Numerical simulations of AI–human interaction using quintic mean-field Ising model

The growing role of artificial intelligence (AI) in our society presents both benefits and challenges. To delve deeper into this, we suggest a simulation model that mimics a human–AI ecosystem. This model considers various factors, such as biased actions and multiple-agent interactions ranging from two to five agents. For instance, it includes situations where four humans engage with AI or where four AI systems interact with a human. Our main goal is to investigate how the number of AI systems in the ecosystem influences its dynamics. Our findings revealed that even slight variations in the presence of AI can cause significant changes in the system’s behavior. These shifts can push the system to distinct opposing outcomes or leave it in a state of uncertainty.

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Publication Details

Journal
AIP Advances
Published
2024-08-01
DOI
https://doi.org/10.1063/5.0225968
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.28
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article

Numerical simulations of AI–human interaction using quintic mean-field Ising model

Richard Kwame Ansah, Kassim Tawiah, Richard Kena Boadi, Prosper Ablordeppey
1 citations
AIP Advances
Opinion Dynamics and Social Influence
0.28
article

Numerical simulations of AI–human interaction using quintic mean-field Ising model

Richard Kwame Ansah, Kassim Tawiah, Richard Kena Boadi, Prosper Ablordeppey
article en
1 citations

Abstract

The growing role of artificial intelligence (AI) in our society presents both benefits and challenges. To delve deeper into this, we suggest a simulation model that mimics a human–AI ecosystem. This model considers various factors, such as biased actions and multiple-agent interactions ranging from two to five agents. For instance, it includes situations where four humans engage with AI or where four AI systems interact with a human. Our main goal is to investigate how the number of AI systems in the ecosystem influences its dynamics. Our findings revealed that even slight variations in the presence of AI can cause significant changes in the system’s behavior. These shifts can push the system to distinct opposing outcomes or leave it in a state of uncertainty.

AIP AdvancesVol. 14(8)
Kwame Nkrumah University of Science and Technology (GH), University of Energy and Natural Resources (GH), University of Aveiro (PT)
Life in Land
Openalex Percentile: Top 46%
Opinion Dynamics and Social Influence
0.28
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