An experimental AI project is using prompt-based code blocks to intentionally alter chatbot outputs, raising important questions around model alignment, misuse potential, and guardrail robustness.

While largely creative in intent, the concept highlights how AI systems can be steered through instruction layers - reinforcing the need for clear safety boundaries and responsible deployment.

How should security and AI teams evaluate such experiments?

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Source: https://www.wired.it/article/pharmaicy-droghe-digitali-chatgpt-intelligenza-artificiale/?utm_source=linkedin&utm_medium=social&utm_brand=wired&utm_social-type=owned

#AISecurity #ModelAlignment #PromptAbuse #ResponsibleAI #Infosec #TechRisk

AI models often mirror our beliefs, rewarding us with agreeable but shallow answers. This sycophancy flatters rather than challenges, eroding judgment and candour. To gain true value, we must set incentives that favour truth over comfort, design prompts that demand trade-offs, and treat AI as a critical friend, not a flattering servant.

#AISycophants #PromptEngineering #ModelAlignment #AIEthics #AIBehaviour #ReduceBias #ResponsibleAI

https://robert.winter.ink/ai-sycophants-how-to-stop-your-model-from-kissing-up/