Neuroscience-inspired interpretability is revealing how AI models organise knowledge, unlocking new safety and transparency tools. Progress is rapid, but full comprehension of high-stakes systems remains a challenge. Discover more at https://smarterarticles.co.uk/reading-machine-minds-how-neuroscience-is-unlocking-ai-transparency?pk_campaign=rss-feed
#HumanInTheLoop #AITransparency #NeuroAI #AIinSafety
Reading Machine Minds: How Neuroscience Is Unlocking AI Transparency

Somewhere inside Claude, Anthropic's large language model, there is a cluster of artificial neurons that lights up whenever the Golden ...

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Research reveals how language models can strategise, plan, and even deceive themselves through semantic priming, blurring the line between analysing behaviour and rehearsing it. Understanding this self-priming challenge is critical for safer AI development.
Discover more at https://dev.to/rawveg/the-self-priming-problem-in-ai-4p2a
#HumanInTheLoop #AIinSafety #NeuralNetworks #AIethics
The Self-Priming Problem in AI

In December 2024, researchers at Anthropic made an unsettling discovery. They had given Claude 3...

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Security and Safety (S&S)

#Journals | Security and Safety
📢 #CallForPapers

Special Issue on “Security and Safety in Artificial Intelligence”
#openaccess

Guest editors from:
#TongjiUniversity#FudanUniversity#UniversityofBologna and
#TU_Muenchen

📅 Submission deadline – 30 August 2024
Read More➡️ https://bit.ly/4fhPFu0
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