Artificial hearts, since their inception, have long since been devices of great intrigue. The stories and narratives of their recipients has been as much a part of the history as the technology itself, making the user experience of an artificial heart one that is as human as the heart itself. Though examination of the marketing of medical products is nothing new, there has yet to be any study conducted within the field of artificial hearts. Since the beginning of their commercial use, artificial hearts, due to their unique indications for use, have often been subject to a particular series of challenges in regard to their marketing to consumers. In this paper, we examine the current promotional and informational materials for the two currently commercially available artificial hearts, the SynCardia Temporary Total Artificial Heart, and the Carmat Aeson. We selected patient narratives that centered on the individual experience as our focus. In these, we looked at the topoi and means of persuasion employed in the narratives used in these materials and how they reflected the user experience of the patients. Within our examination we found that as part of a website update, SynCardia's current materials were heavily abridged which frequently limited in their rhetorical quality and compromised their functionality. Within both companies’ materials, were able to find an emphasis on choice, as well as use of both kairotic and chronic aspects of time. We also found a focus on the life-extending qualities of these products in marketing, with few references to complications or the impact of the day to day to user experience to the patient.
Augmented reality (AR) and virtual reality (VR) are very different forms of media that are commonly grouped under the term extended reality (XR). This paper examines the differences of AR and VR and develops a heuristic for identifying what may be the more appropriate media form for a project. To create this heuristic, I review literature on AR and VR and present a case study where I simultaneous designed and developed AR and VR apps with similar audiences, goals, and topics. This heuristic guides designers on practical considerations of affordances, access, and asset generation as well as interaction considerations of attention to place versus alteration, attention to re-envisioning versus realism, and narrative contextualization.
The intersections of power and conspiracy rhetorics represent complexities for scholars who seek to understand social engagement and its various discursive properties. Our study addresses these complexities through the lens of facial recognition technology (FRT), analyzing how conversations on the platform X (formerly Twitter) surrounding FRT mirror discourse in other places that have been called conspiracy theories. By gathering Tweets that contain discourse about FRT and coding them using features synthesized from previous literature, we work to understand the ways that populations express valid feelings of disenfranchisement through traditionally conspiratorial rhetorical tropes. Our results highlight the importance of traditionally conspiratorial discursive features as legitimate means of critiquing powerful but obfuscated technologies and their roles in social systems. This research aims to provoke thought in the field of conspiracy by challenging scholars to consider what they would call a conspiracy theory and look deeper to see what features make it one.
As spatial computing gains focus within mobile technologies, augmented reality (AR) is a useful tool for digital publishing and communication. However, most AR platforms are cost prohibitive, limiting uptake by digital humanities practitioners and requiring end-users to download apps poses other barriers. We explain how to implement a free, open-access AR platform for browser-based AR experiences and offer considerations for integrating it into design activist projects.
This article examines the role of communication design within platforms that combine the affordances of remote sensing and artificial intelligence (AI) technologies, focusing specifically on decision support systems used for managing climate risks and disasters such as wildfire. Building upon Carroll et al.’s [65] principles for Indigenous data governance, the authors advance an original heuristic for considering the design justice [17] of smart and connected community technologies in risk management. The authors perform a heuristic evaluation [58] of one AI wildfire detection platform (AIWDP), illustrating how platforms designs might promote openness, trust, and justice.
This article addresses the critical intersection of generative AI technology and Technical and Professional Communication (TPC) practices, highlighting the urgent need for scholarly inquiry into its implications for learning, research, and workplace environments. Drawing on key conversations within TPC history, including iteration and process, theory and agency, actors and activity, and social justice, this article delves into the ethical and social ramifications of generative AI adoption. By revisiting these conversations, and framing current and future work, we aim to showcase the tools and perspectives necessary to navigate the evolving landscape of communication design with a focus on vigilance and justice. Through this exploration, TPCs must consider TPC's ongoing role in ensuring the ethical and inclusive integration of emerging technologies into both scholarly and practical contexts.
This poster reports a design process to build a research-informed allyship network to help BIPOC technical communication junior scholars articulate strategies of resilience collectively and acquire essential skills towards “a caring democracy” [15].
Building on research identifying manipulative communication design (MCD) tactics, including clickbait and dark patterns, in the 2020 U.S. election, we analyzed the interface of political emails from the 2023 Kentucky gubernatorial contest between Andy Beshear (D) and Daniel Cameron (R). This extended abstract reports study results from a critical interface analysis of 291 emails to answer the question: How does political ideology influence the use of MCD tactics? Such tactics exploit cognitive biases to gain political advantage by maximizing the extraction of donations from supporters. Five MCD tactics were prominent in both campaigns (individualization and personalization, inverted authority appeals, political culture jacking, polarizing urgency, and manipulative visual rhetoric. Our poster presentation visualizes these tactics and encourages discussion on ethical design in political communication.
This research article presents the results of an experiment with AI-generated images, using methods drawn from both UX testing and visual analysis, in which we compare images generated from two different applications (DALL-E and FireFly), using various prompting strategies and analyze them individually and collectively for biased representations and factual inaccuracies; we discuss our findings in terms of a hypothetical scenario in which we are using generative AI applications to produce an image for a website homepage. Based on the extensive instances of both biased representations and physical inaccuracies, we found the generated images unsuitable for the purpose we described. Finally, we discuss these findings in terms of the larger questions of AI use and whether technical and professional communication can be automated away.
Introduction Building from established work on wearable rhetorics and wellness culture [1-4], this project examines how audience impacts health and wellness narratives surrounding Continuous Glucose Monitors (CGMs) by exploring the following research questions: (1) How does audience impact the marketing narratives surrounding CGM usage? (2) What are the affordances and implications of the narratives told to each audience group? (3) What can this case tell us about the current state of health and wellness culture in the United States? Methods I use a modified conventional content analysis framework [5] informed by Tracy's [6] iterative content analysis and inductive coding methods to identify emerging themes across four CGM websites made up of two audience groups. Results and Discussion Audience impacted narrative content in expected ways in the Type 1 Diabetic group. However, the non-Diabetic narrative positioned CGMs as luxury wellness technologies, which points to possible trends in the larger health and wellness consumer market, especially for consumer health wearables. Conclusion This case illustrates how medical technologies are adapted for non-target audiences by adjusting preexisting narratives for a different purpose and context, centering an explicitly empowered user. Ultimately, blood glucose is positioned as an emergent health indicator for non-diabetic audiences, which excludes users who cannot afford CGMs that would benefit from preventative monitoring for Type 2 Diabetes.
This research focuses on understanding the design collaboration process through students’ reflections on working with professional clients to design interfaces. This utilizes a qualitative approach to analyze collaboration between students and clients and how these experiences influence students' perception of design, their identities as designers, and their future design work. This provides insights to designers, educators, and other stakeholders—such as non-profit and industry clients interested in leveraging students for design work— structure and organize the collaboration process for maximizing the quality of work output and learning opportunities.
When the Aurora supercomputer launches at Argonne National Laboratory it will operate at the exascale and be one of the fastest supercomputers in the world. We have been invited by Argonne to do field work to understand both the day-to-day processes that maintain supercomputing (e.g. user documentation, government reporting, user testing) and the sociotechnical national imaginaries [11], -in particular the increasingly tense global competition between the US and China in the supercomputing race-that shaped the development of Aurora. This article proposes our work-in-progress methodological approach that accounts for both higher-level imaginaries and the everyday practices of supercomputing. We also describe how our project plan is designed to answer multiple research questions: 1. What kind of new science will be possible when Aurora comes fully online? 2. What political, economic, technological, human and ideological resources has it required to build the supercomputer, bring it online, and to keep it running? 3. What does answering these questions tell us about the state of science in the US, the geopolitical race for computing power and the discursive and material infrastructures [5, 19] required for success?
Chatbots have become a popular method through which to deliver conversational-style information to users about a range of topics, including providing customer service, news and weather updates, educational content, and medical information. This article compares two chatbots created with different methods, including via custom architecture and custom GPT to determine the strengths and limitations of the development methods. The bots that our research team developed were built to deliver information about water and drought to Arizona residents. We compare the initial setup process, customization capabilities, the training process, prompt engineering requirements, file handling, costs, and outputs of each bot. The custom architecture bot offers the flexibility and control of answers, but it costs more than its comparator and takes more time. The custom GPT requires little experience with Large Language Models (LLMs) and no experience with coding, but offers less control. Because we recognize that public agencies often don't have the expertise or funding to build a fully-customized bot architecture, we conclude with suggestions about the contexts and purposes or which each type of bot should be developed.
This experience report examines how, across several stages of grant-based exhibit work, thoughtful data management processes and collaborative, community-based exhibit development can turn data points into inclusive communal experiences. This is exemplified in the development of the Creativity in the Time of COVID-19 (CC-19) Public Art Exhibit, which was funded by a Just Futures Grant from the Mellon Foundation, taking place in an abandoned Sears building in Lansing, Michigan in the spring of 2023. CC-19 examined how people from around the world creatively expressed themselves during the COVID-19 pandemic, emphasizing intersectional social justice issues. As such, accessibility was of the utmost importance, both in terms of accessibility to people with disabilities and general ease of use for all exhibit visitors. This experience report is framed through my perspective as the Label and Translations Manager for CC-19 and primarily addresses the development of interpretive materials, accessible exhibition practices, and collaborative efforts for this exhibit.
Drawing on data from two parallel IRB-approved studies, this paper examines how students incorporate AI-generated text in their TPC writing assignments. In both studies, students were coached through the process of using AI tools for specific writing tasks, including an emphasis that AI-generated text should be scrutinized for rhetorical, stylistic, and factual errors. By looking at examples of students’ work and reflections of students’ experience, the authors identify differences in AI use between successful and unsuccessful writing samples. The authors consider how these differences could challenge the notion that AI might “level the playing field” of writing skill levels. The authors conclude with four AI literacies that will be necessary to prevent further stratification of student-writers’ skills.
This project shares research into collaborative distributed work by undergraduate researchers, as part of a larger investigative team, conducted with the Corpus & Repository of Writing (Crow). This study tests the “Constructive Distributed Work (CDW)” model, a heuristic for ethical collaboration developed by Crow, to study Crow's application of the framework. Through coding a dataset pulled from a team communication platform used by Crow, we describe the collaborative processes of researchers on our team, and share information about our evolving methods for coding and analyzing the data.
This project examines do-it-yourself (DIY) fecal microbiota transplants (FMT) through the lens of tactical technical communication and rhetoric of health and medicine. While research on microbiome-related interventions like FMT is nascent, patient communities are eager for additional treatment options, leading to the proliferation of online user-generated instructional artifacts for attempting DIY FMT without medical assistance or FDA approval. Simultaneously, generative AI is transforming the information ecologies in which patients engage with medical information and pursue health-related behaviors that align or diverge from approved practices. This project investigates these divergent healthcare practices enabled by user- and AI-generated content.
Bill Hart-Davidson's “Writing with Robots” [1] describes current practices of creating augmented research and writing teams that include robots, algorithms, and other machine partners with their human collaborators in designed space. In writing about emergent workplace practices in high technology environments, we (authors Michael and John) created a team of researchers, undergraduate research interns, and robot assistants to create the forthcoming book Artificial Infrastructures. In preparing the book, we used Otter.ai [2] to transcribe interviews with three working professionals. These rough transcriptions, produced by algorithmic assistants, saved the team important resources, namely time, money, and attention. Transcription tools like Otter.ai quickly create transliterated texts—word-for-word transcripts of spoken speech. In our ensemble, transcriptions were then edited by undergraduate researchers trained using Weiss's Learning From Strangers [3] as well as practice editing transcripts of other recordings of subject matter experts. The core finding was that we, as researchers, were able to concentrate on writing our analyses and organizing book contents while our undergraduate team members remained focused and more productive than previous teams working without advanced artificial intelligence (AI) tools. Overall, it was a productive and enjoyable research process with less frustration and tedious, repetitious work, leading to more productive engagement. Our initial findings suggest that as long as researchers retain their autonomy in establishing the study agenda, and SMEs are informed how AI tools are going to be used, research can be streamlined and made more productive. We are realizing the Human-Centered Artificial Intelligence (HCAI) outlined in Shneiderman [4] in which AI becomes a “superpower.” This experience report describes how AI tools, such as Otter.ai's transcription service, played a role in our research ensemble for creating our forthcoming book Artificial Infrastructures. It outlines the research team structure, use of AI tools, and the interplay between human and algorithmic agents to create a research ensemble that gestures towards a future for the design of communication.
