Generative AI in Higher Education Volume 2

Generative AI in Higher Education Volume 2

Ethical Governance, Skills, and Employability
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Ethical Governance, Skills, and Employability

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Building upon the foundational principles established in the first volume, this second volume of Generative AI in Higher Education advances the debate on AI beyond theoretical frameworks toward concrete institutional practice. Where the first volume developed guiding principles for higher education institutions to use GenAI effectively and ethically in teaching and learning, this volume introduces original, research-informed frameworks that redefine employability as an ethical, adaptive, and human-centred practice. It presents distinctive models including Skills Dynamics, the Justice-Responsibility Framework for Human Flourishing, and the AI Dialogic Partner frameworks that move decisively from principles to practice.

The book integrates ethical governance, curriculum design, and skills formation through actionable models such as the Double ERL Framework (Ethical Regulation Literacy and Ethical Reflexive Learning), the ERL Justice Framework, and the Institutional AI Stewardship Lab (IASL) model. Uniquely combining philosophical depth with policy relevance, it bridges global and local perspectives-drawing on UNESCO, OECD, and regional policy frameworks-to address the ethical, social, and regulatory dimensions of AI in higher education. The volume includes comprehensive international policy analysis, diverse global case studies, and practical tools that transform conceptual exploration into implementable guidance.

Generative AI in Higher Education: Ethical Governance, Skills, and Employability serves as essential reading for university leaders, policymakers, educators, and employers seeking to align AI innovation with justice, inclusion, and sustainability. Its practical frameworks and transparency principles empower institutions to position education not merely as a response to technological change but as a transformative force for human flourishing, providing both scholarly contribution and actionable roadmap for embedding ethical AI in higher education practice.

Building upon the foundational principles established in the first volume, this second volume of Generative AI in Higher Education advances the debate on AI beyond theoretical frameworks toward concrete institutional practice. Where the first volume developed guiding principles for higher education institutions to use GenAI effectively and ethically in teaching and learning, this volume introduces original, research-informed frameworks that redefine employability as an ethical, adaptive, and human-centred practice. It presents distinctive models including Skills Dynamics, the Justice-Responsibility Framework for Human Flourishing, and the AI Dialogic Partner frameworks that move decisively from principles to practice.

The book integrates ethical governance, curriculum design, and skills formation through actionable models such as the Double ERL Framework (Ethical Regulation Literacy and Ethical Reflexive Learning), the ERL Justice Framework, and the Institutional AI Stewardship Lab (IASL) model. Uniquely combining philosophical depth with policy relevance, it bridges global and local perspectives-drawing on UNESCO, OECD, and regional policy frameworks-to address the ethical, social, and regulatory dimensions of AI in higher education. The volume includes comprehensive international policy analysis, diverse global case studies, and practical tools that transform conceptual exploration into implementable guidance.

Generative AI in Higher Education: Ethical Governance, Skills, and Employability serves as essential reading for university leaders, policymakers, educators, and employers seeking to align AI innovation with justice, inclusion, and sustainability. Its practical frameworks and transparency principles empower institutions to position education not merely as a response to technological change but as a transformative force for human flourishing, providing both scholarly contribution and actionable roadmap for embedding ethical AI in higher education practice.

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