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[2602.21584] Exploring Human-Machine Coexistence in Symmetrical Reality
Summary
This paper explores the evolving relationship between humans and AI, proposing a framework for harmonious coexistence termed 'symmetrical reality' that integrates both virtual and physical interactions.
Why It Matters
As AI technology advances, understanding the dynamics of human-machine interaction is crucial for developing systems that enhance collaboration and coexistence. This research provides a new perspective that could reshape future AI applications and their integration into daily life.
Key Takeaways
- Introduces the concept of 'symmetrical reality' for human-machine coexistence.
- Challenges traditional human-centric paradigms in AI interaction.
- Proposes a framework for studying interactions across virtual and physical realms.
- Highlights the importance of reassessing human-AI relationships.
- Offers innovative insights for future research in human-machine interaction.
Computer Science > Human-Computer Interaction arXiv:2602.21584 (cs) [Submitted on 25 Feb 2026] Title:Exploring Human-Machine Coexistence in Symmetrical Reality Authors:Zhenliang Zhang View a PDF of the paper titled Exploring Human-Machine Coexistence in Symmetrical Reality, by Zhenliang Zhang View PDF HTML (experimental) Abstract:In the context of the evolution of artificial intelligence (AI), the interaction between humans and AI entities has become increasingly salient, challenging the conventional human-centric paradigms of human-machine interaction. To address this challenge, it is imperative to reassess the relationship between AI entities and humans. Through considering both the virtual and physical worlds, we can construct a novel descriptive framework for a world where humans and machines coexist symbiotically. This paper will introduce a fresh research direction engendered for studying harmonious human-machine coexistence across physical and virtual worlds, which has been termed "symmetrical reality". We will elucidate its key characteristics, offering innovative research insight for renovating human-machine interaction paradigms. Comments: Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) Cite as: arXiv:2602.21584 [cs.HC] (or arXiv:2602.21584v1 [cs.HC] for this version) https://doi.org/10.48550/arXiv.2602.21584 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Zhenliang Zhang [view em...