Communication Technology and New Media Commons^™

The End Of Unmeasured Exploitation: How A.S.M., C.A.S., And S.I.A. Challenge Digital Attention Capitalism, Delante Clark

Graduate Scholarship and Creative Works

Digital attention capitalism generates value through the capture and monetization of human attention, yet it has historically lacked standardized mechanisms for measuring attention-related harm. This paper argues that the Attention Safeguard Models (A.S.M.), Cognitive Attentional Standards (C.A.S.), and Sociological Impact Assessment (S.I.A.) collectively challenge this system by introducing an integrated framework for classifying, measuring, and evaluating digital attention harm and its societal consequences. C.A.S. provides standardized measurement of digital attention harm, A.S.M. identifies and classifies patterns of attentional disruption and manipulation, and S.I.A. evaluates broader impacts on institutions, communities, civic engagement, education, social cohesion, and inequality. Together, these systems transform …

Tool Or Social Actor? How Ai Perception And Interaction Modality Influence Perceived Credibility Of Communicative Ai Over Time, Stefanie H. Klein, Sonja Utz

Human-Machine Communication

People increasingly interact with conversational agents based on artificial intelligence (AI) for a variety of tasks. While these communicative AI (comAI) systems often produce responses that are natural and engaging, the information they provide is not always correct and unbiased. This makes it essential to understand how users perceive the credibility of such systems. Drawing on data from four waves of a longitudinal survey (NT1 = 618, NT4 = 485), we investigated how active users’ perceptions of comAI as a tool or social actor and their primary interaction modality (text vs. voice) influence the credibility perceptions of comAI, both cross-sectionally …

The Comforting Potential Of A Social Robot, Regardless Of Looks And Designed Affordances, Peggy Van Minkelen, Elly A. Konijn

Human-Machine Communication

Two field studies examined the comforting potential of an autonomously functioning humanoid robot and whether participants formed an affective bond with it, guided by a new Human-Robot Bonding framework. We designed a 2 (Designed Humanness: high versus low) × 2 (Designed Affordances: high versus low) mixed-factorial repeatedmeasures field experiment. Participants completed a stress-inducing task, followed by an interaction with the robot, which provided comfort. We measured participants’ stress levels (objectively via heart rate and subjectively via perceived stress) and their level of Bonding with the robot. Results showed that perceived stress, but not heart rate, decreased after human-robot interaction across …

Gender And Task Alignment Influences The Credibility Of Feminine But Not Masculine Ai Conversational Assistants, Joana Videira, David Deandrea

Human-Machine Communication

The present study investigated how the perceived gender of AI conversational assistants and the tasks they perform combine to influence perceptions of AI competence, trustworthiness, and goodwill (i.e., credibility). Participants evaluated AI assistants that appeared female or male and varied in the task they performed (stereotypically feminine or masculine task). Findings did not support an overall preference for female AI assistants over male AI assistants. Rather, perceived AI gender interacted with gender stereotypes associated with the task performed to affect perceptions of AI credibility. Notably, AI perceived to be very feminine had the highest credibility when performing stereotypically feminine tasks …

The Right Kind Of Human-Like: Measuring And Testing Human-Likeness Perceptions Of Text-Based Conversational Agents, Carolin Ischen, Elizabeth Wang, Edith G. Smit

Human-Machine Communication

While conversational agents are designed with human-like features to facilitate interaction, the scholarly understanding of users’ perception of human-likeness as a key concept in human-machine communication remains underexplored. This paper provides a threelegged typology of human-likeness perceptions of text-based conversational agents, including the dimensions of appearance, capacity, and personality. Based on responses of 373 participants, the paper identifies measurement instruments for the different dimensions. Furthermore, it tests to what extent social cues commonly applied in customer service chatbots influence the different dimensions of human-likeness perception. Next to a set of direct measurements, factor analysis confirmed two indirect measurements for appearance-based …

Unexpected Encounters With Spot In The Wild: Sensemaking As Communicative Boundary Work With Robots, Annette Markham, Constanze M. Leeb, Brooke Ann Coco, Daniel Kirby, Lu Liu, Edoardo Lomi, Lucy Thornton, Kelly Ka-Lai Chan, Bradley R. Crammond

Human-Machine Communication

As near-autonomous and AI-embedded robots continue to appear in public settings, their sociality and interactivity is a critical part of the social fabric. This article presents emerging themes from a large-scale ethnographic study of granular-level public interactions between more than 400 people who have an unexpected encounter with Boston Dynamics’ robot “Spot” in a public square in Melbourne. Conceptualizing Spot as a boundary object enables us to highlight patterns of sensemaking as people grapple with ontological disruptions through micro-level interactions; within the self, with other people, or between the self and the robot. Based on thematic analysis of multimedia data …

Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design, Delante Clark

Graduate Scholarship and Creative Works

Artificial intelligence is increasingly shaping how individuals access information, make decisions, and interact with digital environments. The Cognitive Attentional Standards Platform (C.A.S.) was developed to assess attention related harms, cognitive safety, digital autonomy, and platform influence across digital systems (Clark, 2026). However, the growth of generative AI, conversational agents, and algorithmic decision support technologies has introduced new forms of influence that may not be fully captured by existing assessment domains. This paper proposes the Artificial Influence Assessment (AIA) as an expansion of the C.A.S. framework designed to measure AI mediated influence on cognition, behavior, autonomy, and information processing. Drawing on …

Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence, Delante Clark

Graduate Scholarship and Creative Works

Algorithmic recommendation systems and interface designs shape attention by combining visually salient cues with uncertain reward timing and low friction interaction. These conditions can sustain anticipatory checking, extend time on task, and reduce natural disengagement points through patterns such as infinite scrolling and autoplay. This paper synthesizes research across neuroscience, human computer interaction, behavioral economics, and artificial intelligence to argue that attention capture is a predictable outcome of incentive driven design rather than an individual failure of self regulation. It advances the Attention Safeguard Models and the Cognitive Attentional Standard as system level interventions that regulate exposure conditions, pacing, and …

Rethinking The Mindfulness And Mindlessness In Media Evocation Of Human-Machine Communication: A Case Study On The In-Car Robot “Nomi”, Bing Wang, Longxiang Luo, Weizi Liu

Human-Machine Communication

The commonly used Media Equation framework in human-machine communication research exhibits limitations when explaining human-machine relationships in the AI era, giving rise to the Media Evocation paradigm. Based on the Media Evocation framework, this study employs in-depth interviews to investigate whether interactions between humans and the in-car robot Nomi are mindful or mindless, while also examining whether these interactions prompt reflections on the machine’s ontology. The findings indicate that most participants perceive Nomi as a human-like actor and interact with it mindfully. Highquality social cues, such as voice and facial expressions, can trigger mindful anthropomorphic responses in human-machine interaction, eliciting …

Human-Machine Communication: Complete Volume. Volume 12

Human-Machine Communication

This is the complete volume of HMC Volume 12.

Normalizing Ai: The Evanishing Effect And Rethinking The Machine Heuristic, Bumju Jung, Cameron W. Piercy, Patric R. Spence

Human-Machine Communication

This study examines how people evaluate factual claims attributed to human journalists versus artificial intelligence (AI) news bots, and how these evaluations are shaped by individual endorsement of the machine heuristic. An online experiment (N = 233) used a 2 (Agent: human vs. AI) × 2 (Information Veracity: accurate vs. inaccurate) design in which participants viewed a short tweet embedded in either a human or AI profile and then rated perceptions of source credibility, objectivity, bias, and accuracy. Endorsement of an AI-focused machine heuristic was significantly associated with higher source credibility, perceived objectivity, and perceived accuracy, and lower perceived bias, …

Ai Humanizers, Pragmatists, Skeptics: A Cluster Analysis Of Normative Attitudes For Ai’S Capabilities And Roles, Kate K. Mays, Ekaterina Novozhilova

Human-Machine Communication

This study explores people’s attitudes about artificial intelligence’s (AI) capabilities through a normative lens. Drawing from literature on phenomenological, ontological, and heuristic judgments about machines, we aim to better understand what capabilities people think AI should be able to have and how that relates to enthusiasm about having AI take certain roles in their lives. Survey participants (N = 601) were grouped via two-step clustering based on their attitudes, revealing three clusters: AI humanizers, who expect empathy and social interaction from AI; AI pragmatists, who expect cognitive capabilities; and AI skeptics, who prefer AI with limited human-like traits and emphasize …

Explain. Write. Edit. Summarise: An Exploratory Study On Agency Negotiations In Student-Chatbot Conversations, Árni Már Einarsson Mr, Ekaterina Pashevich

Human-Machine Communication

LLM-based chatbots such as ChatGPT have given technologies that traditionally operated on the back end a user-friendly, conversational interface. Their rapid adoption among students has prompted universities worldwide to issue guidelines and re-examine existing practices. Supplementing prior research based on discourse analysis and self-reported measures (e.g., surveys and interviews), we propose an approach for analyzing naturally occurring student–chatbot interactions, rooted in conversation analysis of chats (n = 503) donated by eight current Danish university students. The analysis identifies conversational patterns across three main types of activities and examines how agency is negotiated across the structural dimensions of signification, domination, and …

Two Years To Madness: A 30-Month Journal Of Human–Machine Communication And Second-Hand Reality, Andrew Prahl

Human-Machine Communication

Drawing on a 30-month analytic-autoethnography of the first author’s journal as an earlyaccess OpenAI user, this study examines how sustained communication with generative AI affects everyday lived experience and identity. Inductive content analysis of 166 entries by independent coders is followed by theory-driven coding with the extended-mind and sensemaking frameworks. Three interlocking themes emerge. Enabled and Degraded captures the tension between new capabilities and efficiency versus creeping skill atrophy. Scary New World charts rising anxiety as productivity gains erode competitive and relational distinctiveness. The findings also show a growing, pervasive doubt about the human authorship of texts, images, and other …

The Material Condition: A Practice Theory-Oriented Infrastructural Turn To The Ethics Of Human-Ai Communication, Anne Mollen, Sigrid Kannengießer

Human-Machine Communication

This paper calls for an infrastructural turn in human–AI communication, centered on the materiality of generative AI. We argue that a nuanced understanding of ethical implications of generative AI necessitates examining the socio-technical infrastructures that constitute these systems. These infrastructures encompass not only technological artifacts but also human actors (developers, users, data subjects, etc.) and their practices as well as social contexts in designing, developing, implementing, and maintaining AI. Therefore, we propose to adopt a practice theory approach, to analyze how ethical concerns materialize within these infrastructures. This perspective reveals how infrastructures are contested spaces in global production chains, highlighting …

Whole Earth Machines: Human-Machine Communication For A Green Transition, Klaus Bruhn Jensen

Human-Machine Communication

The climate crisis of the 21st century represents an existential risk to humanity and biodiversity, posing essential questions of how communication may serve to coordinate mitigation of and adaptation to climate change. One recent response has been massive investments by governments and corporations in systems providing feedback on the state of Earth— Whole Earth Machines (WEMs). For human-machine communication (HMC) studies, WEMs invite sustained engagement with communication infrastructures as a key constituent of research agendas, beyond the interface encounters at the center of many HMC studies to date. The article presents a conceptualization and operationalization of WEMs as critical infrastructures …

Creation And Representation: Rhetorical Effectiveness Of Audience Construction Within The Deaf Vlogging Community, Imani Rodriguez

Honors Undergraduate Theses

Diverse minority groups use YouTube as a platform to share stories, grow brands, and develop communities online. While previous research has investigated Deaf-focused videos on YouTube, past focus has been on video genres, creator purpose, and how content engages with existing representation and stigma (Hibbard & Fels, 2011; Li et al., 2022; Souza et al., 2023; Martzos et al., 2021; Oliveira et al., 2021; Parton, 2016). There has also been research on how online communities can initiate open conversation for many minority groups that may not be possible due to location, disability, or censorship (Case, 2012).

This research focuses on …

Independent And Interacting Effects Of Co-Presence And Social Media 'Likes' On Online Disinhibition, Margaret M. Doheny

Graduate Studies Theses and Dissertations 2026

Social media platforms have fundamentally transformed interpersonal communication by creating environments in which behaviors are publicly reinforced through visible social feedback systems such as “likes.” Although prior research has linked online environments with increased disinhibition and negative behavior, existing literature has primarily focused on anonymity and invisibility as the primary mechanisms underlying these effects. However, the mechanistic role of physical and psychological co-presence in driving online disinhibition has received little empirical investigation. The central aim of the present study was to determine whether reduced social presence and the selective reinforcement of negative content contribute to online disinhibition and anticipatory reward-seeking …

Online Risk And Harm For Marginalized Users: How Social Influence Amplifies Or Mitigates Vulnerability, Tangila Islam Tanni

Graduate Studies Theses and Dissertations 2026

Social media has reshaped how people connect, communicate, and influence one another, yet these environments also create harms that disproportionately affect marginalized users. Participation in online communities can expose users to identity-based harassment, emotional distress, and the normalization of harmful attitudes, shaping identity, well-being, and participation online and offline. Prior work has documented many forms of online harm, yet less is understood about how harmful norms and behaviors are reinforced across different forms of social media interaction, from private direct messages to online communities. Guided by the Social Ecological Model, this dissertation investigates how online harms toward marginalized users emerge …

The Algorithmic Public Sphere: Ai-Generated News Site As A Conduit To Social Capital, Seungahn Nah, Xinlei Wu, Ernest Makata, Jun Luo, Ian Koratsky, David Park, Seungbae Kim

Human-Machine Communication

A growing body of scholarship on AI-generated news has examined its impact on various outcomes. However, less attention has been paid to the actual implementation of AI-generated news sites and their effectiveness on civic consequences. This study examines the effects of an AI-generated, community-centered, nonprofit news site on civic outcomes such as trust in nonprofit organizations, trust in AI-generated news, social capital, and civic engagement. Data was collected from participants at a large southeastern university who visited the AI-generated news site over a four-week period and responded to a series of open-ended questions weekly. A total of 721 open-ended responses …

Disentangling (Hybrid) Trustworthiness Of Communicative Generative Ai As Intermediary For Science-Related Information—Results From A Qualitative Interview Study, Evelyn Jonas, Esther Greussing, Monika Taddicken

Human-Machine Communication

The increasing prevalence of communicative Generative AI, such as ChatGPT, highlights their transformative potential for science communication while raising critical questions about users’ trust in these systems conveying science-related information. As perceptual hybrids these agents challenge traditional notions of trustworthiness, and it remains unclear to whom or what users refer to as the object of trust. This qualitative interview study integrates dimensions from human-machine and epistemic trustworthiness within a hybrid framework, complemented by a descriptive source orientation model. It highlights that trustworthiness assessments can extend beyond a chatbot’s interface, emphasizing the perceived salience of its underlying infrastructure, developers, and organizations. …

Generative Artificial Intelligence And Collaboration: Exploring Religious Human-Machine Communication And Tensions In Leadership Practices, Pauline Hope Cheong, Liming Liu

Human-Machine Communication

The adoption of generative artificial intelligence (GAI) applications has bolstered efforts toward human-machine collaboration. Given the lag in research on AI and religion, this study examines how pastors engage GAI to develop religious human-machine communication practices that constitute their leadership. Findings from in-depth interviews with pastors in the U.S. reveal that they view GAI as an idea generator, research assistant, co-author and translator. Clergy enact multiple ways to incorporate GAI communication in religious education and to enhance sermonic performances. Concurrently, pastors perceive tensions between innovation and established rites, as they contend with the authenticity and spiritual depth of GAI content …

Tools Or Teammates? Examining Agency Negotiation In Human-Genai Collaboration In Creative Work, Yuan Sun, Ignacio Fernandez Cruz, Donggyu Kim

Human-Machine Communication

As Generative AI (GenAI) becomes increasingly integrated into creative work, creative professionals face an emerging dilemma: while they can leverage powerful AI capabilities through prompts, the automated process also introduces uncertainties and risks. This study, based on semi-structured interviews with 18 creative professionals, explores their experiences and perceptions of using GenAI tools in creative work. The findings revealed that GenAI’s perceived adaptability, creativity, and scalability enhanced sense of agency in the creative process. Conversely, limitations in customizability, uncertainty, and feedback mechanisms undermined human agency. These perceptions were influenced by users’ conceptualization of GenAI—as either a simple tool or a collaborative …

Investigating The Persuasive Potential Of Communicating With Generative Artificial Intelligence Chatbots For Mental Health: The Roles Of Perceived Message Contingency, Cognitive Elaboration, And Issue Involvement, Hanyoung Kim, Yanyun (Mia) Wang

Human-Machine Communication

With the ever-increasing adoption of generative artificial intelligence (GenAI) chatbots in diverse communication roles, there is a burgeoning need to address how people process and respond to messages from these technologies. This study explores the theoretical mechanisms by which the use of GenAI chatbots influences persuasive outcomes related to mental health, examining perceived message contingency and cognitive elaboration as mediators, and issue involvement as a moderator between the two mediators. Through an experimental setting using ChatGPT, compared to non-conversational online resources, we discovered that GenAI chatbot use led to greater cognitive elaboration through an increased sense of message contingency, leading …

Generative Ai In Higher Education: A Comparative Study Of Chatgpt Adoption, Perception, And Use Among College Students In The Global North And Global South, Shudipta Sharma, Louisa Ha

Human-Machine Communication

Generative AI tools like ChatGPT have become the fastest-adopted technology, raising concerns about its misuse in education. This study explores ChatGPT usage for class assignments among 646 college students in the U.S. and Bangladesh, focusing on their perceptions and trust in the tool. Using the technology acceptance model, along with internet efficacy and social persuasion theories, we found that students in both countries had high levels of awareness and adoption. Individual factors did not significantly influence ChatGPT usage, while social persuasion, perceived usefulness, perceived ease of use, and country were the strongest predictors. The findings suggest that AI technology may …

Making Sense Of The Role Of Chatgpt In Education: An Examination Of Student Views In China, Italy, Kenya, Uruguay, And The U.S., Leopoldina Fortunati, Autumn P. Edwards, Weiming Ye, Anna Maria Manganelli, Chad Edwards, Soledad Caballero, Lusike Mukhongo, Giovanni Ferrin

Human-Machine Communication

This article investigates the diffusion and adoption of ChatGPT among college students from a multinational convenience sample, informed by the scholarly literature on the diffusion and progressive appropriation of ChatGPT by students and teachers within the education sector and the strategies adopted by academic institutions. We applied a figurational approach to this study, offering two theses that try to understand the societal meaning of ChatGPT diffusion in the educational sector. Operationally, we explored university students’ behavioral intentions, practices of use, and opinions toward ChatGPT in five countries (China, Italy, Kenya, Uruguay, and the United States of America) through an online …

Coding Openai In An Open-Sourced Code Sharing Platform: Exploring The Collaboration Networks On Chatgpt Projects On Github, Jingyi Pu, Xinzhi Zhang

Human-Machine Communication

Amid rapid advancements in generative AI (GenAI) tools, individuals and organizations—including both professional and amateur developers—are actively sharing and collaboratively developing GenAI code on open-source platforms, driving the adaptation and creation of new applications. However, it remains unclear whether such collaboration disrupts existing technological hierarchies or reinforces them; addressing this question is crucial for assessing the democratizing potential of open-source practice and informing policies for equitable innovation. Drawing on world-systems theory, we examine owner-contributor networks in ChatGPT-related GitHub repositories since ChatGPT’s launch in late 2022, complemented by qualitative content analysis of major repository themes and code functions. We find that …

Creepy, Invasive, And Exploitative Algorithms: A Cpm Analysis Of Users' Privacy Breakdowns And Recalibration Practices With Social Media Algorithms, Matthew J. A. Craig, Jeffrey T. Child

Human-Machine Communication

Social media content filtering algorithms can both provide desired personalized content and ads for users. However, sometimes these recommendations can resemble individual private information. How might users navigate these experiences to best manage their private information? The present exploratory study utilizes the rules- and systems-based framework of communication privacy management (CPM) theory to explore social media users’ experiences of privacy breakdowns with social media algorithms and investigates what users do in response to said breakdowns. These responses were refined using content analysis and divided into different categories of privacy breakdowns and recalibration strategies. Implications for future research surrounding human-machine communication …

The Hai-Io Model: A Framework For Understanding The Human-Ai Communication Process, Rae Francis Quilantang

Human-Machine Communication

The increasing integration of artificial intelligence (AI) into daily life calls for new theoretical frameworks that capture human-AI interaction’s dynamic, feedback-driven nature. Traditional models treat AI as a passive medium, overlooking its adaptive capabilities. This paper proposes the Human-AI Interaction Outcomes (HAI-IO) model, an interdisciplinary framework synthesizing human-machine communication, social exchange theory, dialogue systems, and computational feedback models like cybernetics and reinforcement learning. The HAI-IO model frames interaction as iterative and bidirectional—AI adapts through predictive processing while users adjust based on AI feedback. This mutual adaptation shapes trust, engagement, and system optimization. The model informs AI system design, user education, …

College Students’ Perceptions Of Artificial Intelligence (Ai) Risks And Benefits In Pakistan, Rauf Arif, Muhammad Ittefaq, Lamia Zia

Human-Machine Communication

With the rapid advancements in technology over the past 2 decades, it has become crucial to understand people’s attitudes toward artificial intelligence (AI) adoption and its associated risks. Given the increasing access to the AI technologies, it is imperative to examine how young people in non-Western societies like Pakistan perceive AI risks and benefits. We conducted an online survey of college students who had used AI technology in the past 6 months. The results of our study indicate that the majority of college students view AI technology positively and perceive it as an opportunity to enhance workplace productivity. In addition, …