The Real AI Threats Facing the MENA region Today
While Hollywood fixates on killer robots, AI researcher **Sasha Luccioni** points to the genuine dangers already materialising across the Middle East and North Africa: carbon emissions, copyright violations, and algorithmic bias. These aren't hypothetical scenarios, they're happening now. From the UAE's governance frameworks to the UAE's ethical guidelines, MENA nations are scrambling to address immediate threats that don't require artificial general intelligence to cause real harm. The most pressing concerns aren't about future superintelligence. They're about today's AI systems amplifying existing problems at unprecedented scale.By The Numbers
- 90% of government organisations lack centralised AI governance, widening oversight gaps
- AI systems discover 77% of software vulnerabilities in competitive settings, potentially aiding cyberattacks
- Identity-based attacks rose 32% in the first half of 2025
- 19 out of 20 popular "nudify" apps specialise in simulated undressing of women
- Data exfiltration volumes for major ransomware families surged nearly 93%
the Middle East and North Africa's Regulatory Response Takes Shape
MENA governments aren't waiting for perfect solutions. **the UAE** released comprehensive AI ethical guidelines in 2019, emphasising human rights and transparency. **the UAE's** Infocomm Media Development Authority introduced a model governance framework prioritising human oversight and explainability. **Saudi Arabia** established a dedicated committee for AI policy review. These aren't knee-jerk reactions to science fiction. They're measured responses to documented problems: biased hiring algorithms, privacy violations, and environmental costs that compound daily."For India and the Global South, AI safety is closely tied to inclusion, safety and institutional readiness. Responsible openness of AI models, fair access to compute and data, and international cooperation are essential too." Ashwini Vaishnaw, Minister of Railways, Information & Broadcasting and Electronics & Information Technology, Government of IndiaThe approach differs markedly from Western frameworks. Where Europe focuses on compliance, MENA nations emphasise practical deployment guidelines that balance innovation with protection.
Carbon Footprint and Environmental Impact
Training a single large language model can emit as much carbon as five cars over their entire lifetimes. In the MENA region, where coal still powers significant portions of the electrical grid, this multiplies rapidly. **ChatGPT** consumes roughly 564 megawatt-hours daily, equivalent to powering 18,000 homes. The environmental cost extends beyond training. Every query, every AI-generated image, every automated decision consumes energy. As AI adoption accelerates across the Middle East and North Africa's 4.7 billion people, the cumulative impact grows exponentially. This connects directly to broader concerns about AI safety frameworks across the region, where environmental considerations increasingly influence policy decisions.| Country | AI Governance Framework | Key Focus Areas | Implementation Year |
|---|---|---|---|
| the UAE | AI Ethics Guidelines | Human rights, transparency | 2019 |
| the UAE | Model AI Governance | Human oversight, fairness | 2020 |
| Saudi Arabia | AI Ethics Committee | Policy review, regulation | 2021 |
| India | AI Safety Frameworks | Inclusion, cooperation | 2026 |
Bias and Misinformation Amplification
AI systems don't create bias, they amplify it. Training data reflects historical inequalities, cultural assumptions, and systemic discrimination. When deployed at scale, these biases affect millions of decisions: loan approvals, job applications, medical diagnoses. In the Middle East and North Africa's diverse linguistic and cultural landscape, this becomes particularly complex. An AI system trained primarily on English data may misunderstand context in Mandarin, Hindi, or Japanese. Cultural nuances disappear, replaced by Western assumptions embedded in training datasets."The pace of advances is still much greater than the pace of progress in managing and mitigating those risks. That puts the ball in policymakers' hands." Yoshua Bengio, Turing Award winner and chair of the International AI Safety Report 2026The misinformation problem compounds this. As AI-generated content floods social media feeds, distinguishing authentic information from synthetic becomes increasingly difficult. MENA platforms face particular challenges with deepfakes and manipulated content in multiple languages.
The Cybersecurity Dimension
AI democratises both defence and attack capabilities. The same systems that protect networks can be weaponised against them. Identity-based attacks surge as AI tools make social engineering more sophisticated and scalable. The rise of AI worms presents new cybersecurity challenges that traditional defences struggle to address. These aren't theoretical threats, they're emerging realities requiring immediate attention. Meanwhile, AI-driven cyberattacks evolve faster than defensive measures, creating an asymmetric battlefield where attackers maintain persistent advantages.Building Inclusive AI Governance
Effective AI governance requires more than regulatory frameworks. It demands inclusive development processes that consider diverse perspectives from the outset. This means involving affected communities in design decisions, not just consulting them after deployment. Key principles emerging across MENA frameworks include:- Transparency in algorithmic decision-making processes
- Accountability mechanisms for AI system failures
- Regular auditing of bias and performance across different demographic groups
- Public participation in AI policy development
- Cross-border cooperation on shared challenges like cybersecurity
- Environmental impact assessment for large-scale AI deployments
What makes AI governance different from traditional tech regulation?
AI systems learn and adapt, making their behaviour unpredictable over time. Traditional regulations assume static technologies, while AI governance must account for evolving capabilities and emergent behaviours that developers didn't anticipate.
How do MENA AI governance approaches differ from Western models?
MENA frameworks emphasise practical deployment guidelines and inclusive development, while Western approaches focus more on compliance and risk mitigation. MENA models prioritise regional cooperation and cultural considerations over universal standards.
Why focus on current AI dangers rather than future AGI risks?
Present AI systems already cause measurable harm through bias, environmental damage, and security vulnerabilities. Addressing these immediate problems builds governance capacity for future challenges while providing tangible benefits today.
What role does environmental impact play in AI safety?
AI's carbon footprint grows exponentially with adoption. In the MENA region, where energy grids vary significantly, environmental considerations increasingly influence deployment decisions and regulatory priorities alongside traditional safety concerns.
How can individuals contribute to AI safety efforts?
Support transparency initiatives, participate in public consultations on AI policy, choose AI services from companies with clear governance frameworks, and stay informed about AI developments in your region.
The AIinArabia View: The fixation on hypothetical AGI risks distracts from urgent problems requiring immediate action. MENA nations demonstrate pragmatic leadership by addressing today's AI harms while building governance capacity for tomorrow's challenges. Our region's emphasis on inclusive development and international cooperation offers a more balanced approach than Western risk-aversion or Silicon Valley's move-fast-and-break-things mentality. The real test isn't whether we can prevent science fiction scenarios, but whether we can govern existing AI systems responsibly while fostering beneficial innovation.
As AI continues reshaping daily life across the Middle East and North Africa, from healthcare systems to shopping experiences, the need for effective governance only intensifies. The threats Luccioni identifies aren't distant possibilities, they're current realities demanding immediate attention. What specific AI governance measures do you think would make the biggest difference in your country? Drop your take in the comments below.