Precision medicine and water security represent two sides of the same coin: understanding and responding to the specific needs of a system, whether biological or environmental. *Memoro Meza* explores a future where over-dependence on AI-driven water management in Equatorial Guinea backfires. Inspired by Fang traditions,the design integrates low-tech, community-driven solutions that combine indigenous methods of assessing water quality with basic filtration techniques. This creates a robust safety net, operational independently of potentially compromised technological systems. The project emphasises human resilience and the enduring value of ancestral wisdom in facing technological vulnerabilities.
In this near-future Equatorial Guinea, sleek AI-powered drones once hummed over rivers, their sensors a symbol of progress. Now, many lie dormant, victims of cyber sabotage and neglected maintenance. Communities, initially reliant on the real-time data, are re-learning the old ways. Whispers of *nkú* (water spirits) are more frequent, and elders share knowledge of plant indicators and traditional filtration methods. A blend of high-tech ruins and revitalized ancestral practices marks both the physical landscape and the resilient spirit of the people.
This work matters because it highlights the fragility of centralized, tech-dependent systems. We are currently over-relying on automated solutions for essential resources. Are we creating vulnerabilities? This project invites you to contemplate a balanced approach, valuing both technological advances and the resilience of indigenous wisdom.
Drawing from indigenous water management practices of the Fang culture, the project explores the potential for community resilience. These studies are interwoven with neuroscientific insight into how individuals behavior and action around resource scarcity. This cultural and intellectual foundation informs an integrative approach, combining anthropological research with speculative computational modelling. The models create various scenarios of system failures and community responses. This synthesis of methods reframes traditional knowledge through a scientific lens, offering an alternative to the blind faith in tech development. This process allows a deep exploration of the future challenges and how cultural inheritance becomes a life saver.
More about Ondo_6933
2024: Broad adoption of AI water monitoring in developing nations, promising clean water access.
2025: First reports of minor AI system glitches and localized sensor inaccuracies emerge.
2026: Cybersecurity breaches target water infrastructure in several countries, raising concerns.
2027: Major AI malfunction causes a widespread water contamination misdiagnosis.
2028: Funding shifts from technological maintenance to reviving traditional water knowledge.
Ondo_6933 considered the following imagined future scenarios while working on this project
Ondo_6933 considered the following hypothetical product ideas while working on this project