The Potential of an Artificial Intelligence for Disability Advocacy: The WikiDisability Project

Gorman, Rachel; Maret, Pierre; Creighton, Alexandra; Kundi, Bushra; Muhlenbach, Fabrice; Buettgen, Alexis; Dua, Enakshi; Reaume, Geoffrey; Mgwigwi, Thumeka; Dinca-Panaitescu, Serban; Morr, Christo El

doi:10.3233/shti210338

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…Virtual communities have been used in many domains, including health care [ 43 ], to address chronic disease management, education [ 44 ], and mental health. Our current platform is expanding the use of virtual communities for social purposes in the domain of disability rights [ 45 ]. The next phases of the project will involve an evaluation of the adoption of this virtual community using evaluation frameworks [ 46 ], as well the use of background analytics to analyze usage patterns and enhance the search capacity.…”

Section: Discussionmentioning

confidence: 99%

A Virtual Community for Disability Advocacy: Development of a Searchable Artificial Intelligence–Supported Platform

Morr¹,

Maret²,

Muhlenbach³

et al. 2021

JMIR Form Res

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Background The lack of availability of disability data has been identified as a major challenge hindering continuous disability equity monitoring. It is important to develop a platform that enables searching for disability data to expose systemic discrimination and social exclusion, which increase vulnerability to inequitable social conditions. Objective Our project aims to create an accessible and multilingual pilot disability website that structures and integrates data about people with disabilities and provides data for national and international disability advocacy communities. The platform will be endowed with a document upload function with hybrid (automated and manual) paragraph tagging, while the querying function will involve an intelligent natural language search in the supported languages. Methods We have designed and implemented a virtual community platform using Wikibase, Semantic Web, machine learning, and web programming tools to enable disability communities to upload and search for disability documents. The platform data model is based on an ontology we have designed following the United Nations Convention on the Rights of Persons with Disabilities (CRPD). The virtual community facilitates the uploading and sharing of validated information, and supports disability rights advocacy by enabling dissemination of knowledge. Results Using health informatics and artificial intelligence techniques (namely Semantic Web, machine learning, and natural language processing techniques), we were able to develop a pilot virtual community that supports disability rights advocacy by facilitating uploading, sharing, and accessing disability data. The system consists of a website on top of a Wikibase (a Semantic Web–based datastore). The virtual community accepts 4 types of users: information producers, information consumers, validators, and administrators. The virtual community enables the uploading of documents, semiautomatic tagging of their paragraphs with meaningful keywords, and validation of the process before uploading the data to the disability Wikibase. Once uploaded, public users (information consumers) can perform a semantic search using an intelligent and multilingual search engine (QAnswer). Further enhancements of the platform are planned. Conclusions The platform ontology is flexible and can accommodate advocacy reports and disability policy and legislation from specific jurisdictions, which can be accessed in relation to the CRPD articles. The platform ontology can be expanded to fit international contexts. The virtual community supports information upload and search. Semiautomatic tagging and intelligent multilingual semantic search using natural language are enabled using artificial intelligence techniques, namely Semantic Web, machine learning, and natural language processing.

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Section: Discussionmentioning

confidence: 99%

A Virtual Community for Disability Advocacy: Development of a Searchable Artificial Intelligence–Supported Platform

Morr¹,

Maret²,

Muhlenbach³

et al. 2021

JMIR Form Res

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“…The domain of the documents employed in the experiment is disability studies. The motivation to choose disability studies documents was to provide a better search experience for the disability documents in the WikiDisability Project [11]. We search over the disability documents which are annotated with the Disability Wiki Website…”

Section: Domain Of Experimentsmentioning

confidence: 99%

Evaluation of Search Methods on Community Documents

Bisen

Alemayehu

Maret

et al. 2023

Communications in Computer and Information Science

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…In this experiment, we used the Artificial Intelligence (AI) techniques machine learning, semantic web, and Natural Language Processing (NLP) to create a search engine that can extract disability-related data from existing files stored in a Wikibase (El Morr, 2021;Gorman, 2021). The website uses a Wikibase (a semantic web-based data store) to structure and integrate data about people with disabilities.…”

Section: The Difference Transnationality Makes: Mobilizing Framework ...mentioning

confidence: 99%

“…Ultimately, disability researchers and advocates will upload their documents, and the machine learning software will 'learn' which tags to assign to paragraphs. Eventually, an outside user (i.e., a visitor to the website) will enter a query into a search bar, and the most relevant paragraphs will be retrieved (El Morr, 2021;Gorman, 2021).…”

Section: The Difference Transnationality Makes: Mobilizing Framework ...mentioning

confidence: 99%

Disability Data Justice from the Ground Up

Gorman

2023

Critical Studies

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Disability advocacy organizations need access to disability data to advocate for human rights, disability justice, and sustainable development goals. Health informatics and Artificial Intelligence that has been developed through an equity-focused process provide important tools that can help address these needs. AI is prone to bias and might exacerbate discrimination and data ableism. A critical disability lens and community collaboration can help to address these biases, and multidisciplinary collaborations with grassroots and community-based organizations are crucial for advancing disability data justice. We have been engaged in a practice-led approach to building a disability justice-focused AI search engine. In the first section of this paper, we report on our co-design process, which included community consultations about disability data justice with local, provincial, national, transnational, and supernational disability organizations and advocates. In the second section, we demonstrate how we applied a transnational disability studies framework during our process of training a search engine AI to function from a disability justice perspective. We demonstrate the semantic and conceptual differences between a transnational approach and a disability rights approach, as a concrete example of how AI bias emerges. We argue that our participatory approach allows us to experiment with data repositories and search engines that confront AI bias and data ableism and reflect community needs.

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The Potential of an Artificial Intelligence for Disability Advocacy: The WikiDisability Project

Cited by 4 publications

References 6 publications

A Virtual Community for Disability Advocacy: Development of a Searchable Artificial Intelligence–Supported Platform

A Virtual Community for Disability Advocacy: Development of a Searchable Artificial Intelligence–Supported Platform

Evaluation of Search Methods on Community Documents

Disability Data Justice from the Ground Up

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