Advantages and Challenges of Using AI for People with Disabilities
Sarah Taleghani
, Bushra
, Fariah Mobeen
, Yahya El-Lahib
, Rachel Gorman
and Christo El Morr
School of Health Policy and Management, York University, 4700 Keele St, Toronto, Canada
Master of Science in eHealth, McMaster University, 1280 Main Street West, Hamilton, Canada
Faculty of Social Work, University of Calgary, 2500 University Drive NW, Calgary, Canada,
Keywords: Artificial Intelligence, Critical Disabilities, Equity Informatics, Health Policy, Machine Learning, People with
Abstract: This paper discusses the usage of AI in health informatics and its benefits and challenges for people with
disabilities. While AI can assist in tracing pandemics, predicting disease onset, and advocating for human
rights, it can also perpetuate biases towards different groups, including people with disabilities. A systematic
scoping review was conducted to explore the interplay between disability and AI. We examined 45 articles
from eight online databases and highlighted the potential of AI in enhancing healthcare. However, it also
revealed a high prevalence of a narrow medical model of disability and an ableist perspective in AI research,
emphasizing the need for more inclusive AI systems. Using AI has the potential to benefit all members of
society equitably. The findings suggest that AI has great potential for transforming healthcare. However, there
is a need to conduct more research in this area, particularly in relation to AI bias, inclusive design, and
considering social factors.
The CRPD, or Convention on the Rights of Persons
with Disabilities, defines disability as a dynamic
concept. This concept results from the interaction
between impaired individuals and social or
environmental obstacles. These obstacles prevent
them from fully participating in society. This is
referred to as the "social model" of disability.
It is essential to understand the impact of AI on
people with disabilities, as AI software uses existing
data to make predictions. However, there needs to be
more published reviews on this topic. To address this
gap, a scoping review has been conducted to provide
an overview of the current knowledge on the benefits
of AI for people with disabilities.
We utilized eight online databases for this scoping
review, including ProQuest, IEEE Xplore, ACM
Digital Library, Web of Science, Medline, PubMed,
PsycINFO, and CINAHL. With the guidance of my
supervisor, I established a set of key search terms to
conduct the literature search strategy. The search
terms included people with disabilities, disabilities,
disability, disabled, disable, artificial intelligence, AI,
A.I., and machine learning. Out of the 354 citations
extracted, 84 articles were unique.
To conduct this scoping review on the topic of AI
and machine learning and people with disabilities,
certain inclusion and exclusion criteria were
established. The inclusion criteria specified that
studies published in the last five years in the form of
Taleghani, S., Kundi, B., Mobeen, F., El-Lahib, Y., Gorman, R. and El Morr, C.
Advantages and Challenges of Using AI for People with Disabilities.
DOI: 10.5220/0012626900003699
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2024), pages 176-180
ISBN: 978-989-758-700-9; ISSN: 2184-4984
Proceedings Copyright © 2024 by SCITEPRESS Science and Technology Publications, Lda.
journal articles or conference papers would be
considered. Studies not written in English or not
scholarly publications were excluded. Due to the
nature of the systematic scoping review, the search
was limited to the titles of the journal articles. The
most recent search was conducted on February 17,
During the research, 84 abstracts were screened
based on the inclusion and exclusion criteria. Both
FM and BK, the two authors, used Rayyan software
to review the 84 articles, and they identified 64
articles as potentially eligible. Subsequently, both
authors reviewed the full-text version of the 64
articles retrieved for review and synthesis, as shown
in Figure 1. FM was responsible for conducting the
literature search and collecting the articles, while FM
and BK collected data from the articles and conducted
the literature review. CE, another author, repeated the
process to ensure accuracy. In case of ambiguities or
disagreements, a discussion was held to decide
whether to include or exclude.
The studies were restricted to scholarly
publications, such as journal articles and conference
papers published in the last five years and focused on
AI or machine learning and individuals with
disabilities. The most recent search was conducted on
February 17, 2023.
Out of the 84 articles, 45 were kept for analysis.
We are reporting here an interim analysis of 34
articles related to addressing the advantages of AI for
people with disabilities.
Out of the total number of studies, 16 were focused
on adults, while 7 were centered on children and 3 on
the elderly population. Only 1 of the studies had both
children and adult participants, and 7 didn't provide
any information about the age groups they studied.
Twenty-three studies had a medical perspective,
while eleven looked at disability from a formal social
model perspective.
Out of all the studies reviewed, 14 were
conducted in a clinical setting, 8 used pre-existing
datasets, 5 were focused on educational settings, 5
were carried out in a laboratory setting, and only 1
targeted home setting. Additionally, 1 study did not
require or specify a particular setting.
3.1 Advantages
3.1.1 Self-Management of Health
According to our analysis, the use of AI technology
has been observed in 24 studies for self-management
of health, including diagnosis, disability risk
assessment, disability progression, and rehabilitation
risk factors (Alves et al., 2022; De Brouwer et al.,
2021; Erbeli et al., 2023; Flauzino et al., 2019; Fuh-
Ngwa et al., 2022; Hori et al., 2021; Islam et al., 2018;
Koc et al., 2021; Law et al., 2019; Modak et al., 2020;
Montolio et al., 2022; Montolio et al., 2021; Mostafa
et al., 2021; Nikam et al., 2019; Rehak Buckova et al.,
2023; Roca et al., 2020; Song et al., 2022; Tommasin
et al., 2021; Wolff et al., 2022; Xiang et al., 2023;
Yang & Bai, 2022; Youssef & Youssef, 2019;
Yperman et al., 2020; Zivadinov et al., 2022).
The debilitating conditions that were covered
included multiple sclerosis, developmental disorders,
dyslexia, and autism.
3.1.2 Assistive Technologies
There was a total of six studies that focused on the
application of AI in assistive technologies (Blanc et
al., 2019; Encinas Cantaro & Montano Isabel, 2020;
Ghazal et al., 2021; Herbuela et al., 2022;
Tamilselvan et al., 2020; Tanabe et al., 2023). Three
the six studies were related to assistive
communication, while the remaining three were
related to mobility.
3.1.3 Disability Justice
Out of all the articles on AI, only four focused on
disability justice (El Morr et al., 2021; Gorman et al.,
2021; Sobnath et al., 2020; Terziyan & Kaikova,
2021). Among these, one was related to the
development of AI specifically designed for people
with disabilities, while the remaining three were
centered on social justice concerns. The use of AI
techniques has facilitated semi-automatic content
tagging and intelligent semantic searches. This has
been a great help for people with disabilities and
disability advocacy organizations to access trusted
sources of information (El Morr et al., 2021; Gorman
et al., 2021). There are challenges that advocacy
groups often face with monitoring human rights and
identifying systemic discrimination against disabled
people because of the lack of disability data, but ML
approaches provided a solution.
Advantages and Challenges of Using AI for People with Disabilities
3.2 Challenges
3.2.1 Ethical and Legal
While cutting-edge technologies like AI bring
advancements, they also pose challenges such as
privacy concerns and biases. Legal frameworks can
help address privacy and cyber-security issues posed
by wireless communication devices (Fichten et al.,
However, the high costs of AI-based tools could
worsen economic disparities, especially for people
with disabilities. Anticipating and incorporating
ethical solutions into the design of assistive
technologies can help mitigate these challenges
(Zdravkova et al., 2022).
3.2.2 Non-Participative Design
It is essential to involve people with disabilities in
developing AI-based tools to ensure their needs and
concerns are considered (Fichten et al., 2022).
This is particularly crucial for older adults with
disabilities who often face challenges with the
installation and use of complex, intelligent elderly
care products, resulting in inadequate supporting
facilities (Teng & Ren, 2021). Failure to engage
people with disabilities can result in designs that do
not meet their needs and may be paternalistic.
Therefore, oversampling people with disabilities can
also help reflect their needs and concerns in the data.
3.2.3 Pervasiveness of the Medical Model of
Previous studies have used AI from a medical
perspective to help people with disabilities. For
example, AI-based e-health systems were proposed
for the early detection of autism and intellectual and
developmental disabilities (2021). It uses sensors and
AI algorithms to provide personalized treatments to
patients. Another study used machine learning to
predict the progression of disability in cases of MS.
3.2.4 Absence of Discussion of AI Bias
The reviewed articles on prediction failed to
acknowledge bias or assess it across diverse
populations, such as gender or disability types. This
suggests that the studies needed to be aware of
recognizing bias and implementing debiasing
strategies. It is critical to emphasize the potential risks
associated with AI, including bias and ways to
mitigate them, in the research agenda of AI experts
and academic curricula.
The development of artificial intelligence (AI) has
been a remarkable achievement for humankind, as it
has revolutionized the way we live, work, and
communicate with one another. However, to ensure
that AI systems are truly beneficial and inclusive, it is
essential to involve interdisciplinary AI research with
critical disability and social work scholars.
This collaboration can help shift our focus from a
techno-centric approach to a more disability-centric
one, ultimately leading to more effective and
equitable AI systems. The findings of this scoping
review provide a solid foundation for further research
in this field, which can help us explore the potential
of AI to support individuals with disabilities and
create a more inclusive society. Therefore, we must
continue to prioritize this area of research and work
toward building AI systems that are not only
advanced but also fair, safe, and accessible for all.
This research is funded by the Social Sciences and
Humanities Research Council (SSHRC). (Grant No.
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