Thinking About AI, Human Rights, and Education

Felisa Tibbitts

UNESCO Chair in Human Rights and Higher Education and Chair in Human Rights Education at Utrecht University

Felisa Tibbitts is dedicated to the role that education can play in advancing human rights. She is UNESCO Chair in Human Rights and Higher Education and Chair in Human Rights Education at the Human Rights Centre of Utrecht University (Netherlands). She is also an Adjunct Assistant Professor at Columbia University and Visiting Professor at Nelson Mandela University (South Africa). Felisa is actively engaged in the field of AI, human rights and education through her research and curriculum development efforts.

AI & EDUCATION — CHAPTER 2

AI advocates are enthusiastic about its potential to enhance efficiency, automation, and data-driven policy decision-making, but a rising chorus of voices has begun to sound the alarm about the risks of AI posing threats to human rights, and the endurance of democratic values such as non-discrimination and equality. AI is not neutral; it operates within frameworks shaped by the biases and inequalities embedded in the data it processes and the systems it supports. These dynamics make it important to consider AI’s impact on human rights worldwide. This is particularly relevant in the educational sector, given how education has emerged as a high-stakes arena for upholding human rights. 

Human rights, broadly defined, are the fundamental rights inherent to all individuals, regardless of nationality, ethnicity, gender, or socioeconomic status. These rights are codified in international legal frameworks such as the Universal Declaration of Human Rights (1948) and the Convention on the Rights of the Child (1989). As AI becomes increasingly integrated into educational systems, human rights can offer a critical lens for assessing the opportunities and risks of using AI in education.

Numerous human rights are at stake in relation to the use of AI, including, among others, the right to privacy, freedom from bias and discrimination, the right to equality, the right to a healthy environment, and the right to democratic participation. 

The right to education is another core human right and is recognized as essential for empowering and developing individuals and societies. This right emphasizes not only access but also quality and inclusiveness of education, aiming to foster the full development of human potential and promote social equality (UNESCO, 2021).

AI technologies have demonstrated considerable potential to enhance education. Personalized learning platforms, for example, adapt content and pacing to individual students’ needs, enabling more tailored and effective educational experiences. Intelligent tutoring systems provide real-time feedback, helping students to overcome challenges and facilitating more efficient learning processes. Such innovations hold promise to address some long-standing gaps in education, particularly for students requiring additional support. 

However, overreliance on AI in education can narrow the scope of learning to metrics that are easily quantified, potentially sidelining broader educational goals such as critical thinking, creativity, and social-emotional development. Automated grading systems, for instance, often prioritize surface-level correctness over more nuanced skills like problem-solving or collaborative reasoning (Luckin et al., 2016). This emphasis risks reducing education to a transactional process, undermining its role as a transformative force that nurtures holistic personal and intellectual growth. 

The right to education is another core human right and is recognized as essential for empowering and developing individuals and societies.

The right to education is fundamentally tied to the principle of inclusivity. Unfortunately, AI systems often fail to adequately accommodate the needs of students with disabilities, those from linguistic minorities, or those with non-standard learning trajectories (Kleinberg et al., 2020). For example, many adaptive learning platforms rely on language models that do not account for regional dialects or non-native speakers, alienating students who may already face barriers to learning. Similarly, speech recognition tools frequently perform poorly with diverse speech patterns or accents, alienating students whose needs are not represented in the training data (Noble, 2018). 

The digital divide is another significant barrier to the equitable deployment of AI in education. Access to AI-driven tools is predicated on reliable internet connectivity, technological infrastructure, and digital literacy—resources that are unevenly distributed across socio-economic lines. Rural and underfunded schools often lack the means to adopt advanced AI technologies, leaving their students at a significant disadvantage compared to their peers in wealthier institutions. A study by the World Economic Forum (2020) found that students in low-income households were twice as likely to lack basic digital literacy skills compared to those from higher-income households. This disparity exacerbates educational inequities, limiting the ability of underserved communities to benefit from the transformative potential of AI. 

AI poses risks to numerous core principles like equality, privacy, and freedom of expression within learning environments—if deployed without rigorous safeguards. Conversely, this technology also holds immense promise to enhance access, personalization, and efficiency in education, provided it is harnessed in the service of empowering students rather than optimizing for narrow metrics. 

Ultimately, establishing a balanced, rights-respecting approach to AI in schools will require collaborative policymaking that centers the voices of diverse stakeholders—from technical experts and educators to marginalized community members directly impacted. Robust transparency, accountability, and redress mechanisms must be enshrined to ensure algorithmic decision-making is fair, contestable, and aligned with human dignity. Moreover, comprehensive digital and AI literacy programs empowering both students and teachers are crucial to cultivating agency and critical thinking in an increasingly automated world.

References

1. Kleinberg, J., Ludwig, J., Mullainathan, S. & Sunstein, C. R. (2020). Algorithms as discrimination detectors. Proceedings of the National Academy of Sciences, 117(48), 30096–30100. https://doi.org/10.1073/pnas.1912790117  
2. Luckin, R. & Holmes, W. (2016). Intelligence Unleashed: An Argument for AI in Education. UCL Knowledge Lab. London, UK. [Report]. UCL Knowledge Lab. https://www.pearson.com/content/dam/corporate/global/pearson-dot-co m/files/innovation/Intelligence-Unleashed-Publication.pdf 
3. Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press.  
4. UNESCO. (2021). UNESCO Publications. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000380063
5. United Nations. (1989). Convention on the Rights of the Child. United Nations. https://www.ohchr.org/en/instruments-mechanisms/instruments/conventi on-rights-child 
6. United Nations. (1948). Universal Declaration of Human Rights. United Nations. https://www.un.org/en/about-us/universal-declaration-of-human-rights 
7. World Economic Forum. (2020, October 20). The Future of Jobs Report 2020. World Economic Forum. https://www.weforum.org/reports/the-future-of-jobs-report-2020