Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences

• URL: http://arxiv.org/abs/2305.19278v1
• Date: Fri, 26 May 2023 04:13:59 GMT
• Title: Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences
• Authors: Rui Hao, Dianbo Liu, Linmei Hu
• Abstract summary: We introduce a novel concept in Human-AI interaction called Symbiotic Artificial Intelligence with Shared Sensory Experiences (SAISSE) SAISSE aims to establish a mutually beneficial relationship between AI systems and human users through shared sensory experiences. We discuss the incorporation of memory storage units for long-term growth and development of both the AI system and its human user.
• Score: 6.033393331015051
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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