The dark side of artificial intelligence adoption: linking artificial intelligence adoption to employee depression via psychological safety and ethical leadership | Humanities and Social Sciences Communications - Nature
<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFBPVzdudVdGUVJCalUxeUJpYzVGUTdEYzlISmFRZ3ZQQTE0Q0ZqaG9SbzhxRUxsekVHa1lRYlA3N2hrLWtMYjBmajYyWjZVd1JITFpIVTlMNHBCWlZWSExV?oc=5" target="_blank">The dark side of artificial intelligence adoption: linking artificial intelligence adoption to employee depression via psychological safety and ethical leadership | Humanities and Social Sciences Communications</a> <font color="#6f6f6f">Nature</font>
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safetyAnthropic partners with Australia to advance AI safety and track economic impact - CXO Digitalpulse
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<a href="https://news.google.com/rss/articles/CBMiowFBVV95cUxOd2ZVam0yQXZhYTFsWXdSSjRRaGFncUx1bnBDTFNMZU05VHhXT2JxRzJ0VDZHNEpfQzZoejR0TG90Y1pSaWljdmU4VWF1RUh6QXp1eDdZYmNrRXktTEVQMDVoQ1BlRG9UekxnMGJGdmhLT3Q0TlZpNTVWOUNsU2Y2X014ZmVNdGpYRTdTbFVINExWTkhuTkkxSy1KSWVDNkhoLVNB?oc=5" target="_blank">AI giant Anthropic signs safety pact with Australia</a> <font color="#6f6f6f">Inner East Review</font>
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arXiv:2603.29038v1 Announce Type: new Abstract: Fine-tuning APIs offered by major AI providers create new attack surfaces where adversaries can bypass safety measures through targeted fine-tuning. We introduce Trojan-Speak, an adversarial fine-tuning method that bypasses Anthropic's Constitutional Classifiers. Our approach uses curriculum learning combined with GRPO-based hybrid reinforcement learning to teach models a communication protocol that evades LLM-based content classification. Crucially, while prior adversarial fine-tuning approaches report more than 25% capability degradation on reasoning benchmarks, Trojan-Speak incurs less than 5% degradation while achieving 99+% classifier evasion for models with 14B+ parameters. We demonstrate that fine-tuned models can provide detailed resp
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