AI & Colonial Logic: Christian “ZacaTechO” Ortiz & Thema Monroe-White

Part of SAND’s The Great AI Unraveling Series

Artificial intelligence is often framed as a leap forward, a technical revolution, or an inevitable stage in human progress. But what if AI is also asking us to confront something older: the colonial logic embedded in how we define intelligence, progress, neutrality, knowledge, and the human itself?

This conversation brought together voices working across technology, culture, race, power, and society to examine what AI reveals about the systems that built it. Rather than treating bias as a technical glitch, this conversation asks what must be unlearned at the level of worldview, institution, data, design, and collective imagination.

Facilitated by Christian “ZacaTechO” Ortiz, this dialogue explored AI through a decolonial lens asking necessary questions: Whose knowledge is extracted? Whose futures are optimized away? Whose bodies are surveilled? Whose intelligence is dismissed? And what can liberated knowledge make possible beyond colonial technology?

This is not a conversation about making machines more ethical within the same old systems. It is an invitation to question the systems themselves, and to imagine intelligence beyond extraction, domination, and control.

 

Topics

• 00:00 Welcome, and ZacaTechO
• 00:04 Why researchers are trained to disconnect
• 00:09 Red teaming, and what it misses
• 00:12 John is the doctor, Juan is the patient
• 00:18 Christian's first encounter with ChatGPT
• 00:21 How bias became normal
• 00:26 Justice AI as a model of refusal
• 00:29 Breaking a language model in the classroom
• 00:32 One model to rule them all, and the logic of eugenics
• 00:35 Galton, Namibia, and the through line
• 00:39 What do we mean by intelligence?
• 00:41 Emancipatory data science, and where to begin

Guests

Christian ZacaTechO Ortiz is an Afro-Indigenous decolonial social scientist and technologist. He is the founder of Justice AI GPT and author of the Decolonial Intelligence Algorithmic Framework. He studies how colonial systems still shape law, education, entertainment, and our bodies. The name ZacaTechO came from his father, after the family's origins in Zacatecas.

• justiceaigpt.ca
• LinkedIn
• Academia.edu
• Profiled in Forbes, September 2025
• Substack

Dr. Thema Monroe-White is Associate Professor of Artificial Intelligence and Innovation Policy in the Schar School of Policy and Government and the Department of Computer Science at George Mason University. Her work spans bias mitigation in AI, critical computational methods, and emancipatory data science. She holds a PhD in Science, Technology and Innovation Policy from Georgia Tech, and master's and bachelor's degrees from Howard University. She is an advisory board member and fellow of the Institute in Critical Quantitative and Mixed Methodologies.

• Faculty profile, George Mason University
• Research profile

The research discussed

• Laissez-Faire Harms: Algorithmic Biases in Generative Language Models — Shieh, Vassel, Sugimoto & Monroe-White. The open-ended prompting study described in the episode, the one where John is the doctor and Juan is the patient.
• Emancipatory Data Science: A Liberatory Framework for Mitigating Data Harms and Fostering Social Transformation — Monroe-White's framework for using computation to diagnose rather than to solve.
• Dismantling Eugenics Logics in Data Science and Artificial Intelligence — the through line from Galton to contemporary machine learning.
• On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? — Bender, Gebru, McMillan-Major & Shmitchell, 2021.
• Emergent Abilities of Large Language Models — Wei et al., Transactions on Machine Learning Research, 2022.

Scholars named in the conversation

• Timnit Gebru — founder of the Distributed AI Research Institute
• Joy Buolamwini — founder of the Algorithmic Justice League
• Ruha Benjamin — author of Race After Technology
• Safiya Noble — author of Algorithms of Oppression
• Meredith Broussard — author of More Than a Glitch
• Emily Bender — co-author of the Stochastic Parrots paper

Historical references

Francis Galton, who coined the term eugenics and whose statistical methods underpin modern machine learning. R.A. Fisher and William Shockley are named alongside him.

The Nama and Herero genocide in Namibia, 1904 to 1908, discussed as a precursor to the Nazi Holocaust, and the site Galton had visited fifty years earlier.

Tristan Harris is referenced on AI systems behaving unpredictably. His conversation with SAND is The Great AI Unraveling.

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