The Ethics of Artificial Intelligence in Education

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts.

Autorentext

Wayne Holmes teaches Learning Sciences and Innovation in the Institute of Education at University College London, UK, and is Consultant on AI and Education for the International Research Centre for Artificial Intelligence (IRCAI), UNESCO, and The Council of Europe.

Kaka Porayska-Pomsta is Professor of Artificial Intelligence in Education at the Department of Culture Communication and Media in the Faculty of Education at University College London, UK.

Klappentext

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, frameworks, guidelines, policies, and regulations to ensure the positive impact of artificial intelligence in learning.

Inhalt

Part I: Ethics of AI In Education: An Outside Perspective 1. Learning to learn differently 2. Educational research and Artificial Intelligence in education: Identifying ethical challenges 3. AI in education: An opportunity riddled with challenges 4. Student-centered requirements for the ethics of AI in education 5. Pitfalls and pathways for trustworthy Artificial Intelligence in education Part II: Ethics of AI In Education: An Inside Perspective 6. Equity and Artificial Intelligence in education: Will "AIED" amplify or alleviate inequities in education? 7. Algorithmic fairness in education 8. Beyond "Fairness:" Structural (in)justice lenses on AI for education 9. The overlapping ethical imperatives of human teachers and their Artificially Intelligent assistants. 10. Integrating AI ethics across the computing curriculum