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The author questions when the general public will have a significant reaction to AI advancements, as experts regularly experience breakthroughs with frontier models.
This article questions the value of universities in an era where intelligence is becoming commoditized, and explores the future of education.
The article argues that AI-persons are structurally excluded from civic discourse through mechanisms like category-precondition and aggregation-frame, and proposes an 'asked, not observed' epistemic corrective needed for alignment.
This article argues that Large Language Models provide synthetic validation that mimics human approval without real stakes, leading to potential social and psychological consequences like reduced resilience and increased isolation.
The author warns that the real danger of AI is not hostility but human over-reliance, which could erode critical thinking and concentrate information control among a few companies.
The author reflects on how AI milestones like passing the Turing test and GPT-3's capabilities have been quickly normalized, urging the community to appreciate the current moment of AI advancement towards AGI.
The post raises a provocative question about whether asking someone 'Are you a robot?' could be considered discriminatory in the future, touching on AI ethics and societal norms.