As noted in my previous editorial, this semester I've been adjusting to my new role as CDQ 's Editor-in-Chief. It has been rewarding working with Associate Editor Casey McArdle on our first issue together. In keeping with CDQ 's roots, Casey has been spearheading a comprehensive review of our in-house and public-facing documentation and streamlining our production processes. He also helped to shoulder the load associated with copyediting and producing the articles for this exciting issue. Later in this editorial, you'll hear more from Casey about generative artificial intelligence (GenAI), pedagogical trust, bridges between academia and industry, and accessibility as a core design competency. Meanwhile, I've been settling into my new role as Associate Professor and Chair of Professional and Public Writing at the University of Rhode Island, reconnecting with old friends, and making trips to the shore where I've observed firsthand how the coastline has changed. On clear days, it is now possible to identify windmills on the horizon offshore.

Content analysis is a common research method in technical and professional communication (TPC) journals. But TPC content analyses often lack intercoder reliability (ICR) statistics, possibly due to the lack of resources required to train human coders. This proof-of-concept study explores the viability of replacing a second coder with a generative AI tool to calculate an ICR. Using three previously published studies, I calculated a Krippendorff's alpha for various data types and various codebooks using non-modified versions of five popular generative AI tools. While the tools could code TPC data, most tools did not produce alphas strong enough to replace human coders. While it is premature in most cases to replace human coders with generative AI tools to calculate an ICR, generative AI may prove to be useful to researchers as a means of codebook and unit of analysis refinement prior to human coding.

The first time I recall encountering artificial intelligence was in the early 2000s while working in a recording studio. After singing a take of a song, I watched as an engineer opened a plug-in called Auto-tune and then listened as he worked on tuning my vocals. I recall him explaining to me that the vocal had to be pretty close to the note I was trying to sing, otherwise the tuned version would sound fake. He demonstrated by tuning my vocal too sharp and then too flat. The sound of the stressed vocal created a distorted tremolo effect, with maybe even a bit of delay. It no longer sounded like me. It sounded like a robot who was impersonating me. I bristled. "No, not like that," I said uncomfortably laughing. "That doesn't sound like me."

Have you ever wondered how a researcher from the periphery can gain an enduring foothold in the pantheon of researchers from the center? This essay will attempt to answer that question. Halcyon Lawrence was a researcher, writer, and professor from the Global South who has made a mark on a community of technical communication scholars, writers, researchers, and professors with her widely discussed research articles dealing with the pros and cons, perils and promises, boon and bane of speech recognition tools and technology. Lawrence's research explores the thickets of speech recognition and proposes strategic and revisionary measures toward neutralizing the lopsided corpora of speech recognition software, vaporware, and artificial intelligence (AI)-powered technology. To crystalize her contributions to justice, data justice, and racial-linguistic justice, I chose a chapter, "Siri Discipline," she (2021) wrote for the book Your Computer is on Fire (Mullaney et al, 2021). My essay highlights how her ideas have gained more traction in relation to the current disruption of the AI revolution (Gopal, 2020). That disruption is often exemplified through ChatGPT, a platform that shows how Lawrence's core insight from "Siri Discipline" can have a direct bearing on normative frameworks being developed to address burgeoning challenges ushered in by the AI revolution.

In this article, we propose (re)designing privacy literacy as an essential component of our digital lives in an age of Generative Artificial Intelligence (genAI). Our study emphasizes the layered digital, technical, rhetorical, and algorithmic literacies associated with design thinking and genAI to support theorizing privacy literacy. We introduce Design as an analytical element complementary to Woods and Wason's (2021) multi-pronged framework for analyzing Terms of Service (ToS) documents. Using a cluster of Adobe Generative AI ToS, we illustrate the necessity of including Design , which allows those invested in Communication Design (CD) and Technical and Professional Communication (TPC) to interrogate how or if design supports or undermines values related to user privacy, data ownership, and informed consent. We conclude by detailing how collective surveillance apathy regarding emergent data infrastructures signal a Post-Surveillance era in our global society and digital lives.

In this article, we propose (re)designing privacy literacy as an essential component of our digital lives in an age of Generative Artificial Intelligence (genAI). Our study emphasizes the layered digital, technical, rhetorical, and algorithmic literacies associated with design thinking and genAI to support theorizing privacy literacy. We introduce Design as an analytical element complementary to Woods and Wason's (2021) multi-pronged framework for analyzing Terms of Service (ToS) documents. Using a cluster of Adobe Generative AI ToS, we illustrate the necessity of including Design , which allows those invested in Communication Design (CD) and Technical and Professional Communication (TPC) to interrogate how or if design supports or undermines values related to user privacy, data ownership, and informed consent. We conclude by detailing how collective surveillance apathy regarding emergent data infrastructures signal a Post-Surveillance era in our global society and digital lives.

Have you ever wondered how a researcher from the periphery can gain an enduring foothold in the pantheon of researchers from the center? This essay will attempt to answer that question. Halcyon Lawrence was a researcher, writer, and professor from the Global South who has made a mark on a community of technical communication scholars, writers, researchers, and professors with her widely discussed research articles dealing with the pros and cons, perils and promises, boon and bane of speech recognition tools and technology. Lawrence's research explores the thickets of speech recognition and proposes strategic and revisionary measures toward neutralizing the lopsided corpora of speech recognition software, vaporware, and artificial intelligence (AI)-powered technology. To crystalize her contributions to justice, data justice, and racial-linguistic justice, I chose a chapter, "Siri Discipline," she (2021) wrote for the book Your Computer is on Fire (Mullaney et al, 2021). My essay highlights how her ideas have gained more traction in relation to the current disruption of the AI revolution (Gopal, 2020). That disruption is often exemplified through ChatGPT, a platform that shows how Lawrence's core insight from "Siri Discipline" can have a direct bearing on normative frameworks being developed to address burgeoning challenges ushered in by the AI revolution.

The first time I recall encountering artificial intelligence was in the early 2000s while working in a recording studio. After singing a take of a song, I watched as an engineer opened a plug-in called Auto-tune and then listened as he worked on tuning my vocals. I recall him explaining to me that the vocal had to be pretty close to the note I was trying to sing, otherwise the tuned version would sound fake. He demonstrated by tuning my vocal too sharp and then too flat. The sound of the stressed vocal created a distorted tremolo effect, with maybe even a bit of delay. It no longer sounded like me. It sounded like a robot who was impersonating me. I bristled. "No, not like that," I said uncomfortably laughing. "That doesn't sound like me."

In the wake of the controversy surrounding the new AI chatbot application, ChatGPT, I wonder how Logie would seek to include this new technology in his work. I ponder this because, throughout the book, Logie presents compelling evidence for why the concepts of invention, composition, and internetworked writing should be embraced and not feared. While some denounce the application and take to social media to disparage the possible negative impact on students, creativity, and composition, ChatGPT, I believe Logie would argue, would be a powerful tool we can implement to become "composers." He believes that through cloud computing services we are now more apt to collaborate, use, remix, and create rhetorical modes that extend far beyond the formulaic argument, therefore we are composers. So, Logie applies the idea of a composer as someone who is a "prosumer" (Toffler). This composer is media literate and transforms traditional rhetorical canons into multimodal compositions such as memes, Google Docs, and digital collages. However, his overarching argument is that internetworked writing tools have democratized writing through that same offering of innovative outlets. His book is arranged in a way that walks the reader through this argument.

As artificial intelligence (AI) automates technical and dialogic processes, technical communicators produce value through articulating complex problems, facilitating new forms of participation, and managing user-generated content via experience architecture. Automated and intelligent agents are least able to grasp the context of experiences, requiring human input/feedback for maximum performance. The examples we trace both prepare communities to embrace AI as part of the available information infrastructure and create an automated infrastructure of intelligent augmented action. Following Star's anthropological investigation of infrastructure, we analyze organizational examples where rhetoric entangles AI, automation, generative design, additive manufacturing, gift labor, and assembly lines.

This article uses a machine learning algorithm to demonstrate a proof-of-concept case for moderating and managing online comments as a form of content moderation, which is an emerging area of interest for technical and professional communication (TPC) researchers. The algorithm sorts comments by topical similarity to a reference comment/article rather than display comments by linear time and popularity. This approach has the practical benefit of enabling TPC researchers to reconceptualize content display systems in dynamic ways.

With growing attention to "intelligent content" and "dynamic delivery" in the advent of connected technologies (i.e., Internet of Things, artificial intelligence agents), component content management and structured authoring skills are becoming increasingly required of technical communicators today. To produce reusable intelligent content, technical communicators need a systematic workflow and common authoring standard. Our experience in industry and in educating technical communicators has led us to seek out resources for understanding existing standards and practicing them with technical communication students. As such, both authors have used the Darwin Information Typing Architecture (DITA) markup standard and experienced what may be a perplexing process in content creation and management. Carlos Evia's book, Creating Intelligent Content with Lightweight DITA , caught our attention as the title suggests an accessible way into learning and applying what has become a widely adopted standard for structured authoring. Understanding that Lightweight DITA (LwDITA) does not aim to replace existing DITA standards, we approach this review not with an intention to examine its viability, but rather a focus on the rhetorical work in structured content authoring and its continuous evolution.

Research examining women's voices in academia, women's leadership in academic and industry contexts, and their management styles in business and social spheres has been more or less steady since the late 1970s. For the last ten years, female students have accounted for approximately 57% of the students enrolled in colleges and universities around the world (Martin, 2014). Despite these enrollment numbers, female administrators in many academic institutions and non-academic businesses are still outnumbered by their male counterparts. The collection Women's Voices in Management: Identifying Innovative and Responsible Solutions edited by Helena Desivilya Syna and Carmen-Eugenia Costea asks readers to consider women's voices in different cultural and global settings, "emphasizing and materializing gender equality [...] in top management, entrepreneurship, and leadership in complex sociopolitical and culturally diverse societies" (p. 10).