Algorithmic Bias, AI Safety, Machine Learning Ethics, Technology Impact

AI Will Flatten Workforce Inequality–If We're Honest About What That Means
danielkliewer.com·2d·
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Legible vs. Illegible AI Safety Problems
lesswrong.com·1d
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OpenAI for Science
openai.com·20h·
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The Paradox of a Principled Machine
artificiallyintelligentspace.substack.com·1d·
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The future of LLMs: cognitive core and cartridges?
killerstorm.github.io·15h·
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Accumulating Context Changes the Beliefs of Language Models
lm-belief-change.github.io·6h·
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Why Are We Talking About Superintelligence?
calnewport.com·3d·
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AI web browsers are cool, helpful, and utterly untrustworthy
computerworld.com·1d·
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📵Digital Minimalism
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Smarter AI models show more selfish behavior
psypost.org·1d·
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The Drift Principle: why systems get worse even when they're "working"
news.ycombinator.com·22h·
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From vibe coding to context engineering: 2025 in software development
technologyreview.com·1d·
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Don't Trust Smart People
mtmason.com·1d·
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A Decade of AI Platform at Pinterest
medium.com·1d·
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Experiences with AI-Generated Pornography
link.springer.com·1d·
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The AI development trap that wastes your time
suchdevblog.com·23h·
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😴Sleep Optimization
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Sable and Able: A Tale of Two ASIs
lesswrong.com·1d
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Topographical sparse mapping: A training framework for deep learning models
sciencedirect.com·1d·
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Bullying Is Not Innovation
perplexity.ai·1d·
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An ARENA 6.0 Capstone: Model Organism of Encoded Reasoning
lesswrong.com·13h
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How to talk to people about AI threat
lesswrong.com·1d
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