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Human-AI Collaboration for Remote Sighted Assistance: Perspectives from the LLM Era.

Rui Yu1, Sooyeon Lee2, Jingyi Xie3

  • 1Department of Computer Science and Engineering, University of Louisville, Louisville, KY 40208, USA.

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Summary
This summary is machine-generated.

Remote sighted assistance (RSA) helps people with visual impairments (VI) navigate daily tasks. This study identifies technical and navigational challenges, proposing human-AI collaboration for future visual prosthetic solutions.

Keywords:
artificial intelligencecomputer visionconversational assistancehuman–AI collaborationlarge language modelspeople with visual impairmentsremote sighted assistance

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Area of Science:

  • Human-Computer Interaction
  • Assistive Technology
  • Computer Vision

Background:

  • Remote sighted assistance (RSA) utilizes real-time video chat to connect individuals with visual impairments (VI) to sighted agents.
  • Understanding the challenges faced by both users and agents is crucial for improving RSA effectiveness.

Purpose of the Study:

  • To review existing literature and interview RSA users to identify technical and navigational challenges.
  • To explore potential computer vision solutions and formulate emerging problems requiring human-AI collaboration.
  • To envision the future integration of large language models (LLMs) within RSA for enhanced visual prosthetics.

Main Methods:

  • Conducted a comprehensive literature review on remote sighted assistance.
  • Performed qualitative interviews with 12 individuals who use RSA.
  • Categorized technical challenges and identified real-world navigational scenarios (indoor and outdoor).

Main Results:

  • Identified four categories of technical challenges for RSA agents: orientation/localization, environmental perception, situation-specific information delivery, and network connectivity.
  • Presented 15 real-world navigational challenges, highlighting areas where computer vision can offer solutions.
  • Formulated 10 emerging problems requiring synergistic human-AI collaboration, including integration with LLMs.

Conclusions:

  • Human-AI collaboration is essential for addressing complex challenges in remote sighted assistance.
  • Integrating large language models offers a promising pathway for developing advanced visual prosthetics.
  • Future research should focus on human-AI frameworks to enhance RSA capabilities for individuals with VI.