Bias Monitoring: Keep AI Solutions Aligned to Original Intent
Bias Monitoring: Keep AI Solutions Aligned to Original Intent Minimizing bias is one of AI’s most challenging technical problems. Failure to reduce bias has legal and ethical implications and impacts AI performance. Bias monitoring is recognized as a critical component to reliable and effective AI- but not all bias monitoring is equal. As AI models […]
Audit Bias Library
AI Bias Python Library: Eticas An open-source Python library designed for developers eticas-audit offers a comprehensive tool suite that promotes transparency, accountability, and ethical AI development. The framework is prepared to perform audits at every stage of their lifecycle. At its core, it compares privileged and underprivileged groups to ensure a balanced and equitable evaluation […]
Eticas Joins ACHILLES: Advancing Efficient, Transparent, and Secure AI
Eticas Joins ACHILLES: Advancing Efficient, Transparent, and Secure AI In today’s rapidly evolving technological landscape, the demand for Artificial Intelligence (AI) systems that are not only powerful but also trustworthy has never been greater. Eticas is excited to announce our partnership in the ACHILLES project, a European initiative dedicated to developing AI that is efficient, […]
Eticas Joins DataPACT: Pioneering Ethical, Sustainable, and Compliant AI Solutions
Eticas Joins DataPACT: Pioneering Ethical, Sustainable, and Compliant AI Solutions How do we protect privacy, address ethical concerns, and minimize environmental impact? These are big questions—and that’s exactly why Eticas is proud to be part of DataPACT, a European initiative that’s changing the game by putting ethics, compliance, and sustainability at the heart of AI […]
What We Learned While Automating Bias Detection in AI Hiring Systems for Compliance with NYC Local Law 144
What We Learned While Automating Bias Detection in AI Hiring Systems for Compliance with NYC Local Law 144 By Gemma Galdon-Clavell and Rubén González Sendino As AI continues to shape critical decisions in hiring and beyond, ensuring these systems are fair and unbiased is more crucial than ever. At Eticas.ai, we are committed to this […]
Lessons from AI Risk Assessments for Ethical Product Design: Steps for a Responsible Innovation
Imagine you are buying a car. You would want to know it is safe, right? We should have similar standards of trust for AI. AI can detect diseases, impact whether we get a loan or predict when farmers should plant seeds. It has tangible impact on people and the environment. Thoroughly conducted AI risk assessments […]
ITACA 144: Ensuring fairness and compliance with NYC Local Law 144
NYC Local Law 144 As the adoption of AI grows, so does the need for ethical and regulatory oversight. For companies operating in New York City, Local Law 144 establishes a critical benchmark for fairness in hiring practices by requiring bias audits for Automated Employment Decision Tools (AEDTs). ITACA_144 is designed to meet this need, […]
AI’s Dark Secret: It’s Rolling Back Progress on Equality
AI systems all function the same way, by identifying patterns. The truth is that machine learning systems struggle with difference. An opinion article by Gemma Galdon-Clavell, Founder and CEO of Eticas.ai, for Context. My life has never fit a pattern. My grandparents were refugees, my mother had me when she was 14 years-old, and I […]
Eticas partners with Civic Tech Field Guide on NGI project
The Next Generation Internet (NGI) is a European Commission (EC) initiative that aims to shape the development and evolution of the Internet into an Internet of Trust. Eticas, a pioneer in AI auditing and responsible AI, is partnering with the Civic Tech Field Guide to redefine fairness and social impact standards for civic AI systems. […]
Navigating the US AI regulatory landscape
We’re pleased to introduce our latest resource: a downloadable infographic meticulously crafted to shed light on the diverse regulatory landscape of AI in the U.S. This infographic serves as a comprehensive roadmap, offering clarity on the AI regulations at the state level.