Howard Rheingold10 posts about #metacognition -- a vital skill in the age of social media and #ai
Teaching #metacognition techniques to 4-6 year olds leads to better learning outcomes (and may immunize against cognitive decline caused by #ai use)
phb256Of maps and metacognition…
https://blog.raptnrent.me/2026/05/29/of-maps-and-metacognition/
Benjamin HanOn whether LLMs can abstain effectively and whether chain-of-thought can help, two recent papers seem at odds on the surface. COLING 2025 finds prompted CoT raises abstention on instruct models. AbstentionBench (NeurIPS 2025) finds extending the reasoning budget lowers it on a trained reasoner. What gives?
[Followup] Prompted vs. Trained Chain-of-Thought on Abstention: Reading Two Studies Together – synesis
Why prompted chain-of-thought raises abstention recall on instruct models in COLING 2025 but extending the reasoning budget on a trained reasoner lowers it in AbstentionBench, and three experiments that would clarify the picture.
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Can language models monitor and steer their own internal activations? A neuroscience-inspired neurofeedback paradigm finds yes, but only within a low-dimensional metacognitive space: semantically interpretable directions are accessible, raw-variance directions aren't. The prerequisite for spoofing activation-based oversight already partially exists.
#Paper #Metacognition #LLMs #AISafety #Neuroscience #NeurIPS #AI
Language Models Are Capable of Metacognitive Monitoring and Control of Their Internal Activations – synesis
A neuroscience-inspired neurofeedback paradigm shows LLMs can introspect and steer a low-dimensional metacognitive space of their hidden activations, with implications for activation-based oversight.
I used chatGPT to research cognitive risks of undisciplined use of #AI and what to do about it, then created a series of 7 books for my 5 year old grandson. If you don't want to download the 60 mb PDF of the illustrated books, this detailed curriculum guide details the pedagogy of #metacognition for very young people
https://rheingold.com/READ_FIRST_Thinking_System_Curriculum_Intro.pdf
and the entire set of books
https://rheingold.com/ThinkingCurriculum.zip
Does training an LLM to be calibrated on one task format transfer to another? A new arxiv paper tests two formats: single-question confidence and pairwise comparison. Training only on one doesn't improve the other. Multitask training closes most of the gap, but Llama doesn't inherit the comparison-task benefit.
Given a problem queue and a token budget, can an LLM plan which to attempt, in what order, and how much to spend on each — before any execution feedback? TRIAGE tests 20 frontier and open-source LLMs. Most plan worse than random. Reasoning-trained modes systematically lose to standard ones. Even when shown its own per-problem budget, the best complier respects it on 37% of attempts.
