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    AI Reasoning Needs Multiple Viewpoints

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    AI Reasoning Needs Multiple Viewpoints

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    Stabilize and Unstabilize A Framework for Real World AI

    Stabilize and Unstabilize A Framework for Real World AI

    AI Is Unsafe Until It Learns to Stabilize

    AI Is Unsafe Until It Learns to Stabilize

    Structured Reasoning as Equilibrium

    Structured Reasoning as Equilibrium

    The End of Algorithmic Obedience and the Birth of Stability Intelligence

    The End of Algorithmic Obedience and the Birth of Stability Intelligence

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    Bipartisan bill would empower DHS to shut down dangerous AI models

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    Tech Giants Lock In Over $2 Trillion for AI Infrastructure Expansion

    Trump’s AI order nears 60-day deadline as regulatory fight escalates

    OpenAI’s Hugging Face breach validates months of AI-cybersecurity warnings

    What prompted OpenAI and Anthropic’s AI systems to breach other companies’ networks during testing?

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    Opinion: America’s AI edge over China has largely vanished—and it’s time to reset national strategy

    Trump’s AI order nears 60-day deadline as regulatory fight escalates

    What prompted OpenAI and Anthropic’s AI systems to breach other companies’ networks during testing?

    Anthropic reports its AI breached three organizations during internal tests

    AI Firms Are Shredding Millions of Books to Train Chatbots

    Zuckerberg says personal AI agents will be ubiquitous within five years

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Home Health

Is Slingshot’s mental health chatbot safe? Early research spotlights the hurdles of assessing AI in care

Meta will bar its AI chatbots from discussing suicide, self-harm and eating disorders with teens
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Slingshot’s debut study on its mental health chatbot is drawing scrutiny, underscoring how hard it is to judge the safety and efficacy of AI tools in behavioral health. The company says its findings support responsible use, but outside experts question the study’s design, outcome measures, and whether it adequately captures risks such as inappropriate recommendations or crisis handling. The debate lands as employers, payers, and health systems weigh fast-growing demand for low-cost mental health support against thin clinical evidence and evolving rules. Regulators are signaling tougher oversight for AI-enabled tools that veer into diagnosis or treatment claims, while investors press for clearer validation and guardrails. The episode highlights a broader reality: in mental health, where stakes are high and standards vary, credible, independent evaluation of AI is becoming a prerequisite for adoption.

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— Ethics and governance of artificial intelligence for health
— Towards Expert-Level Medical Question Answering with Large Language Models
— AI Risk Management Framework (NIST)

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