A critique of The Hidden Life-Ground of Artificial Intelligence focused on AI metabolism and Caribbean resource security. This episode asks how the paper can streamline its diagnostic frameworks, bring SIDS realities forward, and confront the geopolitical AI arms race through sufficiency, public-interest compute, regional bargaining, and life-ground security. Read More
A debate on the hidden physical cost of artificial intelligence. This episode asks whether AI governance should restrict demand through sufficiency and minimum symbolic form, or focus on supply-side accountability, data-center governance, public-interest compute, community consent, and AI commons. Read More
A critique of the AI life-capacity framework focused on Caribbean small island developing states. This episode asks how AI governance can be grounded in SIDS realities, made corrigible by affected communities, and translated into practical mechanisms such as civic stop buttons, public audits, procurement safeguards, and institutional resilience metrics. Read More
Artificial intelligence has rapidly become a planetary infrastructure for producing symbols: language, images, classifications, predictions, rankings, recommendations, simulations, and decisions. Yet symbolic intelligence is not wisdom, fluency is not truth, prediction is not judgment, personalization is not relationship, and optimization is not flourishing. This white paper applies the life-coherent framework developed in The Tears of Life to artificial intelligence as a defining test case of the present age. It argues that AI becomes harmful when its symbolic power is structurally coupled to commercial extraction, institutional control, immature human desire, surveillance architectures, and life-blind metrics. In such cases, AI functions as oracle, idol, or enclosure: it invites surrender of judgment, receives excessive trust and sacrifice, or captures the conditions of human meaning-making. Conversely, AI becomes life-coherent when governed as a bounded tool and shared commons in service of human agency, ecological limits, public truth, education, care, democratic participation, and systemic repair. The paper proposes a life-capacity test for AI governance and a practical framework for evaluating whether AI systems restore or disable the conditions through which life continues, recovers, and flourishes.
