What is The New Jim Code, and how are AI systems automating discrimination in policing, hiring, banking, and healthcare?

In this episode of The Miseducation of Technology, Attorney Danielle takes a deep dive into The New Jim Code, a term coined by Ruha Benjamin to describe how artificial intelligence doesn’t just reflect racial bias—it automates and amplifies it, embedding discrimination into the very systems that shape our daily lives. AI is often framed as objective, but when it learns from biased data, it doesn’t correct historical injustices—it makes them worse.

Inside this episode, Danielle explores:

• What is an algorithm? Understanding how AI systems make decisions and why their neutrality is a myth.

• Facial recognition bias: AI-powered surveillance tools misidentify Black faces at alarming rates, leading to wrongful arrests like those of Robert Williams, Nijeer Parks, Michael Oliver, and Porcha Woodruff—real people whose lives were disrupted by flawed technology.

• Algorithmic redlining in banking: AI-driven lending models continue the legacy of housing discrimination, disproportionately denying loans to Black and Hispanic borrowers, even when they meet financial qualifications.

• Predictive policing: AI models trained on biased crime data fuel over-policing of Black and Brown communities, keeping them under constant surveillance while reinforcing dangerous racial stereotypes.

• AI failures in hiring and image recognition: From tools that penalize women applicants to systems that have misclassified Black faces in harmful ways, Danielle unpacks how bias seeps into technologies designed to streamline decision-making.

• AI in healthcare: A 2019 study exposed how AI used in hospitals systematically deprioritized Black patients for critical medical care, reinforcing existing disparities in the healthcare system.

But it’s not just about uncovering the harm—it’s about pushing for solutions. Attorney Danielle discusses:

• The role of diversity in AI development—why representation matters in designing fairer systems.

• The need for transparency and accountability—how tech companies must audit their AI for bias before deploying it.

• How we can take action—from advocating for ethical AI policies to staying informed about the ways technology impacts our lives.