Generative midtended cognition and Artificial Intelligence. Thinging with thinging things
Project Overview
The document examines the transformative role of generative AI in education, particularly through the lens of 'generative midtended cognition,' which merges AI technologies with human cognitive processes to enhance creativity and learning. It highlights key applications of generative AI, such as personalized learning experiences, content generation, and interactive educational tools, which facilitate hybrid interactions that can enrich traditional educational practices. The findings suggest that while generative AI offers significant advantages, such as fostering innovative thinking and improving engagement, it also poses risks and ethical dilemmas, including concerns about authenticity, the potential for creative atrophy, and the commodification of human intention. The paper calls for a new theoretical framework to navigate these complexities and to ensure that the integration of AI in educational settings promotes positive outcomes while addressing these challenges responsibly. Overall, it emphasizes the need for a careful approach to harness the benefits of generative AI in education while mitigating its associated risks.
Key Applications
Generative technologies like ChatGPT and image generators
Context: Creative tasks such as writing and drawing in professional settings
Implementation: Integration of generative AI into tools used by designers and writers, allowing real-time collaborative creation.
Outcomes: Enhanced creative processes, improved efficiency in generating ideas, and increased accessibility to creative tools.
Challenges: Concerns about authenticity, potential creative atrophy, and dependency on AI-generated suggestions.
Implementation Barriers
Ethical Barrier
Concerns regarding authenticity and ownership of AI-generated content.
Proposed Solutions: Develop clear guidelines for authorship and transparency in AI interactions.
Technological Barrier
Current limitations of generative AI models leading to inaccuracies and hallucinations.
Proposed Solutions: Continuous improvements in AI algorithms and user training to mitigate errors.
Cognitive Barrier
Risk of creative atrophy due to over-reliance on generative AI.
Proposed Solutions: Encourage active engagement and critical interaction with AI outputs to foster original creativity.
Project Team
Xabier E. Barandiaran
Researcher
Marta Pérez-Verdugo
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Xabier E. Barandiaran, Marta Pérez-Verdugo
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai