Launch, Deploy, Release: ASL Interpreting in the Tech Sector

Nicole Cartagna, MA, CI, CT

Nicole began her interpreting career over 20 years ago in the San Francisco Bay Area, and is now based in her hometown of New York City. Her specialization is designated interpreting in STEAM (Science, Technology, Engineering, Arts, Math) settings. Learn more at www.interpretopia.com

ASL Version: https://youtu.be/A4YJeFn01pI

Inspired by the multilingualism of my native New York City and being a kinesthetic learner who already knew how to fingerspell, I started studying ASL the summer after graduating high school. That fall I started college in upstate New York about 30 minutes south of Rochester, which I was to learn in my first semester, has a Deaf college and a large Deaf population. After taking some extension courses at NTID, instead of studying abroad I spent my senior year as a visiting student at Gallaudet University. After college, I moved to the San Francisco Bay Area, and a few years after that, became a proud graduate of the Ohlone Interpreter Preparation Program. I earned my RID certification in 2001 and it was around the same time that I also got a Handspring Visor, one of the first personal digital assistants, a multi-purpose mobile device.

This photo was taken after an interpreting assignment in Oakland, California, with my colleague and dear friend Cathrael Hackler. We both just bought Handspring Visors and having an electronic calendar seemed high-tech and magical. Additional features included an address book, notepad and calculator. When we started interpreting, we managed our schedules by writing out each assignment in a paper calendar. Most of our work was coordinated with agencies over the phone or on campus in the interpreter coordinator’s office. We were both interpreting a lot of post-secondary course work at the time, so they were recurring assignments. As such, we would have to tediously flip through the pages to write out the details for each week, ready at a glance. With the Visor, the device held the details. Recurring events became one entry set on repeat with an end date. Being able to sync the devices with our computers and back-up our calendars alleviated the fear of losing, or spilling coffee on, this single source of collated job details. I didn’t realize this until years later, but the adoption of this device in my interpreting practice became the catalyst for my interest in the digital revolution and its intersection with sign language interpreting.

A few years later while I was a staff interpreter at San Francisco State University, I joined the Instructional Technology graduate program there. My final project was designing instructional resources to support interpreter training programs as they transitioned their labs from analog to digital tools. My exploring new technologies to support freelance work, as well as my graduate studies focusing on digital video, led me to interpreting in the tech sector. By “tech sector” I am referring to computer science, software development, in particular, within the start-up culture of the last two decades. Interpreting for Deaf professionals in tech and coordinating designated interpreting teams has been the focus of the latter half of my career. An ongoing project that I have been working on, in various permutations over the past few years, is developing training resources for interpreting in tech. Much of my career experience in the tech sector has been working in a designated interpreting dynamic, one Deaf person with one interpreter or a small team of interpreters. I have found the book “Deaf Professionals and Designated Interpreters, A New Paradigm,” by Hauser, et al to be incredibly informative and influential in this regard. Designated interpreting in workplace settings is the reference and lens with which I am framing this essay and developing training resources.

While exploring, offering, and receiving, interpreter training experiences that focus on tech content and contexts, the focus is often on lexical items and vocabulary. I know and use at least 3 different signs for CODE on a regular basis. Learning tech related signs is interesting and important. At the same time, I would like to challenge the notion that this should be the starting point when approaching interpreting tech content. Even though we are interpreters, often in these contexts we are not technically interpreting dialogue and discussion from English into ASL, and back again. We are providing communication access services, which includes ASL-English interpretation as part of our repertoire, which is not exactly the same as providing an interpretation. Often in any workplace setting with specialized jargon, we are not just seeking a linguistic equivalent, we are considering the Deaf person’s goals, linguistic preferences, as well as other competing visual demands and inputs, since we often interpret alongside slides or other written content.

We often reference information, as opposed to translating it, adopting some of the written conventions being used, such as acronyms, copying diagrams, noting bullet points, the color of highlighted text, or a line number in code. In designated interpreting settings we apply our awareness of how the Deaf person best receives information, their background and fund of knowledge, and deliver content to them in a personalized way. We might be advised to be more lax in our interpretation when the Deaf person is attending to something else, conserving energy and attention for when the conversation is directed to the Deaf person or their topic of interest. We employ their preferred lexicon, in contrast to interpreting for a general audience or someone for the first time.

When I have coordinated interpreting teams in tech contexts, I noticed a trend in the resumes I reviewed, that ASL-English interpreters tend to have liberal arts educational backgrounds. I also notice this amongst my teams in the tech sector in general. I am very interested in exploring if there is any evidence to my anecdata. If this is the case, when working with technical content it can be more difficult to draw upon our own fund of knowledge as we might in other contexts. In many tech employment settings, interpreters are also working as independent contractors with limited opportunity for explicit instruction or training. As an approach to interpreting in these contexts and this content, I propose a narrative approach that focuses more on discourse and less on lexicon. I think there is a tendency for interpreters to become overwhelmed with the fast pace of computer science terminology being spoken. The goal of my approach is to reduce overwhelm by capitalizing on our human tendency to categorize inputs for cognitive efficiency, improving our ability to listen for the story. In focusing on lexical items, we might overlook the “story of tech,” Despite the vast diversity of tech contexts and workplaces, I propose that most “tech talk” touches on one or more of the following categories: Time, Change, Power, Code, Data, and Network.

Technology can be defined in several ways. I succinctly define technology as the development and diffusion of tools and innovation over time. Technology changes. Software and hardware are under continuous development, from Version Now to Version Next, for example, iPhone 15 to iPhone 16. Power is expressed in various ways in the tech industry, from practical elements such as how we power our tech devices, source components, make batteries, and cool servers, to power dynamics that lead to mass layoffs, and the way the tech industry can influence politics and policies about tech usage. Most importantly: Who has the power to decide what gets developed, how, and where? Much of contemporary tech is made with code. Some code and development tools have signs that have been adopted, like Python being signed as “snake,” and Kubernetes signed following the written abbreviation “K8”. Meetings that are interpreted in tech contexts are often reviewing an aspect of the software development lifecycle (SDLC), the changing of code over time. Code is used to collect data How data is collected, stored, shared, and represented is the subject of much debate and varies around the world. Data is also considered a contemporary currency, and enterprise decisions are expected to be “data-driven.” People, and data, arranged and connected to each other form networks and the internet is a global network. Artificial intelligence systems are actually networks of large language models. Like most professions, it’s developing one’s personal networks that are crucial to getting work in the tech sector as well.

I propose we approach our work by: preparing, listening, interpreting, and reflecting. When preparing for a tech related assignment, reviewing videos online of Deaf people signing about tech content is one of the best resources. Over the past few years, major tech companies announcing new products or features have increasingly included ASL interpretation or interpreted versions of their presentations. Watching these recordings is a great way to get tech information in both English and ASL. Deaf developers are also making vlogs and video podcasts, for example the vlog “Deaf in the Cloud.” The Atomic Hands website has a page that lists various STEM sign resources. I frequently reference ASLCORE.org for STEM related ASL signs and explanations.

As part of the interpreting process, I propose listening “from the outside in,” focusing less on the novelty of the lexical items and more on the relationships between elements. What is the problem this team or company is trying to solve? What was the previous way and what is the new approach? Who are the cast of characters involved? Considering these questions can help us listen for the story and approach our use of space in our interpretations. Interpret considering the goals of the communication and the Deaf person’s additional visual demands and inputs. Throughout the interpreting process we reflect on our work and choices. Developing a practice of having a place where these thoughts go can be supportive and informative. Perhaps it is the latest handheld digital device, or a classic analog notebook. Regardless of the tool or approach, strive to share these reflections to further expand your skill set and horizons.