AI safety in the Caribbean and the path toward more inclusive AI implementation

The Caribbean region faces unique challenges in artificial intelligence adoption and development, stemming from its distinct post-colonial history and current socioeconomic realities. Global AI safety frameworks have historically failed to address the specific needs of smaller regions like the Caribbean, where cultural preservation and linguistic diversity present particular concerns.

Cultural and linguistic context: The Caribbean’s complex post-colonial environment has created distinct challenges for AI implementation and development.

• Historical slavery and indentureship have led to cultural fragmentation and language erosion, which contemporary AI systems struggle to properly address
• Caribbean Creole languages lack adequate representation in AI training datasets, contributing to ongoing linguistic marginalization
• Local data collection and control often resides with external entities rather than Caribbean institutions, raising concerns about cultural sovereignty

Infrastructure and economic challenges: The region faces significant structural barriers to AI development and implementation.

• Unstable internet connectivity and frequent power outages create obstacles for consistent AI system deployment
• Key economic sectors like tourism and business process outsourcing face potential disruption from AI automation
• Limited access to advanced hardware and high-performance computing resources constrains sovereign AI development efforts

Resource limitations: Technical and financial constraints impact the Caribbean’s ability to participate in global AI advancement.

• Development of independent AI capabilities requires substantial resources that many Caribbean nations struggle to access
• Brain drain of skilled technical professionals to other regions hampers local capacity building
• Geopolitical dynamics create additional hurdles in obtaining necessary advanced computing hardware

Proposed solutions: A comprehensive framework for inclusive AI development requires multiple coordinated interventions.

• Promotion of low-compute AI models that can function effectively with limited resources
• Development of open-source processing hardware architectures to reduce dependency on external suppliers
• Creation of ethical data collection initiatives focused on underrepresented languages
• Establishment of sustained funding mechanisms for local research and infrastructure development
• Identification and development of niche AI industries that can generate foreign exchange

Regional implications: The future of Caribbean AI development depends heavily on how global frameworks evolve to accommodate regional needs.

• Success requires meaningful inclusion of historically underrepresented regions in multilateral agreements
• Capacity development initiatives must address both technical skills and brain drain concerns
• Alignment with broader sustainability goals is essential for long-term viability

Beyond the frameworks: While proposed solutions offer a pathway forward, implementation will require sustained commitment from both global and regional stakeholders to ensure the Caribbean’s unique cultural heritage and economic interests are protected in the emerging AI landscape.