Page 406 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

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Item Details
Data Availability HEART Engine integrates multiple types of data through a structured
process designed to create a rich, hyperlocal knowledge foundation for
training and workforce development:
Primary Data Collection:
• Website Content Scraping: HEART Engine systematically scrapes and
analyzes publicly available information from regional nonprofit organi-
zations, civic tech groups, STEM accelerators, and innovation hubs to
build a real-time map of local ecosystems.
• Community Surveys: Targeted surveys are conducted within regional
communities to gather residents' perspectives on digital equity, tech-
nology adoption, and workforce needs, ensuring direct input from
underrepresented populations.
• Manual Aggregation of Cultural Artifacts: The HEART Engine manu-
ally curates essential regional cultural elements, including local music
history, entertainment trends, regional vernacular, and significant
cultural milestones, by analyzing public sources, local media archives,
and historical records.
Secondary Public Databases:
HEART Engine pulls structured datasets from trusted public repositories,
including:
• Government Labor Databases (e.g., U.S. Bureau of Labor Statistics,
Census American Community Survey)
• Education Datasets (e.g., National Center for Education Statistics,
Higher Education APIs)
• Digital Equity Reports (e.g., NTIA Digital Equity Act data, regional
broadband access maps)
These sources provide macro-level context for local workforce trends, digi-
tal divides, and educational attainment.
AI-Enriched Synthetic Cultural Data:
• Using Generative AI and natural language processing tools, HEART
Engine processes local cultural data, such as song lyrics from regional
artists, local news media coverage, and community storytelling proj-
ects, to extract meaningful cultural themes, values, and trends.
• This synthetic data is transformed into training modules that improve
the cultural fluency of Public Interest Tech Workers, making them more
effective at engaging communities in public interest tech work.

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