ArticlePDF Available
EDITORIAL
https://doi.org/10.1007/s11616-022-00754-8
Publizistik
Human-machine-communication: introduction to the
special issue
Katrin Etzrodt · Peter Gentzel ·SonjaUtz · Sven Engesser
Accepted: 18 October 2022
© The Author(s) 2022
The natural point of departure for an editorial of a special issue on Human-Machine
Communication (HMC) is the question of what HMC is. Addressing this question
is not an easy task, as it is inherently linked to the more fundamental and general
question of what communication is. The definition of communication, in turn, shapes
the identity of an entire scholarly field and is thus subject to a vibrant and continuous
debate. We do not aim at intensifying or complicating this debate but rather at
providing an operational definition of HMC, which is merely supposed to serve as
a framework for the special issue.
1 Definition of human-machine communication
In our view, communication can be regarded as the process of at least two enti-
ties “sharing” (Schramm 1954) something, suggesting an act of “bringing together”
(Cobley 2008). These entities, in our context, are humans on the one hand, and
machines or “digital interlocutors” (Edwards and Edwards 2017, p. 487) on the
other hand. What they share is widely conceived of as messages or compilations
of symbols. These messages are encoded, decoded and interpreted (cf. Schramm
The authors Katrin Etzrodt and Sven Engesser have contributed equally to this introduction.
Katrin Etzrodt · Sven Engesser
Institut für Kommunikationswissenschaft, Technische Universität Dresden, Dresden, Germany
E-Mail: katrin.etzrodt@tu-dresden.de
Peter Gentzel
Department Medienwissenschaft und Kunstgeschichte & Department Digital Humantitis & Social
Studies, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Sonja Utz
Leibniz-Institut für Wissensmedien, Eberhard Karls Universität Tübingen, Tübingen, Germany
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K. Etzrodt et al.
1954) by both humans and machines. By exchanging and interpreting the messages,
humans and machines engage in “meaning-making” (Guzman 2018,p.17),estab-
lish “relationships” (Spence 2019, p. 285; Knorr Cetina 1997), or display social
behavior (Reeves and Nass 1996). These processes can be conceptualized as merely
unidirectional (from humans to machines) or bidirectional.
Any agency originating from machines may be partly observed intersubjectively
(across observers) and partly attributed to them subjectively by the human commu-
nicators resulting in “hybrid constellations of inter-agency” (Rammert 2012, p. 15).
For our operational definition, it is not relevant to address the philosophical questions
if machines act intentionally, truly comprehend the meaning of the messages, or are
completely equivalent to humans. We are also aware of the recent social theoretical
development toward relational concepts of subjectivity and the related problemati-
zations of humans’ intentionality, consciousness, and agency (Gentzel 2019). For
our operational definition, however, it is sufficient that humans socially engage with
machines (Geser 1989).
HMC is also embedded in different layers of social context, similar to mass media
(Shoemaker and Reese 2014). Among them are a micro-level layer containing the
social situation and immediate reality of the communicators (e.g., Suchman 2007;
Etzrodt 2022), a meso-level layer where institutions and organizations are located
(e.g., Carlson 2015), and a macro-level layer encompassing societal structures and
systems (e.g., Howard 2015). HMC is influenced by these layers and influences them
in complex interdependencies. For instance, the presence of additional communi-
cators, professional routines, regulatory structures, or public discourse may affect
HMC and vice versa. Against this backdrop, we define HMC as a process of mes-
Fig. 1 Model of Human-Machine Communication
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Human-machine-communication: introduction to the special issue
sage exchange between humans and machines, and its associated meaning-making,
relationships, and social behavior, embedded in different layers of social context on
micro level, meso level, and macro level (see Fig. 1).
2 Relevance of human-machine communication
Why is it time for a special issue on HMC in Publizistik? On the one hand, there
has been a proliferation of HMC as an object of investigation. Digital interlocutors,
such as Artificial Intelligence (e.g., Gunkel 2020; Guzman and Lewis 2020; Schäfer
and Wessler 2020; Sundar and Lee 2022), avatars (e.g., Banks and Bowman 2016),
chatbots (e.g., Araujo 2018; Edwards et al. 2014; Brandtzaeg and Følstad 2017;
Gehl and Bakardjieva 2017), voice-based assistants (e.g., Etzrodt and Engesser 2021;
Humphry and Chesher 2021; Natale and Cooke 2021), and social robots (e.g., Hepp
2020; Fortunati 2018; Peter and Kühne 2018) are on the rise. As a result, we are
witnessing a profound change, in which communication through technologies is
extended by communication with technologies (cf. Guzman and Lewis 2020). Thus,
the study of HMC is essential for socially and practically relevant communication
and media studies—and it implies several theoretical, empirical, and methodological
challenges, such as applying, changing, or reconceptualizing approaches.
On the other hand, the scholarly field of HMC has increasingly taken shape.
Recent milestones have been Steve Jones’ programmatic piece in 2014, Andrea
Guzman’s (2018) seminal anthology, the special section on the topic in Computers
in Human Behavior edited by Patric R. Spence (2019), the establishment of the
Human-Machine Communication journal under the auspices of Autumn Edwards,
Chad Edwards, Leopoldina Fortunati, and Patric R. Spence, as well as the formation
of the HMC interest group within the International Communication Association
lead by founding chair, Andrea Guzman. HMC has started as an interdisciplinary
field. It combines approaches from the social sciences, humanities, and engineering
sciences. It also integrates other scholarly fields, such as Human-Robot Interaction
(HRI), Human-Computer Interaction (HCI), and others (cf. Guzman 2018; Spence
2019). As a result, HMC is inherently inclusive and multifaceted. However, in order
to be institutionally successful and to generate a cumulative epistemological gain,
a framework of common research questions, theories, and methods needs to be
further established. This is where this special issue comes into play.
3 Content of the special issue
With the call for this special issue, we attempted to map HMC research and to
provide an overview of trends within this widely dispersed field. In addition to
current research subjects, theories, findings, and methods in HMC, we were also
looking for specific challenges and avenues for future research.
As a result, the special issue has gathered nine contributions: four theoretical
papers (Hepp et al.; Dickel & Dogruel; Mooshammer; Edwards et al.), one method-
ological paper (Greussing et al.), and four empirical studies—two of them drawing
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on qualitative methods (van der Goot; Wassmer & Schwarzenegger) and two of
them employing quantitative methods (Bastiansen et al.; Weidmüller et al.). None
of the empirical studies explicitly focuses on the exchange of messages between hu-
mans and machines. Instead, Bastiansen et al., van der Goot et al., and Wassmer &
Schwarzenegger place emphasis on meaning-making, while Weidmüller et al. bring
relationships to machines (i.e. trustworthiness) to the fore.
Several authors suggest broadening the field: Some argue that HMC scholars
should not only take the mere exchange of messages into account but also the social
context (Hepp et al.; Dickel & Dogruel). Others reach out toward journalism studies
(Mooshammer), computer-mediated communication (Weidmüller et al.), and inter-
personal communication (Bastiansen et al.; Edwards et al.). The empirical studies,
the methodological contribution, and one theoretical paper (Edwards et al.) focus on
the micro level of HMC, Mooshammer addresses the meso level, and the papers of
Hepp et al. and of Dickel & Dogruel deal with implications of HMC on the macro
level.
Andreas Hepp, Wiebke Loosen, Stephan Dreyer, Juliane Jarke, Sigrid Kan-
nengießer, Christian Katzenbach, Rainer Malaka, Michaela Pfadenhauer, Cornelius
Puschmann, and Wolfgang Schulz take up the challenge of defining the research
field of automated communication. The authors argue for complementing the anal-
ysis of direct interaction processes between humans and machines with the entire
spectrum of social communication processes. By reconstructing the transformation
of communication through the integration of “communicative AI”, the contribution
sensitizes the readers to the breadth and depth of this transformation process at the
micro, meso and macro level.
Sascha Dickel and Leyla Dogruel argue that communication with chatbots, voice
assistants, and social robots is already part of our social reality. From that start-
ing point, the essay proposes a conceptualization of HMC, which converges on
a symmetric relationship between human and machine communicators. In devel-
oping their model, the authors adopt Knoblauch’s (2017) sociological approach
of “Kommunikativierung”, which they trace back to three drivers: the decrease of
human control over the communication process, the increase of the simulation of
human mediation of meaning, and the discursive attribution of communication to
machines.
Sandra Mooshammer introduces Rammert and Schulz-Schaeffer’s (2002)ap-
proach of gradualized action within socio-technical constellations to HMC by us-
ing the example of automated journalism. Thus, the author provides a conceptual
framework for differentiating between levels of agency in the broader context of
communication. By referring to automated journalism, the paper offers a theoreti-
cally grounded differentiation of human and machine agency and disentangles the
use of the term “automation” in this regard.
Autumn Edwards, Andrew Gambino, and Chad Edwards address the question of
whether concepts from theories on interpersonal relationships can be adapted to
human-machine relationships. Using the example of attraction, the essay explores
the peculiarities of the relationship between humans and machines compared to the
human “gold standard”. They identify tensions in constructs such as aesthetics or
personality, similarities concerning physical attraction, and a distinct peculiarity of
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Human-machine-communication: introduction to the special issue
machines in terms of being more available and visually appealing or configurable
than humans. Based on these explorations the authors discuss further avenues for
research.
Esther Greussing, Franziska Gaiser, Stefanie Helene Klein, Carolin Straßmann,
Carolin Ischen, Sabrina Eimler, Katharina Frehmann, Miriam Gieselmann, Char-
lotte Knorr, Angelica Lermann Henestrosa, Andy Räder, and Sonja Utz summarize
the challenges in the methodological conception of HMC research that focuses on
the interactions between humans and machines. They differentiate between research
on chatbots, smart speakers, and robots—machines that differ in modalities (written
text vs. voice) and degree of embodiment. The paper focuses mainly on quantitative,
in particular, experimental research because it is confronted with several challenges
that do not apply to qualitative studies, such as the decision between using simu-
lated or real interactions. The authors aim to provide a guideline for researchers by
outlining the caveats of the various methods.
Margot van der Goot explores the concepts of source orientation, anthropomor-
phism, and social presence, which are crucial for understanding users’ entity percep-
tions when interacting with AI-enabled technologies such as text-based chatbots. By
using a qualitative methodological approach, these concepts are explored and delin-
eated from each other. The findings challenge CASA’s understanding that assumes
source orientation to be a constant, the ascription of certain cues as exclusively hu-
man characteristics, and the labeling of mindful and mindless anthropomorphism.
Furthermore, not all participants felt the presence of another entity, challenging the
emergence of a communication situation in the first place.
Marlene Wassmer and Christian Schwarzenegger investigate the epistemological
principles that guide users’ actions during their communication with smart speakers.
Employing a qualitative methodological approach, they found that smart speakers
challenge the classic media repertoire by being a peripheral part, primarily used for
easy tasks but differing from other media due to their ambivalent role between object
and subject, interlocutor and device, and a higher presence during use. Furthermore,
the authors demonstrate that how the sensemaking of smart speakers translates into
use is ambivalent and sometimes even contradictory.
Mathilde Bastiansen, Anne C. Kroon, and Theo Araujo demonstrate how the trans-
fer of theoretical concepts and standard research methods from interpersonal inter-
actions can inform empirical research in HMC by investigating the effect of gender
stereotypes on interpersonal trust in text-based chatbots. The absence of signifi-
cant effects in the study underlines how difficult the transfer of theoretical and
methodological concepts from human contexts to HMC is. Furthermore, it raises
the question of whether gendered chatbots are so different from humans that stereo-
typing does not manifest itself in a similar manner as it does in human-to-human
interactions.
Finally, Lisa Weidmüller, Katrin Etzrodt, and Sven Engesser empirically inves-
tigate the trustworthiness of voice-based assistants. The authors analyze how in-
fluencing factors related to the interlocutor function and factors meaningful to the
intermediary function of voice-based assistants contribute jointly to the prediction
of trustworthiness. The findings demonstrate that considering both functions of the
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voice-based assistant—the communicator and the medium—provides a better un-
derstanding of trust in this new technology.
Although we were privileged to attract a wide range of contributions with our
call, the field of HMC is even more diverse. We are aware that the special issue
does not cover all of its aspects and bears some biases, one of the most evident
concerning the nationalities of the authors who work in Austria, Germany, Hong
Kong, the Netherlands, and the US.
4 Challenges and avenues for research
The contributions provideinsight into the current challenges posed by the emergence
and proliferation of digital interlocutors, which concerns our understanding of these
machines and how we interact with them but also has implications for the discipline
as a whole by contesting traditional conceptions of communication, being human,
and social behavior.
Definitional and ontological First of all, questions of how communication with
machines can be defined, and whether or not this is communication in the first
place arise. Closely related to these questions is the ontological definition of the
machine as a communicator. Although communication and its neighboring disci-
plines have dealt with these questions extensively, fundamental problems remain to
be unsolved. In particular, it is unclear if there is an ontological threshold where
the machine changes from a tool/medium to a communicator and if so, how it can
be determined. There are at least three ways to approach this threshold: (1) from
atechnological perspective through characteristics inherent to the machine, such as
degrees of automation, (2) from a psychological perspective through perceptions of
the human communicators, and (3) a sociological perspective through the defini-
tion of the situation and the social context. HMC is challenged to acknowledge and
integrate these three perspectives.
This leads to another important question: How do changing HMC practices and
HMC theories interact with general conceptions of subjectivity? This is not merely
an academic gimmick because the social relevance of the social sciences is linked
to their potential for critical analyses of observable processes and phenomena. Sev-
eral traditional critical concepts (e.g., culture industry, alienation, acceleration) have
been reserved for humans alone because those are regarded as the only sovereign
subjects capable of reflecting on and critiquing social realities. More simply: Our
understanding of what machines and subjects are and what HMC is should not
be limited to observation and description but needs to (re)formulate standards to
evaluate machines beyond observable success or failure.
Theoretical There is a scarcity of theories in HMC. As a relatively new field,
not many theories have had sufficient time to develop. Already existing theories are
frequently derived from interpersonal communication or from computer-mediated
communication. Even the Media Equation framework (Reeves and Nass 1996), one
of the theoretical cornerstones of HMC, largely draws on findings from interper-
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Human-machine-communication: introduction to the special issue
sonal communication. Such theories bear the challenge that it is frequently an open
question if and how they can be transferred and generalized to HMC. Therefore,
HMC should invest in developing and testing theories of its own that are specifically
tailored to the communication with digital interlocutors.
From a theoretical and conceptual perspective, it is also vital to keep in mind
and systematically reflect on a seemingly contradictory movement: While HMC
scholars convincingly argue that human communication as the only “gold standard”
for concept and model development can be dysfunctional, this “gold standard” seems
to be exactly the point of orientation for design and further development of robots
(e.g., child schema with a round face and big eyes to trigger psychological and
emotional effects) or voice-based assistants (e.g., to perform small talk practices).
Thus, a challenge for HMC will be to specify this tension and explore appropriate
solutions.
Methodological Digital interlocutors as objects of research also pose major
methodological challenges. First, maybe even more than in other areas of commu-
nication research, they imply a combination of qualitative and quantitative methods.
On the one hand, they frequently offer large datasets for quantitative analyses. On
the other hand, their novelty and complexity often call for qualitative methods.
Second, the complexity of digital interlocutors, such as voice assistants or robots
require even more technical and methodological skills from the communication
scholars than digital media (Greussing et al.).
Integration of micro level, meso level, and macro level A large proportion of
empirical HMC research focuses on the micro level. This is also the case in our
special issue, with papers examining chatbot cues (Bastiansen et al.; van der Goot)
or the trustworthiness of smart speakers (Weidmüller et al.). The theoretical papers,
in contrast, often take a meta perspective and also address the broader impacts of
HMC on the societal level (Dickel & Dogruel; Hepp et al.). As our model shows,
the implications of HMC also transcend to the meso and macro level. A challenge
for future work is to take these effects into account in empirical studies and, ideally,
integrate them through multi-level approaches.
Again, practical social and political challenges are evident. One example is the
increasing spread of the Internet of Things in Smart Homes or Smart Cities. Digi-
tal interlocutors such as artificial companions, voice-based assistants, or robots and
their AI-supported systems will increasingly become the interfaces for complex in-
formation, distribution and supply systems. For this reason, HMC should be equally
accessible for all groups of actors (e.g., young and old, rich and poor, integrated or
marginalized).
Interaction with neighboring fields of research The proliferation of digital in-
terlocutors in all areas of society also affects neighboring scholarly fields, such
as journalism studies and computer-mediated communication. Another challenge
for HMC is the interaction with these fields and to engage them in a meaningful
exchange that generates common knowledge and demonstrates the contribution of
HMC to these fields and vice versa.
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K. Etzrodt et al.
Finally, the relevance of critical conceptions such as surveillance capitalism
(Zuboff 2019), platform society (van Dijck et al. 2018) or data colonialism (Couldry
and Mejias 2019) for HMC becomes apparent because the producers of, for example,
voice-based assistants, such as Google Assistant, Apple’s Siri, or Amazon’s Alexa,
are big technology companies which operate platforms and collect large quantities
of data. Thus, it is plausible that the economic interests of these companies influence
the design of digital interlocutors through the selection and prioritization of con-
tent, affordances, and communication opportunities. Thus, HMC needs to take these
normative questions into account. A closer dialogue between the research fields
may also focus on the “decoding process” of machines and automated communica-
tion, for example, the quantitative and qualitative expansion for data collection and
processing.
Funding Open Access funding enabled and organized by Projekt DEAL.
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from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.
0/.
References
Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and com-
municative agency framing on conversational agent and company perceptions. Computers in Human
Behavior,85, 183–189. https://doi.org/10.1016/j.chb.2018.03.051.
Banks, J., & Bowman, N.D. (2016). Avatars are (sometimes) people too: Linguistic indicators of parasocial
and social ties in player-avatar relationships. New Media & Society,18(7), 1257–1276. https://doi.org/
10.1177/1461444814554898.
Brandtzaeg, P.B., & Følstad, A. (2017). Why people use chatbots. In I. Kompatsiaris, J. Cave, A. Sat-
siou, G. Carle, A. Passani, E. Kontopoulos, S. Diplaris & D. McMillan (Eds.), Internet science, 4th
International Conference, INSCI 2017, Thessaloniki, Greece, November 22–24, 2017 Proceedings
(pp. 377–392). Cham: Springer. https://doi.org/10.1007/978-3-319-70284-1_30.
Carlson, M. (2015). The robotic reporter: Automated journalism and the redefinition of labor, composi-
tional forms, and journalistic authority. Digital Journalism,3(3), 416–431. https://doi.org/10.1080/
21670811.2014.976412.
Cobley, P. (2008). Communication: Definitions and concepts. In W. Donsbach (Ed.), The international
encyclopedia of communication Vol. II. Malden: Blackwell. https://doi.org/10.1002/9781405186407.
wbiecc071.
Couldry, N., & Mejias, U.A. (2019). The costs of connection. How data is colonizing human life and ap-
propriating it for capitalism. Stanford: Stanford University Press. https://www.sup.org/books/title/?
id=28816
van Dijck, J., Poell, T., & de Waal, M. (2018). The platform society. Oxford: Oxford University Press.
https://doi.org/10.1093/oso/9780190889760.001.0001.
Edwards, A., & Edwards, C. (2017). The machines are coming: Future directions in instructional com-
munication research. Communication Education,66(4), 487–488. https://doi.org/10.1080/03634523.
2017.1349915.
Edwards, C., Edwards, A., Spence, P.R., & Shelton, A. K. (2014). Is that a bot running the social media
feed? Testing the differences in perceptions of communication quality for a human agent and a bot
K
Human-machine-communication: introduction to the special issue
agent on Twitter. Computers in Human Behavior,33, 372–376. https://doi.org/10.1016/j.chb.2013.
08.013.
Etzrodt, K. (2022). The third party will make a difference—A study on the impact of dyadic and triadic so-
cial situations on the relationship with a voice-based personal agent. International Journal of Human-
Computer Studies.https://doi.org/10.1016/j.ijhcs.2022.102901.
Etzrodt, K., & Engesser, S. (2021). Voice-based agents as personified things: Assimilation and accom-
modation as equilibration of doubt. Human-Machine Communication,2, 57–76. https://doi.org/10.
30658/hmc.2.3.
Fortunati, L. (2018). Robotization and the domestic sphere. New Media & Society,20(8), 2673–2690.
https://doi.org/10.1177/1461444817729366.
Gehl, R. W., & Bakardjieva, M. (Eds.). (2017). Socialbots and their friends: Digital media and the automa-
tion of sociality. New York: Routledge. https://doi.org/10.4324/9781315637228.
Gentzel, P. (2019). Materialität, Technik und das Subjekt: Elemente kritischer Kommunikations- und Me-
dienanalyse [Materiality, technology, and the subject: elements of critical communication and media
analysis]. In P. Gentzel, F. Krotz, J. Wimmer & R. Winter (Eds.), Das vergessene Subjekt. Subjektkon-
stitutionen in mediatisierten Alltagswelten [The forgotten subject. Subjects in mediatized everyday
worlds] (pp. 87–113). Wiesbaden: Springer VS. https://doi.org/10.1007/978-3- 658-23936-7_5.
Geser, H. (1989). Der PC als Interaktionspartner [The PC as interaction partner]. Zeitschrift für Soziologie,
18(3), 230–243. https://doi.org/10.1515/zfsoz-1989-0305.
Gunkel, D. (2020). An introduction to communication and artificial intelligence. Cambridge: Polity Press.
Guzman, A. L. (2018). Introduction: “What is human-machine communication, anyway?”. In A. L. Guz-
man (Ed.), Human-machine communication: Rethinking communication, technology, and ourselves
(pp. 1–28). New York: Peter Lang. https://doi.org/10.3726/b14399.
Guzman, A. L. , & Lewis, S. C. (2020). A rtificial intelligence and communication: A human-machine
communication research agenda. New Media & Society,22(1), 70–86. https://doi.org/10.1177/
1461444819858691.
Hepp, A. (2020). Artificial companions, social bots and work bots: Communicative robots as research
objects of media and communication studies. Media, Culture & Society,42(7–8), 1410–1426. https://
doi.org/10.1177/0163443720916412.
Howard, P. N. (2015). Pax technica: How the internet of things may set us free or lock us up.NewHaven:
Yale University Press. https://doi.org/10.12987/9780300213669.
Humphry, J., & Chesher, C. (2021). Preparing for smart voice assistants: Cultural histories and media
innovations. New Media & Society,23(7), 1971–1988. https://doi.org/10.1177/1461444820923679.
Jones, S. (2014). People, things, memory and human-machine communication. International Journal of
Media & Cultural Politics,10(3), 245–258. https://doi.org/10.1386/macp.10.3.245_1.
Knoblauch, H. (2017). Die kommunikative Konstruktion der Wirklichkeit [The Communicative Construc-
tion of Reality, engl. translation in 2019]. Wiesbaden: Springer VS. https://doi.org/10.1007/978- 3-
658-15218-5.
Knorr Cetina, K. (1997). Sociality with objects: Social relations in postsocial knowledge societies. Theory,
Culture & Society,14(4), 1–30. https://doi.org/10.1177/026327697014004001.
Natale, S., & Cooke, H. (2021). Browsing with Alexa: Interrogating the impact of voice assistants as web
interfaces. Media, Culture & Society,43(6), 1000–1016. https://doi.org/10.1177/0163443720983295.
Peter, J., & Kühne, R. (2018). The new frontier in communication research: Why we should study social
robots. Media and Communication,6(3), 73–76. https://doi.org/10.17645/mac.v6i3.1596.
Rammert, W. (2012). Distributed agency and advanced technology—Or: How to analyze constellations of
collective inter-agency. In J.-H. Passoth, B. Peuker & M. Schillmeier (Eds.), Agency without actors?
(pp. 89–112). New York: Routledge. https://doi.org/10.4324/9780203834695.
Rammert, W., & Schulz-Schaeffer, I. (2002). Technik und Handeln: wenn soziales Handeln sich auf men-
schliches Verhalten und technische Artefakte verteilt [Technology and action: when social action is
distributed between human behavior and technical artifacts]. In W. Rammert & I. Schulz-Schaeffer
(Eds.), Können Maschinen handeln?: Soziologische Beiträge zum Verhältnis von Mensch und Technik
[Can Machines act?: Sociological contributions to the relationship between humans and technology]
(pp. 11–64). Frankfurt a.M.: Campus.
Reeves, B., & Nass, C. I. (1996). The media equation: How people treat computers, television, and new
media like real people and places. Cambridge: Cambridge University Press.
Schäfer, M. S., & Wessler, H. (2020). Öffentliche Kommunikation in Zeiten künstlicher Intelligenz [Public
communication in times of artificial intelligence]. Publizistik,65, 307–331. https://doi.org/10.1007/
s11616-020-00592-6.
K
K. Etzrodt et al.
Schramm, W.E. (1954). The process and effects of mass communication. Urbana: University of Illinois
Press.
Shoemaker, P. J., & Reese, S. D. (2014). Mediating the message in the 21st century: A media sociology
perspective. New York: Routledge. https://doi.org/10.4324/9780203930434.
Spence, P.R. (2019). Searching for questions, original thoughts, or advancing theory: Human-machine
communication. Computers in Human Behavior,90, 285–287. https://doi.org/10.1016/j.chb.2018.09.
014.
Suchman, L. A. (2007). Human-machine reconfigurations: Plans and situated actions. Cambridge: Cam-
bridge University Press. https://doi.org/10.1017/CBO9780511808418.
Sundar, S. S., & Lee, E. J. (2022). Rethinking communication in the era of artificial intelligence. Human
Communication Research,48(3), 379–385. https://doi.org/10.1093/hcr/hqac014.
Zuboff, S. (2019). The age of surveillance capitalism. The fight for a human future at the new frontier of
power. London: Profile.
Katrin Etzrodt is a research assistant and Ph.D. candidate at the Chair of Science and Technology Com-
munication at TU Dresden.
Peter Gentzel is an Assististant Professor of Digital Transformation of Media Communication at FAU
Erlangen-Nürnberg.
Sonja Utz is a Professor of Communication Via Social Media at the University of Tübingen and the head
of the Everyday Media lab at Leibniz-Institut für Wissensmedien Tübingen.
Sven Engesser is a Professor of Science and Technology Communication at TU Dresden.
K
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Voice assistants such as Siri, Alexa, and Google Assistant have recently been the subject of lively debates in regard to issues such as artificial intelligence, surveillance, gender stereotypes, and privacy. Less attention, however, has been given to the fact that voice assistants are also web interfaces that might impact on how the web is accessed, understood and employed by users. This article aims to advance work in this context by identifying a range of issues that should spark additional reflections and discussions within communication and media studies and related fields. In particular, the article focuses on three key issues that have to do with long-standing discussions about the social and political impact of the internet: the role of web platforms in shaping information access, the relationship between production and consumption online, and the role of affect in informing engagement with web resources. Considering these issues in regard to voice assistants not only helps contextualize these technologies within existing debates in communication and media studies, but also highlights that voice assistants pose novel questions to internet research, challenging assumptions of what the web looks like as speech becomes one of the key ways to access resources and information online.
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The aim of this article is to outline ‘communicative robots’ as an increasingly relevant field of media and communication research. Communicative robots are defined as autonomously operating systems designed for the purpose of quasi-communication with human beings to enable further algorithmic-based functionalities – often but not always on the basis of artificial intelligence. Examples of these communicative robots can be seen in the now familiar artificial companions such as Apple’s Siri or Amazon’s Alexa, the social bots present on social media platforms or work bots that automatically generate journalistic content. In all, the article proceeds in three steps. Initially, it takes a closer look at the three examples of artificial companions, social bots and work bots in order to accurately describe the phenomenon and their recent insinuation into everyday life. This will then allow me to grasp the challenges posed by the increasing need to deal with communicative robots in media and communication research. It is from this juncture from where I would like to draw back on the discussion about the automation of communication and clearly outline how communicative robots are more likely than physical artefacts to be experienced at the interface of automated communication and communicative automation.
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In this provocative, consequential book, Couldry and Mejias theorize the dynamics of change in contemporary capitalism as grounded in a new form of data colonialism. They conceptualize the distinctive nature of data colonialism as appropriating myriad aspects of human life as the raw material for capitalism. Data colonialism thus extends the process of commodification into new spheres of social life. This includes all areas of social activity where data are appropriated for profit; they range from work to education, health care, economic transactions, and social media. As we engage in these diverse activities, corporations treat these various kinds of data as “‘just there’, freely available for extraction and the release of its potential for humankind” (Couldry and Mejias 2019, 9). Such corporate appropriation of contemporary data is similar to historical claims to land as belonging to no one under earlier forms of colonialism. In developing this argument, the authors draw persuasively on a 2011 World Economic Forum report that refers to personal data as a resource as valuable as oil, because of its ability to fuel economic processes. They delineate intriguing parallels between historical processes of colonial expansion by taking over land and other natural resources and contemporary processes of mining personal data as inputs for capitalism.
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Public communication is changing—a change manifested in a crisis of legacy media’s business models, the proliferation of new channels of communication and increasingly individualized media repertoires, among other things. Often, these changes are associated with sociotechnical innovations, i.e. with novel ideas, methods and applications emerging from the interaction of technical infrastructures and technologies with human action. It was suggested, for example, that users’ ability to configure their own information sources and content in mobile and social media led to the creation of echo chambers, that algorithmic curation on search engines and social networks resulted in filter bubbles, or that social bots led to an over-representation of certain public positions and a higher prevalence of mis- and disinformation in public debates.In this essay, we criticize the reaction of communication science to these developments and its role in the corresponding scientific and public discussions: Communication science too often imports problem diagnoses from the outside, limits itself to the post hoc description and measurement of these phenomena, and excludes relevant contexts of their origin. In addition, too little knowledge from our discipline makes its way into public debate, and only few communication scientists dare to make regulatory proposals, or are even perceived as relevant providers of such proposals.This is problematic in two respects: Firstly, it hampers communication science’s standing in the concert of academic disciplines. Its current mode of analysis means that the discipline is often late in defining social problems, and consequently leaves agenda setting to other disciplines or actors. On the one hand, this opens the door to questions about the relevance and analytical value of communication science as a discipline. On the other hand, it leads to simplified views or misinterpretations of social phenomena which could be avoided if expertise from communication science had been included earlier, but is difficult to remedy after the fact.Secondly, it is also problematic for the cognitive core and epistemological perspective of communication science. If we analyze sociotechnical innovation and its effects detached from its origins, the values and institutional logics inscribed into these innovations are “blackboxed”: they move into the blind spot of our discipline.We argue that communication science should pay more attention to sociotechnical innovations that are (potentially) relevant to public communication. This demand could have been made for early innovations like the printing press or the telegraph already, but is more urgent for digital innovations, which proliferate more quickly, permeate almost all areas of life, and influence human interaction directly and deeply. To do so, it is necessary to incorporate sociotechnical innovations into the conceptual foundations of public communication that has, so far, mostly taken structural and cultural conditions into account. It is necessary to broaden this conceptualization, and to assess the socio-techno-cultural foundations of public communication. This includes the actor constellations around sociotechnical innovations, e.g. financiers, potential customers, programmers, researchers, but also regulators, and users. It also encompasses innovation practices, such as decisions on the development, testing and implementation of innovations, involving a variety of “systems of thought, finance, politics, legal codes and regulations, materialities and infrastructures, institutions [and] inter-personal relations” (Kitchin). And it includes technical artefacts, e.g. hardware and software affordances which enable and limit pathways of action.The endeavor we propose can stand on the shoulders of several seasoned and recent approaches from within and outside communication science: Within communication science, it should make use of recent approaches in ethnographic journalism research which analyzes the organizational makeup and procedural workings of newsrooms. This strand of research produces “thick descriptions” of a social context that is decisive for public communication, using multi-methodical, primarily qualitative approaches and a quasi-ethnographic perspective. Similarly, the “Pioneer Communities” approach may be instructive. Its focus on “communities” that are relevant for public communication extends the view beyond journalism and facilitates a prospective, future-oriented perspective.Beyond our discipline, social constructivist approaches from science and technology studies, namely “Social Construction of Technology” (SCOT) approaches and “reflective technology assessment” are promising. Both emphasize the social embedding and construction of technologies, with a historical and a forward-looking perspective, even though they do not focus strongly on public communication.Finally, a re-orientation of communication science can benefit from interventionist innovation research. “Values in Design” approaches combine ideas from science and technology studies with influences from computer science and philosophy, arguing that technology and innovation design can already have moral consequences and trying, accordingly, to inscribe desirable values in technologies. “Critical Data Studies” examine the social processes underlying the generation, analysis and use of data. Like “Values in Design”, it aims to reconstruct how social contexts shape technology or data, and to improve the respective practices.A re-oriented communication science can learn from all of these approaches. Overall, we plead for a contextualized, theory-generating and cooperative research process, which would strengthen the explanatory power and future viability of communication scholarship.
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Smart voice assistants have become popular thanks largely to their default naturalistic female voices and helpful personae. In this article, we trace changes in robot voices in popular culture and explain how this history influenced the voice design of smart voice assistants. Our research draws on cultural analysis of Hollywood and international films, television and literature, and observations from our personal experiences with voice assistants. We argue that designers of devices like the Google Home and Amazon Echo inherited a cultural imaginary of alien and dangerous robots with artificial voices and personalities. Manufacturers leveraged techniques of modality, personae and invocation and pre-existing social connotations of the voice to create positive associations of these devices in the home. We conclude by arguing that smart voice assistants are new media innovations prepared for consumers through pre-domestication and represent an emerging regime of power and influence based on technologised voice interaction.
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Individuals all over the world can use Airbnb to rent an apartment in a foreign city, check Coursera to find a course on statistics, join PatientsLikeMe to exchange information about one’s disease, hail a cab using Uber, or read the news through Facebook’s Instant Articles. In The Platform Society, Van Dijck, Poell, and De Waal offer a comprehensive analysis of a connective world where platforms have penetrated the heart of societies—disrupting markets and labor relations, transforming social and civic practices, and affecting democratic processes. The Platform Society analyzes intense struggles between competing ideological systems and contesting societal actors—market, government, and civil society—asking who is or should be responsible for anchoring public values and the common good in a platform society. Public values include, of course, privacy, accuracy, safety, and security; but they also pertain to broader societal effects, such as fairness, accessibility, democratic control, and accountability. Such values are the very stakes in the struggle over the platformization of societies around the globe. The Platform Society highlights how these struggles play out in four private and public sectors: news, urban transport, health, and education. Some of these conflicts highlight local dimensions, for instance, fights over regulation between individual platforms and city councils, while others address the geopolitical level where power clashes between global markets and (supra-)national governments take place.