What Pronouns for Pepper? A Critical Review of Gender/ing in
Research
Katie Seaborn∗

Alexa FrankTokyo Institute of Technology
seaborn.k.aa@m.titech.ca.jp

Independent Scholara.frank93@yahoo.com

ABSTRACT
Gender/ing guides how we view ourselves, the world around us,
and each other—including non-humans. Critical voices have raised
the alarm about stereotyped gendering in the design of socially embodied artificial agents like voice assistants, conversational agents,
and robots. Yet, little is known about how this plays out in researchand to what extent. As a first step, we critically reviewed the caseof Pepper, a gender-ambiguous humanoid robot. We conducted asystematic review (n=75) involving meta-synthesis and content
analysis, examining how participants and researchers gendered
Pepper through stated and unstated signifiers and pronoun usage.
We found that ascriptions of Pepper’s gender were inconsistent,
limited, and at times discordant, with little evidence of conscious
gendering and some indication of researcher influence on participant gendering. We offer six challenges driving the state of affairs
and a practical framework coupled with a critical checklist for
centering gender in research on artificial agents.

CCS CONCEPTS• Human-centered computing → Human computer interaction(HCI); • Social and professional topics → User characteristics;
Gender.

KEYWORDS
Gender, Socially embodied artificial agents, Humanoid robots, Pepper, User perception
ACM Reference Format:
Katie Seaborn and Alexa Frank. 2022. What Pronouns for Pepper? A Critical
Review of Gender/ing in Research. In CHI Conference on Human Factors in
Computing Systems (CHI ’22), April 29–May 05, 2022, New Orleans, LA, USA.
ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3491102.3501996

1

INTRODUCTION

Within HCI and adjacent spaces, there has been a growing recognition that we must consider socially-constructed and situatedcharacteristics such as gender [4, 40, 111, 116], race [5, 97, 135], andtheir intersections [128] in design and research practice. This does
not just mean the platform being designed or studied and its users:
it also includes the creators, researchers, and other stakeholders
within the larger communities of practice. In other words, we needThis work is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike International 4.0 License.
CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA© 2022 Copyright held by the owner/author(s).
ACM ISBN 978-1-4503-9157-3/22/04.
https://doi.org/10.1145/3491102.3501996

to turn the lens on ourselves, as well. This call is not new, especiallywithin HCI spaces. A decade ago, Bardzell wove together feminist
theory and interaction design practice under the heading of feminist HCI [4, 28]. She proposed two broad ways of how feminist
theory can enhance how we do HCI: through critique and throughaction. Yet, a recent 10-year review indicated a lack of genuine
follow-through within HCI [28]. The notion of feminism throughdesign (FtD) was summarily proposed, calling on researchers, practitioners, and educators to explicitly carry out feminist praxis in
HCI research [27]. Now that the tides have shifted again and new
calls are being made, we have a renewed impetus to do better.
One area in which a self-critical perspective may be necessary is
the study of socially embodied artificial agents. Such agents, ranging
from voice assistants like Apple’s Siri to humanoid robots like
Aldebaran-SoftBank’s Pepper, are often designed with humanlike
features. Of these, gender and the act of gendering, or the associationof gender with a person, place, or thing, has been recognized aseminent. Decades of research has shown that people tend to react
to even subtle gender cues in stereotyped ways, often without
realizing it [32, 34, 40, 54, 58, 93, 95, 111, 115, 118, 119, 127, 129,
134, 141, 145]. Humanoid robots, in particular, are designed to lookand feel human in form factor, clothing, voice, gestures, and soon. Yet, gender/ing is often overlooked in their design and study[96, 115, 116, 118, 127]. Gender tends to be arbitrarily prescribed byroboticists, who end up perpetuating the status quo [115]. Moreover,people tend to attribute gender even when robots are intended to begender neutral [34, 134]. On the research side, little is known about
how the academic community approaches gender/ing outside of
the studies in which it is the subject. Yet, we are surely not exempt
from the human tendency to gender our world, even if we are notaware of it. The implications are grave. Without acknowledging
gender/ing in research, we cannot know how and to what extent it
has influenced previous scholarship and is currently steering thecourse. As with race in “colour-evasiveness” [1, 97], we cannot be“gender-evasive” and disregard the issue. To do so is risky and raises
ethical questions about representation, inclusion, and reinforcing
known negative states of affair [95, 96, 116, 150]. Finally, without
confronting the issue of gender/ing in our midst head-on, we cannot
create a gender-sensitive path forward in the vital and evolving
field of human-agent interaction.
This work is a first step towards a more gender-conscious wayof doing and thinking in research on socially embodied intelligent
agents. The novelty of this work is its self-critical frame: looking
at ourselves and our own practice, as well as the experience ofparticipants. Our goal was to uncover how gender/ing has beentreated within research in the recent past—after sounding calls
could reasonably have been answered. To this end, we chose toanchor our work on Pepper (2014-21), a commercial humanoid robot
created by Aldebaran-SoftBank Robotics. We chose Pepper due toCHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

anecdotal evidence of ambiguity in ascriptions of its gender. For
instance, while its creators’ stated aims were for a gender neutral
robot [103, 134], official text materials1 clearly gender Pepper as
masculine, i.e., through the use of he/his pronouns. Yet, others
have chosen to not use Pepper based on their interpretation of its
gender as feminine (cf. [63]). Anecdotally, we have encountereddifferent takes on Pepper’s gender in conversations with roboticists,
technical experts, and the public. We started to ask, more seriously:
What gender is Pepper—how is it being gendered by people, andis there consensus? Followed closely by: Are we on the researchside aware of this phenomenon? Then, to the present work: Whatis the nature of this phenomenon, and how widespread is it within
our own circles? With these questions in mind, we conducted asystematic review of the literature on the social construction of
Pepper’s gender. We discuss our results with respect to the state ofgender sensitivity in HCI and beyond. While we used Pepper as acase study, at a high level, this work is relevant to research on anysocially embodied artificial agent. Our main contributions are:• Empirical evidence of unconscious gendering and diverse
ascriptions of gender to Pepper, derived from a corpus of patterns in participant and researcher (i.e., academics, designers,
practitioners, roboticists, etc.) data;• Initial evidence that researcher gendering influences participant gendering of Pepper;• A framework and critical checklist grounded in these findings and informed by critical theories and human-centered
design methods to guide theory and practice in the designand study of socially embodied agents.
We now turn to how gender/ing has been theorized across disciplines of study as well as within the context of HCI, and thenparticularly with respect to robotic agents like Pepper.

2 RELATED WORK
2.1 Conceptualizing Gender
Gender is a fundamental aspect of humanity: a universal facet ofmodern and historical cultures, and present as far back as records
allow us to see. But what is gender? The notion of gender is often
positioned against the notion of sex. While used analogously in thepast [68], these terms have been reimagined within gender studies, feminist theory, sociology, anthropology, and psychology asbased in a distinction between biology (sex) and culture (gender)[45, 68, 114]. Sex refers to the spectrum of visible and invisible physical markers in anatomy, typically associated with reproduction andpuberty. People can be male, female, or intersex, having ambiguous
characteristics [41]. Gender refers to the social and psychologicalside as situated within a given cultural context: how people identify(internally or personally), express themselves on the outside, e.g.,through mannerisms, clothes, etc. (presentation or expression), andare perceived by others (social perception). Typically, this is within abinary model of masculine and feminine. At a societal level, expectations about a person’s behavior, role in society, value, and so on
are socially constructed in relation to gender [45] in ways that are
dynamic, contested, policed, assumed, weaponized, restricted, subverted, and performed [19, 116]. Most people are assigned a gender
1 https://www.softbankrobotics.com/emea/en/pepper

Katie Seaborn and Alexa Frank

at birth in line with their visible sex characteristics, and then raisedin accordance with the dominant cultural views of that gender.
Those whose gender and sex align with societal expectations are
considered cisgender, while those who do not feel that their gender
identity matches their apparent sex may identify as transgender,
non-binary, genderqueer, or gender fluid [46, 65, 114]. There arealso recognized third genders, Two-Spirit [64], and agender people.
Notably, some have argued that in practice it can be difficult toseparate the biological from the cultural, leading to arguments for aframing of “gender/sex” [55]. Misgendering is a social phenomenon
that can occur when someone misreads another person’s gender [2].
This can happen purposely or not, for many reasons, but is based
in a person’s mental models and perceptions of outward gendercues and expressions that are themselves based on social gendernorms. In sum, both sex and gender are continuums, and arguablysocially constituted as well as socially situated.
In this work, we use the conceptualization of gender as a sociallysituated and constituted construct, with caveats. First, we recognizethat it can be difficult to untangle sex and gender [55, 82], similar
to how it can be difficult to untangle nature and nurture. Second,
pronoun usage is unreliable: “woman” may refer to gender and “female” may refer to sex, but in practice there is little standardization.
Third, researchers tend to collect gender and sex as a single variable,
without distinguishing between the two [29, 55]. Given that we use
self-reported demographics in HCI research, we will assume gender, i.e., the participant’s social identity, unless stated otherwise. A
further issue, however, is that researchers may not provide a range
of gender/sex options when collecting demographics [2]. This issomething that we will grapple with when discussing results basedon participant gender. However, robots do not have a sex, and theirgender identity, if any, is one-sided: up to users, roboticists, and researchers to assign [134]. Indeed, this will be a central issue in our attempts to understand how gender has been framed in the literature.

2.2

Gender/ing in and of Socially Embodied
Agents and Their Study

Gender/ing of technological artefacts is not a new concept. Decadesago, Harding [47] introduced the notion of gender as a symbolic quality of concepts and abstractions; for instance, gendered
metaphors and the gendering of concepts such as objectivity andsubjectivity. This idea was later extended to objects, especially
technological objects [12, 99]. Objects can be consciously or unconsciously gendered based on their properties or become genderedthrough use. For instance, a computer used for clerical work may
be gendered feminine because of symbolic and societal associationsof women with such work. Within HCI, seminal work by Nass,
Reeves, Moon, and colleagues has revealed that people tend to unknowingly attribute gender to computer voice when gender cues inpitch and timbre are present—and then react to their ascriptions ingender stereotyped ways [93, 112]. Later work confirmed many of
the same effects in scenarios with “bodied” agents like humanoid
robots [107, 108]. Following this, a body of work emerged in whichrobot gender/ing was directly considered, especially in terms ofgender stereotyping in robotic design and deployment: femininized
robots in home scenarios [20]; perceptions of agency (masculine)
and communalness/warmth (feminine) in facial cues [40], waistto-hip ratio [13]; hats [69]; uncanny reactions [102]; acceptance ofWhat Pronouns for Pepper? A Critical Review of Gender/ing in Research

help when coded feminine [77]; men donating more money to arobot coded feminine [132]; and occupation assignment [142]. Most
recently, the growing availability of conversational agents and voiceassistants has led to critiques of the standard “female by default”
vocal embodiments that reflect gendered ideas of women as subordinate [54, 129, 145]. In general, this work has confirmed stereotyped
gender/ing, with some exceptions (cf. [111]). Men compared to
women have been found to prefer robots more, with little known
for those of other genders [78, 92, 113, 126]. Also less explored arecultural differences in gender/ing. For instance, Robertson [116]reported on the case of Wakamaru, a robot with a form factor basedon traditional men’s clothing in Japan that resembles Western petticoats worn by women; subsequently, Japanese people tend togender Wakamaru masculine, while Westerners tend to gender it
feminine.2 In short, people attribute gender based on the design
and/or context of use of robots and other computer-based artificial
agents, and often in unconscious, stereotyped ways.
Virtually all of this work has focused on participants as users or
potential users. However, engineers and researchers are surely not
exempt [116, 134]. A trickle-down effect can occur, where genderis taken for granted based on societal models. In most cultures,“man/male” is the default, assumed when no other cues exist, andsometimes even when they do [6, 48, 127]. This “default setting”
then extends to choices in the design and study of socially embodied artificial agents like robots. For instance, Robertson [116]revealed the prevalence of gender stereotypes in Japanese robots,
which were gendered in ways that “effectively [reproduced] a sexist
division of gendered labor among humans and humanoids alike”[116]. Education, exposure, and community homogeneity also haveconsequences for approaches to gender [128, 138]. When working
with people of diverse gender identity, one is positioned to see
gender from new perspectives. When not, one may resort to limited models of gender, without realizing other options exist. Moreresearch is needed to map out how this has and continues to playout, especially its extent. Importantly, what little work exists has
so far focused on the creator side: engineers and roboticists. Afterall, it is not difficult to detect when the robot itself is evidence.
As practitioners, we can take on at least three orientations to gender/ing: we can remain unwitting, we can address it explicitly, or wecan choose to avoid it. This last point, a “gender-evasive” approach,means consciously choosing to avoid the matter of gender/ing
rather than engage with its complexities. But this runs the riskof reinforcing limited and harmful representations of gender that
may cascade back to people [136]. While the relationship between
sexist portrayals and attitudes, let alone behaviour, remains contentious, some compelling arguments for robots [136] and empiricalfindings for video game characters [7, 140] exist. Furthermore, thepossibility of enacting or enforcing negative associations based on
gender/ing needs to be considered against the availability of theagent. For example, Fessler [44] conducted a technical test on how
the predominant range of “feminine” voice assistants responded
to sexual harassment in 2017, which was later replicated by Chinand Robison [26] in 2020. In the first run, responses ranged from“flirtatious” to evasive: conscious and unconscious but no less sexist
2 Robertson goes on to describe Wakamaru’s shifting gender attribution by its makers,a case in reconstituting gender ascriptions within engineering praxis.

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

scripts that cast the feminine as sexualized and subservient. The
follow-up test indicated corrective redevelopment, with responses
ranging from dehumanizing the agent (“I’m code”), ignoring theprompt, and declining to respond. Still, while confronting sexism
may disrupt attitudes [85], ignoring or declining to respond may
not. Nevertheless, this work shows that confronting gender/ing isa step in the right direction.
Avoiding gender in pursuit of a tabula rasa or stateless, genderneutral humanoid robot may also not be possible. For the same
reasons others have argued that AI algorithms may always be biased, i.e., fairness may be unattainable [71], robots are created bypeople who live in a gendered world, and so they may always begendered [134]. Yet, we also live in a world where gender is socially constructed and robots are made: we thus have the power toconsciously construct robot bodies [116]. Over a decade ago, Rode[117] raised the possibility of other valid options brought in fromcritical gender studies, including non-binary genders, gender fluidity, and third genders. In fact, we can view robots as an opportunity
to explore new gender forms and expressions. This leaves room for“mechanical genders” [134] that may emerge as robots diverge fromhuman models. As Schiebinger proposed [127], we can promote a“virtuous circle” towards the prosocial goal of equality and recognition of gender diversity. We “. . . have the opportunity to intervenein this cultural cycle by creating hardware that promotes social
equality [..] helping users rethink gender norms and eventuallyreconfiguring gender norms” [127].
As yet, we know very little about how researchers have approached gender/ing. Gender/ing may take different forms within
research, reflecting the larger discourse outside of HCI spaces orpointing to disciplinary alternatives. In this sense, obtaining a better understanding of the state of affairs through the artefacts produced by researchers that are emblematic of their approach/es togender/ing—namely publications—is a crucial first step. Such a selfcritical positioning may be classified as reflexivity [117]. Reflexivity
typically involves critical and theory-driven engagement with researchers as social actors and research itself as a social phenomenon[15, 88, 117]. Since publications are largely text-based, we can use
the written word as data. Pronoun use and referents based on gendersignifiers (e.g., feminine) are clear textual indicators of gendering.
Analysis of such patterns in the language used by researchers inpublications can thus act as an unobtrusive, objective measure of
how gender/ing has been approached.
In short, gender/ing is an important factor to consider in our
research. Yet, despite a growing body of work on the participant oruser experience, as well as critiques of roboticists’ approaches togender/ing of robots, there is little known about the researcher’sside—our side. We argue that it is time to confront this issue by
taking a self-reflective stance: unmask how gendering has affected
our practice. We take a first step in this paper, using Pepper as a
guiding example.

3

METHODS

We conducted a systematic review [72, 131] to explore the role ofgender and gendering in the case of Pepper from both “our” (researchers, designers, engineers, roboticists, practitioners, etc.) andCHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

users’ perspectives. We used an adapted3 version of the PRISMA
checklist [81] to structure our process and reporting. Our study
selection flow chart can be found in Appendix 1 in the Supplementary Materials. We used a meta-synthesis approach [66], focusing
on integrating paper metadata, descriptive statistics, and qualitative findings. We supplemented this with directed content analysis[52, 76] of how gender was treated in-text by the authors as wellas in quotes from participants, focusing on pronoun usage anddescriptions of gender/ing. We did not use or register a protocol.
Our high-level research question was: How has gender/ing been
approached by researchers in research on Pepper? To answer it, we
focused on several sub-questions.
RQ1. What gender has Pepper been assigned by researchers (if any)?
Mapping out how researchers have gendered Pepper or avoided
gendering Pepper will reveal what gender model(s) have been used
as well as how Pepper’s gender, or lack thereof, has been ascribedby researchers.
RQ2. What gender has Pepper been assigned by participants (ifany)? Mapping out how participants’ gendering of Pepper can
provide insight on the extent to which participants and researchers
gender the same or differently. It can also answer the basic questionof what gender, if any, is most appropriate for Pepper in terms ofuser experience.
RQ3. Has there been a manipulation check on gender? Use ofa manipulation check is an indication of researcher’s awarenessof gender. It also provides more robust findings on participant
gendering of Pepper.
RQ4. What reasons (if any) are given by researchers for Pepper’s
gender? Researchers who are oriented towards addressing or explicitly avoiding gender may give their reasons for doing so. This
would provide a deep understanding of researcher approaches togender and how they relate to larger models of gender outside of
HCI spaces.
RQ5. What findings are there based on participant gender? Researchers’ approaches to gender can be revealed through choices
in research design, methods, measures, and data analysis based onparticipant gender. Additionally, what participant genders were accounted for—and which ones were not—can reveal researcher viewsof gender that would likely relate (in the trickle-down fashion) totheir views on Pepper’s gender/ing.
RQ6. What findings are there based on participant perception of
Pepper’s gender? As with RQ5, reporting of participant’s genderingof Pepper—ideally, how this data was collected—can reveal how researcher’s themselves approached gender. For instance, researchers
may provide a questionnaire with certain response options and notothers.
RQ7. Is there a relationship between participant and researcher
gendering? Researchers’ approaches to gender/ing may influenceparticipants’ orientations to Pepper’s gender/ing. Great similarities
may suggest influence or congruence, while divergence may indicate a lack of influence and greater level of gender consciousness.
Before outlining our methods in more detail, we will first introduce Pepper, the impetus for our study.

Katie Seaborn and Alexa Frank

3.1

Case Study: Pepper the Humanoid Robot

Pepper (Figure 1) is the spiritual successor of the Nao robot, a widely
available humanoid robot that has enjoyed a rich life in researchand child education [8]. Compared to Nao, Pepper is taller, sports
a tablet on its chest, and is described as “socially smarter,” i.e., hasmore sophisticated realtime processing of user-derived data. Unlike its predecessor, Pepper can recognize people and emotions byinterpreting faces4 . Like Nao, Pepper has been taken up as a tool
for research, as well as used outside of the academy, especially as astorefront greeter. As discussed, people seem to gender Pepper inwidely different ways. For example, Pepper has been gendered as a“young girl” when placed in the role of caretaker within societies
where caretaking work is othered and considered “less than,” andthus the domain of “anything other than white adult males” [86].
This and other divergent ascriptions of its gender inspired us toempirically explore how gendering plays out in robotics research5
with Pepper as a case study. Additionally, neither of us has conducted research on Pepper, allowing us to take on a more objective
view than we would be able to with robots familiar to us.

3.2

Eligibility Criteria

Any human subjects research on Pepper was included. In our firstsearch, we focused on the major engineering and/or computer science publication venues that cover human-robot interaction (CHI,
HRI, HAI, RO-MAN, etc.) using IEEE Xplore and ACM Digital Library. We then expanded our search to include venues from any
field by using Scopus and Web of Science. We excluded work that
did not include human subjects studies, that were proposals ofstudies, and that were gray literature. Distinctions were made to
maximize the papers that would include both researcher and participant perspectives. We limited results to work published within
and after 2015, the year that Pepper was first available.

3.3

Search Queries and Study Selection

We began with a search of the core databases (ACM Digital Library
and IEEE Xplore) on June 4, 2020. We used the following searchterms: “Pepper” and “robot” and (“sex” or “gender”). We removed
duplicates and papers that did not meet the eligibility criteria. We
then read the full text of each paper and removed all that did not explicitly use Pepper (i.e., Pepper as an example, cited for other work,etc.). We then used general databases (Scopus and Web of Science)
to search for other relevant work. We followed the same procedure
with the resulting papers as before. The databases, queries, andtotal results at each stage are presented in Appendix 1. On June 22,2020, we ended with a total of 75 papers.

3.4

Data Analysis

One author extracted all data relevant to the research questions.
This included: participant demographics (mean age, age ranges,
gender), researcher’s attribution of gender to Pepper, researchers’
reasons for this attribution, participants’ attribution of gender toPepper, study findings related to participant gender and Pepper’s
4 The extent to which Pepper can recognize emotions through facial expressions has

3 The PRISMA checklist is based on norms in medicine, so not all parts are relevant toa CHI paper. For instance, structured abstracts.

been debated [116].
5 For the sake of transparency and author self-disclosure [128], one of us is in HCI andthe other studies robots from cultural and literary perspectives.

What Pronouns for Pepper? A Critical Review of Gender/ing in Research

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

Figure 1: Pepper close-up (left) and at a storefront in Japan (right). Left photo by the first author and right photo by Lukas(@hauntedeyes), used under the free use license provided by Unsplash (https://unsplash.com).
perceived gender, and the presence or absence of a gender manipulation check for Pepper. Categories for assigning gender emerged
from the use of pronouns in the text, and thus the range of options
increased over the course of data extraction.
For the meta-synthesis, one author generated descriptive statistics for the quantitative variables: means, standard deviations,medians, and interquartile ranges. Quantification of the qualitative
data related to researchers’ and participants’ gendering of Pepper
as well as presence or absence of a gender manipulation check
was generated in the form of frequency counts and percentages toenable comparisons between the possible options per variable. Bothauthors then conducted three thematic analyses on researcher’sreasons for their attribution of Pepper’s gender as well as study
findings (divided by participant’s gender and Pepper’s perceived
gender). One generated a set of initial themes based on the researchquestions as per a typical directed thematic analysis process [17].
Then, both separately coded all of the three sets of qualitative data.
Cohen’s Kappa was calculated as a measure of inter-rater reliability;
the value for each of the included themes in all three sets of data
was .79 or above. Where possible, t-tests were used to compare
results.

4

FINDINGS

We now present the results from our analyses of the surveyed
papers. The full list of papers and their metadata is available inAppendix 2 in the Supplementary Materials.

4.1

Author and Participant Demographics

In 75 papers, there were 322 authors, 286 of which (89%) wereunique, i.e., had only one paper in the set of surveyed papers. Acrossall studies, there were a total of 3993 participants. The average ageof participants was 31.7 (STDEV = 14.4, MED = 27.9, IQR = 49.2),
with ages between 4 to 94 (a span of 90 years). 17 papers (22.7%)
did not report on age. 1810 men (45.3%) and 1599 women (40%)
participated, with 11 undeclared or attributed as “other” (0.3%);transgender, gender fluid, agender, and other genders were notreported. 14 papers (18.7%) did not report participant gender.

4.2

Researchers’ Gendering of Pepper (RQ1)

In most papers (47 or 63%), researchers attributed object gender
to Pepper, using the pronoun “it.” In 26 papers (35%), no gender
attribution was found; researchers used Pepper’s name or “therobot” instead of pronouns (e.g., [61, 87, 109]), or used multiple
robots and so avoided pronouns (e.g., [110]). In three cases, Pepper
was gendered feminine, in two cases masculine, and in one caseneutral. In some cases, assignment was enforced via gender cues
or by modifying Pepper; for instance, the authors of [38] renamed
Pepper as “Tina” so as to “contextualize its gender as female” (p.
244). In 4 cases (5%), researchers switched their use of pronouns:
two cases of feminine pronouns and object pronouns [37, 120],and two cases of masculine pronouns and object pronouns [21, 30].
Researchers did not consider Pepper’s gender in any of these cases.
Indeed, the authors of only 12 papers (16%) recognized and openly
discussed Pepper’s gender. Of these, the majority (8 out of 12)
referred to Pepper as an “it.” Of the rest, one attributed a neutral
gender to Pepper and the others avoided attribution. Non-textual
cues to Pepper’s gender could be present, but this was hard to
extract and confirm, especially in the face of conflicting evidence.
For instance, the authors of [80] used objective pronouns for Pepper,
but also compared Pepper to a virtual woman character and a real
woman. This suggests that they viewed Pepper as feminine or fluid,leaving interpretation of gender to comparison. In another case[130], Pepper was called a “semi-humanoid,” which could imply
that the authors believed that certain characteristics such as gender
do not apply to Pepper.

4.3

Participants’ Gendering of Pepper (RQ2)

In most papers (52 or 69%), participant attribution of Pepper’s gender was not available, i.e., direct quotes were not reported in the

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

paper. Of the rest (23 papers), 15 papers (65%) included object gendering, 13 papers (57%) included masculine gendering, 8 papers(35%) included feminine gendering, and 8 (35%) included neutral
gendering (e.g., use of “they” and “them” as a singular pronoun).
For example, in one paper [101]: “Pepper’s response was suddenly
delayed, so I thought he could not hear well” (p. 197). Just over half(57%) of papers included participants gendering Pepper differently,
e.g., one participant used object pronouns while another used feminine pronouns. For example, in one case [104], most participants
used object pronouns, but one used a neutral pronoun: “I don’t
like to be disrupted by them” (p. 8): perception of Pepper’s genderdepended on the participant. Notably, children as young as four
years old attributed gender to Pepper. For instance, in one paper[156], children used the masculine referents “sir” and “he.” Children
also asked if Pepper had a wife—an implicit masculine gender cue,given the above. It is possible that participants were influenced byresearchers’ use of pronouns for Pepper in these studies, which wecannot confirm using our methods.

4.4

Gender Manipulation Check (RQ3)

Only 6 (8%) papers reported on a manipulation check for Pepper’s
perceived gender. Put another way, 92% of papers did not report on(and we assume did not conduct) a manipulation check. Of thosethat did, most studies conducted a typical check: before the main
study, with participants. One study [18] involved a post-hoc checkwith only those participants who agreed with the researchers on
their own gendering of Pepper in various conditions; this of course
means that their results are not representative. Another study [102]involved researchers tasked with independently assigning genderto multiple robots, including Pepper, to build a consensus about
each robot’s perceived gender. When they could not agree, theresearchers assigned a “neutral” gender label, including to Pepper.
We point out that this use of “neutral” does not match most definitions of the word; more fitting labels could be “undetermined”
or “contested” or perhaps “fluid.” We will reveal more cases andcontinue to tease out issues in researchers’ reasons for gendering
Pepper next.

4.5

Researchers’ Reasons for Pepper’s Gender(RQ4)

The majority, a total of 50 or 67% of papers, did not discuss Pepper’s
gender. In 12 papers (16%), the authors acknowledged the issue ofgender but did not act on it; for example, by citing other work (e.g.,[24, 36, 91, 100]) or acknowledging gender as a factor for future
work (e.g., [31, 51]). 8 papers (11%) provided some kind of reasoning,but it was insufficient to understand their assignment of gender. For
instance, there were claims that the TTS used to produce Pepper’s
voice is childlike (e.g., [37, 57], with the implication that children do
not have gender or are gender-neutral (e.g., [89, 104]). Other reasonsvaried. For instance, the authors of [67] gave their robots “unfamiliar
male Hawaiian names ... to reduce possible gender biases” (p. 590)
without explaining how this would reduce, rather than introduce,
a male gender bias. In [23], the authors focused on “appearance,”
excluding gender as an aspect of appearance.
The authors of 7 papers (9%) noted that gender cues existed, butthere was a lack of consensus across papers about what gender/s

Katie Seaborn and Alexa Frankthose cues cued. One case [10] interpreted Pepper as gender neutral
and then explained participants’ gendering of Pepper as male as“probably related to its physical appearance, because participants
look at only a picture of the robot, without interacting with it.
Therefore we guess that Pepper robot is identified as male because ofits body shape” (p. 42). The authors of [121] found that participants
gendered Pepper despite impressions from a previous study whereparticipants would not. In contrast, the authors of [89] suggested
that their participants’ gendering of Pepper as feminine may havebeen due to its “feminine quality of having a smiling expression”
or “round” appearance (p. 217).
Pepper tends to be seen as masculine or feminine, despite authors’ ascriptions or efforts to present Pepper as gender neutral. In
6 papers (8%), the authors claimed that Pepper is gender neutral.
For example, the authors of [10] stated that “we focused on a robotthat has no sex and we do not apply any kind of alterations thatlead people to attribute easily a sex to a robot” (p. 42). Similarly,
another case [102] relied on the premise that robots are gender
neutral unless gender cues are added: “robots without gender cues"
such as "facial features, hairstyles or a voice” (p. 218). However,their independent raters did not agree with this perspective, withmost not classifying Pepper as gender neutral. In one case [121],
participants were asked to design a robot through illustrations andstoryboards; in reviewing these, the authors decided that participants “did not provide explicitly gendered cues” and decided tomake a gender-neutral version. While they do not explain why,
they equated a high pitch voice with a gender-neutral voice, relying on that along with Pepper’s “boxy, simple body” to enforce a
gender-neutral presentation. However, participants did not see Pepper as gender neutral: “in interacting with the robot, participantstended to use a variety of pronouns” (p. 8). The authors of [18], in
contrast, explored several voices to pinpoint those that could be
red as feminine, masculine, or gender neutral.
A final 2 papers made claims of language or translation issues.
In [156], the authors decided to use masculine referents for Pepper
after translating to English because “children referred to robot at[sic] ‘he’ due of the [sic] Polish grammar” (p. 5). The authors of[43] avoided the issue of gender in the Hebrew language, which isconnected to verb conjugation, by inputting gender as a variable
for Pepper to act on.
Considering the above and 4.2, it seems that different peopleinterpreted Pepper’s gender differently. Some of the same reasons
were used by different researchers to justify these positions. Pepper’s gender and aspects thought to indicate gender (e.g., voice,body shape) appear to rely on the perception of the individual.

4.6

Findings Based on Participant Gender(RQ5)

About half (49% or 37) of the surveyed papers reported but did notuse participant gender in their designs or analyses (e.g., [3, 35, 59,
73, 74, 84, 98, 123, 139, 147, 152, 155]). A further 20% (15 papers)
did not mention participant gender at all (e.g., [49, 53, 90]). In somecases, gender was used in other ways; for instance, in [73], theresearchers customized Pepper’s speech to refer to participants’gender, while in [9] the authors used Pepper’s built-in “gender
estimation” data stream. About 16% (12 papers) conducted analyses

What Pronouns for Pepper? A Critical Review of Gender/ing in Researchbased on participant gender but found no effects. For instance, one
study [10] found that men and women attributed gender to Pepper
the same way. Another [137] found no differences on willingness
to sign a petition between men and women, whether the petitioner
was a human or Pepper. In their exploration of the moral agency ofrobots, the authors of [62] found no difference based on participant
gender.
In contrast, 11% (8 papers) did find effects. One [56] found thatwhen people lied to Pepper, their heart rate was higher, regardlessof their gender. For example, when the stress level of a task varied,
men tended to be more empathetic towards Pepper in less stressful
situations, but less empathetic towards Pepper in stressful situations, with the opposite being true for women [106]. One study [67]found that boys preferred the “introverted” robot and more girls
preferred the “extraverted” robot. In [122], while watching a movie
together, people paid attention to Pepper the same, but women
expressed more joy and smiled more when Pepper reacted oddly.
While the authors concluded that “men did not let themselves be
distracted from robot inconsistency” (p. 4), implying that woman
are easily distracted and men have greater self-control, we pointout that other interpretations are possible, such as women having
a better sense of humour.
Several papers reported on results despite methodological andanalysis weaknesses. In particular, relying on non-statistically significant results (e.g., [106, 149]) and running analyses despite uneven groups (e.g., [14, 33, 101]). For example, despite finding noeffect based on participant gender, the authors of one study [106]concluded that “an engineer could design less human-like responses
for women operators and more human-like responses for male operators based on the task” (p. 5). We decided not to report on the resultsof studies with such limitations. Indeed, we caution against suchpractices: we must learn to accept null results and/or strengthen
our research, e.g., by recruiting more participants.
When gender was considered, almost all assumed a binary model(e.g., [11, 70, 79, 83]). Some used a male-as-default/male-as-neutralmodel, e.g., the authors of [22] referred to the generic participant
as “he/him.” Only 4 (5%) adopted an inclusive model. Some (e.g.,[146, 153]) used “they/their” pronouns to refer to participants, whileothers (e.g., [18, 124, 148, 149]) provided non-binary gender options
for participants.
Given the noted issues in collection and analysis, it is difficult
to draw general conclusions about whether and when participant
gender matters.

4.7

Findings Based on Pepper’s Perceived
Gender (RQ6)

The vast majority (about 87% or 65) of papers did not look at how
perceptions of Pepper’s gender influenced results. 5 papers (7%)
explored Pepper’s gender from a binary perspective, and 3 papers(4%) explored inclusive genders. 4 of these (5%) found an effect. One[119] found that only 15 of 50 participants in Pepper’s “gender neutral” condition agreed with that gender assignment. Other resultsfrom their study aligned with gender stereotypes, e.g., participantspreferred a robot instead of a woman for package delivery and arobot instead of a man in a receptionist position. Similarly, one[10] found that male participants reported that Pepper would be

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

best for what they argued are stereotypically feminine tasks, i.e.,reading fairy tales, despite participants assigning masculine or neutral genders to Pepper. This could mean that such tasks are notnecessarily feminine, or that Pepper’s gender was more complex
or even fluid, depending on the task. The authors of [102] foundthat feelings of uncanniness about Pepper only occurred when Pepper was “gendered” either masculine or feminine. The authors of[38] found that feminizing the robots they used led to them being
better accepted by the older adult and elderly participants. In [18],researchers found no effects based on Pepper’s perceived gender;
rather, other aspects of performance affected results.
Methodological limitations and lack of detail obscured understanding of some results. For example, the authors of [141] foundthat feminine robots received more sexual and negative comments
than male robots. However, they did not state which robots they
had categorized as feminine. They also could not collect participant
gender because they used comments posted online by unknown,
semi-anonymous parties as their data source. In another case, theauthors of [143] wrote that “this study has not taken any measures
to ensure that the effects are actually caused by the different degrees of anthropomorphism [...] this leaves open the possibility that
other properties of the robots are the true causes of the observed
effects” (p. 300). Another [105] analyzed Pepper’s perceived genderbut did not account for participant gender. The authors of [154]read gender into children’s descriptions of Pepper: “creepy is agendered term; people perceive men to be creepier than women,
particularly as a sexual threat” (p. 3). However, this seems to referto adults’ mental models of the world, so to apply it to children is aleap, and the authors do not provide a source for this view.
Some who did not explore Pepper’s gender discussed it in otherways. For instance, the authors of [151] included gender in their
proposed model of a robot persona; it is not clear what results,
if any, this decision was based on. The authors of [156] noted,
without detail, “[points] of interest on Pepper’s body ... [the] issueof embodiment needs further investigation” (p. 5). Others (e.g.,[75, 89, 143, 144]) referred to Pepper’s anthropomorphism or social
influence but without explicitly mentioning gender. Still others
cited literature on robot gendering (e.g., [36, 91, 94, 125]), but did
not consider it as a factor in their own work.
Given the lack of gender manipulation checks in most studies (see4.4), it is possible that participant perception of gender was a latentvariable that could have been influenced by researcher decisions
about Pepper’s presentation (e.g., voice, body modifications) as wellas its role or the task/activity.

4.8

Relationship Between Participant andResearcher Gendering (RQ7)

Of the 23 papers in which participants ascribed gender to Pepper,
8 (35%) papers demonstrated that researcher ascriptions matchedthose of participants exactly, i.e., both used the same pronouns orgender signifiers for Pepper. In the other 15, the researchers’ gendering was among those used by participants in 5 (33.3%) cases. Of
the 11 cases where researchers addressed gender/ing directly andprovided data about participant gendering, 8 (73%) showed diverse
participant ascriptions of gender, with the other three matching the
researchers’ ascriptions exactly. Of the 12 cases where researchers

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

did not explicitly address gender and data about participant gendering was available, 7 (58%) matched exactly, 3 (25%) matched
partially, and two did not match. A t-test comparing number ofmatches between researcher and participant gendering based on
researcher recognition of gender/ing showed a significant difference, t(10) = -2.07, p = .03, d = 1.33. These results suggest that
there was some influence of researcher gendering of Pepper onparticipants, assuming participants were faithfully recorded anddid not in fact influence the researchers themselves. Additionally,
researcher recognition of gender/ing appears to have played a role,with significantly more exact matches between researcher and participant ascriptions of gender when the researchers did not directly
consider gender/ing.

5

DISCUSSION

Our results overwhelmingly demonstrate that Pepper’s perceived
gender is not a simple fact, nor without consequences. We havesummarized our main findings in six challenges underlying thisstate of affairs. We then offer a practical framework to guide consideration of gender/ing in research praxis. We also provide a criticalself-reflection on terminology choice, disciplinarity and readership,
and walking the line between science and humanities approaches.

5.1

Invisibility

Gender/ing was often invisible, having been taken for granted orassumed [115]. This means that gender was not used as a factor
of design or analysis, or critically interrogated. Additionally, whatever influence (or lack thereof) gender/ing had is largely unknown.
Gender/ing can become visible through participant data (such as
through the use of multiple pronouns), through post-hoc reflective
work on the part of researchers, through follow-up work (such as
running gender manipulation checks), or through outside critique(e.g., the present work). Pronoun switching can indicate genderinvisibility on the part of the researchers. A lack of gender content
can indicate null results, but we would argue that these should bereported as a part of establishing knowledge about the influence(or lack thereof) of gender/ing.

5.2

Variability

One effect of gender invisibility was variability in Pepper’s perceived gender. In many cases, we did not have access to how Pepper
was or was not gendered, by researchers or participants. In therest, perceptions of Pepper’s gender varied from objective to masculine, to feminine, to neutral, to fluid (depending on the task andcontext), to multiple attributions (whether or not participants andresearchers were aware of it). In contrast, researchers’ models ofparticipant gender tended to be binary. This means that researchers’
implicit or explicit models of gender did not quite match what was
really going on in the world. This also means that a broader view ofgender is necessary. The implications for a broader view of gender
extend beyond Pepper and other agents. In particular, the act ofrecognizing the variability in perceptions of Pepper’s gender may
inspire researchers to take a more diverse perspective on participant gender. As we found, reporting of participant gender waslargely limited to the gender binary, “other,” or unstated categories.

Katie Seaborn and Alexa Frank

Very little representation of other possibilities, including transgender, gender fluid, agender, and third genders, existed, despite agrowing recognition of genderful folk and, with increasing societal
acceptance, comfort in being out [46].

5.3

Decentrality

Decentering gender is the opposite of centering gender. By decentering gender, we mean acknowledging but not acting on gender
as a nucleus of study. In the surveyed papers, this appeared in several forms. One was the act of citing and discussing other workthat addressed gender, without doing the same. Another was recognizing the importance of gender after the main work was done
and proposing future work. Still another was a kind of agender
anthropomorphism: considering the human-likeness of Pepper without discussing gender (i.e., what “points of interest on Pepper’sbody” were there?). A more subtle form was through researchers’
insufficient justifications of their limited approach to gender. Moresubtle yet, relegating these to footnotes. All of these are ways
in which gender was moved from the center to the sidelines. In
this way, decentering gender contributes to gender invisibility andvariability—moving it away from view, providing it no structure.
The reasons behind decentering are unclear, and could span a rangeof topics, e.g., hesitation due to lack of knowledge or training about
gender, prioritization of research matters, lack of awareness, etc.
A next step for future work is to unearth these reasons, such as
through interviews, reflexivity activities, and so on.

5.4

Neutrality

A common theme in ascribing Pepper’s gender was “neutrality.” Yet,most of the literature showed a failure to find agreement among
participants when it came to attributing a “neutral” gender to Pepper, even when given the option and even when tested against
masculine and feminine alternatives. This and Pepper’s Japaneseorigins point to the idea of mukokuseki, or “statelessness,” a termcoined by Koichi Iwabuchi [60] to describe the “cultural vagueness”
of Japanese exports. In theory, mukokuseki aims to break borders
and enable interpretability. For example, trademark “anime-isms,”
like big eyes and colourful hair, are meant to be digested by nonJapanese audiences according to their own culture’s notions about
appearance. This has led to some long-standing debates, such as the“Are anime characters white?” conversations that continue to percolate through social media and online forums. Still, mukokuseki
design has helped anime, manga, video games, and electronics toflourish overseas. Pepper also appears to be stateless in appearance.
Although primarily used in Japan, Pepper is cute, appealing, andambiguous in a way that makes it an ideal export. Yet, mukokuseki
products cannot control their reception or interpretation when sent
abroad. Even if genderlessness was the design team’s intention, as
they have claimed, the surveyed findings show that Pepper’s designcommunicates a range of genders. This is not to say that Pepper’s
design should be re-interpreted or more clearly marked “masculine”
or “feminine.” Mukokuseki design raises questions about genderand other markers, such as race, age, and nationality, by pushingresearchers to observe the inevitable biases that come into playthrough the non-interrogation of these very aspects. We cannot

What Pronouns for Pepper? A Critical Review of Gender/ing in Research

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

assume that Pepper’s pronouns should be neutral, and this is likely
true for other agents.

of response options on questionnaires. We provide some options to
avoid this in the framework presented next.

5.5

5.7

Convergency

Latent factors that converged with gender but were unexaminedby the researchers seem to have influenced perceptions. Age wasmost apparent, both in terms of participant age and how gender
was conceptualized and described, generally within the paper or
specifically with respect to Pepper. Children as young as 4 years
old were found to gender Pepper, and gender was collected about
these child participants. Yet, some researchers interpreted Pepper’s
default voice as both childlike and genderless. What this suggests isthat age and gender need to be interrogated together. Gender does
not disappear as a result of age, but age can mask the issue of genderand catch us unaware. Some work also pointed to a convergence offactors related to language and translation. For instance, explicit
decisions were made to use masculine identifiers as gender-neutral
referents (e.g., Hawaiian male names, Polish pronouns) without areason why. Language can shape and change our perceptions of
the world. For instance, previous work has shown that people are
more likely to gender even gender-neutral objects and beings when
their language uses gendered pronouns, i.e., like English, comparedto those who use “epicene,” or genderless, languages, i.e., Karitiâna[39]. We were lucky to find examples in the surveyed work, madepossible by the authors’ transparency. We suspect that there aremany more latent factors at play, but we are unable to spotlightthem due to their very nature as latent. Even so, this presents anopportunity for cross-disciplinary work involving linguists, gerontologists, critical theorists, and others who may have insight into
what latent factors converge with gender. Possibilities can then be
explicitly studied and confirmed or rejected.

5.6

Circumscriptivity

Gender was circumscribed in ways related to the embodiment of
Pepper and larger models in society. One of the clearest ways inwhich this played out was a reliance on dominant models of gender. This involved focusing on binary models, conflating sex andgender, and not considering the nuanced relationship between sex
and gender. For instance, voice was an important aspect of Pepper’s embodiment. The results showed that voice was consciously
used (and even changed) to influence binary attributions of gender to Pepper and gender stereotyped perceptions, attitudes, andreactions to Pepper. Gender being decentered and invisible contribute to how it has been circumscribed. Even when gender wasconsidered explicitly, there was a general exclusion of models andperspectives that deviate from the norm. With some exceptions(e.g., [18, 102, 121]), researchers made decisions about their researchand its results in ways that appear to align with their (almost entirely undiscussed) models of gender alone. Finally, we found someevidence that researchers’ gendering of Pepper influenced how
participants gendered Pepper, especially when researchers did not
explicitly address gender. We recognize these as issues of power. As
researchers, we are in a position to determine how participants contribute to our research by limiting the options we provide for them.
For instance, we can unintentionally prime participants through ourown unconscious gendering of the agent expressed in our design

A Practical Framework

Even while most studies did not treat gender/ing as a key factor,
the results indicate that we must. Yet, we may not think to consider
gender/ing when not conducting studies on gender/ing. Moreover,those of us in engineering and computer science may not know
about or be exposed to the idea of gender/ing. Disciplinary norms
have been shown to play a key role in what is recognized, valued,
and promoted, and technical fields, like robotics, are no exception[16, 25]. Even if we are on board, we may not have the background toensure that we have considered it fairly. As a baseline, we advocate
for taking a gender neutral stance, especially in language use, so
as to remain open and nonprescriptive. As a means of centering
gender, i.e., targeting the problem of gender being decentred, weoffer this framework for researchers working on socially embodied
artificial agents like Pepper. It is built upon the critical insights
about gender/ing that we uncovered in this work using Pepper as a
guiding example. We first present the centerpiece of the framework:a critical checklist geared towards researchers and research. We
then provide strategies and examples that researchers can use tohelp answer or take action on these self-check questions. We note
how each addresses the six challenges we identified above.
5.7.1 A Critical Checklist. In Table 1, we provide a list of self-checkquestions that all researchers can ask themselves in the context of
any research project involving socially embodied artificial agents.
We have marked the questions that we feel are essential even incases where gender is not a locus of study. Each question was derived from our results, based on the gaps, inconsistencies, assumptions, and limitations we discovered. Answering these questions
or taking action where needed will center gender/ing as well as
raise the quality of the research produced. While this checklist may
not cover every issue or guarantee a perfect approach, it should gosome way in increasing rigour when it comes to gender/ing.
5.7.2 State Your Position on Gender/ing. Most of the surveyed
work, even ones that considered gender, did not state a position ongender/ing. In this, there are at least two perspectives that need tobe addressed: (1) gender as a characteristic and (2) our propensity
to gender agents and their embodiment. Gender as a characteristic
applies to participants (i.e., as a demographic variable), ourselves,
and the agent (i.e., gender cues in its design and context of use). We
do not have to keep to conventional models or academic research;gender is a dynamic factor and so established models may not
match participant—or our own—experience. If our positionality on
gender differs between participants and the agent, we should state
so. All models and theory should be cited. Ideally, there should bejustification for the choice of models and discussion of alternatives.
Challenges Targeted: Invisibility, Variability, Neutrality
Example: We use the conceptualization of gender as a socially situated and constituted construct (continued in 2.1). We both identify
as cisgender women, and one of us leans towards gender apathy.
5.7.3 Document Participant Gender. Even though effects based onparticipant gender were found, a portion of the surveyed literature
did not collect and/or report on participant gender. This should be a

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

Katie Seaborn and Alexa Frank

Table 1: Critical self-check questions, listed by focus and related to the challenge/s each target and strategies, where applicable.
Questions deemed essential even in cases where gender is not a focal point are also marked.
Focus

Questions

Strategy

Challenge/s Targeted

Essential

Researcher/s

What model/s of gender have we used, in general and for theagent?
Have we gendered the agent under study, in its design,
context of use, or descriptions in ethics forms, scripts, orother materials?
If so, what gender/s?
Have we been consistent with our pronoun use and use ofother gender signifiers?
Have we captured participant gender?
Have we allowed for a range of responses, regardless of ourown positioning?
Have we considered asking participants about how they
conceptualize gender, in general and/or with respect toagents, without enforcing our own views?
Have we included a way to capture participants’ genderingof the agent, if it occurs, without assuming it does?
Have we allowed for a range of responses, regardless of ourown positioning?
What gender/s is/are the agent perceived to be byparticipants, if any?
What gender referents have been ascribed to the agent?

5.7.2

Invisibility, Neutrality

·

5.7.7

Invisibility, Neutrality

⃝

5.7.2
5.7.7

Variability
Variability

⃝
⃝

5.7.3
5.7.4

Invisibility
Variability, Neutrality,
Circumscriptivity
Variability, Neutrality,
Circumscriptivity

⃝
⃝

5.7.4

Variability, Neutrality

⃝

5.7.4

Variability, Neutrality,
Circumscriptivity
Invisibility, Variability,
Neutrality
Invisibility, Variability,
Neutrality
Circumscriptivity
Variability, Neutrality,
Circumscriptivity
Variability,
Circumscriptivity
Convergency⃝

Participant
Gendering

Agent Gendering

Data Analysis

Did participant gendering match that of the researcher/s?
What models or novel ideas about gender emerged?

Reporting

How did participants react to the agent, especially in any
stereotyped ways?
What other factors may have influenced or confounded theseresults?
Did we report on gender demographics, including genders
not covered?
Did we report on all results related to gender, including
non-significant results?
Did we check our paper and other materials to be publishedfor consistent gendering of participants and the agent understudy?

baseline demographic variable in all such research. As our findings
show, the gender of participants (and likely ourselves) can havereal effects on research outcomes, including gendering.
Challenges Targeted: Invisibility
Example: Collect and report on participant gender as a part ofdemographics.
5.7.4 Use Gender-Expansive Framings. Regardless of our own positioning or the expected positioning of participants, we should allow
for breadth of gender/ing. Partly this is to avoid unintentionallybiasing participants. Our findings revealed some evidence of a link
between researcher gendering of Pepper and participants’ gendering of Pepper. This was pronounced in cases where researchers did
not recognize gender/ing, but also seems to have occurred even incases where gender/ing was recognized. Additionally, participants

5.7.4

5.7.5
5.7.5

5.7.4
5.7.6

·

⃝
·
·
·
⃝
·
⃝

5.7.6

Invisibility, Variability,
Circumscriptivity
Invisibility

5.7.7

Invisibility, Neutrality

⃝

5.7.3

·

ascribed a range of genders to Pepper; Pepper was not necessarily
seen as neutral or agender, even among participants in a single
study. It is possible participants will ascribe gender options that wecannot imagine and account for in advance. Finally, participants
may have a gender identity that does not match our positioning; thelimited results for non-binary genders is telling. To counter theseissues, we can adopt a gender-expansive framing. In practice, we
can allow participants to tell us how they are gendering themselves
and a given agent, as freely as possible.
Challenges Targeted: Variability, Neutrality, Circumscriptivity
Example: We recommend an item and response set similar to thefollowing, which is based on theories of gender, gender critical approaches to humanoid robots, and how gender has been formulated
in the Pepper literature so far:What Pronouns for Pepper? A Critical Review of Gender/ing in Research

How would you gender the agent, if at all?
• Genderless or neutral• Feminine• Masculine• Somewhere in between feminine and masculine, having characteristics of both
• Fluid, changed over time
• Mechanical• Another gender: [fill in here]
We do not propose this as a final set. We offer this as a format
and starter set to provoke discussion. A standard approach to capturing perceptions of agent gender will be useful for consensus
building and future survey work, i.e., standardizing practice for
optimal knowledge construction. We suggest developing a standard for future research. Additionally, these categories may be too
limited to fully understand participants’ models of gender and/or
approach to gendering. Open-ended questions could be used togather information on how participants conceptualize gender.
5.7.5 Confirm Perceptions of Gender and Gendering. We should
confirm whether and how gendering occurs. One standard approachis a manipulation check [50]. This can be done in a pilot study or
pre-study, especially if a gender is a key factor or when theory or
previous research suggests that perceptions of gender will have aneffect. But a simple post-study (to avoid priming effects or stereotype threat) item recording perceptions of gender may be fine inmost cases. This approach is somewhat limited by its subjectivity,
however. A more objective approach could be a content analysis ofpronoun usage and gender signifiers.
Challenges Targeted: Invisibility, Variability, Neutrality
Example: The content analysis in the present paper.
5.7.6 Report All Findings on Gender/ing. Our findings suggest thatgender/ing should be included as a basic variable of analysis. Yet,in most cases, gender/ing was not reported. It is possible that researchers conducted some kind of analysis but did not report it.
This may have been due to fear of publication bias against nonsignificant results, a long-standing problem [133]. In that case, wesuggest that authors include a statement that gender/ing analyses
were done, with no significant results found.
Challenges Targeted: Invisibility
Example: We conducted a manipulation check of Pepper’s perceived gender, but all participants indicated that Pepper was agender or gender neutral.

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USAvery different backgrounds to tackle an interdisciplinary topic in a
critical way. The challenges we encountered ran the gamut fromterminology to disciplinary conventions to readership. Terminology choice was tricky. We realized that we had to decide about
using or not using pronouns for Pepper: Should we avoid explicitly gendering Pepper by using “Pepper” repeatedly? Would the
awkwardness of repetition be better than taking a position on Pepper’s gender? For ease of reading, we settled on using grammaticalobject referents, e.g., “its.” To the best of our knowledge, this is
the most neutral referent in the English language for agents thathave not achieved personhood by most measures. Our challenges
with terminology were not limited to Pepper’s pronouns, however.
Reviewers pointed out a clash arising from disciplinary conventions
between engineering and the humanities, notably regarding thewords “latency” and “decentralization.” Our use of these words may
be at home in a gender theory paper. But in an HCI paper, evena critical computing one, they may cause confusion due to theirsameness/similarity with computer science terms. We realized that
we could not simply import terms from other disciplines and letthem stand, at least without comment. This also relates to consideration of our prospective readers: What assumptions could we
make about what they know, how could we fill in gaps, and what
extra-disciplinary framings would be accepted? For example, thetopic of cultural tropes about Japan may not be familiar or seen
as relevant to STEM readers who may or may not consider how
gender dynamics in that country informed Pepper’s design. The
surveyed papers did not address this, making it difficult for us touse our empirical data, but also giving us pause when drawing
conclusions in ways that would be acceptable for critical theorists,
anthropologists, and others in critical cultural studies that may
not be acceptable in STEM fields. Ultimately, we decided that skating the boundaries between the sciences and the humanities has
considerable merit for starting dialogue and inspiring a different
viewpoint; we pushed forward despite these risks. We await to see
what discourse emerges.

5.9

Limitations and Future Work5.7.7 Ensure Consistency in Gendering. Findings pointed to someincongruency in how researchers gendered Pepper, even within
a single study. A consistency check in terms of pronoun use andgender signifiers (in text, but potentially also in images, audio clips,
video, or other media, including the agent’s speech) may be useful.
For greater objectivity, a third party can do the check.
Challenges Targeted: Variability, Neutrality
Example: Ask a colleague to review the paper for inconsistencies
in gendering. Be sure that they know your position.

This work was affected by the COVID-19 pandemic [42]. One of
us was repatriated and had our funding nullified, while both of
us grappled with the suspension of research as usual, e.g., ethics
board closures, bans on human subjects work. We were not able
to source all potentially relevant research materials and researcher
demographics. In particular, we could not extract author gender.
We also did not have access to how gender was handled in researchmaterials for participants. We recognize that additional efforts areneeded to determine whether researcher gendering was purposiveor unintentional. Gendering or its absence in the published papers
may reflect an effort to write with scientific objectivity, possibly
influenced by editorial assistance. Author surveys and/or interviews
could provide insight on these matters as well as how gender is/was
framed, why it was considered or not, etc. We also acknowledge
that focusing on one agent (Pepper) limits the generalizability of
our findings. Future work should critically review other cases.

5.8

6

Critical Self-Reflection

We would be remiss if we did not critically reflect on our own positioning and process. We were two people coming together fromCONCLUSIONSOur critical exploration of the humanoid robot Pepper has revealed
how gender/ing can be an important, influential, and overlooked

CHI ’22, April 29–May 05, 2022, New Orleans, LA, USA

factor of research practice. This work represents a first step towards a more self-reflective stance on the part of us researchers. As
shown through the empirically non-gender-neutral case of Pepper,a gender-evasive or gender unconscious approach has limited our
research. We have outlined six reasons underlying this state ofaffairs: invisibility, variability, decentrality, neutrality, convergency,
and circumscriptivity. We have provided a practical framework
for more critically and deeply integrating gender within research
practice. There is great risk of missing out on what is really goingon in human-agent experiences as well as perpetuating genderstereotypes, sexist tropes, and unequal representation. We haveprovided a way forward through clear and reasonable changes totypical practice in terms of theory engagement and methodology.
We commit to taking this on in our future work—and we hope you
will join us.

ACKNOWLEDGMENTS
Our gratitude to M.R. Ganda and Peter Pennefather, who reviewed
early drafts of his manuscript. We also thank the anonymous reviewers for their careful and insightful feedback.

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