<h3 dir="ltr">Introduction</h3>
In 2020, Egypt began formulating its Artificial Intelligence (AI) strategy for select sectors such as economy, healthcare, and education (NCAI 2025). The strategy targets increasing the country&rsquo;s ICT/AI sector share of the GDP to 7.7% by 2030, building an ecosystem of technological innovation that features 30,000 AI specialists, and a resulting 150+ AI startups, and ensuring that about 36% of Egyptian citizens use AI in their daily lives with 25% of governmental employees using the tool to improve bureaucratic and governmental performances (SIS 2025). Many other African and Middle Eastern countries have joined the race for establishing national strategies to foster AI ecosystems solely for development (Trigui et al. 2024). However, important questions require our attention: how do challenges in knowledge production, equity, localization, and society adversely affect any&nbsp; implementation of AI?
In this commentary, I highlight the problematics of anchoring AI policy discourse in Egypt and the MENA region in economic optimization, efficiency, and technological competitiveness. Such an approach, I argue, narrows AI adoption into a purely technical trajectory that reproduces epistemic dependency on Western conceptions of intelligence, modernization, optimization, and development. In addition, it risks excluding large portions of society from engaging with AI, seeing as the foundations of education, the fostering of the humanities and social sciences, and literacy rates are not given as much attention, and reinforcing global asymmetries in knowledge production. I set out to expand the policy dialogue on AI by reframing it as an epistemic and cultural question as much as an economic one. The article further argues for developing policies that recognize and cultivate local and regional intellectual and cultural resources as part of our AI infrastructure. If implemented, such policy recommendations would inspire a more plural and just AI landscape and diverse epistemic ecology.
<h3 dir="ltr">Skewed epistemology</h3>
There are several epistemic predicaments facing us when it comes to MENA AI governance policies. First, there is the privileging of Western knowledge and expertise over others. This allows Western-centric data infrastructures to shape how the machine &ldquo;sees&rdquo; and &ldquo;produces&rdquo; knowledge about the world, which results in a distorted and biased representation of the non-West. A call has been put out to suggest that MENA countries collectively emphasize &ldquo;the preservation of their cultures, the importance of indigenous languages and religion, and safeguard users from AI products that lack local data training&rdquo; (Trigui et al. 2024; Arab Barometer 2023; Pew Research Center 2018). By adopting the approach of &ldquo;epistemic ecology,&rdquo; how individuals, communities, and environments &ldquo;adapt to one another to generate evolving understandings&rdquo; (Elgin 2025), policy makers in Egypt and MENA can think beyond concerns over technical capacity and instead focus on knowledge justice. This ensures that non-Western productions of knowledge and intellectual traditions are not erased from the global digital space, and that interdisciplinary policy frameworks link AI governance and ethics with cultural policy, academic research, and linguistic diversity.&nbsp;
<h3 dir="ltr">Data colonialism and protection</h3>
The second type of epistemic predicament is &ldquo;data colonialism&rdquo;. In this age of AI, human experiences are seen as free raw material for commercial practices of extraction, prediction, and sales. It is argued that this is an extension of older forms of knowledge extraction, which turns digital infrastructure into new frontiers of inequality.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
Egypt&rsquo;s AI strategy faces a challenge in trying to reconcile the Personal Data Protection Law (PDPL) No. 151 of 2020 with the insatiable data demands of Artificial Generative Intelligence (AGI), which are machine learning models &ldquo;trained on massive amounts of data, typically media such as text, images, audio or video, in order to produce representative instances of such media&rdquo; (Kay et al. 2024). The PDPL, hailed as a foundation for ethical AI governance, mandates explicit consent, adherence to purpose limitation, and grants the right of citizens to erase all personal and sensitive data (El Bolock 2025), while AGI models, are built through indiscriminate, global data maximization (Arora et al. 2023; Kay et al. 2024). This leads to unresolved issues surrounding copyright infringement and privacy and opens the door to data colonialism, where powerful foreign and local Big Tech companies could exploit the need for broad data by rapidly collecting and exporting large volumes of Egyptian cultural and social data without proper compensation or governance. To overcome this, Egypt's national strategy must move beyond simple regulation and establish a &ldquo;Sovereign Data Framework&rdquo;, secured repositories that host critical datasets across sectors that are gathered and curated through investment and not infringing upon copyrights (ATSE 2025). Such a framework compels international entities to either license this protected data or enter local partnerships that strictly adhere to the PDPL, thus safeguarding Egypt's digital assets and epistemic sovereignty.
<h3 dir="ltr">Devaluation of Social Sciences and Humanities (SSH)</h3>
The third epistemic predicament, and the most important one, is that disciplines of Social Sciences and Humanities (SSH) are still mostly left out of debates about AI strategies, governance, and their ethics, in both global strategies (Chades et al. 2025), as well as MENA AI national strategies, and are seen as having no value for societal development. There is a significant blind spot that is created when SSH expertise is excluded from AI policy. Above all, this non-humanistic approach to AI ignores the interdependence of the two, whereby technology is shaped by culture, and vice versa.&nbsp;
Drawing on the thesis of &ldquo;AI model collapse,&rdquo; which occurs when systems lose coherence because of homogenized data, poor-quality data, or the lack thereof of data (Peterson 2025), a thriving epistemic ecology and a fostering of cultural life is necessary for the sustainable development of AI in our region. Both conditions depend on one another; but the justification for supporting SSH should not just be for the sake of creating better data sets for AI development. Governmental snubbing of SSH, as university degrees that do not bring income, should be abandoned. Instead, governmental entities, civil societies, and social groups should work on developing more encouragement to pursue such university degrees and highlighting the importance of SSH.
This trend is particularly pronounced in Egypt, which in recent years has witnessed a sharp increase in private institutions, increasing the number of universities to 128, according to the Ministry of Higher Education (Ahram Online 2025). Many of the departments established within these new institutions are overwhelmingly dedicated to technical and scientific fields.&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The Alan Turing Institute published a White Paper titled &ldquo;Doing AI Differently: Rethinking the Foundations of AI via the Humanities&rdquo;. In it The Alan Turing Institute team argue that AI systems, mainly AGIs, are facing limitations seeing as they are shaped by narrow operational metrics that &ldquo;fail to reflect the diversity, ambiguity, and richness of human experience&rdquo; (Hemment and Kommers 2025), and they produce and act upon cultural outputs such as language, images, and narratives, that they have no training for interpreting. They argue that this predicament requires the integration of SSH academics, specialists, etc., within the process of AI development from the start, as they are disciplines that specialize in understanding and interpreting cultural meaning, contextual nuance, and interpretive complexity (Hemment and Kommers 2025).
<h3 dir="ltr">Conclusions and first steps before the AI race</h3>
Prior to engaging in any attempts to participate in the global race for AI, the MENA region must confront the set of epistemic challenges this commentary has laid out. These challenges are concerned with how our technological, educational, and social policies deal with knowledge, data, and culture. The main hurdle to sustainable, efficient, and successful AI adoption in the region is not a technical or infrastructural lack, but rather a problem of epistemic agency and ecology.&nbsp;
A race towards purely AI-driven economic and financial development without attending to the cultural, social, and intellectual infrastructures within the region will inevitably have countries failing to make any growth sustainable or meaningful in such sectors. The future of AI in the MENA requires a revolution in epistemology, cultural plurality, and understanding, not only technical and infrastructural foundations.
<hr>
References
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