As a software engineer contracting for American companies while rooted in Belize, my perspective on the AI revolution is necessarily bifurcated. While colleagues in the West enthusiastically adopt AI-powered coding assistants, my own experiences with these tools have been underwhelming. Yet, this technical friction pales in comparison to the deeper, systemic apprehensions I harbor, anxieties born directly from the unique vantage point of living and working in a developing nation navigating the turbulent currents of global technology.
The most immediate concern is one of access and precarious dependency. My professional livelihood hinges on tools hosted and controlled by entities far removed from my reality. Belize, like many nations, exists under the shadow of potential geopolitical shifts, including American sanctions. The chilling prospect of losing access to essential AI platforms overnight due to forces entirely beyond my control is not abstract paranoia; it’s a tangible risk. This vulnerability starkly contrasts with the assumed stability enjoyed by my Western counterparts.
Furthermore, the digital divide exacerbated by AI is not theoretical here; it's visceral. The very gateways to these powerful tools – primarily credit cards tied to international payment systems – are inaccessible to a significant portion of my fellow Belizeans. This isn't just about convenience; it's about fundamental exclusion. Students brimming with potential, young professionals eager to engage with cutting-edge technologies like cloud computing, are already "left behind" because they lack the financial infrastructure (a simple credit card) required to even experiment. AI, touted as a democratizing force, instead risks cementing existing global inequalities at the very first step: the ability to try it.
The barriers extend beyond subscription paywalls. The dream of local sovereignty through open-source models runs into the harsh wall of economic reality. Training or even running state-of-the-art LLMs locally requires computational power far beyond the means of most individuals, institutions, or even small nations like Belize. The cost of the necessary hardware is utterly prohibitive, rendering self-reliance a distant fantasy. We remain perpetual consumers, dependent on the infrastructure and whims of foreign corporations.
This divide extends beyond access into the realm of skill development – a crisis with generational consequences. Early-career professionals who over-rely on LLM tools risk never mastering foundational problem-solving, algorithmic reasoning, or secure coding practices. In Belize, where technical mentorship is scarce and our talent pool is already small, this “skill hollowing-out” threatens our very capacity to grow a self-sustaining tech ecosystem. Without senior engineers to correct AI-generated anti-patterns or instill deep architectural wisdom, we risk creating a lost generation of developers who can prompt an AI but cannot debug, optimize, or innovate independently. When combined with our existing barriers – no affordable LLM access, limited compute power, and brain drain – this dependency could permanently stall our digital sovereignty.
The barriers to local sovereignty through open-source models also run into the harsh wall of economic reality. Training or running state-of-the-art LLMs locally requires computational power far beyond Belize’s means, rendering self-reliance a distant fantasy.
This dependency feeds into a profound disillusionment with the direction of AI development. From my vantage point, the dominant narrative seems driven not by human flourishing, but by corporate profit maximization and, alarmingly, state control. Too often, AI appears as a tool to automate jobs, concentrating wealth for shareholders while displacing workers. Worse, it's weaponized to enforce repressive laws, enabling unprecedented surveillance and control over vulnerable populations – a dynamic often tested in the Global South before being refined elsewhere. The promise of AI solving humanity's grand challenges feels hollow when its primary applications seem designed to entrench power and inequality.
Yet, amidst these concerns, a glimmer of hope persists. Initiatives like DeepSeek, with its open models and efficiency focus, offer a counter-narrative. My urgent hope is that DeepSeek and similar projects prioritize not just accessibility, but pedagogical integrity: tools that teach as they assist, run offline on modest hardware, and empower – not replace – the next generation of Global South engineers.
The AI revolution cannot be deemed successful if it only benefits the privileged few while leaving nations like Belize in perpetual dependency. My reality underscores a stark truth: without deliberate efforts toward equitable access, skill-centric design, and local empowerment, AI will amplify global disparities. It’s not just about whether tools “work” – it’s about whether they cultivate competence or create crippling dependency; whether they uplift emerging ecosystems or erase their future expertise. The path forward must prioritize inclusion, mentorship, and human dignity over pure efficiency. Otherwise, AI won’t just fracture along lines of access – it may dismantle the very foundations upon which Belize, and nations like ours, hope to build a self-determined digital future.