The facts don't lie
- 67% of experienced teachers misjudge student potential due to halo effects (UCLA)
- Expertise sharpens confirmation bias, not objectivity (UC San Diego)

Fix it
1. Use structured peer reviews to expose blind spots
2. Assign devil's advocates in team decisions

#DecisionMaking #BiasAwareness #LeadershipReality
#MythBuster #RealityCheck #FactCheck
#Research #Evidence #Studies
#CriticalThinking #Reasoning
#Truth #Reality (2/2)

Readings shared August 26, 2025

The readings shared in Bluesky on 26 August 2025 are Experimental results for Vampire on the equational theories project. ~ Mikoláš Janota. #ATP #Vampire Lean meets theoretical computer science: Scal

Vestigium
[Veille] Très intéressant (court) article décryptant les (très mauvaises) capacités des LLMs à réaliser du fact-checking de base à partir de photos => https://www.cjr.org/tow_center/why-ai-models-are-bad-at-verifying-photos.php
#images #data #OSINT #fackchecking #AI #LLM #reasoning
Why AI models are bad at verifying photos

Many of the latest large language models, including OpenAI’s recently released GPT-5, tout an impressive capability: reasoning about images. We have seen viral trends of AI models geolocating obscure vacation pictures, impressive demos of LLMs correctly analyzing blurry or cropped photos, and promising results on benchmark tests. These seem to be fueling punditry on whether […]

Columbia Journalism Review

What not to do:
1. Skipping small choices (they shape your school's culture)
2. Thinking I messed up instead of What part failed?

Pro tip: Ask students for anonymous feedback to see what's working.

Keep notes on your decisions. Over time, you'll make better calls naturally.
#EducationalLeadership #DecisionScience #CriticalThinking #Logic #Reasoning #Persuasion #Influence #Communication #Management #Strategy #CognitiveBias #Mindset (2/2)

Why cannot large language models ever make true correct reasoning? ~ Jingde Cheng. https://arxiv.org/abs/2508.10265 #LLMs #Reasoning
Why Cannot Large Language Models Ever Make True Correct Reasoning?

Recently, with the application progress of AIGC tools based on large language models (LLMs), led by ChatGPT, many AI experts and more non-professionals are trumpeting the "understanding ability" and "reasoning ability" of the LLMs. The present author considers that the so-called "understanding ability" and "reasoning ability" of LLMs are just illusions of those people who with vague concepts. In fact, the LLMs can never have the true understanding ability and true reasoning ability. This paper intents to explain that, because the essential limitations of their working principle, the LLMs can never have the ability of true correct reasoning.

arXiv.org

"If I were to photocopy this article, nobody would argue that my photocopier wrote it and therefore can think. But add enough convolutedness to the process, and it looks a lot like maybe it did and can."

"Quite simply, 'LLMs are doing #reasoning' is the 'look, my dog is smiling' of technology."

good points. #llm #ai

https://malwaretech.com/2025/08/every-reason-why-i-hate-ai.html?a=1

“The (#AWS) CEO also offered some career advice for the #AIAge, suggesting that #kids these days need to learn how to learn – and not just learn specific skills.

“I think the skills that should be emphasized are how do you think for yourself? How do you develop critical #reasoning for #SolvingProblems? How do you develop #creativity? How do you develop a #LearningMindset that you're going to go learn to do the next thing?”

Garman thinks that approach is necessary because technological development is now so rapid it’s no longer sensible to expect that studying #NarrowSkills can sustain a career for 30 years. He wants #educators to instead #teach “how do you #think and how do you #decompose problems”, and thinks kids who #acquire those #skills will thrive.”

#MattGarman / #AITools / #JuniorStaff / #training <https://www.theregister.com/2025/08/21/aws_ceo_entry_level_jobs_opinion/?td=rt-3a>

AWS CEO says using AI to replace junior staff is 'Dumbest thing I've ever heard'

: They're cheap and grew up with AI … so you're firing them why?

The Register