Augmented Reality Research: Benefit or Detriment for Neurodiverse People

The intersection of technology and innovation has always been a double-edged sword for humanity, offering both profound benefits and potential risks. This paper examines the positive and negative impacts of augmented reality (AR) and generative artificial intelligence (GAI) on neurodiverse users (NDU). While AR, coupled with large language models (LLM), has the potential to revolutionize the diagnosis and training environments for NDUs, inherent biases in LLM training data, which predominantly reflects neurotypical user (NTU) content, pose significant risks. These biases can result in environments and interactions that are less accessible and potentially harmful to NDUs. The paper explores the implications of these biases, including the possibility of privacy invasion and the misuse of technology for diagnosing undiagnosed NDUs, leading to severe personal and professional consequences. The study advocates for industry-wide collaboration to mitigate these biases, develop NDU-specific datasets, and create secure AR frameworks that safeguard the neurodiverse population while enhancing their quality of life.

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Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/ismar-adjunct64951.2024.00015
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
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article

Augmented Reality Research: Benefit or Detriment for Neurodiverse People

Denis Gračanin, Mohamed Azab, David S. Jones
Augmented Reality Applications
article

Augmented Reality Research: Benefit or Detriment for Neurodiverse People

Denis Gračanin, Mohamed Azab, David S. Jones
article en

Abstract

The intersection of technology and innovation has always been a double-edged sword for humanity, offering both profound benefits and potential risks. This paper examines the positive and negative impacts of augmented reality (AR) and generative artificial intelligence (GAI) on neurodiverse users (NDU). While AR, coupled with large language models (LLM), has the potential to revolutionize the diagnosis and training environments for NDUs, inherent biases in LLM training data, which predominantly reflects neurotypical user (NTU) content, pose significant risks. These biases can result in environments and interactions that are less accessible and potentially harmful to NDUs. The paper explores the implications of these biases, including the possibility of privacy invasion and the misuse of technology for diagnosing undiagnosed NDUs, leading to severe personal and professional consequences. The study advocates for industry-wide collaboration to mitigate these biases, develop NDU-specific datasets, and create secure AR frameworks that safeguard the neurodiverse population while enhancing their quality of life.

Virginia Military Institute (US), Virginia Tech (US)
Gender equality
Openalex Percentile: Top 78%
Augmented Reality Applications
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