Inspiration
Investigation possible correlation of "by-proxy" liability of Data center placement on human longevity (health, poverty, environmental factors, etc).
What it does
Quantifies Environmental Harm: It identifies the literal "toll" of AI, noting that by 2030, emissions from data center backup systems are projected to cause 1,300 premature deaths annually. It highlights that a single facility can consume 5 million gallons of water daily, often in water-stressed regions like Arizona and Texas.
Exposes Systemic Inequality: The project maps how data centers are disproportionately sited in areas with high Social Vulnerability Index (SVI) scores. It specifically calls out patterns of environmental racism, such as developers redirecting projects to majority-minority counties (e.g., South Memphis) after being rejected by wealthier, white communities.
Audits Economic Extraction: It reveals how "tax incentives" for tech giants starve local infrastructure. For example, in Virginia, these subsidies resulted in a $267 million loss for K-12 education in one year, effectively underfunding students by $212 per person.
Predicts a "Longevity Gap": It illustrates a grim dichotomy: while AI software is used to extend the lifespans of the wealthy, the physical reality of its production (pollution, noise, and resource depletion) acts as a "longevity depressant" for those living near the infrastructure.
Advocates for "Health-Informed Computing": The project concludes by demanding a shift in tech development that prioritizes human life and environmental health over raw processing power and corporate revenue.
How we built it
Utilizing AI automation to build an ETL pipeline that aggregates public data into a comprehensive master dataset to feed into a gelocation mapped visualizer modeled in Unity.
Challenges we ran into
Fractured and blocked public data access: Critical public data blocked by insanely expensive paywalls; No prior Unity experience; SonySDK was windows only (we were all on Macs); R&D pipeline for complex scale project in 12 hour timeframe.
Accomplishments that we're proud of
Aggregating public data into a centralized master dataset to be open sourced. Clear relationships visualized to validate primary hypothesis. Solving something urgent that matters.
What we learned
Get a Unity expert and check SDK requirements before choosing device to develop for :,)
What's next for The Longevity Project
Continue investigating the relationships and correlation with data scientists.
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