A combined approach of evolutionary game and system dynamics for user privacy protection in human intelligence interaction DOI Creative Commons
Lan Yao, Qiyang Zhang, Shuai Deng

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

Abstract The rapid development of generative artificial intelligence (GenAI) has generated significant economic and social value, alongside risks to user privacy. For this purpose, study investigates privacy protection in human-AI interaction by employing a combined approach evolutionary game system dynamics. A three-party model was developed analyze the interactive effects evolution strategies among government, GenAI company, users. Sensitivity analysis through dynamics simulations conducted on four kinds factors—government, users, incentive mechanisms, reveal how these factors influence strategy choices three parties. results suggest that government’s reputation, subsidies, free-riding benefits, fines, rewards from company cost–benefit considerations all parties are key affecting strategic decisions. Moderate fine subsidy policies can effectively promote protection, with proving be more effective than penalty policies. This paper provides theoretical support decision-making guidance for balancing technological human–AI interaction, contributing regulated orderly Generative Artificial Intelligence.

Language: Английский

A combined approach of evolutionary game and system dynamics for user privacy protection in human intelligence interaction DOI Creative Commons
Lan Yao, Qiyang Zhang, Shuai Deng

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

Abstract The rapid development of generative artificial intelligence (GenAI) has generated significant economic and social value, alongside risks to user privacy. For this purpose, study investigates privacy protection in human-AI interaction by employing a combined approach evolutionary game system dynamics. A three-party model was developed analyze the interactive effects evolution strategies among government, GenAI company, users. Sensitivity analysis through dynamics simulations conducted on four kinds factors—government, users, incentive mechanisms, reveal how these factors influence strategy choices three parties. results suggest that government’s reputation, subsidies, free-riding benefits, fines, rewards from company cost–benefit considerations all parties are key affecting strategic decisions. Moderate fine subsidy policies can effectively promote protection, with proving be more effective than penalty policies. This paper provides theoretical support decision-making guidance for balancing technological human–AI interaction, contributing regulated orderly Generative Artificial Intelligence.

Language: Английский

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