A Manifesto for a Pro-Actively Responsible AI in Education
Project Overview
The document highlights the transformative role of generative AI in education, focusing on its potential to personalize learning experiences and enhance engagement among diverse learners. It outlines the ongoing efforts within the Artificial Intelligence in Education (AIED) community to implement adaptive technologies that cater to individual needs, thereby moving beyond traditional educational frameworks. Key applications of generative AI include creating customized learning materials, facilitating real-time feedback, and supporting educators in instructional design. The text also addresses ethical considerations surrounding AI's integration into education, emphasizing the importance of responsible usage and the broader societal implications of these technologies. By advocating for a manifesto that guides the AIED community towards inclusive and impactful educational practices, the document underscores a commitment to evolving educational paradigms that prioritize learner diversity and accessibility. Ultimately, the findings suggest that generative AI can significantly enhance educational outcomes when implemented thoughtfully and ethically.
Implementation Barriers
Engagement Barrier
The AIED community's disengagement from discussions and actions around responsible AI and its reluctance to define its role in guiding EdTech industry policies.
Proposed Solutions: Pro-active engagement with the EdTech industry and policies, and addressing the community’s responsibility to help steer the discussion around responsible AI.
Focus Barrier
The persistent focus on dominant groups of learners, reinforcing a top-down educational perspective.
Proposed Solutions: Shift towards treating diverse abilities as strengths and embracing inclusive practices in AIED.
Research Methodology Barrier
Skepticism towards qualitative and interpretivist research methodologies by the AIED community that favors quantifiable outcomes.
Proposed Solutions: Recognize the value of diverse research methodologies that can inform better practices for non-mainstream education.
Project Team
Kaska Porayska-Pomsta
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Kaska Porayska-Pomsta
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