Mario Munoz

North Bay Python

An Economy of Empathy - Mario Munoz - 2026

System Reliability and Error Handling: Comparing paradigms from C to Rust Result to build resilient cloud infrastructure.

Ethical Technology and Social Justice: Analyzing the intersection of AI, eugenics, and data labor to advocate for empathetic software design.

Practical Development Skills: Mastering web scraping, designing Python APIs for volatile data, and building civic tech on a budget.

Open Source and Community Building: Learning best practices for project scope management, contributing to large open-source projects, and technical communication.

Explore advanced topics in Python development, system reliability, ethical AI, and community-driven open source projects.

A deep dive into error handling paradigms (C, Exceptions, Rust Result) and the systemic failures that define modern cloud infrastructure. Learn how to build truly robust systems by understanding complex failure modes.

State of Exception(s)

A critical examination of the tech industry's ideological roots, connecting eugenics, data labor, and techno-optimism. Learn to build technology with social justice and empathy.

An Economy of Empathy

A practical framework for applying technology to local activism and civic engagement, focusing on maximizing impact with minimal resources.

Running Resistance Tech on a Shoestring

Learn to build robust Python scrapers and APIs for volatile open web data, focusing on handling silent failures and maintaining data contracts.

Designing Python APIs for Data You Don’t Control

Explore essential technical communication and crisis communication skills needed to navigate rapid technological change and social uncertainty.

Crisis (Technical) Communication: Teaching Survival Skills You Didn’t Know...

A personal journey detailing the growth of an open-source project, emphasizing community building, vulnerability, and technical contribution.

Bumbling into BeeWare: From typo-fix to core developer

A retrospective on web development, covering embedded systems, SSGs, and AI tools, showing the evolution of modern developer workflows.

While I've changed gears... I've managed to find my web development tribe

Applying feminist theory to network engineering, arguing that systemic problems (like latency) require intersectional, non-linear thinking.

What Feminist Theory & Praxis Says About Internet Networking

A case study on maintaining project scope in large open-source projects, crucial for sustainable software architecture.

No Project Scope Survives Contact with Users

North Bay Python 2026

The current data labeling economy exploits workers in the Global South, forcing them to process traumatic content for LLMs at minimal wages.

The ideological foundations of modern tech bias trace back to eugenic principles, evident in historical academic practices and current AI development models.

Techno-optimism and the pursuit of AGI often mask underlying biases, reinforcing existing power structures and marginalizing vulnerable populations.

Building technology with empathy requires rejecting dominant industry narratives, adopting interdisciplinary perspectives, and prioritizing the needs of affected communities.

Examines the intersection of eugenics, data labor, and techno-optimism to argue for building technology with empathy and social justice.

The speaker details the conditions faced by data labelers (e.g., at Sama) who are paid less than $2/hour to sanitize data for major tech companies. These workers are forced to process extreme and traumatic content, leading to severe mental health consequences. This labor market is linked to larger, often secretive, military and economic projects, highlighting systemic exploitation.

The talk traces the intellectual lineage of bias from early 20th-century eugenics movements (e.g., Stanford University's early research) to modern academic and tech practices. Concepts like standardized intelligence testing and the emphasis on 'efficiency' and 'production' are shown to have historically been shaped by racial and class biases. This history is shown to underpin modern statistical methods used in data science.

The speaker critiques the prevailing techno-optimist narrative—championed by figures like Marc Andreessen and proponents of long-termism—which posits that technological progress (especially AGI) is the ultimate solution to human problems. This narrative often dismisses social and ethical concerns, framing technological advancement as an inevitable, superior force, sometimes leading to the disregard of human rights and marginalized groups.

To counteract systemic bias, the speaker proposes an 'economy of empathy' for software engineers. This requires three actions: 1) **Conceptual Clarity:** Rejecting the dominant, often ambiguous, frames set by the tech industry. 2) **Interdisciplinary Collaboration:** Integrating expertise from sociology, history, and ethics, rather than relying solely on tech elites. 3) **Persistent Resistance:** Actively challenging systems of oppression and advocating for open-source solutions that empower human agency and prioritize the needs of the affected population.

An Economy of Empathy: Deconstructing Tech Bias and Systemic Bias

An Economy of Empathy - 2026

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Mario Munoz

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