A Transparency Index Framework for AI in Education
Project Overview
The document explores the integration of generative AI in education, focusing on the creation of a Transparency Index framework designed to enhance ethical practices in AI development for educational purposes. By emphasizing the necessity of transparency, the framework aims to improve key ethical dimensions such as explainability, accountability, and safety within AI systems. Developed collaboratively with input from diverse stakeholders—including educators, ed-tech professionals, and AI experts—the framework addresses the distinct needs of various user groups in the education sector. The research seeks to fill a notable gap in existing transparency frameworks, proposing a structured methodology for ethical AI development in educational technology. Through this initiative, the document underscores the potential of generative AI to positively impact educational environments while ensuring that ethical considerations remain at the forefront of its implementation.
Key Applications
Transparency Index framework for AI in education
Context: Educational context for educators, ed-tech experts, and AI practitioners
Implementation: Co-designed with stakeholders through iterative phases, incorporating feedback from interviews.
Outcomes: Enhanced understanding of AI products among educators, improved documentation processes for AI practitioners, and a tool for ed-tech experts to evaluate AI-powered products.
Challenges: Balancing the need for transparency with the risk of information overload for end-users.
Implementation Barriers
Awareness Barrier
Stakeholders, especially educators, are generally unaware of the ethical implications and transparency needs of AI products.
Proposed Solutions: Educating stakeholders about the importance of transparency and ethical AI in educational contexts.
Complexity Barrier
The AI development process is complex, making it challenging to document and share all relevant information without overwhelming users.
Proposed Solutions: Implementing tiered transparency that provides information relevant to different user groups based on their technical background.
Project Team
Muhammad Ali Chaudhry
Researcher
Mutlu Cukurova
Researcher
Rose Luckin
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Muhammad Ali Chaudhry, Mutlu Cukurova, Rose Luckin
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