Building Sustainable AI
Building Sustainable AI: Why Startups Must Collect Ground-Level Data In the race to develop artificial intelligence (AI) for sustainable manufacturing and equitable human well-being, startups hold immense potential to reshape how AI serves humanity. A critical strategy for achieving long-term sustainability and practicality lies in collecting ground-level data from diverse, often marginalized communities to train AI models. Unlike top-down, profit-driven approaches that treat underprivileged groups as mere variables, grassroots data collection ensures AI solutions are inclusive, contextually relevant, and resilient, aligning with the goal of empowering workers and addressing basic needs without prioritizing investor gains. Ground-level data collection involves engaging directly with workers, informal laborers, rural communities, and other underrepresented groups to gather insights that reflect their lived realities. For instance, in sustainable manufacturing, factory workers ...