Blog de Insights

New tool connects organizations that are confronting AI bias, data rights, tech worker exploitation, and other social justice issues.

Investigaciones de Mozilla revelaron que las herramientas de detección no siempre son tan confiables como dicen. Además, los investigadores descubrieron que se puede incitar con éxito a los modelos de lenguaje de gran tamaño, como ChatGPT, a crear textos con más «sonido humano»

Los métodos populares empleados para revelar contenido sintético obtienen resultados de tan solo «Bajo» o «Suficiente» en el análisis de Mozilla. Persisten deficiencias en el contexto de un año, 2024, en que se celebrará un máximo histórico de elecciones

Mozilla investigates Common Crawl’s influence as a backbone for Large Language Models: its shortcomings, benefits, and implications for trustworthy AI

A simple experiment by Mozilla Foundation found that anyone can generate targeted campaign materials, despite OpenAI's policy banning this behavior.

It might appear that we’re at an impasse when it comes to regulating foundation models in the AI Act — in fact, this could put the entire AI Act at risk. But we believe there’s a middle ground for all sides to come to an agreement.

Mozilla's multi award winning podcast, IRL: Online Life is Real Life, returns for a seventh season.

The theme of this year's Webby Award-winning IRL podcast is how to put people over profit in artificial intelligence. Episodes spotlight people putting ideas on how to build more trustworthy AI into practice

Mozilla's multi award winning podcast, IRL, is back for a seventh season, all about putting people over profit in AI. Listen to the trailer.

The EU’s AI Act and Foundation Models: Considerations for the Final Stretch of Negotiations

In this explainer, we tackle one of the most basic questions: What are some of the key moments of human decision-making in the development of generative AI products? This question forms the basis of our current research investigation at Mozilla to better understand the motivations and values that guide this development process.

What is open source when it comes to AI? How should regulation treat open source to foster innovation without providing a pink slip to necessary regulatory compliance? What are the contours of the commercial deployment and corresponding liability in open source software?