’s role is turning the central core norms
and prescriptions into concrete courses of action, answering to
concrete daily challenges. To do so, the peripheral system is sensitive and determined by context, showing flexibility and accepting
contradictions. Given these characteristics, the peripheral system
serves a regulatory function in the adaptation of central core norms
to new situations. It functions as a buffer, absorbing new information and events that challenge the core prescriptions of the
representation, serving as a protection mechanism. This flexibility also allows for individual differences and creativity, integrating
personal experiences and history in individualized social representations, but keeping them organized around the central core shared
by the social group. From the interplay of this dual structure, central core and peripheral system, emerges the social representation
apparently incongruent character, at once stable and fluid, consensual but marked by inter-individual differences.
The presence of conflicting ideas and practices can result in several outcomes for the social representation (Abric, 1993): if the
situation is perceived as reversible, the transformation is limited
to the peripheral elements of the representation (the core remains
unchanged) and limited in time. If the situation is perceived as
irreversible, the results can be, a resistance to transformation,
through rationalization and latter explanation of the facts; a gradual transformation, if the new facts are not in total disagreement
with the central nucleus norms; or a total rupture, questioning the
prescriptions of the central nucleus, leading to its change and the
emergence of a new social representation, in line with the new
facts.

Table 1
Socio-demographic characteristics of the participants in study 1.

3.3. Social representations and behavior

5. Method

Social representations play a role in the creation of expectations
and needs (Abric, 1996), in communicating and organizing behaviors (Vala, 1993). As such, it is reasonable to expect them to play a
role in individual behaviors. This hypothesis has received empirical
support. Guimelli (1993), for example, reports the effect of individual representations, in nursing student’s choice of wanting to work
in the public or private health systems. After looking at the students’
representation of the nurse’s job, it become clear that their choice
of future work place, was the result of the students’ perception of
which of those two options, public or private sector, allowed them
better to fulfill what they though (social representation) where the
nurse’s function. More recently, Gomes and Nunes (2011) argued
for a relation between the social representation of sex, as portrayed
in newspapers and magazines, and an inconsistent use of condoms.
Apostolidis and Dany (2012) studied how the social representation
of risk informed health practices regarding AIDS and psychoactive
substance use.
Research also suggests that the social representation operates
differently according to the relation the person entails with the
social object. Moliner and Gutermann (2004) found that depending on the kind of relation that the person established with the
social object (i.e., deviating people), the social representation would
take a descriptive role (when participants had little to no contact
with the social object), or an explanatory role (when participants
had frequent contact with the social object). Salès-Wuillemin et al.
(2011) studied how the social representation of hospital hygiene
changed from student nurses to professional nurses, showing how
professional training and common knowledge intertwine. In a similar vein, Gangl, Kastlunger, Kirchler, and Voracek (2012) compared
experts and laypeople’s social representation of the financial and
economic crisis. Lin, He, Jin, Tao, and Jiang (2013) on the other hand
focused on gender and health, identifying differences in the social
representation of pain, which lead to differential social expressions.

5.1. Participants

Study 1
Age
M
SD
Min–max
Not reported
Gender
Female
Male
Not reported
Years of school
Up to 9
Up to 12
University degree
Not reported

n = 212
34.01
12.58
19–69
16
128
76
8

Occupation
Student
Management, sales &
public service
Education & health
Engineering
Construction
Tourism
Unemployed
Other
Not reported

108
26
9

8
26
26
5
4

67
23
116
6

4. Objectives and overview of the research
This study aims to determine the social representation of robot
in a sample of Portuguese adults in order to understand how the
concept of social robot will fit it (or misfit). Following a structural
approach, a four-quadrant diagram was constructed to identify the
candidates to the central nucleus and the periphery of the social
representation. A similitude analyses was conducted to identify the
relations between the elements of the social representation. The
social representation of robot was further analyzed by gender, age
and years of schooling.

The convenience sample is composed of 212 Portuguese participants (128 women and 76 men; 8 not reported). Data was collected
in the University of the Algarve, Gambelas campus, and at an adult
education center in the district of Faro. Table 1 shows the sociodemographic characteristics of the participants.
5.2. Material and procedure
The method used to collect data was free evocation (Rouquette
& Rateau, 1998), with participants receiving the following instructions: “Please write the ideas (names, adjectives. . .) that pop up
into your mind when you listen to the word robot. Use a line for
each idea.” No limit number of ideas was given. Participants where
only asked to write their evocations, as this kept the task simpler, allowing to circumvent the logistic constraints of collecting
data in different locations. The instructions were accompanied by
an explanation of the voluntary character of the participation, of
the confidentiality of the data and the explicit statement that they
could stop to respond whenever they wanted if they felt uncomfortable with the task.
6. Results
6.1. Coding
All data was transcribed to a spreadsheet in order to be prepared
for lexicographical analysis. Since some responses were given in the
form of a sentence, they were replaced by a word that summarized
the idea. If the sentence encompassed several ideas, several words
would be used in order to represent each of the ideas.

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

281

Table 2
Evocation frequency distribution.
Frequency

No. of words

Cumulative evocations

1
2
3
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
24
27
30
31
32
36
38
45
74
100

413
56
29
15
14
3
1
4
5
4
3
3
2
1
2
3
1
1
1
2
1
1
1
1
1
2
1
1
1
1
1

413
525
612
672
742
760
767
799
844
884
917
953
979
993
1025
1076
1094
1113
1133
1175
1197
1221
1248
1278
1309
1373
1409
1447
1492
1566
1666

Cumulative inversed
24.8%
31.5%
36.7%
40.3%
44.5%
45.6%
46.0%
48.0%
50.7%
53.1%
55.0%
57.2%
58.8%
59.6%
61.5%
64.6%
65.7%
66.8%
68.0%
70.5%
71.8%
73.3%
74.9%
76.7%
78.6%
82.4%
84.6%
86.9%
89.6%
94.0%
100.0%

1666
1253
1141
1054
994
924
906
899
867
822
782
749
713
687
673
641
590
572
553
533
491
469
445
418
388
357
293
257
219
174
100

100.0%
75.2%
68.5%
63.3%
59.7%
55.5%
54.4%
54.0%
52.0%
49.3%
46.9%
45.0%
42.8%
41.2%
40.4%
38.5%
35.4%
34.3%
33.2%
32.0%
29.5%
28.2%
26.7%
25.1%
23.3%
21.4%
17.6%
15.4%
13.1%
10.4%
6.0%

Minimum frequency and mean frequency in bold.

6.2. Lexicographical analyses of the social representation of robot
The lexicon for this study is composed of a total of 1666 words,
with 581 unique occurrences. It was built following Vergès, Scano,
and Junique (2002) recommendations. On average, participants
evoked 7.74 words (SD = 4.63). The number of evocations varied
between 1 and 22.
Evocations were organized by frequency and evocation order, in
a four-quadrant diagram, which allows the identification of what
ideas are central to the social representation and what ideas compose the peripheral system (Abric, 2003; Vergès, 1992; for a review
of other methods see Moliner & Guimelli, 2015).
In order to conduct a lexicographical analysis, three values must
be determined: mean frequency, minimum frequency and mean
order. Mean frequency and minimum frequency were calculated
through the analysis of the frequency distribution of the evocations
(see Vergès et al., 2002). The frequency table allows the identification of three distribution zones:
• many words and very low evocation frequency (e.g. 419 words
are present only 1 time in the lexicon);
• few words and low evocation frequency (e.g. 4 words are present
8 times in the lexicon);
• few words and high evocation frequency (e.g. 1 word is present
26 times in the lexicon).
Minimum frequency was considered 6, which represents the
point where word frequency changes from many words and very
low evocation to few words and low evocation. Mean frequency
was considered 13, which represents the point where word frequency changes from few words and low evocation to few words
and high evocation frequency. Literature on social representations
(e.g. Dany, Urdapilleta, & Lo Monaco, 2015) suggests the use of 2.5
as the mean order. The data was analyzed using the software EVOC

2000 (Vergès et al., 2002). Table 2 shows the words frequency distribution and Table 3 shows the four-quadrant diagram representing
frequency and order of evocation.
6.2.1. Analysis of the candidates to the central nucleus
According to Vergès, Tyszka, and Vergès (1994), the elements
of the central nucleus display two features: consensuality and easiness of recall. That is, if people are asked what their ideas about
robots are, the ideas pertaining to the central nucleus would be
those with a recollection rate above the average of the ideas recalled
(consensus) and a recollection order below the average recollection
order of the ideas recalled (evocation readiness).
In the four-quadrant diagram the ideas more likely to pertain
to the central nucleus are represented in the superior left quadrant (see Table 3). In this quadrant, machine is the idea with the
highest frequency (100) and lowest rank order (1.9). That is, when
participants are asked about the word robot, the idea of machine
is not only the most evoked, but is also the one invoked first more
frequently. The idea of machine is accompanied by the idea of automatic. It should be noted however that despite being among the
easily evoked ideas (order = 2.4), automatic may not be a very consensual idea given its evocation frequency (19).
In brief, the word robot evokes an idea of a machine that performs by itself, that is, automatic.
6.2.2. Analysis of the candidates to the first periphery
The upper right quadrant of the diagram is called the first
periphery (Abric, 2003; Vergès, 1992). The words presented here,
although having a frequency above the mean frequency, are ranked
below the mean order. Even though these elements are peripheral
in the representation, they keep a close connection to the central nucleus, and function as a buffer to external threats (Abric,
1993). That is, they serve a regulatory function, adapting central
core norms not only to daily but also new situations, absorbing new

282

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

Table 3
The four-quadrant diagram representing frequency and order of evocation.
Frequency ≥ 13
Mean order < 2.5
Central nucleus
Machine
Automatic

Frequency < 13
Mean order < 2.5

Frequency

Order

100
19

1.9
2.4

Frequency

Order

Contrast zone

information and events even when they contradict the consensual
nucleus elements.
The ideas identified in the first periphery, present a more concrete vision of what a robot (the machine) can be. A quick read
through the list of ideas evoked shows words related to the material
used to build it, capabilities, usefulness and socio-economic impact.
The upper right quadrant depicts robots as: a technology, derived
from artificial intelligence, electronics, programming and computers.
The work of science and innovation. An evolution, the future. Something that will help, facilitate chores and replace men in some tasks.
Industrial robots, domestic robots, entertainment robots (puppets)
are examples. Despite this futuristic view, the idea of robot still
evokes images somewhat related to the industrial age like mechanization, metal and mechanical.
The socio-economic effects of the deployment of robots is also
present in the evoked ideas, namely through the idea of unemployment. However, it is not clear how this is related to ideas like

Frequency ≥ 13
Mean order ≥ 2.5
First periphery
Technology
Future
Help
Metal
Artificial intelligence
Replaces men
Industrial robot
Mechanical
Movies
Domestic robot
Science
Unemployment
Evolution
Facilitates
Intelligent
Puppet
Computer
Electronics
Innovation
Without feelings
Mechanization
Programming
Robocop
Frequency < 13
Mean order ≥ 2.5
Second periphery
Toy
Iron
Robotics
Fiction
Invention
Fast
Artificial
Grey
Electrical
Useful
Autonomous
Development
Entertainment
I robot
Information technology
Improvement
Space
Humanoid
Japan
Tin can
Domination
Parts
Star wars

Frequency

Order

74
45
38
36
32
32
31
30
27
24
22
21
21
20
18
17
17
17
16
16
14
13
13

3.9
4.9
5.0
4.0
4.3
5.0
5.0
3.6
6.7
4.7
6.4
6.4
5.9
4.1
3.3
3.0
5.5
6.1
6.8
6.2
3.7
6.4
6.4

Frequency

Order

12
12
12
11
11
11
10
10
10
10
9
9
9
9
9
8
8
8
8
7
6
6
6

4.4
4.8
5.5
6.0
6.8
4.6
3.0
5.4
5.5
4.0
5.0
5.3
6.2
7.4
6.1
8.4
5.6
7.6
8.0
4.9
13.2
7.5
4.0

replacement of men, help or mechanization, since these ideas seem
to be equated with replacement of men in unpleasant or dangerous
tasks.
Interestingly, the concept of robot seems to evoke the age old
dichotomy between reason (intelligent) and emotion (without feelings), thus underlining one of the tenets of the social representation
theory, that is, how the old is used to make sense of the new
(Moscovici, 1961). This however contrasts with the current trend
in technology towards the humanization of interfaces.
Finally, the significant contribution of popular culture for the
construction of social representations is also present through the
association of the idea of robot with that of movies and robocop. This
suggests the major role popular culture plays, molding promises
and perils people associate with a future populated by robots. Curiously, the pop culture icon more frequently evoked is robocop, a
cyborg police agent that is in clear contrast with the idea of the
robot machine present in the first quadrant.

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

By definition, the first periphery plays an important role both in
maintaining the nucleus stability and in accommodating new and
unfamiliar objects. This is visible in the diverse and contrasting
set of ideas presented here, where ideas like artificial intelligence
and mechanical are set side-by-side. If on the one hand the general idea of machine is prevalent in the evoked ideas, on the other
hand the popular icon most evoked is that of a cyborg, part men,
part machine, torn apart by his ambiguous nature. In short, the
idea of machine accommodates to a wide range of meanings and
embodiments.
In spite of the presence of the idea of unemployment, the evoked
ideas present a positive view of robots as helpers, replacing men in
hard tasks, providing an evolution relative to prior technologies.
6.2.3. Analysis of the candidates to the contrast zone and the
second periphery
The lower left quadrant of the diagram is called the contrast
zone (Abric, 2003; Vergès, 1992). The words present in this quadrant have an order of evocation above the mean order of evocation,
but their evocation frequency is lower than the mean frequency
of evocation. The contrast zone sometimes reveals complementary
ideas or the presence of a subgroup with a different social representation (Abric, 2003; Vergès, 1992). This research did not identify any
ideas pertaining to this quadrant. This absence reinforces the consensual character of the ideas present in the first quadrant (upper
left quadrant).
The lower right of the diagram is composed of words with a
frequency and an evocation order bellow the mean evocation and
mean order. These are the more peripheral elements of the representation and they constitute the second periphery (Abric, 2003;
Vergès, 1992). Among the ideas found in the lower right quadrant there are references to the technological aspects of robots
(e.g. robotics, electrical, artificial, autonomous), its social impact (e.g.
useful, development, improvement) and its ludic character (e.g. entertainment, toy, fiction, I robot, star wars). Despite their low frequency
and recall order, it is interesting to note that these ideas are still
within the framework provided by the first periphery, representing
cases of more general ideas or concepts.
6.2.4. Synthesis of the representation
Analysis of the four-quadrant diagram shows the idea of
machine as a strong candidate to the central nucleus of the social
representation. Although the idea of automatic is also present in
the upper left quadrant, it presents a lower frequency than some
words of the first periphery. That is, although the idea of automatic
is easy to recall, ideas like technology or future are more frequently
recalled.
The ideas pertaining to the first periphery can be roughly organized around robot characteristics (e.g. technology, metal, artificial
intelligence, electronics), social consequences (e.g. help, facilitates,
replaces men, unemployment) and time of deployment (future).
Like it is proposed by the structural model of social representations (Abric, 1993; Moliner & Guimelli, 2015), the first periphery
proposes concrete embodiments for the concept of robot, while
allowing the co-occurrence of contradictory representations like
the high-tech machine (e.g. artificial intelligence, programming,
innovation) vs. the old industrial machine (e.g. mechanization,
mechanical, metal), or the helpful machine (e.g. help, facilitates,
replaces men, evolution) vs. the disruptive machine (e.g. unemployment).
In short, if on one hand, the idea of robot as a machine is consensual, on the other, there is plenty of room for diversity in terms of
embodiment and competences expected, with the co-occurrence
of several robot “models” (e.g. industrial robot, domestic robot, robocop). However, it should be noted that that this diversity occurs
within the framework of machine. A machine which is intelligent

283

but without feelings. This is at odds with the current trend toward
social interfaces and social robots.
6.3. Similitude analysis of the social representation of robot
Central to the structural approach to social representations is
the notion that meaning derives, not from its elements alone, but
from their organization. As such, besides identifying what are the
composing elements of the representation, a second step is necessary, studying how these elements are interconnected and what
meaning emerges from these relations (Rouquette & Rateau, 1998).
This can be accomplish using the similitude analysis. This is a technique derived from graph theory (see Degenne & Vergès, 1973 for
a description), which allows the study of the interrelations of the
elements composing a social representation. With it, is possible to
display graphically the organization of these elements, in what is
called the maximum tree (i.e., l’arbre maximum; Degenne & Vergès,
1973). In this representation, the vertices are occupied by the words
pertaining to the representation. These vertices are connected by
edges that indicate the degree of connection between these words.
This allows seeing which ideas have more connections, how strong
they are and if words connect in such a way as to give rise to new
ideas (Degenne & Vergès, 1973), thus providing a more dynamic
view the social representation’s structure.
For the purpose of this study, the ideas identified as candidates
to the central nucleus and the first periphery where organized
into 25 categories and then analyzed with the software SIMI 2000
(Junique, Barbry, Scano, Zeliger, & Vergès, 2002). Fig. 1 shows the
results. The ticker the line, the stronger the relation between the
ideas (see Vergès, 2001).
The representation of robot is organized around the nodes of
technology and future. The idea of technology is connected to science, machine, artificial intelligence, help and innovation. The idea of
machine is connected to that of computer. The idea of help is connected to facilitate and replaces men. Although the idea of machine
is still present, it lost the centrality it had in the analysis of the
quadrants. The similitude analysis of the social representation of
robot portrays it as a technology, which can help humans. Also significant is the strong relation between facilitates and replaces men.
The second organizational node of the tree is the idea of future.
This idea is connected to movies, evolution, electronics and industrial robot. Although given concrete uses (e.g., industrial, electronics
or movies) the robot is projected as something belonging to the
future. In short, robots are seen as the helping technology of the
future.
6.3.1. Comparison by socio-demographic characteristics
One of the characteristics of social representations is their ability to form a coherent whole, while allowing the development of
more individual and contextual representations. In order to better
understand these dynamics, the sample was split by gender, age
(two groups formed using the median, 32 years), and years of school
(two groups, up to 12 years of schooling and university degree or
frequency). The analysis used the same 25 categories as above.
6.3.1.1. Gender. Figs. 2 and 3 show the organization of the
representation for female and male participants. The social representation of robot in female participants (n = 128) is organized
around the nodes of technology and help (see Fig. 2). Technology is
connected to innovation, machine, science, evolution and future. Also
noteworthy is the strong relation between future and replaces men.
Although the role of technology is similar to what was found for
the total sample, the idea of help assumes a more central role in the
organization of the representation. This node presents two distinct
views of robot, the domestic robot and the puppet.

284

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

Fig. 1. Tree with the elements of the social representation of robot.

Fig. 2. Elements of the social representation of robot by female participants.

The male participant (n = 76) social representation is organized
around two nodes, artificial intelligence and help (see Fig. 3). Artificial intelligence is connected to programming, metal, industrial robot,
mechanical and future. The node of help is connected to movies,
machine, replaces men and unemployment. It is interesting to note
that concrete aspects of what is a robot (e.g. artificial intelligence)
assume a more central role in the organization of the male’s social
representation than in female’s representation. Also, unlike the
female social representation, the model of robot in the male representation is the industrial robot. Also noteworthy is the connection
between technology, unemployment and help, which suggests that

for the male participants the use of robots might have some negative social effects. This connection is not present in the female
representation.
The representation is gendered in the way that it reflects the
traditional gender roles, patriarchal norms and family dynamics.
Robots are for men a form of intelligence to be controlled and
mastered (programming) associated with work, while they are for
women technological tools to be used in a domestic context, and a
technology also seen in movies. Such results are in line with previous research on gender and technology. For example, it was shown
that males considered computers as an artefact to be mastered

Fig. 3. Elements of the social representation of robot by male participants.

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

285

Fig. 4. Elements of the social representation of robot by participants bellow 32 years of age.

whereas females considered computers as an instrumental tool to
complete a task (Morritt, 1997; Turkle, 1988). In other words, the
social representation of robots is associated to the classical patriarchal dichotomies in terms of economic roles (male breadwinner vs.
female homemaker), space (outside home/public sphere for men
vs. inside home/private sphere for women), agency (action, i.e.,
mastering for men, vs. passivity, i.e., passive use for women) and
masculine vs. feminine culture.

6.3.1.2. Comparison by age. For the comparison by age, the group
was divided using the median (32 years), resulting in two groups
with 98 participants each. The social representation of robot, for
the group aged bellow 32 years, is organized around the idea of
technology (see Fig. 4). Noteworthy is the diversity of ideas connected to technology, ranging from artificial intelligence to movies.
Once again the representation includes the idea of an intelligent
machine, an industrial robot that helps and replaces men in the
future.
For the group aged above 32 years, the representation of the
robot is organized around the nodes of help and future (see Fig. 5).
Help is connected with technology and unemployment, while future
is connected with computer, replaces men and evolution. Albeit
the idea of a technology that replaces men in some tasks is well
received by both groups (facilitates, evolution), it raises some concerns among the older participants (unemployment). It is interesting
to note that, while younger participants equate the idea of robot

with artificial intelligence, older participants view it as something
akin to computer.
Another characteristic of the subgroup, age above 32 years, is
that robots portrayed in movies or toys (puppets) are considered
apart from those of real life.

6.3.2. Comparison by years of schooling
For the comparison by years of schooling, the group was divided
in two groups, up to 12 years of schooling (n = 90) and university
degree (n = 116). For the first group, the social representation is
organized around the node of help (see Fig. 6). Help is connected
with intelligent, future, technology and puppet. Two main ideas of
robot can be identified, the industrial robot and the robots from
science fiction movies.
The representation for the subgroup university degree, is
organized around the node technology, with artificial intelligence
forming a second node (see Fig. 7). The idea of help is also present,
but is not central. The representation for this group is more complex, integrating diverse ideas like artificial intelligence, mechanical,
innovation and science. This means that this subgroup has more
ideas available to think about the effects robots will have in their
lives. Also noteworthy is the idea that robots are without feelings.
This idea is connected with that of machine and metal. It is not clear
the ontological significance of this attribution. Nonetheless, both a
lack of feelings derived from the robot’s mechanical nature, or its
opposition to what is considered to an inherently human trait, will

Fig. 5. Elements of the social representation of robot by participants above 32 years of age.

286

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

Fig. 6. Elements of the social representation of robot by participants up to 12 years of schooling.

Fig. 7. Elements of the social representation of robot by participants with university degree.

have an effect on the acceptance of robots in general, and social
robots in particular.
6.4. Synthesis of the similitude analysis
The similitude analysis provides a second step in the study of
social representations, allowing the study of the interrelations of
its elements. From this analysis surfaced a rearrangement of the
elements previously identified as candidates to the central nucleus
and the first periphery. The social representation of robot for the
total sample is organized around the nodes technology and future,
with the idea of machine losing the centrality previously identified.
In general, the robot is viewed as a technology, a machine (computer)
with artificial intelligence, an innovation brought by science. It helps
and facilitates work, replacing men. Robots are seen as a future event,
an evolution of electronics that will take the form of industrial robots.
This future with robots can already be seen in some movies. Finally,
robots are viewed as competent but emotionless machines.
The themes of technology, help and future are common to the
various subgroups studied, underlining the homogeneity of the
representation. Despite these common elements, the similitude
analysis displayed different structural organizations for the social
representation regarding gender, age and schooling years. A brief
description of these differences follows.
The male representation is organized around a concrete
characteristic of robot (artificial intelligence), while the female representation is organized around a vaguer idea (technology). They
also privilege different uses for robots, industrial in male’s representation, domestic in female’s representation. Although both

representations ascribe a central role to help, males show some
apparent concern with unemployment.
Participants aged bellow 32 organize their representation
around the idea of technology, while those aged above 32 organize
it around the ideas of help and future. Participants aged above 32
also show some concern with unemployment.
Besides organizing their social representations around different
nodes (help for participants up to 12 years, technology for participants with a university degree), these two subgroups also present
a different level organizational complexity.
It should be noted however, that these differences represent not
diverse conceptions of what robots are, but a focus of the participants on particular aspects of the social representation, which are
more relevant for their social contexts.
7. Discussion
The results presented above are in line with previous research.
In 1983, Argot et al., interviewed the workers of a plant during the
installation of a robotic unit. When prompted with the open question “How would you describe a robot to a friend?” the answers
were: mechanical man, preprogrammed machine, something that
loads machines, increases productivity or reduces manual work.
More recently, the results of the special eurobarometer 382, titled
“Public Attitudes Towards Robots” (TNS Opinion & Social, 2012), a
report that describes EU residents’ general attitude towards scientific discoveries, technology and robotics, presented a similar
panorama. Participants were shown a picture of an industrial robot
(an automated programmable arm filling boxes) and a picture of a

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

humanized home helping robot. They were then asked to rate how
much, each of the pictures fitted their image of a robot. Around
80% of the participants stated that the image of the industrial robot
fitted well with the image they had of robots, while 66% of the
participants stated that the image of the humanized home helping
robot fitted well with the image they had of robots. This suggests
that the image of the industrial robot, automated, programmable,
mechanical arm is still very pervasive amongst the layperson. In
the case of Portugal, the gap was smaller with 64% of the participants stating that the industrial robot fitted well their image of
robot and 55% stating that the humanized home helping robot fitted well their image of robot. In short, the present results confirm
that, in Portugal, the idea of the robot as an industrial, mechanical,
technology, is central. Since previous reports did not find significant
differences among European’s view of robots and technology (TNS
Opinion & Social, 2012), the results of this research may provide
a good starting point for a cross cultural exploration of the social
representation of robot. It is also noteworthy to point that, in more
than 30 years, in spite of all the technological developments, very
little seems to have changed in the way people perceive robots.
In spite of this apparent inertness, the dynamic process of objectification and anchoring is visible at work in the representation
of robot. Indeed, elements pertaining to diverse technologies (e.g.
computer) and contexts (e.g. industrial processes) are integrated
in the representation of robot. Drawing from a set of characteristics common to traditional machinery (e.g. metal, mechanical, fast)
and current technology (e.g. electronics, artificial intelligence) people built a shared representation of what a robot is. Drawing on
their conception of work, people built a shared representation of
what it does (help, facilitates, replaces men), and where it operates
(industrial and domestic robots). Also, the role of cultural icons portrayed by science fiction movies should not be overlooked in this
process.
Although it is not possible to anticipate what elements, if any,
of the social representation of robot will be used in the construction of the socially shared knowledge about social robots, these
elements will surely be anchored in daily practices. Indeed, the
social representation of robots is gendered and rooted in gendered
practices. Men and women’s everyday life practices (e.g., at work, at
home) are guided and controlled by social routines, schemas, conventions, norms, and ideologies associated to gender that prescribe
how men and women should make sense, experience and use technology. Actually, the present study showed that men associated
robots to workplace while women associated them with domestic
contexts. Moreover, although both genders perceived robots as a
helping technology, men perceived robots as a threat (i.e., replacing men and creating unemployment) while women associated
robots with help in a domestic context. Such results might indicate that women may accept more easily social robots than men,
and the laundry might be the first entry to social robots in our
daily life. First, women are still mainly responsible for the house
related tasks, and the introduction at home of social robots could
be seen as way to free women from domestic drudgery. Previous research has showed that “compared with men, the women
talked more explicitly about the importance of domestic technologies in their lives” and “described how technologies helped
them – with their chores, with childcare.” (Livingstone, 1992, p. 5).
Moreover, Carpenter Davis Erwin-Stewart Lee, Bransford, and Vye
(2009) showed that after viewing video clips presenting two exemplars of social robots that could be use at home, participants
reported that they could mainly be used for chores like washing
dishes, doing laundry, general cleaning, ironing clothes. Second,
women seem to use technology like gaming, computers and
social networks for social interaction more than men (e.g., Veltri,
Krasnova, Baumann, & Kalayamthanam, 2014). The fact that social
robots are programmed to communicate on a human mode may

287

facilitate their acceptance. For example, Carpenter et al. (2009)
showed that participants reported that socialness of social robots
(e.g., speech) would made easier their use. However, a new technology as social robots could be threatening and unfamiliar, especially
when it challenges a fundamental dimension of gender identity
and roles. Indeed, “technologies are represented as objects of identity projects – objects that may stabilize or de-stabilize hegemonic
representations of gender”. (Oudshoorn & Pinch, 2003, p. 10). For
example, Carpenter et al. (2009) reported that participants did not
want social robots to be used for childcare or companionship.
To sum up, first, given its role as organizers of knowledge,
the study of social representation uncovers not only the tendency
towards robots, but also what robots are, where they are and why
they are there. Participants in this study portray the robot as a
technology, a sort of machine with an artificial intelligence, an
innovation produced by science (what), deployed on industrial or
domestic settings (where), performing hard, dangerous and mundane tasks, helping, assisting and replacing men (why). Given this,
it can be said that there is a fairly positive social representation of
robots, as they are equated with technological progress and the pursuit of a “better life”. These results are also in line with the results
of previous research, including that conducted more than 30 years
ago.
Second, although the social representation of robot is quite consensual in terms of its components, there are clear organizational
differences within the subsamples studied. One example is the
connection between the ideas of replacement of men, help and
facilitates. If on the one hand, these are common themes for all
subsamples suggesting a positive view, on the other hand, in the
case of male participants and participants above 32 years, the ideas
of technology and help are connected with the idea of unemployment, which is per se a negative outcome. That is, if for participants
in general the robot is a welcomed help, for some participants it may
be a source of anxiety. Another example, is the subsample of participants with university degree, who describe the robot as a machine
without feelings. Thus, for these participants the notion of a social
robot may stir some resistance. Both examples are in line with the
results reported by Ray et al. (2008) that showed that, in spite of
a general positive view of robots, some participants showed concern with job loss, trust and inhumanity (absence of affection). This
underlines the need for further studies in this area.
Finally, if the layperson idea of robot did not change much in
the last 30 years, the same cannot be said about the robotic industry. This means there is a gap between the layperson expectations
and current trends in robotics research. While people still think
of a “high-tech” mechanical tool, something that will facilitate,
or replace them in unpleasant or dangerous tasks, the industry is
preparing the social robot. A robot that recognizes and expresses
emotions uses natural speech and engages in social interactions. A
robot that will take the role of an “high-tech” co-worker, a teacher,
a nurse, a companion. This expectation gap was also identified by
previous research, people expect from robots the performance of
practical daily tasks and a limited autonomy. And although people
mention preferring to communicate in a natural fashion, i.e. using
verbal instructions, they imagine future robots as small machines
that can be easily fitted in the house (Dautenhahn et al., 2005;
Oestreicher & Eklundh, 2006; Ray et al., 2008). The acceptance of
social robots will depend, not only on the efforts to narrow this
expectation gap, but also, on the understanding of how people make
sense of what is the meaning of work, help and replacement.

8. Further research
Although the similitude analysis allows the study of the interrelations between the elements of the social representation, further

288

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289

studies are necessary to confirm the structure of the social representation and the central nucleus (see Moliner & Guimelli, 2015 for
a review of methods).
The use of other evocation stimulus (e.g. different types of robot
and technologies), requesting evocations about the use of robots in
different professional and social settings (e.g. factory, warehouse,
hospital, school), or further exploring the social representation of
different social groups (e.g. unemployed, retired), and nationalities,
could bring further insights on the social representation dynamics
and structural organization.
The use of a longer timeframe could bring some insights on
the changes brought by the increasing presence of technology
and robots, to the social representation’s structural organization,
namely the buffer role of the first periphery. It could also allow
the application of a developmental outlook on the presence and
acceptance of robots.
Funding
This paper is financed by National Funds provided by
FCT-Foundation for Science and Technology through project
UID/SOC/04020/2013.
The study was conducted without any direct or indirect sources
of funding from organization or entity with financial interests in
robotics.
Disclosure of interest
The authors declare that they have no competing interest.
Acknowledgements
We would like to thank the two anonymous reviewers for their
suggestions and comments.
References
Abric, J.-C. (1993). Central system peripheral system: Their functions and
roles in the dynamics of social representations. Papers on Social Representations – Textes sur les représentations sociales, 2, 75–78 (Retrieved from
http://psych1.lse.ac.uk/psr/PSR1993/2 1993Abric.pdf)
Abric, J.-C. (1996). Specific processes of social representations. Papers on Social Representations – Textes sur les représentations sociales, 5, 77–80 (Retrieved from
http://psych1.lse.ac.uk/psr/PSR1996/5 1996Abric.pdf)
Abric, J.-C. (2003). La recherche du noyau central et de la zone muette des représentations sociales. In J.-C. Abric (Ed.), Méthodes d’études des représentations sociales
[Methods for studying social representations] (pp. 59–80). Ramonville SaintAgne: Erès.
Apostolidis, T., & Dany, L. (2012). Pensée sociale et risques dans le domaine de la
santé : le regard des représentations sociales [Social thought and risks in the
health field: The social representations perspective]. Psychologie franc¸aise, 57,
67–81. http://dx.doi.org/10.1016/j.psfr.2012.03.003
Argote, L., Goodman, P., & Schkade, D. (1983). The human side of robotics: How
workers react to a robot. Sloan Management Review, 24(3), 31–41.
Arras, K., & Cerqui, D. (2005). Do we want to share our lives and bodies with
robots? A 2000-people survey (Technical Report Nr. 0605-001). Autonomous
Systems Lab, Swiss Federal Institute of Technology, EPFL (Retrieved from
http://infoscience.epfl.ch/record/97585/files/SurveyPaperArrasCerqui.pdf)
Bagozzi, R., & Lee, K.-H. (1999). Consumer resistance to, and acceptance of, innovations. Advances in Consumer Research, 26, 218–225 (Retrieved from http://
www.acrwebsite.org/search/view-conference-proceedings.aspx?Id=7902)
BBC News. (2011). Robotic prison wardens to patrol South Korean prison. BBC News
(Retrieved from http://www.bbc.co.uk/news/technology-15893772)
Carpenter, J., Davis, J. M., Erwin-Stewart, N., Lee, R. L., Bransford, J. D., & Vye,
N. (2009). Gender representation and humanoid robots designed for domestic use. International Journal of Social Robotics, 1, 261–265. http://dx.doi.org/
10.1007/s12369-009-0016-4
Cesta, A., Cortellessa, G., Giuliani, M., Pecora, F., Scopelliti, M., & Tiberio, L.
(2007). Psychological implications of domestic assistive technology for the
elderly. PsychNology Journal, 5(3), 229–252 (Retrieved from http://psychnology.
org/File/PNJ5(3)/PSYCHNOLOGY JOURNAL 5 3 FULL.pdf#page=9)
Chao, G., & Kozlowski, S. (1986). Employee perceptions on the implementation of
robotic manufacturing technology. Journal of Applied Psychology, 71(1), 70–76.

Dany, L., Urdapilleta, I., & Lo Monaco, G. (2015). Free associations and
social representations: Some reflections on rank-frequency and importancefrequency methods. Quality & Quantity, 49, 489–507. http://dx.doi.org/10.1007/
s11135-014-0005-z
Dautenhahn, K., Woods, S., Kaouri, C., Walters, M., Koay, K., & Werry, I.
(2005). What is a robot companion – friend, assistant or butler? In IROS’05,
International conference on intelligent robots and systems (pp. 1192–1197).
http://dx.doi.org/10.1109/IROS.2005.1545189
Degenne, A., & Vergès, P. (1973). Introduction à l’analyse de similitude
[Introduction to similitude analysis]. Revue franc¸aise de sociologie, 14(4),
471–511.
Fagan, M., Neill, S., & Wooldridge, B. (2003). An empirical investigation into the
relationship between computer self-efficacy, anxiety, experience, support and
usage. Journal of Computer Information Systems, 44, 95–104 (Retrieved from
http://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1027&context=
mkt fac)
Flament, C. (1994). Consensus, salience and necessity in social representations – Technical note. Papers on Social Representations – Textes sur les
représentations sociales, 3, 1–9 (Retrieved from http://www.psych.lse.ac.uk/psr/)
Fong, T., Nourbakhsh, I., & Dautenhahn, K. (2003). A survey of socially interactive robots. Robotics and Autonomous Systems, 42(3–4), 143–166. http://dx.doi.
org/10.1016/s0921-8890(02)00372-x
Gangl, K., Kastlunger, B., Kirchler, E., & Voracek, M. (2012). Confidence in the
economy in times of crisis: Social representations of experts and laypeople. The Journal of Socio-Economics, 41(5), 603–614. http://dx.doi.org/10.1016/
j.socec.2012.05.018
Gomes, A., & Nunes, C. (2011). Representac¸ão Social do Sexo nas Revistas e
Jornais Portugueses [Social representation of sex in portuguese newspappers and magazines]. Revista Interamericana de Psicología – Interamerican
Journal of Psychology, 45(1), 11–19 (Retrieved from http://www.redalyc.org/
articulo.oa?id=28421134003)
Guimelli, C. (1993). Locating the central core of social representations:
Towards a method. European Journal of Social Psychology, 23(5), 555–559.
http://dx.doi.org/10.1002/ejsp.2420230511
Hegel, F., Muhl, C., Wrede, B., Hielscher-Fastabend, M., & Sagerer, G. (2009).
Understanding social robots. In Second International conferences on advances
in computer-human interactions, ACHI’09 (pp. 169–174). http://dx.doi.org/
10.1109/ACHI.2009.51
Jodelet, D. (1984). Représentation sociale : phénomènes, concept et théorie [Social
representation: Phenomena, concept and theory]. In S. Moscovici (Ed.), Psychologie sociale (pp. 357–378). Paris: PUF.
Jodelet, D. (1989). Représentation sociale : un domaine en expansion [Social representations: An expanding domain]. In D. Jodelet (Ed.), Les représentation sociales
(pp. 31–61). Paris: PUF.
Ju, W., & Takayama, L. (2011). Should robots or people do these jobs? A survey of
robotics experts and non-experts about which jobs robots should do. In IROS’11,
International conference on intelligent robots and systems (pp. 2452–2459).
http://dx.doi.org/10.1109/IROS.2011.6094759
Junique, C., Barbry, W., Scano, S., Zeliger, R., & Vergès, P. (2002). (Bundle of programmes for the similitude analysis of questionnaires and numerical data
SIMI2000 (manual)) Ensembles de programmes permettant l’analyse de similitude
de questionnaires et de données numériques SIMI2000 (manuel.
Kamide, H., Kawabe, K., Shigemi, S., & Arai, T. (2013). Development of a psychological scale for general impressions of humanoid. Advanced Robotics, 27(1), 3–17.
http://dx.doi.org/10.1080/01691864.2013.751159
Kleijnen, M., Lee, N., & Wetzels, M. (2009). An exploration of consumer resistance to
innovation and its antecedents. Journal of Economic Psychology, 30(3), 344–357.
http://dx.doi.org/10.1016/j.joep.2009.02.004
Lee, M., Forlizzi, J., Rybski, P., Crabbe, F., Chung, W., Finkle, J., et al. (2009). The snackbot: Documenting the design of a robot for long-term human–robot interaction.
In 4th ACM/IEEE International conference on human–robot interaction (HRI) (pp.
7–14). http://dx.doi.org/10.1145/1514095.1514100
Lee, S.-L., Lau, I., & Hong, Y.-Y. (2011). Effects of appearance and functions on
likability and perceived occupational suitability of robots. Journal of Cognitive Engineering and Decision Making, 5(2), 232–250. http://dx.doi.org/10.1177/
1555343411409829
Lin, F., He, D., Jin, Y., Tao, Y., & Jiang, Z. (2013). Mapping the central structure
core in social representation of pain. Journal of Applied Social Psychology, 43(9),
1931–1945. http://dx.doi.org/10.1111/jasp.12135
Livingstone, S. (1992). The meaning of domestic technologies: A personal construct
analysis of familial gender relations. In R. Silverstone, & E. Hirsch (Eds.), Consuming technologies. London: Routledge. ISBN 9780415069908Oudshoorn & Pinch,
2003.
Moliner, P., & Guimelli, C. (2015). (Social representations) Les représentation sociales.
Grenoble: Presses universitaires de Grenoble.
Moliner, P., & Gutermann, M. (2004). Dynamique des descriptions et des
explications dans une répresentation sociale. Papers on Social Representations – Textes sur les représentations sociales, 13, 2.1–2.12. Retrieved from
http://www.psr.jku.at/PSR2004/13 02Mol.pdf
Morritt, H. (1997). Women and computer based technologies: A feminist perspective.
Maryland, USA: University Press of America, Inc.
Moscovici, S. (1961). (Psychoanalysis, its image and its public) La psychanalyse son
image et son public. Paris: Presses Universitaires de France.
Mutlu, B., & Forlizzi, J. (2008). Robots in organizations: The role of workflow, social, and environmental factors in human–robot interaction. In
HRI’08, Proceedings of the 3rd ACM/IEEE International conference on human

N. Pic¸arra et al. / Revue européenne de psychologie appliquée 66 (2016) 277–289
robot interaction (pp. 287–294). Retrieved from http://repository.cmu.edu/cgi/
viewcontent.cgi?article=1036&context=hcii
Nishio, S., Ishiguro, H., & Hagita, N. (2007). Geminoid: Teleoperated android of
an existing person. In C. Armando, & P. Filho (Eds.), Humanoid robots, new
developments (pp. 343–352). Vienna, Austria: I-Tech Education and Publishing
(Retrieved form http://cdn.intechopen.com/pdfs-wm/240.pdf)
Oestreicher, L., & Eklundh, K. (2006). User expectations on human–robot cooperation. In ROMAN’06, The 15th IEEE International symposium on robot
and human interactive communication (pp. 91–96). http://dx.doi.org/10.1109/
ROMAN.2006.314400
Oudshoorn, N., & Pinch, T. (2003). How users matter: The co-construction of users and
technologies. Cambridge/MA, London: The MIT Press.
Pic¸arra, N., Giger, J.-C., Pochwatko, G., & Gonc¸alves, G. (2015). Validation of the
Portuguese version of the Negative Attitudes towards Robots Scale. European
Review of Applied Psychology – Revue européenne de psychologie appliquée, 65,
93–104.
Ram, S. (1987). A model of innovation resistance. Advances in Consumer
Research, 14(1), 208–212 (Retrieved from http://www.acrwebsite.org/search/
view-conference-proceedings.aspx?Id=6688)
Ram, S., & Sheth, J. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5–14.
http://dx.doi.org/10.1108/EUM0000000002542
Ray, C., Mondada, F., & Siegwart, R. (2008). What do people expect from robots?
In IROS’08, International conference on intelligent robots and systems (pp.
3816–3821) (Retrieved from http://infoscience.epfl.ch/record/125291/files/
iros08 ray final-10.pdf)
Rindova, V., & Petkova, A. (2007). When is a new thing a good thing? Technological
change, product form design, and perceptions of value for product innovations.
Organization Science, 18(2), 217–232. http://dx.doi.org/10.1287/orsc.1060.0233
Rogers. (1983). Diffusion of innovations (3rd edition). New York: Free Press.
Rouquette, M.-L., & Rateau, P. (1998). (An introduction to the study of social representations) Introduction à l’étude des représentations sociales. Grenoble: Presses
universitaires de Grenoble.
Sabanovic, S. (2010). Robots in society, society in robots. Mutual shaping of society
and technology as a framework for social robot design. International Journal of
Social Robotics, 2(4), 439–450. http://dx.doi.org/10.1007/s12369-010-0066-7
Salès-Wuillemin, E., Morlot, R., Fontaine, A., Pullin, W., Galand, C., Talon, D., et al.
(2011). Evolution of nurses’ social representations of hospital hygiene: From
training to practice. Revue européenne de psychologie appliquée, 61(1), 51–63.
http://dx.doi.org/10.1016/j.erap.2010.06.001
Scopelliti, M., Giuliani, M., & Fornara, F. (2005). Robots in a domestic setting: A psychological approach. Universal Access in the Information Society, 4(2), 146–155.
http://dx.doi.org/10.1007/s10209-005-0118-1
Shenkar, O. (1988). Robotics: A challenge for occupational psychology. Journal of
Occupational Psychology, 61, 103–112.

289

Sheth, J. (1981). Psychology of innovation resistance: The less developed concept
(LDC) in diffusion research. Research in Marketing, 4(3), 273–282 (Retrieved from
http://www.bus.emory.edu/jSheth/docs/Psychology%20of%20Innovation%20
Resistance.pdf)
Takayama, L., Ju, W., & Nass, C. (2008). Beyond dirty, dangerous and dull:
What everyday people think robots should do. In Proceedings of the 3rd
ACM/IEEE International conference on human robot interaction (pp. 25–32).
http://dx.doi.org/10.1145/1349822.1349827
TNS Opinion & Social. (2012). Public attitudes towards robots (Special Eurobarometer 382). European Commission (Retrieved from http://ec.europa.eu/
public opinion/index en.htm)
Turkle, S. (1988). Computational reticence: Why women fear the intimate machine.
In C. Kramarae (Ed.), Technology and women’s voices. London: Routledge and
Kegan Paul.
Turkle, S., Breazeal, C., Dasté, O., & Scassellati, B. (2006). Encounters with kismet
and cog: Children respond to relational artifacts. pp. 1–20. Digital Media: Transformations in human communication (Retrieved from http://scazlab.yale.edu/
publications/all-publications)
Vala, J. (1993). Representac¸ões sociais – para uma psicologia social do pensamento
social [Social representations – for a psychology of social thought]. In J. Vala, &
M. B. Monteiro (Eds.), Psicologia Social (pp. 353–384). Lisboa: Fundac¸ão Calouste
Gulbenkian.
Veltri, N. F., Krasnova, H., Baumann, A., & Kalayamthanam, N. (2014). Gender differences in online gaming: A literature review. In Conferences papers, Twentieth
Americas Conference on Information Systems.
Vergès, P. (1992). L’évocation de l’argent. Une méthode pour la définition du noyau
central d’une représentation [The evocation of money. A method for the identification of the central nucleus of a representation]. Bulletin de psychologie, 405(45),
203–209.
Vergès, P. (2001). L’analyse des représentations sociales par questionnaires [The
analysis of social representations using questionnaires]. Revue franc¸aise de sociologie, 42(3), 537–561. http://dx.doi.org/10.2307/3323032
Vergès, P., Scano, S., & Junique, C. (2002). (Bundle of programs for the analysis of evocations EVOC2000 (Manual)) Ensembles de programmes permettant l’analyse des
évocations EVOC2000 (Manuel). Aix-en-Provence: Université Aix-en-Provence.
Vergès, P., Tyszka, T., & Vergès, P. (1994). Noyau central, saillance et propriétés structurales. Papers on Social Representations – Textes sur les représentations sociales,
3, 3–12 (Retrieved from http://www.psych.lse.ac.uk/psr/)
Young, J. E., Hawkins, R., & Sharlin, E. (2009). Toward acceptable domestic robots:
Applying insights from social psychology. International Journal of Social Robotics,
1(1), 95–108. http://dx.doi.org/10.1007/s12369-008-0006-y
Young, J., Sung, J., Voida, A., Sharlin, E., Igarashi, T., Christensen, H., et al.
(2011). Evaluating human–robot interaction. Focusing on the holistic
interaction experience. International Journal of Social Robotics, 3, 53–67.
http://dx.doi.org/10.1007/s12369-010-0081-8


Documents similaires


Fichier PDF donner un sens aux robots sociaux 1
Fichier PDF towards robotics leadership an analysis
Fichier PDF laser kesim makinas
Fichier PDF robart fiber laser
Fichier PDF robart galvo lazer
Fichier PDF robart woodart galvo lazer


Sur le même sujet..