Black Box AI Black Box AI Explained: Navigating Interpretability and Trust in Deep Learning Explore the inherent challenges of "black box" AI algorithms, the crucial shift from explainability to practical interpretability, and how enterprises can manage AI bias and build trust for ethical deployment.
AI Bias Unmasking AI's Troubling Past: The Historical Roots of Bias in Generative AI Explore the uncomfortable history of generative AI, its surprising ties to eugenics, and how historical biases are baked into modern machine learning models. Learn how to address AI bias for ethical deployment.
AI Bias The Unseen History: How Early Eugenics Shaped Modern AI Bias and the Path to Ethical Development Explore the unsettling historical connections between race science and artificial intelligence, as highlighted by Valerie Veatch's film. Understand how this past influences present-day AI bias and learn about responsible AI development.
AI fairness Advancing AI Fairness: How Neural Networks Improve Skin Tone Estimation for Dermatoscopic Analysis Discover how neural networks, supervised by colorimeter data, are revolutionizing skin tone estimation from dermatoscopic images to enhance AI fairness in dermatology and beyond.
LLM in peer review Unpacking AI's Role in Peer Review: Do LLMs Favor Their Own? Explore a comprehensive analysis of LLM use in scientific peer review, revealing insights into interaction effects, rating biases, and the critical role of human oversight.
AI Bias The Unseen Bias: How Prompt Language Shapes AI's Analysis of Political and Business Information Discover how the language of your AI prompt can subtly introduce ideological bias into LLM outputs, impacting critical business and political analyses. Learn to navigate this complex challenge for ethical AI deployment.
