EDUCATING FOR THE FUTURE: HUMAN CAPITAL AND RESPONSIBLE AI IN GLOBAL HIGHER EDUCATION

Abstract

Global higher education is increasingly turning to artificial intelligence (AI) instead of traditional administrative reforms to achieve strategic educational goals. This requires urgent investment in strategic human resource development to create the best educational management system. This article uses qualitative research based on decolonial theory and draws on decades of experience integrating AI into higher education in the US, Europe, and Asia to answer the key question: What human resource practices can be applied to promote equity and responsible use of DI in global higher education? The results of the study show that despite expanded access to digital technologies, countries with poor governance are likely to experience diminishing returns in terms of both human resources and educational quality. To counter this trend, the study proposes a multifaceted approach that includes: fostering critical digital literacy; encouraging hypothesis discovery to navigate conditions of uncertainty; analyzing the interests of dominant technological powers; experimenting with local and global knowledge systems; affirming fundamental human values that AI cannot replicate; engaging with the unresolved complexities of human consciousness that exceed the cognitive capabilities of artificial intelligence; and reforming education management to unlock human potential. Applying decolonial theory, this article contributes to the discussion on the future and responsibility of higher education by proposing a more just and human-centered education ecosystem. It concludes with policy recommendations tailored to the unique challenges faced by countries with weak governance.
Based on decolonial theory, this study calls on policymakers to reconsider the integration of developing HE systems into existing higher education systems that already exhibit significant inequalities. The colonization of DI risks deepening existing inequalities, particularly in countries with weak governance. For DI to be truly accountable, it must be reimagined as part of an alternative ecosystem that fosters trust and empowers each individual to reach their potential. While comprehensive higher education policy frameworks to ensure equitable access to AI tools are a step forward, they are still insufficient to overcome the entrenched power asymmetries between dominant technology corporations and developing countries.
We need to think more deeply about how we can more broadly include people in the creation and implementation of AI across different sectors so that AI does not perpetuate existing structural inequalities. We must demand that AI and technology companies invest first and foremost in the development of safe AI and conduct more thorough research into human interfaces in the AI design process. We must resist the current development of AI and imagine a better ecosystem that promotes the dignity and well-being of people and nature on this planet. 
In summary, digital literacy and participatory governance are becoming fundamental principles in the development of responsible AI strategies that are contextually grounded and socially inclusive. Local stakeholders must critically evaluate how AI is developed and implemented to serve the interests of dominant, often neocolonial, power structures. This approach rejects the notion of AI as a value-neutral technology and exposes its embedded biases, colonial logics, and potential to perpetuate systemic inequalities. By highlighting the voices and knowledge of historically marginalized communities, decolonial higher education systems offer bottom-up, culturally sensitive solutions that resist technological determinism and promote justice-based innovation. A more just and inclusive digital environment must be fostered through the analysis and resolution of epistemic and algorithmic injustices, rather than their reinforcement. Therefore, responsible AI in global higher education is not about AI machines taking more responsibility for their autonomous decisions. It should be a shared responsibility among informed stakeholders who pursue the fundamental goals of education: the holistic development of the individual and the common good. Better ecosystems must be created for AI to be used appropriately in global higher education.

Translated with DeepL.com (free version)