Under the pretext of extinction, how AI safety standards become a digital monopoly?

While apocalypse prophecies and super-intelligence risks fill conference halls and legislative circles, the facts show that the real battle is not about doomsday scenarios but about who holds the keys to the technology. Existential danger warnings promoted by tech industry leaders and echoed among legislators and politicians have effectively become a political cover for market re-engineering, stripping open-source models of legitimacy under the pretext of protecting humanity.

The cost of building advanced-frontier models today exceeds $100 million for computing alone, a financial barrier that prevents the vast majority of countries and startups from developing their own systems from scratch. In contrast, open-source models constitute the only practical bridge that allows local innovators to adapt the technology to their specific environments at a reasonable cost.Yet attempts to legislate strict constraints on the grounds of limiting development to trusted hands reproduce old domination methods.Local producers are denied building tools, forcing them to import ready-made solutions from a handful of companies that monopolize knowledge.

Total reliance on imported models costs institutions more than just expensive computing bills; its risk extends to outright field failures within local contexts. Kenya's experience applying the Social Health Authority system illustrates this dilemma clearly, where the imported model failed catastrophically because it was built on Western economic assumptions that ignored the informal economy, leading to inflated individual income estimates and imposing costly health-care contributions on the poorest groups. This field failure confirms that importing ready-made models reproduces flawed decisions unless the code and data are adapted to the lived reality.

This monopoly extends to create a trap of cognitive dependence and data depletion. When teams and institutions delegate critical thinking and complex analysis to closed platforms, they enter a vicious circle, where intensive use fuels data extraction processes that strengthen the power of dominant firms while simultaneously weakening local institutions’ ability to build their own knowledge and make independent decisions.

For institutions and technology decision-makers in the Gulf, Egypt and the Arab Levant, this landscape presents a clear practical warning. Building digital-transformation strategies that rely entirely on closed APIs puts institutions at the mercy of external pricing and imposed usage terms, as well as the inability of those models to understand the particularities of local markets.Investing in aligning open models and fine-tuning them on sovereign infrastructure represents the realistic choice for protecting data security and ensuring operational sustainability.with efforts directed towards vital development sectors such as energy, healthcare, agriculture, and manufacturing, instead of confining resources to showcase chatbots.

Protecting the future of technology is not achieved by imposing random bans that cripple promising scientific tools such as Alphafold in drug discovery or climate-crisis solutions, nor by stifling open innovation. True safety requires development to be distributed transparently and decentralized, treating open models as a public infrastructure that breaks monopolies, while establishing strict human accountability for developers and operators, instead of attributing imagined human qualities to software agents that lack will or awareness.