A 2019 study focusing on racial-ethnic disparities in air pollution culture found that “racial and ethnic minorities are acutely vulnerable to air pollution because of the neighborhoods in which they live. In District 4, for instance, which includes Long Beach and the ports of Los Angeles, residents are affected by air pollutants caused by proximity to a port and supply chain corridor. As a hub for international trade, Los Angeles “receives 40% of all containerized cargo imports to the United States coming through the Ports of Los Angeles and Long Beach, making the surrounding communities which are primarily working-class Black and Brown communities – particularly vulnerable to deadly pollutants.” As a result, nearby communities that are made of up POC, will experience an eight year lower life expectancy than LA county neighborhoods, alongside having the highest risk of cancer regionally.
The District 4 monolith uses datasets related to racial equity like: Population, Language, Education, Social, Depression, Happiness IndexJoin the whitelist
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These laws of unintended consequences affect all systems—and can also affect the implementation of AI systems. In the future, the design of AI systems specifically work to advance equity rather than propagating systemic bias. This involves intentional work to create responsible AI across the whole cycle of AI use: from model creation to training to systems of application. Models are trained on more diverse datasets. People of color are advocates within the systems in which their data is used. AI decisions are built to be more explainable so that biases can be pointed out. Individuals and communities retain ownership for their data and are compensated properly for use.