Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences
May 26, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Rui Hao, Dianbo Liu, Linmei Hu
arXiv ID
2305.19278
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The merging of human intelligence and artificial intelligence has long been a subject of interest in both science fiction and academia. In this paper, we introduce a novel concept in Human-AI interaction called Symbiotic Artificial Intelligence with Shared Sensory Experiences (SAISSE), which aims to establish a mutually beneficial relationship between AI systems and human users through shared sensory experiences. By integrating multiple sensory input channels and processing human experiences, SAISSE fosters a strong human-AI bond, enabling AI systems to learn from and adapt to individual users, providing personalized support, assistance, and enhancement. Furthermore, we discuss the incorporation of memory storage units for long-term growth and development of both the AI system and its human user. As we address user privacy and ethical guidelines for responsible AI-human symbiosis, we also explore potential biases and inequalities in AI-human symbiosis and propose strategies to mitigate these challenges. Our research aims to provide a comprehensive understanding of the SAISSE concept and its potential to effectively support and enhance individual human users through symbiotic AI systems. This position article aims at discussing poteintial AI-human interaction related topics within the scientific community, rather than providing experimental or theoretical results.
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