Generative AI in the context of assistive technologies: Trends, limitations and future directions

Abstract

With the tremendous successes of Large Language Models (LLMs) like ChatGPT for text generation and Dall-E for high-quality image generation, generative Artificial Intelligence (AI) models have shown a hype in our society. Generative AI seamlessly delved into different aspects of society ranging from economy, education, legislation, computer science, finance, and even healthcare. This article provides a comprehensive survey on the increased and promising use of generative AI in assistive technologies benefiting different parties, ranging from the assistive system developers, medical practitioners, care workforce, to the people who need the care and the comfort. Ethical concerns, biases, lack of transparency, insufficient explainability, and limited trustworthiness are major challenges when using generative AI in assistive technologies, particularly in systems that impact people directly. Key future research directions to address these issues include creating standardized rules, establishing commonly accepted evaluation metrics and benchmarks for explainability and reasoning processes, and making further advancements in understanding and reducing bias and its potential harms. Beyond showing the current trends of applying generative AI in the scope of assistive technologies in four identified key domains, which include care sectors, medical sectors, helping people in need, and co-working, the survey also discusses the current limitations and provides promising future research directions to foster better integration of generative AI in assistive technologies.