Empowering Communities Through AI and Technology

Bias in AI and Potential Solutions

Bias in AI is due to the large data sets that are being used today to train these models. The data sets are a representation of our society, but AI models cannot be engines to spread or amplify similar biases in their responses/solutions. Instead, AI companies bear the responsibilities to actively train their models to identify and mitigate these biases.

Green AI

Green AI represents a transformative approach to harnessing artificial intelligence for the benefit of our planet. By leveraging advanced algorithms, AI is enhancing our ability to predict natural disasters, optimize farming practices to increase yield while minimizing environmental impact, and reduce waste in urban areas through smarter resource management. Additionally, it plays a crucial role in endangered species, helping conservationists protect. Importantly, Green AI also emphasizes sustainability by focusing on that consume less electricity, addressing the energy concerns associated with large AI models.

Accessible Technology Advocacy

We advocate for the widespread adoption of accessible technology, making sure that advancements in AI and tech are inclusive and cater to diverse needs. Our efforts focus on enhancing accessibility for all individuals and communities.

Bias In AI

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Problem

AI models are trained on large data sets available on the internet. These data sets are representative of the current state in hiring, welfare, healthcare and other areas reflecting gender, race and economic biases in our society. AI models trained on this data learn to use these biases as acceptable and build into proposed solutions thus amplifying the bias issue,

Impact

Users of AI models will unknowingly base their decisions and build solutions around AI generated responses. This dissemination of bias will tremendously hurt already disadvantaged communities.

Possible Solutions

AI companies are introducing efforts to reduce bias in AI models through various approaches - trying to create datasets that more balances and representative of all ages/communites/race, building checks and balances to ensure responses are not discriminatory.

Accessible AI

Reaching Audiences

In order to spread our message, it is pivotal to be able to reach audiences of distinctive ethnicities, cultural backgrounds, and economic perspectives. The way to do this is through podcasts, social media, and publishing articles, websites, etc.

On podcasts, interviewing executives, data scientists, environmentalists, and economists can give insight into future projects to help others.
Social media can help spread awareness about Prime Radiant AI's meaning, lighting a spark of curiosity to contribute to our cause.
Finally, publishing polished articles can give detailed instruction and research to more people looking into this topic.

Affected Communities

Artificial Intelligence is an extremely powerful tool, it being able to summarize and solve problems in mere seconds. Like any tool, it can do inspiring feats in the right hands. In this case, healthcare, finance, transportation, which can help struggling communities.

AI assists healthcare by analyzing data to improve diagnostics and personalize treatments.
AI can help the finance industry by automating tasks like data analysis and fraud detection, which increases efficiency and accuracy.
AI enhances transportation by optimizing traffic flow, and allowing safer autonomous vehicles through data analysis and predictive technology.

Green AI

What is Green AI

Green AI is about making artificial intelligence better for our planet.
It focuses on reducing the environmental impact of AI technology.
This means using less energy when training and running AI models, making data centers more eco-friendly (like using renewable power)
Cutting down on electronic waste from AI hardware.
Essentially, Green AI aims to ensure that the amazing things AI can do for us don't come at a cost to the Earth.

Potential Solutions

Some of the countries leading the way include:

United States: Big tech companies in the US are working hard to make their huge data centers more energy-efficient and power them with clean energy.
China: They are investing a lot in AI and are also using it to help with things like reducing pollution in cities and managing energy better.
European Union (EU) countries: These countries have strong environmental goals, and they are bringing those same ideas into how they develop AI. France, for example, is helping lead a global group called the "Coalition for Environmentally Sustainable Artificial Intelligence."