SSCI《Technological Forecasting and Social Change》征稿: 推进负责任的人工智能组合
2024年10月25日
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截止日期:2025/10/30 23:59
征稿期刊
Technological Forecasting and Social Change
期刊级别
SSCI (JCR 2023)
IF 12.9
Q1 (BUSINESS 4/302)
Q1 (REGIONAL & URBAN PLANNING 1/54)
征稿主题
Advancing Responsible AI Composition: Embracing eXplainability for Practical Implementation
细分领域
Techniques for enhancing the transparency of neural network models
Case studies on the application of explainable AI in different sectors, e.g. healthcare, finance, and criminal justice
Methods for incorporating experiential learning into AI systems
Approaches for contextual learning and understanding in AI models
Strategies for aligning AI systems with organizational values and ethics
Frameworks for integrating user feedback and interactions into AI models
Comparative analyses of rule-based systems and modern AI models in terms of eXplainability
Ethical considerations and challenges in the deployment of explainable AI
Theoretical advancements in explainable AI (XAI) and Responsible AI (RAI)
Practical implementation of responsible AI in various industries
The role of big data, LLM attributes in enhancing AI transparency
Impact of machine learning models on AI eXplainability
User-centric approaches to responsible AI development and deployment
Organizational dependencies and their influence on responsible AI systems
Future directions for responsible AI research and practice
重要时间
Submission Deadline: 30 October 2025
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