Ableist Language Teching over Sign Language Research (2023)

Abstract: The progress made in computer-assisted linguistics has led to huge advances in natural language processing (NLP) research. This research often benefits linguistics in a broader sense, e.g., by digitizing pre-existing data and analyzing ever larger quantities of linguistic data in audio or visual form, such as sign language video data using computer vision methods. A large portion of research conducted on sign languages today is based in computer science and engineering, but much of this research is unfortunately conducted without any input from experts on the linguistics of sign languages or deaf communities. This is obvious from some of the language used in the published research, which regularly contains ableist labels. In this paper, I illustrate this by demonstrating the distribution of words in titles of research papers indexed by Google Scholar. By doing so, we see that the number of tech papers is increasing while the number of linguistics papers is (relatively) decreasing, and that ableist language is more frequent in tech papers. By extension, this suggest that much of the tech-related work on sign languages – heavily under-researched and under-resourced languages – is conducted without collaboration and consultation with deaf communities and experts, against ethical recommendations.

## introduction sign language linguistics is a young field, with its inception in the 1960s @xcite . due to the modality of sign languages, using the visual channel for linguistic signals, storing data of signing in its true form has only been possible for as long as video recording has been possible. the analysis of large-scale sign language datasets has consequently relied on an increase in digital storage capacity, and even more recent advances in computer vision and ai technology have led to a growing interest in analyzing sign languages using methods from computer science and natural language processing (nlp) @xcite @xcite . however, while bias and ableism are discussed in nlp and ai research more broadly @xcite @xcite , a substantial part of the research on sign languages in these fields is conducted without including or consulting deaf communities and experts. such inclusive collaboration is crucial for ethical research on sign languages and their communities @xcite @xcite @xcite @xcite , and research without it can easily lead to useless, exploitative and even damaging outcomes, despite good intentions. @xcite introduces the term technoableism, defined as the "rhetoric of disability that at once talks about empowering disabled people through technologies while at the same time reinforcing ableist tropes about what body-minds are good to have and who counts as worthy", which in the context of deaf people can be the development of technical tools -e.g., hearing aids, "sign language gloves" and signing avatars -without consulting the intended users about whether such tools are even wanted (see @xcite . one key identifier of sign language research being conducted without consideration for, and input from, deaf communities and experts is the use of ableist language in the research itself, which sign language linguists observe frequently in published papers. the term ableist language is used here to mean language referring to disabled people -in this paper particularly deaf and hard-ofhearing people -from the perspective of abled people, equating disabled with 'deficient'. in this paper, ableist language refers specifically to words 1 or phrases used as labels or descriptors of deaf and hard-of-hearing people -nb: these offensive labels will be mentioned explicitly in this paper. in the context of deaf and hard-of-hearing communities, particularly those in north america and europe, labels such as "deaf-mute", "deaf and dumb" and "hearing impaired" are considered ableist and offensive. the terms listed here are generally considered ableist and offensive in english, although the direct translations into other languages may be judged differently by the local deaf community. one specific paper on sign language technology garnered some attention after heavy criticism due to the offensive, ableist language used in it. the criticism was outlined in an open letter to the publisher -signed by over 100 academics, professionals and community members -questioning the decision to publish work with highly offensive, ableist language in its title, and resulted in the publisher officially retracting the paper (hochgesang, 2021a). nonetheless, sign language research papers containing ableist language continue to be published, which is evident from notifications of new publications in the field from services such as google scholar alerts. thus, in this paper, i foot_0 look at the impact of tech-related fields on current sign language research, and how it correlates with ableist language, using data from google scholar and google scholar alerts. ## method the data for this paper come from two overlapping sources: 1) google scholar's online search interface and 2) google scholar alerts email notification service. i, the author, have had a google scholar alerts notification for the term "sign language" since october 2017, and the data spans all google scholar alerts from october 6, 2017 to february 27, 2023. the email data is also put in an overall context compared to data on sign language papers searched through the online google scholar interface, searched systematically by annual intervals from 2012 to 2022. ## discussion sign language linguistics is a young field @xcite and sign languages are both underresearched and under-resourced. part of the underresourced issue can be attributed to the visual modality and that technical advances were needed before the recording and analysis of sign language data became possible, but is also likely a result of their minoritized and marginalized status. in the past decade, the number of lexical databases and corpora for various sign languages has exploded @xcite . additionally, there are ongoing efforts to include sign languages in the building of nlp and other language technology resources @xcite @xcite , although there are still many obstacles to overcome before achieving, e.g., machine translation of sign languages @xcite . while there is current nlp and language technology work that is being conducted ethically, by and in direct collaboration with deaf experts and stakeholders, in accordance with the ethical standards for research on deaf communities and sign languages (cf. @xcite @xcite , this paper has illustrated that much of the recent and ongoing work involving technical approaches to sign language research is ignorant of basic nomenclature in the context of deaf communities and their languages. by extension, the use of ableist language in scientific reporting does not instill confidence that the research itself, and resources and tools stemming from it, will be of any higher quality. this is because without engaging with and involving deaf scholars in the process of developing language resources, the input of deaf experiences and expertise is left out (cf. @xcite , which often leads to tools and solutions that are not acceptable or even wanted by the deaf community (see hill, 2020; de meulder, 2021), often summarized by a collective outcry of not another sign language glove (cf. hochgesang, 2021a). unfortunately, many technical applications that target deaf and hard-of-hearing people -as well as other disabled people -often consitute a type of ableism labeled technoableism, in which socalled "solutions" that, while they may be wellintentioned, are rooted in ideas of "fixing" or "mending" any differences from the norm, regardless of whether those solutions are practical or requested by the target group @xcite . similar questioning of normativity in language use and the study of language has been raised within linguistics in a broader sense @xcite @xcite , and feeds into the more narrow question of language technology and resources, both in terms of biases present in the underlying datasets @xcite and in terms of who is developing the technology and for whom @xcite @xcite . the results of this paper illustrate that many of the language resources and tools that are being developed for sign languages -which are all still very much under-studied and under-resourced languages -are likely developed without direct input from the stakeholders, and without sufficient background in the history and ethics of sign language research, as is evidenced by ableist language use. besides being harmful, this also leads to a distrust in the usability of such tools and resources, and potentially also difficulties in finding and funding the quality work due to the overwhelming increase in publications and resources being developed. ## conclusion in this paper, i have shown how ableist language in publications on sign languages correlates with tech-related research. besides being offensive in itself, thus leading to further oppression of deaf and disabled people, it suggests a low level of awareness of the actual wants and needs of deaf communities when it comes to technology, and reinforces biases of both researchers (in terms of who is involved) and their output (in terms of resources and applications). researchers working on developing language resources for any group, but particularly marginalized ones, should at the very least be expected to have enough knowledge and awareness about the context and history of the group to not reinforce offensive and oppressive language use, but ideally also work in direct consultation and collaboration with the community in question. this has been outlined by many scholars advocating for inclusive and ethical research (e.g. @xcite @xcite @xcite : proportion of papers listed in google scholar alerts emails for the term "sign language" from october 6, 2017 to february 27, 2023 with titles containing words identified as ableist by topic divided into tech vs. no tech based on keywords in the titles, using both automated and manual methods of categorizing paper titles. freyman, 2022), and among these, de meulder (2021, 18) directly addresses researchers developing sign language technology, encouraging them to always ask themselves the question "who is the language technology for, and why?"