Published March 28, 2025
By : Staff Writer
The United States will celebrate National AI Literacy Day on March 28, 2025. Several organizations, including the EDSAFE AI Alliance, Tech Interactive, Common Sense, and the AI Education Project, support this annual initiative.
In 2024, Tech Interactive, a science, technology, and education center in Silicon Valley, launched the inaugural National AI Literacy Day Summit, one of several events taking place nationwide.
In collaboration with aiEDU, AI for Education, and the EDSAFE AI Alliance (InnovateEDU), the summit aimed to unite K -12 students, educators, and communities through an immersive exploration and discussion of artificial intelligence.
AI Literacy Day is a nationwide initiative designed to enhance understanding of artificial intelligence, explore its practical applications in education, and identify resources that promote AI literacy.
The advancement of AI across all industries and sectors is a significant development. AI is viewed as a powerful tool for democratizing knowledge, breaking the chains of controlled information, and dismantling systems of inequity.
This topic was a focus at the 29th annual Women of Color STEM Conference and its digital twin experience (DTX).
Several discussions during the three-day WOC STEM DTX Conference featured leading voices in AI, including a product lead responsible for developing and fielding weapon systems with a focus on AI capabilities.
Other panelists discussed leveraging AI technologies to create innovative and forward-thinking solutions.
During the "Inclusive Intelligence" seminar, an executive from Infosys and a computer science instructor from Detroit shared different perspectives on AI.
They addressed how AI systems are often built on statistical biases and emphasized the importance of developers being aware of and concerned about this issue.
Additionally, they discussed the code of ethics for developers and the distinctions between artificial intelligence (AI) and machine learning (ML).
Essentially, AI is programmed by developers and utilizes data models, whereas machine learning (ML) relies on predictions based on observed behavior.The seminar raised essential questions about the ethical responsibilities of developers when building technology.
One concerning issue is that AI often struggles to identify and differentiate individuals with darker skin tones accurately.
Facial recognition systems frequently rely on passport and driver's license photos from federal databases, which poses a risk of misidentification for Black and Brown individuals.
Data have highlighted this concern for Black Lives, as scientists and researchers have reported a significant margin of misidentification in facial recognition technology developed by tech companies.
