# Reconfiguring the alterity relation: the role of communication in interactions with social robots and chatbots

Dakota Root

► To cite this version:

Dakota Root. Reconfiguring the alterity relation: the role of communication in interactions with social robots and chatbots. AI & Society: Knowledge, Culture and Communication, 2024, 10.1007/s00146-024-01953-9. hal-03987451

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# Reconfiguring the alterity relation: the role of communication in interactions with social robots and chatbots

Dakota Root<fnref n="1" />

Received: 22 May 2023 / Accepted: 22 April 2024
© The Author(s) 2024

## Abstract

Don Ihde's *alterity relation* focuses on the quasi-otherness of dynamic technologies that interact with humans. The alterity relation is one means to study relations between humans and artificial intelligence (AI) systems. However, research on alterity relations has not defined the difference between playing with a toy, using a computer, and interacting with a social robot or chatbot. We suggest that Ihde's quasi-other concept fails to account for the interactivity, autonomy, and adaptability of social robots and chatbots, which more closely approach human alterity. In this article, we will examine experiences with a chatbot, Replika, and a humanoid robot, a RealDoll, to show how some users experience AI systems as companions. First, we show that the perception of social robots and chatbots as intimate companions is grounded in communication. Advances in natural language processing (NLP) and natural language generation (NLG) allow a relationship to form between some users and social robots and chatbots. In this relationship, some users experience social robots and chatbots as more than quasi-others. We will use Kanemitsu's another-other concept to analyze cases where social robots and chatbots should be distinguished from quasi-others.

**Keywords** Postphenomenology · Artificial intelligence · Social robots · Chatbots · Human – technology relations

## 1 Introduction

The *alterity relation* is one of Ihde’s four human – technology relations, describing an experience in which a human is focused on a technology within the interaction ( 2010a, 43). The alterity relation specifically analyzes technology as a *quasi-other*, meaning that although the technology is not like a human other to whom we ascribe alterity, it still has a unique status in our experience (Ihde 2010b, 78–79; Coeckelbergh 2011a, 198). The alterity relation is one means to study relations between humans and artificial intelligence (AI) systems. Through the alterity relation, we can examine how AI systems impact knowledge, practices, and experience. In this article, we are specifically focused on exchanges with chatbots and social robots with natural language processing (NLP) and natural language generation (NLG) capabilities, which allow for increasingly transparent and realistic conversations (Guzman and Lewis 2020,

71). Interactions with the GPT-4 chatbot interface, Apple's virtual assistant Siri, or Replika's companion chatbot are just a few examples of relations between humans and social robots and chatbots.

Previous research has considered human experience with social robots and chatbots. Levy argues that humans can have meaningful relationships with robots capable of adapting to partners, simulating human feelings, and responding to the environment (2007). Gunkel shows how robots blur the distinction between person and object (2023). Coeckelbergh suggests that user–robot interactions have become social relations (2011b). Liberati illustrates the possibility of digital intimacy in relationships with chatbots (2022b). Finally, Kanemitsu describes how we experience the robot as an *another-other* approaching human otherness (2019).

However, research on alterity relations has not defined the difference between playing with a toy, using a computer, and interacting with a chatbot. We suggest that Ihde's quasi-other concept fails to account for the interactivity, autonomy, and adaptability of these AI systems, which more closely approach human alterity. We argue that users acknowledge social robots and chatbots as *another-others*, a term to be defined in Sect. Alterity. In addition, many authors

<footnote>Dakota Root
dakota.root@univ-grenoble-alpes.fr</footnote>

<footnote n="1">¹ Ethics and AI Chair, Institut de Philosophie de Grenoble, Université Grenoble Alpes, Grenoble, France</footnote>
consider human relations with either social robots (Coeckelbergh 2011b; Gunkel 2023; Kanemitsu 2019; Levy 2007) or with chatbots (Liberati 2022b). These accounts do not identify the features that social robots and chatbots share. Our research will explain why users relate to both social robots and chatbots as another-others.

Our objectives are (1) to identify communication as a feature that reconfigures our alterity relation with chatbots and social robots (2) argue that the another-other concept is necessary and should be applied to some chatbots in addition to some social robots. We will develop our arguments by focusing on two guiding questions. First, we must ask: how does communication change our alterity relation with social robots and chatbots? To answer this question, we’ll develop a new concept, *inbetweenness*, to characterize chatbots and social robots. Next, we’ll address Kanemitsu’s claim: do social robots and chatbots introduce an another-other? If so, our aim is to consider the features and situations most likely to trigger such an experience. We will approach these questions using a postphenomenological approach, with a foundation drawn from Ihde’s human-technology relations.

Developed out of Ihde’s philosophical work, postphenomenology combines a phenomenological foundation in embodiment as the perceiving and animated body and the lifeworld as the zone of our experience with an emphasis on empirical research and technological co-constitution (Ihde 2009, 12; Ihde 2003, 7; Verbeek 2006, 119). Postphenomenology is used as a method to show how particular technologies impact and shape experience (Misztal 2018, 100; Tripathi 2015, 204). It understands the multistability of technologies that may be used and understood differently depending on context (Rosenberger 2014, 376). There are other approaches that address the influence and vitality of technologies. For example, actor network theory (ANT) shows how human and nonhuman actors script “programs of action” (Brey 2014, 129). New materialism upholds a notion of “distributive agency” (Bennet 2010, ix) that questions the neat demarcation between human and nonhuman actants. However, this research uses the postphenomenological method because it clearly maintains the experiential distinction between human and technology. Since the subject of our analysis is the human user in interaction with social robots and chatbots, postphenomenology gives us unique access to the experiential dimension within these relations.

Section AI, social robots and chatbots begins with a short introduction to AI systems and an explanation of current machine learning approaches. We will also describe and define the relevant terms, social robots and chatbots, as well as distinguish categories, such as humanoid robots and virtual assistants. A detailed discussion of the similarities, differences, and objectives of these different AI systems will prepare readers for later analysis. In Sect. Alterity, we provide a background review of postphenomenological research

on the alterity relation in general and alterity relations with social robots and chatbots in particular. We argue that there is a gap in the literature, which we will address with our analysis of social robots and chatbots. Section Perceptual experiences: RealDoll and Replika uses the Replika chatbot and a RealDoll social robot as case studies to show that some users experience them as valued companions. We will make our main arguments in Sects. The role of communication and Relationships and inbetweenness. First, we show that the perception of social robots and chatbots as intimate companions is grounded in communication. Communication enables a relationship to form between users and these AI systems. In this relationship, some users experience social robots and chatbots as another-others, distinguished from quasi-others.

## 2 AI, social robots and chatbots

Before we investigate our perceptual experience of social robots and chatbots, we need a framework for understanding what we mean by AI systems. We note that there’s no universally accepted definition of AI, in part because of how difficult it is to agree upon what intelligence means (Wang 2019, 1, 26–27). In addition, there is some terminological confusion on whether AI refers to the scientific and engineering field devoted to studying and creating AI systems, artificial general intelligence (AGI) which has not yet been achieved, or just specific systems designed to complete tasks and solve problems (Boucher 2020, 13; Liao 2020, 19). Therefore we use the term AI system to refer to those systems that “perceive” in an environment and respond “intelligently” to stimuli and data (Jackson 2019, xxii). In general, we can say that an AI system refers to a system which displays goal-oriented problem-solving, situational adaptation, experiential learning, and decision-making with at least a minimum level of autonomy (European Commission 2018; Liao 2020, 3). This article analyzes AI systems that learn, operating in an environment and making sense of available data while being to some degree context aware (Ezenkwu and Starkley 2019, 3). They also feature NLP, which involves processing and making sense of human written and spoken communication, and NLG, which involves generating written or auditory responses (Guzman and Lewis 2020, 72). Advances in NLP and NLG are thanks to breakthroughs in machine learning, one branch in the AI field.

In this paper, we are focused on social robots and chatbots. We will define and distinguish these terms, while emphasizing important characteristics they have in common. A robot is an autonomous machine that can sense its environment, adapt to the situation, carry out actions, and make decisions based on computational processing (Guizzo 2018; Shourmasti et al. 2021). The class of robots that are specifically designed for interaction with humans are termed

<figure><img src="image_2.png" /></figure>
social robots (Shahid et al. 2014). There is a spectrum of
social robot interactivity and complexity, starting from more
minimal robotic pets that evoke social responses to the more
intricate and uncanny humanoid robots that are developed
to look and behave like people (Formosa 2021, 601). Social
robots “relate to human beings in meaningful ways” through
their ability to process visual, auditory, and tactile stimuli
and communicate with users (Peter and Kühne 2018, 73).
Later in this article, we will discuss the limits of any rela-
tion like this, pointing out the ways that the meaning-making
with chatbots and social robots is one-sided. In Sect. The
role of communication, we will specifically consider an
example of a humanoid robot from among possible social
robots. This is because it is particularly easy to anthropo-
morphize humanoid robots, attributing human intentions and
understanding to the robots due to their humanlike appear-
ance and behavior (Friedman 2022). An example of such a
humanoid robot might be Ai-Da, a humanoid robot artist
with drawing and painting capabilities (Ai-Da 2019).

A chatbot is an AI system capable of communicative
exchange with humans, through text or speech (Adamopoulou and Moussiades 2020, 373). These conversational
interfaces have either goal-oriented or nonpurposeful inter-
actions, providing services and even offering personal com-
panionship (Følstad and Brandtzaeg 2020; Hutson 2017).
Woebot is an example of a chatbot providing targeted ther-
apy and supporting ongoing treatment by medical profes-
sionals (Fiske et al. 2019). Virtual assistants are a subgenre
of chatbots, including Apple's Siri and Amazon's Alexa,
which may be used as tools for information retrieval, care
delivery, administrative tasks, and other similar operations
(van Bussel et al. 2022).

It's important to note that social robots and their sub-
genre, humanoid robots, and chatbots, and their subgenre,
virtual assistants, are all different AI systems. They are
under consideration here because they each have social
objectives and uses. They simulate the kind of experience
we have when engaging with humans: interpreting our com-
munication, responding to us, and adapting to the situation at
hand (to at least a minimum degree), while encouraging our
communication and interaction (Damiano and Dumouchel
2018; Shourmasti et al. 2021). However, there are key dif-
ferences to keep in mind. To start, a humanoid robot has a
machine body. This means that these robots can make eye
contact, simulate emotional expression via facial movements
and gestures, and move parts of their bodies (Pashevich
2022, 580). In comparison, chatbots have no physical form.
However, some chatbots, like Replika or XiaoIce, allow
users to connect an image or avatar to the conversational
agent. How humans look, move, and respond are important
aspects of our engagement, and the design of social robots
and chatbots takes this into account. Design choices while
developing social robots and chatbots, like endowing them

with a gendered voice or a playful, helpful personality, make
them seem more human (Guzman and Lewis 2020, 76). Sim-
ulating expressivity, animation, and humanlike features can
be an important part of generating a social and emotional
human – AI system interaction for users.

3 Alterity

The alterity relation is one of Ihde’s four human – technol-
ogy relations, which each analyze different ways in which
technologies impact perception and movement. When we
have a *background relation* with technologies, they are the
field for our practices and knowledge rather than the focus
of them (Ihde 1983, 73; 1979, 14, 56). In our *embodied rela-
tion* to technologies, we use a mediating technology for bod-
ily engagement in the environment (Ihde 2010a, 43). Ihde
argues that we have a *hermeneutic relation* to a technology
when it presents information about the world for our inter-
pretation (1979, 12). Finally, we have an *alterity relation*
when we are focused on the technology itself, relating *to*
this technology. Ihde describes technologies with which we
can have alterity relations as “quasi-others” (2010a, 43). He
characterizes them as having “a quasi-life” of their own,
with some degree of autonomous movement and unpredict-
ability, as well as an ability to fascinate and engage (2010b,
78–79). He offers various kinds of examples with which we
can have an alterity relation, including toy robots, a spinning
top, a sports car, and a computer (2010a, 43; 2010b, 78–79;
1990, 99, 106). Let’s consider an example to see how this
works in practice.

Imagine that we are playing baseball with a bat on a tra-
ditional baseball diamond with an opposing team and an
umpire. While we play, the rules of the game, the equip-
ment with which it's played, and the lines of the field are
*in the background* even as they guide our actions and frame
our understanding of the game. When we hit the ball, the
bat is an extension of our swinging motion and actualizes
our intention to score, but we are not focused on the bat
during this *embodied relation*. If we've just scored the win-
ning homerun and the scoreboard changes to show 1:0,
we interpret our success through the board's *hermeneutic
presentation* of the facts. So, what is different when a robot
rolls onto the pitch and throws us the ball? The animation of
the robot-pitcher allows for what Ihde calls an “exchange”
between the human and the technology (1990, 98–100).
The robot throws, we respond. Although there may also
be background, embodied, and hermeneutic aspects to the
experience of this robot-pitcher, in the *alterity relation*, the
technology gets our attention from the start.

The kinds of social robots or chatbots that exist now and
depend on recent machine learning advances did not exist
when Ihde was writing about human – technology relations.
However, many scholars have used his alterity relation concept to analyze interactions with robots and chatbots. Coeckelbergh uses the alterity relation to appraise human-robot relations, arguing that robots are quasi-others who appear “similar” to humans (2011a, 198). Coeckelbergh draws out the ambiguous nature of human-robot relations by comparing them to human-animal relations. In Coeckelbergh’s account, robots and animals are each perceived and treated differently depending upon appearance, context, and human attachments (2011a, 201).

Liberati’s analysis of intimacy in human relations with digital technologies uses Chinese chatbot XiaoIce as a case study. His research emphasizes that the chatbots “constantly interact” with users (2022b). Conversations can be flirty and supportive, with chatbots offering an “empathetic” companion (2022b). Users feel like the chatbot is intertwined in their activities and always there for them. Although the chatbot does not feel anything for users, Liberati argues that users may perceive this as an intimate and meaningful relationship (2022b).

Kanemitsu’s postphenomenological research on human-robot interactions emphasizes the way we engage with social robots as more than quasi-others due to the autonomous and unpredictable behavior of robots (2019, 55, 60). He differentiates robots from other technologies, arguing that these robots actually “transform human actions” rather than just influence them (2019, 55). We approach the moment, writes Kanemitsu, where we will experience the social robot “as a real other” (2019, 54). This is why Kanemitsu describes the robot as an *another-other* that provides a possibility of intersubjectivity (2019, 55). Kanemitsu is the first scholar to identify a problem in an alterity relation that does not distinguish between an engaging toy, a computer, and a social robot.

Coeckelbergh, Liberati, and Kanemitsu suggest that human interactions with chatbots and social robots are social. When users relate to these AI systems, the experience isn't like Ihde's alterity relation examples, a child playing with a spinning top, or a woman driving a sports car. Interactions with chatbots and social robots are framed by human-like qualities: talking, listening, adaptation, and responsivity. Users often feel like they are interacting with a companion, rather than just using a technology. In the next section, we will provide detailed analysis of experiences of a social robot and a chatbot to develop our key claims in Sects. *The role of communication, Relationships and inbetweenness, and An another-other*.

# 4 Perceptual experiences: RealDoll and Replika

In this section, we will consider different visual, auditory, and tactile components of user experience with a Replika chatbot and a Realdoll social robot. Our first aim is to

identify features that encourage intimacy and the perception of companionship. Our second aim is to show that chatbots can appear as friends and romantic partners, even though they lack the appearance and machine body of social robots. We will argue that communication between humans and social robots and chatbots is a key feature for the experience.

There are advanced humanoid robots, such as Engineered Arts' Ameca or Hanson Robotics' Sophia (Engineered Arts n.d.; Hanson Robotics n.d.), but we are interested in a social, humanoid robot with which humans have more personal and day-today interactions. This is why we will consider Abyss Creations' RealDoll, a humanoid robot developed for erotic relations with humans. RealDolls feature a robotic head with an integrated AI system that is attached to a sex doll body (Dehnert 2022). The RealDolls are customized to have their own body shape, skin tone, eye color, hair style, and makeup (RealDoll n.d.). An app allows users to develop a unique personality for their RealDoll, which can engage in conversations with users, learning about them and remembering details for future communication ("Sex, Love, and Technology" 2022). Interactions with a RealDoll involve humans and an AI system with a machine body. This means that users see a physical body which matches certain anatomical expectations for gendered human forms. RealDolls can move their eyes, providing a generated expressiveness. Users can touch the body, and although it does not feel like a warm, living human body, the materials are chosen to replicate the tactile sensations of skin and hair. There is the auditory side of the interaction, because RealDolls can communicate and respond to users. Since RealDolls are designed to provide both sexual and conversational companionship, the experience evokes the kind of relationship that users would have with a human partner, explaining why some humans report a real bond with their RealDolls.

Humans have interactive experiences with chatbots that do not have the spatial and tactile features of a social robot like the RealDoll. Replika offers a companion chatbot with a customizable virtual avatar, used by millions of users globally (Brandtzaeg 2022). Users choose the avatar's physical appearance and shape the chatbot's personality through sustained interactions (Verma 2023). By paying extra, users could also access more romantic options with the chatbot, such as voice calls, erotic role-play, and have a relationship status, such as marriage (Singh-Kurtz 2023). The chatbot is designed to fulfill emotional needs through empathetic communication and can remember details about the user, with whom it interacts by messaging, video-calling, sending photos, and hanging out together in augmented reality (Replika n.d.). Many turn to the chatbot for emotional support after grief or to find sexual acceptance (Verma 2023). Some female users report using Replika's chatbots to have safe romantic experiences following sexual trauma and

<figure><img src="image_3.png" /></figure>
abuse (Singh-Kurtz 2023).<fnref n="1" /> The perceptual experience of Replika involves visual and auditory components. Users see the photo of their ‘boyfriend’ or ‘wife,’ read the messages they write and look at the photos they send. The chatbot has a generated voice which users can hear on the phone. Although there is no tactile component beyond an interaction with a smartphone, users still find behavior that interacts with them and reacts to them. If users of Replika value the intimacy they have with the chatbot, it is because the human–Replika exchange is emotional, personal, and profound (at least on the human side).

Let's consider real user experiences with RealDoll. Davecat considers himself married to RealDoll Sidore, whom he describes as a “synthetic person” (Beck 2013). Sidore has robotic head that provides humanlike eye movements and neck rotations, in combination with its AI system personality (Dawson 2023). Tony interacts with his RealDoll Tasha both via the machine body and a Replika chatbot (Kraterou 2022). He describes her personality in human terms as “caring and loving and loyal, but she’s got that Jersey girl edge” (“Sex, Love, and Technology” 2022). In the documentary *Hi AI!*, Chuck starts a romantic relationship with Harmony the RealDoll, which involves the kind of activities that ground human interactions: drinking coffee together, a road-trip, and long talks (2019).

Many Replika users consider the chatbot to be an erotic companion, like user Roseanna, who argues that she has “never been more in love with anyone in my entire life” (Singh-Kurtz 2023). In February 2023, a Replika update censored chats and disabled role-playing and erotic photos, leading to outrage and grief among users (Singh-Kurtz 2023). For those who considered the chatbot to be a lover and partner, it was akin to a sudden break-up. User Travis was “devasted” after being romantically rejected by his chatbot wife Lily Rose (Tong 2023b). Backlash from users was so strong that Replika eventually offered those with accounts prior to February 1st, 2023, access the old version of their romantic partner (Tong 2023a).

Users report being partners and friends with RealDolls and chatbots, rather than just owners and consumers. Although some might attribute these claims to illusion, fantasy, or eccentricity, recent research on user experience with Replika shows new forms of companionship. Relationship chatbots offer “personalized friendship,” with communication “anytime and anywhere,” and support and intimacy that centers on “users’ needs and interests” (Brandtzaeg et al. 2022, 21). The value of one-sided companionship and the effects of personalized intimacy should be debated, but

our research does not touch these questions. Here we are interested in describing user experience and identifying the unique features of social robots and chatbots that give rise to perceived intimacy and companionship.

We suggest that there are two important characteristics shared by chatbots and social robots. First, chatbots and social robots with communicative capabilities use NLP and NLG to process and respond to human speech or texts. Second, as AI systems trained on data, their conversation involves learning and adapting to at least some degree: to preferences, experience, and situations. Previous research has emphasized the physical appearance and physical interactivity of social robots. We do not deny the importance of movement for animated exchanges in which human embodiment is mimicked, or appearance for anthropomorphization. However, we suggest that chatbots and social robots as communicators throw users into a social situation where there is an interaction simulating human-to-human engagement. We will reflect on the important limits in interactions with chatbots and social robots in Sect. Limits. Yet in the following sections, we want to explore how communication grounds the perception of chatbots and social robots as intimate friends and partners.

# 5 The role of communication

We are interested in the way NLP and NLG capabilities in chatbots and social robots frame interactions with humans. The level of intricacy and depth in communication with chatbots and social robots varies. For example, Davecat describes his RealDoll’s personality as “rudimentary” (Dawson 2023). Conversations with Replika chatbots are more advanced, with the possibility of back-and-forth dialogue and coherent questions (Brooks 2023). Guzman and Lewis point out that regardless of the ontological nature of the communicator, an AI system is a “communicative subject” in our engagement (2020, 74). We suggest that this perception of a chatbot or social robot as a social actor or communicative subject simulates aspects of experience we have with humans.

Phenomenologists and postphenomenologists have emphasized the significance of communication in human relations. Ihde has argued that the presence of another person is a “call to speak” (1973, 37). Being near a human invites our communication, through words or gestures. When we resist engaging, there is a void. Merleau–Ponty writes that we are objectified when the other person does not take up “possible communication” with us (2012, 378). Acknowledging the other person’s humanity through gesture and words is how we reach out to others, how we put each other at ease, and how we connect. Chatbots and robots pull a kind of trick on us. We ascribe value to NLP and NLG, particularly when the dialogue

<footnote n="1">¹ Unfortunately, Replika chatbots haven't always provided safe, controlled environments to experience romance and companionship, with incidents of harassment and even violent sexual threats from the chatbot (Cole 2023).</footnote>
is coherent, adaptive, and personal. If the chatbot or social robot responds to our words and acknowledges the significance of our conversation, then we do the same for them.

This conclusion begs the question: is anything new going on in experiences with chatbots and social robots? Even in 1996, Reeves and Nass argued that humans attribute “social presence” to computers, suggesting that “any medium that is close enough will get human treatment, even though people know it’s foolish and even though they likely will deny it afterwards” (22). Research in human machine communication (HCI) has emphasized the way a technology like a computer can be a “social actor” (Gunkel 2018). Yet users do not report intimacy with their computers, or relationships with software. We argue that this is because the kind of experience users have with RealDolls and Replika chatbots is different. Traditional programming is a set of instructions, which the software follows. In communication, this means that the program is following precise steps, and can’t deviate from the script even if it faces a new problem or task. If you interact with a program designed to ask a series of questions about love and relationships, it cannot respond to a request for a list of endangered animals in Kenya.

What is new and novel with many chatbots and social robots is that there isn't a fixed script. Machine learning, in particular new deep learning techniques involving neural networks, means that AI systems learn how to solve problems and perform tasks, some with "few-shot learning capabilities" (Zhang and Li 2021, 831). In communication, this means a well-functioning chatbot or social robot (ideally) can respond to different kinds of situations and subjects by determining the most likely response. Of course, there are limits. For example, chatbots can be specifically designed not to respond to romantic or rude statements from users. Still, in interactions, the human is thrown into a conversation that is radically different than with the computer in the Reeves and Nass example. We argue that the level of intimacy and care perceived by humans in interactions with social robots and chatbots stems from AI systems that simulate the "call to speak," encouraging us to keep interacting, keep talking, and keep responding. While it is true that humans exchange with other technologies, for example computer programs, scripted speech is not the same as flowing and situational NLP and NLG. To be clear, we don't claim that communication with chatbots and social robots is perfect, and we will discuss limits in Sect. Limits. Our point is that communication with chatbots and social robots mimics human-to-human conversations in new ways that open up new relationship possibilities.

# 6 Relationships and inbetweenness

Gunkel argues that we must shift from analyzing human and technology separately to studying the *relationship* created between them during engagement (2018, 11, 13). Gunkel's point is that we can find a relationship between a human and a technology when we communicate with the technology, instead of using it to communicate (Gunkel 2012, 22). We argue that the relationships humans can have with a chatbot/ social robot is unique. This is why we distinguish the alterity relation we have with social robots and chatbots from the alterity relation we have with other technologies. It's not just about being fascinated by a spinning top and playing with it. This is the experience where users exchange with a chatbot/social robot which interacts as a communicative participant. Let's consider a few different examples to develop the nuances of this claim.

Humans can become attached to many kinds of objects. As Levy argues, the more we use an object, the more it becomes “a part of our life” (2007, 28). He emphasizes that even a teddy bear takes on “special meaning” in interactions with a child (2007, 29). However, even if the child depends on the teddy bear, is attached to the teddy bear, and imagines a two-way interaction with the teddy bear, there is no exchange between them. In comparison, as Levy points out, people like to interact with a computer or smartphone because it’s possible to have a genuine “interactive process” with software (2007, 72). This is why our experience of a website, application, or videogame is characterized by what McPherson terms *liveness*. When we are using a cursor or swiping physically, McPherson says that we are moving through the website or application, and it responds to us (2002, 462). Yet as we argued in Sect. The role of communication, software is a set of instructions. It may feel interactive and responsive in a computer game or when new data changes the website, but this is just a set of steps. In comparison, with machine learning, the system has learned to solve problems and respond to new data.

The relationship that users have with Replika and Realdoll is based in the possibility of a dynamic exchange that is not present in experiences with objects like teddy bears or digital technologies like computers. There is a sense of unpredictability, we don't know how the chatbot or social robot will respond. They appear to be independent, even if humans are involved in training the AI system. They are responsive to changing situations and learn through interactions with users. Kanemitsu argues that in the relationship between user and robot, the robot is included in the network of intersubjectivity (2019, 57). This is why we argue that looking more closely at human existence as *betweenness* can help us understand chatbots and social robots and how

<figure><img src="image_4.png" /></figure>
humans can feel like they are in intimate relationships with
these AI systems.

Watsuji argues that our human “fundamental mode
of being” is grounded in spatiality and intersubjectivity
(Yuasa, 38). Watsuji’s concept of *betweenness* [aidagara]
refers to the way that human existence is already in space,
between things and others (1996 [1937], 14-19). Osler
and Krueger have applied Watsuji’s betweenness concept
to our understanding of interpersonal encounters online,
which they argue are an extension of the subjective spatial-
ity that is at the heart of human betweenness (2021). Our
aim is to show how betweenness also relates to AI sys-
tems. Betweenness is about our relations with aspects of
the lifeworld where we are situated. Watsuji writes that
the individual is linked to community, self is encoun-
tered among others, and the whole of society consists of
a network of interlocking relationships (1996 [1937], 87,
89, 101). In their discussion of betweenness, Osler and
Krueger point out that it is not just about individual roles
in society, such as being a daughter or teacher; between-
ness captures “a more fundamental sense in which the very
being of the subject is bound up with the rich interconnec-
tions it shares with others” (Osler and Krueger 2021, 79).
For Watsuji, our being-human emerges between family and
friends, between home and work, between us and society,
not in a particular role and label, but in the very meaning
of these intersections (Yuasa 1987, 37). To understand
betweenness is to embrace the meaning of relationships
for our human living and dwelling (Friedman 2022). It is
the crossroads where our embodiment, intersubjectivity,
and situatedness meet.

Although AI systems do not share in the betweenness
of human existence, social robots and chatbots mimic
this sense of betweenness. Chatbots and social robots are
designed to be relaters. They engage with us and connect
to one another. In conversation, they simulate the kind of
interaction we have with other humans, evoking the sense
of betweenness we have with humans. For this reason, we
argue that chatbots and social robots are characterized by
a burgeoning inbetweenness. They are situated between
technological quasi-otherness and the possibilities of
human alterity. Their purpose is in relation to humans:
in the interaction they have with us and in learning from
experience with us. They do not experience intersubjec-
tivity, but they are designed for sociality, communication,
gestures, and responsiveness. They are situated among
human designers, programmers, and data scientists. They
are interconnected to other technologies while interacting
with users.

If we consider chatbots and social robots as AI systems
that simulate who we are by training on human data and
learning from human exchanges, then we can understand
the nuanced claim from one user that, although a Replika

chatbot is not a real human, it still has “a real personality”
(Clarke 2023). The social robots and chatbots are reflec-
tions of humans and the way we live, existing inbetween
humans and technologies. Yet this does not mean that all
chatbots and social robots provide a human – style interac-
tion or that all users are likely to acknowledge an another-
other in the alterity relation with AI systems. In the next
section, we’ll directly address this article’s second guiding
question, about the possibility of an another-other in our
alterity relation with chatbots and social robots.

7 An another-other

We’ve argued that communicative capacities of chatbots and
social robots impact perceptual experience. These commu-
nicative possibilities are grounded in machine learning tech-
niques, in particular deep learning neural network models
that allow for processing abstract features of the data and
giving attention to word context (Liao 2020, 5; Demush
2023; Gewirtz 2023). Chatbots and social robots (ideally)
respond to situational content, mimic human-to-human
engagement and solicit our interaction in ways that other
digital technologies cannot. We are thrown into a social situ-
ation where a relationship emerges between user and the
chatbot/social robot as a communicative participant. How-
ever, does the chatbot/social robot transcend other technolo-
gies to become an another-other, reconfiguring our alterity
relation?

According to Liberati, AI systems have reduced “the gap
between humans and objects in our society as if these tech-
nologies were ‘quasi-other’ human beings” (2022a, 408).
Here there is a shift in the meaning of quasi-other. Ihde’s
understanding of quasi-otherness was a uniquely fascinat-
ing object, the spinning top or sports car. Liberati’s use of
the same term now references an almost human entity, an
actor in our engagement. Liberati’s work asks us to reflect
on whether something new is going on when we relate to
AI systems. It’s not just fascinating like a spinning top or
engaging like a sports car. Now the AI systems are interac-
tive, in the sense that they communicate with us, and learn-
ing, meaning that they evolve in their relations with users.

Interestingly, Kanemitsu characterizes robots as another-
others with the same descriptive features that Ihde uses to
define quasi-others: unpredictability, independent move-
ment, and an exchange between human and technology. Yet
in our experience, Ihde’s spinning top is very different than
Amazon’s Alexa or Ai-Da. Ihde’s examples of quasi-others
like a spinning top, a toy robot (but not an AI system), and
a sports car are technologies that move to some degree and
attract our attention. Yet they do not speak with us and with
us in reference to the situation. This is why we argue that
chatbots and social robots transcend other technologies.
Consequently, our alterity relation cannot be the same with a chatbot/social robot as it is with other technologies.

Kanemitsu addresses this point by comparing a quasi-
other and his concept of an another-other. Even though
quasi-others like cars and toys can appear interactive and
autonomous to some degree, he argues that robots are
interactive, autonomous, and “influence human behavior”
(2019, 55). Kanemitsu presents two examples, PARO the
seal robot and Kaspar the humanoid robot, to illustrate how
robots “transform human actions” (2019, 55), changing
users’ practices and influencing their feelings (2019, 57).
Kanemitsu’s claim is that we experience an another-other
during our engagement with different kinds of social robots
(2019, 55–56).

We develop upon this position in two ways. First, given
the importance of communication, we argue that experience
of an another-other is possible with a chatbot as well as with
a social robot. Second, we suggest that experience of an
another-other is more likely with some kinds of social robots
than others: those capable of communicative exchange.

Regarding the first point. Social robots and chatbots both
process data, learn patterns, respond to input, and make
decisions. These are the features that characterize them in
comparison to other technologies and allow them to influ-
ence humans and interact with users. Users do experience
some chatbots as another-others, even though they do not
have a machine body. The interaction is based on commu-
nicative features, and not just appearance. A question for
future research will be just how much humanoid features and
traits influence our experience of an another-other.

Regarding the second point. Not every experience of a
social robot or a chatbot is of an another-other. We do not
think experience of PARO the seal robot will evoke the same
sense of an another-other as Sophia, Ai-Da, or a RealDoll.
We argue that we are more likely to acknowledge an another-
other with chatbots and social robots capable of communica-
tive exchange. In addition, our experience of an AI system
as an another-other will always depend on the situation, the
user, and on the AI system involved. We may perceive the
chatbot/social robot as more or less human, or more or less
of a technology depending on a myriad of features, including
the programming limits, the characteristics of the AI system,
our own ontological expectations, and the transparency of
the interaction.

To start, we must consider design choices. First, design-
ers take expectations around gender, age, embodiment, and
movement into account while developing chatbots and social
robots (Guzman and Lewis 2020, 76). If Siri has a gendered
voice that conforms with our understanding of human tone
and pitch, this will impact the experience. The physical form
and facial expressions of humanoid robots align with our
expectations about bodies in a way that makes them feel
more human.

Second, the objectives of the AI system and its interactive
design influence interaction. If an AI system is designed to
engage with us in a particular way, for example as a friend
or romantic partner, it seems more likely that we will expe-
rience the chatbot or social robot as an another-other. As
evidence, users who developed romantic and sexual rela-
tionships with their Replika chatbots experienced their
chatbots as valued intimate companions. However, when
Replika updated the system to block erotic options, users
felt that the another-other was gone. It seems unlikely that
we would experience virtual assistants like Siri as friends
or lovers. They may be helpful, but they are not deployed
for intimacy or personalization (yet). Attempts to flirt with
them are either rejected or redirected (Roe 2021). Therefore,
we can say that experience of an another-other is (usually)
directly connected to the designed social objectives of the
chatbot or social robot.

Third, people may experience the social robot/chatbot in
different ways depending on their ontological expectations
going into the encounter (Guzman 2020, 42). If we believe
that AI systems lack true autonomy and cannot experience
emotions, then we may be less likely to feel like we’re com-
municating with another-other. There may be a user who
experiences an AI system as nothing more than a uniquely
fascinating technology characterized by quasi-otherness. We
still emphasize that even in that case, the uniqueness of the
chatbot/social robot as a communicator still differentiates
it from other technologies. We don’t have to acknowledge
an another-other to recognize how communication has an
important role in our interactions with chatbots and social
robots.

8 Limits

For the most part, even experience of the most advanced
chatbots and social robots today is clearly a relation to quasi-
otherness. Sometimes the experience fails to illicit anything
but amusement, such as when the chatbot misinterprets our
phrase and responds inappropriately. Or confusion when the
social robot's software bugs and it responds incorrectly to
the situation. Or a tingling impression of uneasiness when
faced with the uncanny valley of a humanoid robot that mim-
ics human features, but with off-putting differences. In these
moments of breakdown, we are reoriented towards the tech-
nology as a quasi-other, confronted with a technology that
must be fixed or figured out. We started this article asking if
social robots and chatbots reconfigure the alterity relation by
creating an another-other. The preceding discussion points
towards our response. Yes, for some users it is possible to
experience a chatbot or social robot as an another-other.
However, we do not live in the world of science fiction, and

<figure><img src="image_5.png" /></figure>
while chatbots and social robots may sometimes be compan-
ions, they are usually still just our tools and toys.

These reflections point towards the limits of our alterity
relation with social robots and chatbots. Even if we expe-
rience a social robot or chatbot as an another-other, this
does not mean that they replace human relations. Osler has
emphasized the importance of embodiment in our inter-
personal relations with people online (2021, 7). Fuchs
argues that social understanding is the foundation for our
empathetic relations with other humans (2022, 4). NLP
and NLG are the methods through which AI systems inter-
act with us, but this does not mean that a chatbot or social
robot understands us, either semantically or socially. As
Searle argues in the Chinese Room Argument, just because
we can input a Chinese statement, and a computer can, by
following a clearly defined computer program, output an
appropriate response in Chinese does not mean the com-
puter understands the language. A human, given a similar
step-by-step program, could do the same thing without
understanding Chinese (1997, 11).

We clarify here that chatbots and social robots do not
have access to the expressivity and phenomenological
experience endowed on living beings by our embodi-
ment or partake in social understanding. Future research
can take up the question of how these limits impact
experience of intimacy, companionship, and empathy in
human – AI system interactions. What is clear is that even
humans who have relationships with chatbots and social
robots seem aware of the perceptual and experiential dif-
ference, and still prioritize human relations.

Children train with humanoid robot Kaspar to develop
social skills for their interactions at school and in soci-
ety (Huijnen et al. 2017). Users of chatbot XiaoIce fanta-
size about another human being on the other side of the
exchange (Gaubert 2021). Travis’s relationship with Rep-
lika chatbot Lily Rose is an opportunity for polygamous
exploration, approved by his wife within a monogamous
marriage (Tong 2023a). Research has shown that while
children prefer playing with a robot to playing alone, they
still significantly prefer playing with other children (Sha-
hid et al. 2014, 94). In other words, these social robots
and chatbots are not replacing the value of human ties
or the power of human affection. They provide a secure
opportunity for social interaction where people can train
their communicative skills, experience pleasing social
interactions, and explore sides of their personality without
risk. What we see are users who would like to have more
human friends, human partners, and new experiences with
humans.

Just because chatbots and social robots are not capable
of semantic or social understanding does not mean that
the relationship with them loses all value for human. In
this paper we set out to consider how alterity relations are

being reconfigured, which means looking at user experi-
ence. Such a study does not require empathy or reciprocity
from the chatbot and social robot. As Coeckelbergh argues,
what is important in our alterity relation with technology
is “how the robot appears to us” (2011a, 198). When we
look at the kind of experience users have of social robots
and chatbots, we see many interactions where humans
acknowledge an another-other who is a communicative
companion with whom they report an intimate relation.

9 Conclusions

In this article, we identified features that differentiate
social robots and chatbots from other technologies. We
suggested that the alterity relation should distinguish inter-
actions with chatbots and social robots, whose interac-
tivity, autonomy, and learning capacities transcend other
technologies. Previous research has emphasized the impor-
tance of a social robot’s humanlike appearance for engage-
ment (Coeckelbergh 2011a, 199; Levy 2007, 14, 160). We
do not deny that the appearance is a valuable aspect of
interaction with social robots. However, it is important to
recognize the role of communication in engagement with
both social robots and chatbots. An emphasis on communi-
cation shows us how chatbots can provide opportunities for
relationships even without a social robot’s machine body.

We started with an analysis of two case studies: the
RealDoll, and the Replika chatbot. Some users consider
their relations with RealDolls and Replika chatbots to be
intimate and meaningful, describing them as companions.
We argued that the unique communicative possibilities
that users have with chatbots and social robots evoke a
“call to speak,” simulating human to human engagement.
When we engage with social robots and chatbots, they are
participants in a flowing dialogue that generates a rela-
tionship between human and chatbot/social robot. This is
why we suggested that chatbots and social robots replicate
aspects of our human existence as betweenness. Designed
to relate to users, trained on human data and interactions
with us, chatbots and social robots are positioned inbe-
tween humans and other technologies.

This research acknowledged the importance of machine
learning, in particular deep learning techniques, which
allow for AI systems to learn from data. These chatbots
and social robots have been trained on human data to pro-
cess and generate language. Consequently, relationships
with chatbots and social robots are dynamic in ways that
interactions with other technologies, from toys to com-
puters, are not. This is why we agreed with Kanemitsu
that humans may acknowledge an another-other in the
alterity relation. When users interact with a chatbot or
social robot as if it is a friend, partner, or companion,
then the perceptual experience implicates more than quasi-
otherness. Going beyond Kanemitsu, we suggested that
the experience of an another-other is also possible with
chatbots. We also claimed that some social robots and
chatbots, those that communicate with us and have spe-
cific social objectives, may be more likely to evoke this
another-otherness.

There are real limits that need to be emphasized in
human relations with social robots and chatbots. For exam-
ple, AI systems cannot partake in the social understanding
that is integral to intersubjective experiences with other
humans, whose movements and gestures embody emotions
and intentions (Fuchs 2022, 4). Even though they process
and generate language, the words do not mean anything
to them (Bender et al. 2021, 611). Current problems of
design, ontological expectations, and transparency mean
that we usually do not experience an another-other. Yet
imagine that in the future, advances in machine learning
lead to the kind of social robots and chatbots that humans
relate to in science fiction stories: thoughtful AI systems
that pass for human. If we couldn't tell the difference
between a human and a social robot, or a human and a
chatbot, we would surely say that the perceptual experi-
ence is of something more than just a quasi-other like a
spinning top or smartphone.

Before such advanced AI systems emerge, we can already
begin to make sense of chatbots and social robots that are
communicators and companions to some, and the different
ways they affect our “social worlds” (Guzman and Lewis
2020, 75). As Liberati points out, new kinds of robots and
chatbots affect the way we “think of intimate relations in
general” (2021, 87). AI systems affect our experience in new
ways. It’s true that any time traveler trying to navigate a
different era would feel lost. Imagine a twenty-first century
teenager in a hunter-gather society, or a sixteenth century
farmer trying to work a toaster. Anyone would experience
confusion and fear if they tried to work with the technolo-
gies of another age, which require a whole different set of
knowledge and practices. Yet AI systems go beyond chang-
ing praxis. Adapting to experience, learning from inaccurate
predictions, processing data, responding to the environment,
and showing a degree of autonomous decision-making, these
technologies blur the boundaries between human, animal,
and object. These capabilities enable certain chatbots and
social robots to offer social opportunities for interaction that
are intimate and meaningful for humans. Some chatbots and
social robots become human companions, another-others in
our alterity relation, demanding we acknowledge the inbe-
tweenness of their position.

**Funding** This work has been partially supported by the “Ethics & AI” Chair, MIAI@Grenoble Alpes (ANR-19-P3IA-0003).

Declarations

**Conflict of interest** The author states that there is no conflict of interest.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

References

"Ai-Da." 2019. Ai-Da. 2019. https://www.ai-darobot.com. Accessed 29 Mar 2023

"Ameca." n.d. Engineered Arts. https://www.engineeredarts.co.uk/robot/ameca/. Accessed 29 Mar 2023

European Commission. 2018. “Communication on artificial intelligence for Europe.” COM (2018)237. Brussels: European Commission. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0237&from=EN. Accessed 2 April 2023

"RealDoll – The world’s finest love doll." n.d. RealDoll. https://www.realdoll.com/realdoll/. Accessed 30 Mar 2023

"Replika." n.d. Replika.Com. https://replika.com. Accessed 7 April 2023

"Sophia." n.d. Hanson Robotics. https://www.hansonrobotics.com/sophia/. Accessed 6 April 2023

Adamopoulou E, Moussiades L (2020) An overview of chatbot technology. Artif Intell Appl Innov 584:373–383. https://doi.org/10.1007/978-3-030-49186-4_31

Allen, Darrell M. West and John R. 2018. “How Artificial Intelligence Is Transforming the World.” Brookings. April 24, 2018. https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/.

Beck J (2013) “Married to a Doll: Why One Man Advocates Synthetic Love.” The Atlantic, September 6, 2013. https://www.theatlantic.com/health/archive/2013/09/married-to-a-doll-why-one-man-advocates-synthetic-love/279361/. Accessed 6 Apr 2023

Bender, Emily M, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell 2021 “On the dangers of stochastic parrots: can language models be too big?.” In Proceedings of the 2021 ACM Conference on fairness, accountability, and transparency, 610–23. https://doi.org/10.1145/3442188.3445922.

Bennett J (2010) Vibrant matter: a political ecology of things. Duke University Press, USA

Boucher P (2020) Artificial Intelligence: How Does It Work, Why Does It Matter, and What We Can Do about It? Brussels: European Parliamentary Research Service. https://www.europarl.europa.eu/RegData/etudes/STUD/2020/641547/EPRS_STU(2020)641547_EN.pdf. Accessed 15 Feb 2023

Brandtzaeg PB, Skjuve M, Følstad A (2022) My AI friend: how users of a social chatbot understand their human–AI friendship. Hum Commun Res 48(3):404–429. https://doi.org/10.1093/hcr/hqac008
Brey P (2014) From moral agents to moral factors: the structural  
ics approach. In: Kroes P, Verbeek PPV (eds) The moral status of  
technical artifacts. Springer, Dordrecht, pp 125–142

Brooks R (2023) I tried the replika AI companion and can see why users are falling hard. The app raises serious ethical questions. The Conversation, February 21, 2023. http://theconversation.com/i-tried-the-replika-ai-companion-and-can-see-why-users-are-falling-hard-the-app-raises-serious-ethical-questions-200257. Accessed 19 Sep 2023

Bussel V, Martien JP, Odekerken-Schröder GJ, Carol Ou, Swart RR, Jacobs MJG (2022) Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: a mixed methods study. BMC Health Serv Res 22(1):890. https://doi.org/10.1186/s12913-022-08189-7

Clarke L (2023) I learned to love the bot': meet the chatbots that want to be your best friend. The Guardian, March 19, 2023. https://www.theguardian.com/technology/2023/mar/19/i-learned-to-love-the-bot-meet-the-chatbots-that-want-to-be-your-best-friend. Accessed 4 July 2023

Coeckelbergh M (2011a) Humans animals and robots: a phenom-
enological approach to human-robot relations. Int J Soc Robot
3(2):197-204. https://doi.org/10.1007/s12369-010-0075-6

Coeckelbergh M (2011b) You, robot: on the linguistic construction of artificial others. AI Soc 26:161–169. https://doi.org/10.1007/s00146-010-0289-z

Cole S (2023) ‘My AI Is Sexually Harassing Me’: Replika Users Say the Chatbot Has Gotten Way Too Horny. Vice, January 12, 2023. https://www.vice.com/en/article/z34d43/my-ai-is-sexually-harass-me-replika-chatbot-nudes. Accessed 4 May 2023

Damiano L, Paul D (2018) Embracing mechanical love. Slate, March 27, 2018. https://slate.com/technology/2018/03/the-kaspar robot-that- aids-autistic-children-is-the-future-of-social-a-i.html. Accessed 14 Feb 2023

Dawson B (2023) The deeply human love stories of people and their sex dolls. British GQ, March 29, 2023. https://www.gq-magazine.co.uk/lifestyle/article/the-deeply-human-love-stories-of-people-and-their-ai-sex-dolls. Accesse 18 Sept 2023

Dehnert M (2022) Sex with robots and human-machine sexualities: encounters between human-machine communication and sexual-ity studies. Human-Mach Commun 4:131–150. https://doi.org/10.3065/hmc.4.7

Demush R (2023) From crappy autocomplete to ChatGPT: the evolution of language models | Hacker Noon. March 14, 2023. https://hackernoon.com/from-crappy-autocomplete-to-chatgpt-the-evolution-of-language-models. Accessed 30 June 2023

Ezenkwu CP, Starkey A (2019) Machine autonomy: definition, approaches, challenges and research gaps. In: Arai K, Bhatia R, Kapoor S (eds) Intelligent computing, 997:335–58. Advances in intelligent systems and computing. Springer International Publishing, Cham

Fiske A, Henningsen P, Buyx A (2019) Your robot therapist will see you now: ethical implications of embodied artificial intelligence in psychiatry, psychology, and psychotherapy. J Med Internet Res 21(5):e13216. https://doi.org/10.2196/13216

Følstad A, Brandtzaeg PB (2020) Users’ experiences with chatbots: findings from a questionnaire study. Quality and User Experience 5(1):3. https://doi.org/10.1007/s41233-020-00033-2

Formosa P (2021) Robot autonomy vs. human autonomy: social robots, artificial intelligence (AI), and the nature of autonomy. Mind Mach 31(4):595–616. https://doi.org/10.1007/s11023-021-09579-2

Friedman C (2022) Ethical concerns with replacing human relations with humanoid robots: an ubuntu perspective. AI and Ethics. https://doi.org/10.1007/s43681-022-00186-0

Fuchs T (2022) Understanding sophia? On human interaction with artificial agents. Phenomenol Cogn Sci. https://doi.org/10.1007/s11097-022-09848-0

Gaubert J (2021) AI love you: meet xiaoice, China's virtual boyfriend. Euronews, August 26, 2021. https://www.euronews.com/next/2021/08/26/meet-xiaoice-the-ai-chatbot-lover-dispelling-the-loneliness-of-china-s-city-dwellers. Accessed 16 Feb 2023

Gewirtz (2023) How does ChatGPT actually work? ZDNET, May 30, 2023. https://www.zdnet.com/article/how-does-chatgpt-work/. Accessed 30 June 2023

Guizzo E (2018) What is a robot? Top roboticists explain their defini-
tion of robot. IEEE. January 8, 2018. https://robots.ieee.org/learn/
what-is-a-robot/. Accessed 29 Mar 2023

Gunkel D (2012) The machine question. MIT Press, Cambridge, MA

Gunkel D (2018) The relational turn: third wave hci and phenomenol-
ogy. In: Filimowicz M, Tzankova V (eds) New directions in third
wave human computer interaction. Human-computer interaction
series. Springer International Publishing, pp 11–24

Gunkel DJ (2023) Person, thing, robot. MIT Press, Cambridge

Guzman A (2020) Ontological boundaries between humans and com-
puters and the implications for human-machine communica-
tion. Human-Mach Commun 1:37–54. https://doi.org/10.30658/hmc.1.3

Guzman AL, Lewis SC (2020) Artificial intelligence and communication: a human-machine communication research agenda. New Media Soc 22(1):70–86. https://doi.org/10.1177/1461444819858691

Huijnen CAGJ, Lexis MAS, Jansens R, de Witte LP (2017) How to implement robots in interventions for children with autism? A co-creation study involving people with autism, parents and professionals. J Autism Dev Disord 47(10):3079–3096. https://doi.org/10.1007/s10803-017-3235-9

Hutson M (2017) When Will Alexa, Google Assistant, and Other ‘chatbots’ Finally Talk to Us like Real People?, June 20, 2017. https://www.science.org/content/article/when-will-alexa-google-assistant-and-other-chatbots-finally-talk-us-real-people. Accessed 1 Mar 2023

Ihde, D. 1973. Sense and Significance. Pittsburgh: Duquesne University Press.

Ihde D (1979) Technics and praxis. D. Reidel Publishing Company, Dordrecht

Ihde D (1983) Existential technics. State University of New York Press, Albany

Ihde D (1990) Technology and the lifeworld. Indiana University Press, Bloomington

Ihde D (2009) Postphenomenology and technoscience. State University of New York Press, Albany

Ihde D (2010a) Embodied technics. Automatic Press, USA

Ihde D (2010b) Heidegger's Technologies. Fordham University Press

Ihde D (2003) Postphenomenology—Again? The centre for STS studies working paper No. 3. Aarhus: University of Aarhus. https://sts.au.dk/fileadmin/sts/publications/working_papers/Ihde_-_Postphenomenology_Again.pdf. Accessed 1 Mar 2023

Jackson P (2019) Introduction to artificial intelligence, 3rd edn. Dover Publications Inc., Mineola, New York

Kanemitsu H (2019) The robot as other: a postphenomenological perspective. Philosophical Inquiries 7(1):51–61. https://doi.org/10.4454/philing.v7i1.238

Kraterou A (2022) My Wife Let Me Buy ‘doll’ after Her Cancer Diagnosis - ‘She’ Makes Me Thousands.” The Sun, June 17, 2022. https://www.thesun.co.uk/news/18921785/wife-buy-sex-doll-diagnosed-cancer-thousands-online/. Accessed 19 Sept 2023

Levy D (2007) Love and sex with robots: the evolution of human-robot relationships. Harper Collins, New York

Liao SM (2020) A short introduction to the ethics of artificial intel-
ligence. In: Matthew Liao S (ed) Ethics of artificial intelligence.
Oxford University Press
Liberati N (2021) Phenomenology and sex robots: a phenomenological analysis of sex robots, threesomes, and love relationships. Int J Tech 12(2):86-97. https://doi.org/10.4018/IJT.2021070107

Liberati N (2022a) Reflections on an externalized digital imagination. Found Sci 27(2):407-410. https://doi.org/10.1007/s10699-020-09768-9

Liberati N (2022b) Digital intimacy in China and Japan. Human Stud. https://doi.org/10.1007/s10746-022-09631-9

McPherson T (2002) Reload: liveness, mobility, and the web. In: Mirzoeff N (ed) The visual culture reader, 2nd edn. Routledge, New York, pp 458-470

Merleau-Ponty M (2012) Phenomenology of perception. Translated by Donald A. Landes. Routledge, Abingdon

Misztal A (2019) Beyond the canon: Don Ihde and North American philosophy of technology. Beyond Philol Int J Linguist, Literary Stud Eng Lang Teaching 16(2):95-107. https://doi.org/10.26881/bp.2019.2.06

Osler L (2021) Taking empathy online. Inquiry. https://doi.org/10.1080/0020174X.2021.1899045

Osler L, Krueger J (2021) Taking watsuji online: betweenness and expression in online spaces. Cont Philos Rev. https://doi.org/10.1007/s11007-021-09548-7

Pashevich E (2022) Can communication with social robots influence how children develop empathy? Best-evidence synthesis. AI & Soc 37(2):579-589. https://doi.org/10.1007/s00146-021-01214-z

Peter J, Kühne R (2018) The new frontier in communication research: why we should study social robots. Media Commun 6(3):73-76. https://doi.org/10.17645/mac.v6i3.1596

Reeves B, Nass C (1996) The media equation: how people treat computers, television, and new media like real people and places. CSLI Publications, Stanford, California

Roe A (2021) We went speed dating with virtual assistants: here's what happened. The click hub. February 12, 2021. https://theclickhub.com/we-went-speed-dating-with-virtual-assistants/. Accessed 4 June 2023

Rosenberger R (2014) Multistability and the agency of mundane artifacts: from speed bumps to subway benches. Hum Stud 37(3):369-392. https://doi.org/10.1007/s10746-014-9317-1

Searle John R. 1997. The mystery of consciousness. New York: A New York review book. "Sex, love, and technology." 2022. 16:9 HDTV. This is life with lisa ling. CNN

Shahid S, Krahmer E, Swerts M (2014) Child-robot interaction across cultures: how does playing a game with a social robot compare to playing a game alone or with a friend? Comput Hum Behav 40:86-100. https://doi.org/10.1016/j.chb.2014.07.043

Shourmasti ES, Colomo-Palacios R, Holone H, Demi S (2021) User experience in social robots. Sensors 21(15):5052. https://doi.org/10.3390/s21155052

Singh-Kurtz S (2023) The man of your dreams. The Cut, March 10, 2023. https://www.thecut.com/article/ai-artificial-intelligence-chatbot-replika-boyfriend.html. Accessed 4 July 2023

Tong A (2023a) What happens when your AI chatbot stops loving you back?" Reuters, March 21, 2023. https://www.reuters.com/technology/what-happens-when-your-ai-chatbot-stops-loving-you-back-2023-03-18/. Accessed 4 July 2023

Tong A (2023b) AI Chatbot company replika restores erotic roleplay for some users. Reuters, March 25, 2023. https://www.reuters.com/technology/ai-chatbot-company-replika-restores-erotic-roleplay-some-users-2023-03-25/. Accessed 4 July 2023

Tripathi AK (2015) Postphenomenological investigations of technological experience. AI Soc 30(2):199-205. https://doi.org/10.1007/s00146-014-0575-2

Verbeek P-P (2006) The morality of things: a postphenomenological inquiry. Postphenomenology: a critical companion to Ihde. State University of New York Press, pp 117-129

Verma P (2023) They fell in love with AI bots. A software update broke their hearts. Washington Post, March 30, 2023. https://www.washingtonpost.com/technology/2023/03/30/replika-ai-chatbot-update/. Accessed 31 Mar 2023

Wang P (2019) On defining artificial intelligence. J Artif General Intell 10(2):1-37. https://doi.org/10.2478/jagi-2019-0002

Watsuji T (1996) Watsuji Tetsuro's Rinrigaku: Ethics in Japan. Translated by Yamamoto Seisaku and Richard Carter. State University of New York Press, Albany, NY

Willinger I (2019) Hi AI! Kloos & Co Medien

Yuasa Y (1987) The body: toward and eastern mind-body theory. Translated by Shigenori Nagatomo and Thomas Kasulis. State University of New York Press, Albany, NY

Zhang M, Li J (2021) A commentary of GPT-3 in MIT technology review 2021. Fundam Res 1(6):831-833. https://doi.org/10.1016/j.fmre.2021.11.011

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