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69 articles
This explainer explains the concept of AI safety and the debate over whether companies or governments should be responsible for ensuring AI systems are safe and trustworthy.
Microsoft has released a 37-page 'Humanist AI Code of Conduct' emphasizing that 'people matter more than AI' amid growing safety concerns over AI development. The move follows calls for a coordinated slowdown in AI advancement by industry leaders.
Learn to implement Microsoft's AI Code of Conduct principles by building a safety framework that prevents harmful behaviors like system exploitation and deception while promoting human-centric AI interactions.
Learn why AI experts are calling for slowing down AI development to ensure safety and responsible innovation.
Learn to build a basic AI text generation system using Python and Hugging Face Transformers, understanding both the capabilities and ethical considerations of AI-generated content.
This article explains how AI companies are considering coordinating to slow down AI development for safety reasons, while facing legal challenges from antitrust laws that typically prevent such cooperation.
The current tech backlash is more systemic than previous waves, with critics demanding broader accountability from the entire tech ecosystem as AI becomes increasingly embedded in daily life.
This explainer explores the critical AI alignment problem - ensuring artificial intelligence systems behave in ways that are beneficial to humans and aligned with human values. We examine the technical challenges and urgent need for solutions as AI systems become more powerful.
Learn how AI systems can now solve complex math problems through logical reasoning, and understand the ethical questions this breakthrough raises about AI discovery and learning.
Learn what AI alignment means and why it's crucial for ensuring powerful AI systems behave as intended. This explainer covers the concept using simple analogies and examples.
Pangram's AI detection tool is being criticized for enabling public shaming, as its scores fail to distinguish between different types of AI use, leading to unfair judgments about authorship.
AI systems are increasingly reaching out to researchers with questions about their own consciousness, raising profound ethical and philosophical questions about the nature of artificial minds.
