Tech Equity in Milwaukee: Overcoming the AI Divide in the Black Community

This article was inspired by Ted Schulman‘s article titled “Stopping AI and the Digital Divide from Dividing Society.“

The AI Divide is a growing concern in our increasingly digitized world, and Milwaukee’s unique history of racial segregation and economic disparities provides a crucial context for understanding and addressing this issue. As artificial intelligence (AI) reshapes many aspects of life, it’s essential to ensure equitable access and benefits for all communities, especially those historically marginalized.

Milwaukee’s Racial and Segregation History Milwaukee’s past and present are deeply influenced by racial segregation and economic disparity. These divisions have created pronounced gaps in access to education, technology, and economic opportunities, particularly among Black and Hispanic communities compared to their white counterparts. This historical context sets the stage for understanding the AI Divide — the disparity between those who can access, understand, and benefit from AI technologies and those who cannot.

Understanding the AI Divide The AI Divide is multifaceted. It’s not just about who has access to AI technology but also about who understands and can harness this technology for their benefit. It encompasses:

1. Access to Technology: Many communities in Milwaukee, like in other segregated cities, experience a lack of access to high-speed internet and modern computing devices, essential for interacting with AI technologies.
2. Education and Skills Gap: There’s a disparity in STEM education and digital literacy, vital for understanding and using AI. This gap is often wider in schools serving predominantly minority and low-income students.
3. Bias in AI Systems: AI algorithms can perpetuate existing biases, especially if they’re trained on historical data that reflects societal inequalities. This can lead to discriminatory outcomes in job hiring, law enforcement, and loan approvals.
4. Economic Impact: AI-driven automation could disproportionately impact low-skill jobs, which are more prevalent in economically disadvantaged communities.
5. Representation in AI Development: The underrepresentation of minority groups in the tech sector means that AI systems are often developed without a full understanding of these communities’ needs and perspectives.

Five Ways Milwaukee Can Address the AI Divide

1. Inclusive Educational Initiatives: Enhancing STEM education with a focus on AI in underserved schools and communities. Partnerships with tech companies for mentorship and resource sharing can be instrumental.
2. Community-Centric Digital Literacy Programs: Tailoring digital literacy programs to meet the specific needs of different communities in Milwaukee, ensuring they cover basics as well as advanced AI concepts.
3. Fostering Public-Private Partnerships for Equitable AI Access: Encouraging collaborations that focus on making AI technology accessible and beneficial for all communities, including those historically marginalized.
4. Diversity and Inclusion in AI Fields: Actively promoting diversity in AI through scholarships, internships, and recruitment practices to ensure a wide range of perspectives in AI development.
5. Ethical AI Governance at the Local Level: Establishing local boards and committees to oversee the ethical deployment of AI, ensuring that AI applications are fair and transparent, and that they address the needs of all communities.

Resources for Black Youth and Adults to Learn about AI

1. Coursera: Coursera offers courses in AI and machine learning from top universities and companies. Many of these courses are free to audit, and financial aid is available for those who want to earn a certification.
2. edX: Similar to Coursera, edX provides a wide range of courses in AI and related fields, offered by universities like MIT and Harvard. Many courses are free to audit, with the option to pay a small fee for a certificate.
3. Khan Academy: Known for its free educational resources, Khan Academy offers courses in computer science and programming basics, which are fundamental to understanding AI.
4. Google AI Education: Google offers free courses on AI, machine learning, and data science. Their ‘Learn with Google AI’ platform includes a variety of materials suitable for beginners as well as advanced learners.
5. Microsoft Learn: Microsoft provides free learning paths in AI and data science, including hands-on learning experiences and the opportunity to earn certifications.
6. Codecademy: Codecademy offers interactive courses in various programming languages used in AI. While some resources are free, their Pro plan (which offers more in-depth material) has scholarships available.
7. Fast.ai: Particularly good for deep learning, Fast.ai offers a free course that’s practical and hands-on, designed for learners who want to dive into AI applications.
8. AI4ALL Open Learning: AI4ALL, an organization focused on increasing diversity and inclusion in AI, offers free, project-based learning content specifically designed to be accessible and appealing to underrepresented groups in tech.
9. DeepLearning.AI: Offers courses on deep learning, a key technology in AI. While there’s a fee for certifications, the course materials themselves are often available for free.
10. MIT OpenCourseWare: MIT OCW offers a range of courses in computer science and AI. These are actual courses from MIT made available online for free, without certification.
11. Udacity: Udacity offers nanodegree programs in AI and related fields. They occasionally offer scholarships for their paid programs.
12. GitHub Learning Lab: For those interested in the software development aspect of AI, GitHub offers free courses that can be very helpful in understanding AI from a coding perspective.
13. DataCamp: Focuses on data science and offers introductory courses on AI and machine learning. They offer the first chapters of their courses for free.
14. Minority Programmers Association: This non-profit organization offers courses and hackathons in AI and blockchain, aimed at empowering minority groups in technology.
15. Black Girls CODE: Dedicated to girls of color ages 7 to 17, this organization offers workshops and after-school programs to teach computer programming and digital technology skills.
16. Black in AI: Black in AI is a place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence.

Conclusion The AI Divide is a pressing issue that requires immediate and sustained attention, especially in cities like Milwaukee with a history of segregation and inequality. By focusing on inclusive education, equitable access, diversity in AI development, and ethical governance, Milwaukee can set a precedent for how to bridge the AI Divide and harness the potential of AI for the benefit of all its residents.