Value adaptive adjustment mechanism based on evolutionary algorithm
Combining evolutionary algorithms with GPT-4 for real-time value adaptation in AI systems.
Framework Design
Develop a framework that combines evolutionary algorithms with GPT-4 to enable value adaptation in AI systems.
Value Conflict Scenarios
Compile datasets of ethical dilemmas and cultural differences for AI training.
Performance Evaluation
Assess alignment accuracy, adaptability, and ethical compliance of the developed AI system.
Framework Design
Developing systems for real-time value adjustment and optimization.
Data Collection
Compiling datasets on ethical dilemmas and decision-making contexts.
Expected Outcomes
This research aims to demonstrate that integrating evolutionary algorithms with GPT-4 can significantly enhance the ability of AI systems to adapt their values in dynamic environments. The outcomes will contribute to a deeper understanding of how advanced AI models can be aligned with societal and ethical norms, improving decision-making and reducing conflicts. Additionally, the study will highlight the societal impact of AI in fostering ethical and culturally sensitive systems, enhancing trust, and supporting responsible AI deployment.