How to Overcome Societal Obstacles How to break into AI from a disadvantaged background.

Reading time
3 min read
Red and green board game pieces

By Benjamin Harvey

The top artificial intelligence companies include many people who earned degrees at elite educational institutions and started their employment with prior work experience. Yet the world is full of people from nontraditional backgrounds. They also have much to contribute to AI, but they face obstacles like minority status, low income, poor education, or social unrest.

I know this first-hand. I grew up poor and black in Jacksonville, the murder capital of the U.S. state of Florida. My neighborhood was a venue for street basketball and dope dealers. Many of my friends from that time are either dead or in jail.

If those challenges resonate with you, I offer a message of hope. I earned a doctorate in computer science, became chief of Operations Data Science at the National Security Agency, and founded an AI startup. You, too can join the community of machine learning engineers. It won’t be easy, but it can be done, and the rewards can be great in terms of both having a satisfying career and bringing good into the world.

The fact is, the AI industry needs a socially diverse workforce. Diversity among workers who curate datasets, design architectures, build models, and deploy systems can reduce bias and increase fairness.That makes for more robust systems and thriving businesses.

There are many ways that both students and companies can smooth the way from a disadvantaged background to a career in AI.

Students: You can benefit from many free services and educational materials available online, if you have access to a good internet connection. You may also be able to get help from your employer and nonprofits.

  • Look for nonprofit programs and companies that offer on-the-job training and cover the costs of courses or computing. If you’re already employed, take advantage of benefits for continuing education and access to technology.
  • Enroll in the nearest university that has a machine learning program. Study subjects that aren’t available locally through online courses. Pursue academic projects and research supported by nonprofits like the Common Mission Project.
  • Gain knowledge and experience by participating in competitions such as those sponsored by Kaggle. Publish your work in a repository on GitHub so others can adopt and contribute to it.
  • Ask people who are ahead of you in their careers to mentor you. Meet with them quarterly to share your experience and gather their insights.

Companies: If you don’t have a process for finding and hiring minority candidates, you’re missing a huge talent pool that is largely untapped by your competitors. Once you’ve hired them, be ready to nurture their talent and fill in gaps in their knowledge.

  • Drive the policies that enable the company to cover the cost of continuing education. Identify people in the organization who would benefit from continuing education. Organize an outreach program to make sure they know of the opportunity, have access to counseling, and don’t drop out (especially due to the demands of their employment).
  • Establish a machine learning center of excellence like Amazon’s. Such organizations can upskill talent and disseminate best practices to staff.
  • Create a nonprofit organization that supports early access to technology and education, especially in low-income areas, to prepare the next generation of AI and technology professionals. Mission Fullfilled 2030 is a good model.

If you work for a company that can open its doors wider to disadvantaged candidates, I urge you to proceed with all due haste. But if you’re an individual trying to find your way, don’t rush the process. You have a long journey ahead. No matter what school you come from, what stage you are in your career, and what adverse conditions you have experienced, continue to seek ways to improve. Face adversity head-on. Don’t give up on your dreams.

Benjamin Harvey is founder and CEO of AI Squared, a startup that helps organizations integrate AI into applications.


Subscribe to The Batch

Stay updated with weekly AI News and Insights delivered to your inbox