Humans and AI: Understanding LLM Impact on Human Decision Making

Übersicht

Explore the synergistic potential between humans and LLMs in decision-making tasks, examining active learning, ML fairness, and collaborative approaches to AI implementation.

Lehrplan

• Introduction to Large Language Models (LLMs)
Overview of LLM capabilities and limitations
Evolution and development of LLMs
Key LLM technologies and toolkits
• Human-AI Collaboration in Decision Making
Synergistic potential of human-LLM interaction
Case studies of successful human-AI partnerships
Frameworks for integrating LLMs in decision workflows
• Active Learning and LLMs
Introduction to active learning principles
Techniques for leveraging LLMs in active learning
Human-in-the-loop models and feedback mechanisms
• Fairness and Bias in Machine Learning
Understanding ML fairness and ethical considerations
Bias detection and mitigation strategies in LLMs
Regulatory and societal implications of AI fairness
• Implementing Collaborative AI Approaches
Designing AI systems for human collaboration
Challenges and solutions in AI-human teamwork
Tools and platforms for building collaborative AI systems
• Practical Applications and Case Studies
Industry-specific applications and impact of LLMs
Comparative analysis of AI and human decision making
Success stories and lessons learned from real-world implementations
• Future Trends in Human-AI Interaction
Emerging technologies and their implications for decision making
Long-term impacts of LLM integration in society
Predictions and future outlook for collaborative AI systems
• Conclusion and Course Recap
Summary of key concepts and learnings
Discussion on the evolving role of humans and AI
Reflection on ethical and practical aspects of LLM deployment

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Fachgebiete

Data Science