Unlocking Language: How AI Can Help Children With Dyslexia
Advances in artificial intelligence (AI) are challenging long-held beliefs about neurodevelopmental conditions. Specifically, AI is showing promising results in addressing dyslexia, a language-based learning disability.
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In a recent EducationWeek article, the author stated, “What Educators Need to Know About Dyslexia—and Why It’s Not Something to ‘Fix.'” However, the development of autonomous AI systems offers new possibilities for addressing the core challenges of dyslexia. As an inventor of autonomous AI, I can explain how these technological advances can resolve previously intractable problems and why the case of dyslexia shows the potential to change how we view and treat similar conditions.
Dyslexia affects approximately one in five individuals and is the most cited reason for special education services. Special education programs represent an enormous financial burden, costing U.S. taxpayers over $120 billion annually.
Traditional approaches have focused on helping students “cope” with their reading difficulties. However, due to recurring expenses from interventions, these measures only offer temporary relief and do not address the neurodevelopmental disorder.
A Logical Approach to a Complex Problem
Research over the past five decades has established that dyslexia fundamentally involves language processing difficulties. A comprehensive solution, therefore, must incorporate these elements:
- Expertise in natural language: Linguistics is a vast field encompassing phonology, semantics, and syntax, among other areas. However, areas of the linguistic system can be affected when language processing is impaired.
- Expertise in language processing in exceptional brains: It is necessary to understand how the brain processes language in neurotypical individuals and compare it with how language is processed in the brains of those with dyslexia.
- A method to identify and correct language processing difficulties in individual brains: Dyslexia does not have an operational definition that researchers can all agree on, which is a problem. Precision is key to solving this condition. We must also devise a non-invasive method to identify the precise cause.
Technical Requirements of an AI Solution
To effectively address these challenges, a new method must possess the following capabilities:
- Analyze vast datasets: The complexity of the language system and brain processing requires the analysis of billions of data points per person.
- Operate at high speed: The rapid nature of language processes, which occur in milliseconds, is an important factor.
- Measure sub-second changes: The ability to track improvements in language processing requires the measurement of changes within sub-second intervals.
- Scale for diversity: The system should accommodate the diversity of individuals affected by dyslexia, considering the different scopes and severities.
These intricate technical requirements are beyond human capabilities. What is needed is an autonomous computer system that can meet the above operation’s demands, precision, and speed. This autonomous system serves as an expert to analyze and retrain each individual and increase language processing efficiency. A language-based, online game provides the interface between the user and the AI, allowing them to engage with the AI system.
The Promise of AI
This highly individualized intervention, created in real-time, has become a reality with cloud computing, scalable technology, and interactive gaming’s evolution. AI provides a new computational view of dyslexia that is not always possible with physical brain scans. AI is also a faster solution, and it is changing how we treat dyslexia and other neurobiological disorders. The brain’s ability to reorganize, neuroplasticity, is beginning to be understood, and this is only the beginning.
AI technology, guided by the necessary knowledge base, has already shown positive outcomes for individuals in the U.S. Last year, several people described their experience with AI-driven intervention reducing their reading difficulties after one to two years. These individuals struggled with reading difficulties due to other interventions. AI changed all of this. The students could then perform like their typical peers academically.
References:
- Elliott, J. G., & Grigorenko, E. L. (2014). The dyslexia debate. New York: Cambridge.
- Huebeck, E. (Feb 13, 2025). What Educators Need to Know about Dyslexia – and Why It’s Not Something to ‘Fix.’ EducationWeek.
- National Center for Education Statistics (NCES). (2024). Students with disabilities. Preprimary, Elementary, and Secondary Education. https://nces.ed.gov/programs/coe/indicator/cgg/students-with-disabiliti…
- National Center for Learning Disabilities (NCLD). (2023). IDEA full funding: Why should Congress invest in special education? Policy & Advocacy.
- Ellis, R. (Dec 20, 2024). A.I. revolution: How artificial intelligence is helping children with dyslexia. NBC Nightly News.https://www.nbcnews.com/nightly-news/video/a-i-revolution-how-artificia…
- Ozernov-Palchik, O., & Gaab, N. (2016). Tackling the early identification of dyslexia with the help of neuroimaging. Perspectives on Language and Literacy, 42(1), 11-17.