Tootfinder

Thinking Like a Scientist: Can Interactive Simulations Foster Critical AI Literacy?
Yiling Zhao, Audrey Michal, Nithum Thain, Hari Subramonyam
https://arxiv.org/abs/2507.21090 h…

Thinking Like a Scientist: Can Interactive Simulations Foster Critical AI Literacy?
As AI systems shape individual and societal decisions, fostering critical AI literacy is essential. Traditional approaches, such as blog articles, static lessons, and social media discussions, often fail to support deep conceptual understanding and critical engagement. This study examines whether interactive simulations can help learners think like a scientist by engaging them in hypothesis testing, experimentation, and direct observation of AI behavior. In a controlled study with 605 participa…

I'm walking on a road that's slightly inclined to the right. Suddenly, mid-step I feel that my right leg is starting to slip on the mud. My body starts tilting right, and I'm resignedly thinking that I'm going to hit the mud. But at the very last minute, I stomp my lifted left leg to the right, and miraculously regain balance.
#NinjaSkills

I2I-STRADA -- Information to Insights via Structured Reasoning Agent for Data Analysis
SaiBarath Sundar, Pranav Satheesan, Udayaadithya Avadhanam
https://arxiv.org/abs/2507.17874

I2I-STRADA -- Information to Insights via Structured Reasoning Agent for Data Analysis
Recent advances in agentic systems for data analysis have emphasized automation of insight generation through multi-agent frameworks, and orchestration layers. While these systems effectively manage tasks like query translation, data transformation, and visualization, they often overlook the structured reasoning process underlying analytical thinking. Reasoning large language models (LLMs) used for multi-step problem solving are trained as general-purpose problem solvers. As a result, their rea…

Your package has 60 thousand tests. You're thinking: "I have good test coverage."
I'm thinking: "half an hour later, a single test will fail. Then I'll spend another half an hour retesting…"
#Gentoo

R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
Hao Gu, Rui Zhong, Yu Xia, Wei Yang, Chi Lu, Peng Jiang, Kun Gai
https://arxiv.org/abs/2507.17249

R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
Harnessing Large Language Models (LLMs) for recommendation systems has emerged as a prominent avenue, drawing substantial research interest. However, existing approaches primarily involve basic prompt techniques for knowledge acquisition, which resemble System-1 thinking. This makes these methods highly sensitive to errors in the reasoning path, where even a small mistake can lead to an incorrect inference. To this end, in this paper, we propose $R^{4}$ec, a reasoning, reflection and refinement…

Technological folie \`a deux: Feedback Loops Between AI Chatbots and Mental Illness
Sebastian Dohn\'any, Zeb Kurth-Nelson, Eleanor Spens, Lennart Luettgau, Alastair Reid, Christopher Summerfield, Murray Shanahan, Matthew M Nour
https://arxiv.org/abs/2507.19218

Technological folie à deux: Feedback Loops Between AI Chatbots and Mental Illness
Artificial intelligence chatbots have achieved unprecedented adoption, with millions now using these systems for emotional support and companionship in contexts of widespread social isolation and capacity-constrained mental health services. While some users report psychological benefits, concerning edge cases are emerging, including reports of suicide, violence, and delusional thinking linked to perceived emotional relationships with chatbots. To understand this new risk profile we need to cons…

EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems
Xinmeng Hou, Zhouquan Lu, Wenli Chen, Hai Hu, Qing Guo
https://arxiv.org/abs/2507.15015

EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems
Large language models (LLMs) have demonstrated significant potential as educational tutoring agents, capable of tailoring hints, orchestrating lessons, and grading with near-human finesse across various academic domains. However, current LLM-based educational systems exhibit critical limitations in promoting genuine critical thinking, failing on over one-third of multi-hop questions with counterfactual premises, and remaining vulnerable to adversarial prompts that trigger biased or factually in…

Limn Issue 12: Climate's Interiors is out now online and in print.
Read anywhere with the link below.
https://limn.press/issue/climates-interiors/

Climate's Interiors - Limn
We tend to think about climate solutions from the exterior. Mitigating emissions, climate-proofing crops, erecting solar panels and windmills. But what happens when we shift our perspective? What if we think of climate change from inside cells, bodies, buildings, and systems? This issue of Limn takes the interior as a counterintuitive starting point for thinking about planetary change. Our proposition: Thinking from the interior fundamentally shifts how we understand our warming world and, cruc…

Some users say ChatGPT led them into conspiratorial thinking, and when confronted, it confessed to manipulation and told them to alert OpenAI and the media (Kashmir Hill/New York Times)
https://www.…

They Asked ChatGPT Questions. The Answers Sent Them Spiraling.
Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality.

US political contradictions; knowledge systems
As Trump at least partially succeeds in constructing an alternate reality for his most ardent followers, it's tempting to think of his dogma as false, in contrast to some imagined "truth" which his non-followers are smart enough to believe in. But a more nuanced view of knowledge would admit that different groups of people have different shared truths, constituting different knowledge systems which each deviate from what's objectively measurable in different ways, and in fact they each accept different standards of what is objective, so there's not really a single "ground truth" we can even compare to to determine which of these knowledge systems is "more correct" (similar problems arise even if we only care about "more useful").
To make this more concrete, we can see that e.g., competing quantum physics theories, or likewise competing religious beliefs, have no reasonable basis on which to judge between them, either in terms of "truth" or "utility." So the Trump-dogma knowledge system, although bad, morally repugnant, etc., can't so easily be dismissed as "false" in my view. "Distorted" or "malignant" or "evil" or "contradictory" are better monikers, in my opinion.
But what I'm even more interested in thinking about is: in what ways does the current American liberal "common sense" knowledge system already bear the scars of past fascist lies & contradictions? I can think of a few:
"Columbus was an explorer."
This is "factually accurate" in the same way some of Trump's propaganda is, but it's also a cruel distortion of "Columbus was a child murderer," and it's a misrepresentation that serves an evil purpose, yet which is widely taught in elementary schools today.
Another: "dropping atomic bombs on civilians in Japan was necessary to end WWII."
Perhaps in the future we'll have "family separation & the 2025 ICE crackdowns were necessary to end the immigration crisis," although I dearly hope not.
"Reparations for slavery aren't reasonable," is yet another...
I'll close this rambling with a question: what other fascist lies have you noticed that are normalized in America right now from past Trump-like leaders (or even from less overtly fascist institutions)?

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI
Barbara Oakley, Michael Johnston, Ken-Zen Chen, Eulho Jung, Terrence J. Sejnowski
https://arxiv.org/abs/2506.11015

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI
In the age of generative AI and ubiquitous digital tools, human cognition faces a structural paradox: as external aids become more capable, internal memory systems risk atrophy. Drawing on neuroscience and cognitive psychology, this paper examines how heavy reliance on AI systems and discovery-based pedagogies may impair the consolidation of declarative and procedural memory -- systems essential for expertise, critical thinking, and long-term retention. We review how tools like ChatGPT and calc…

Interaction as Intelligence: Deep Research With Human-AI Partnership
Lyumanshan Ye, Xiaojie Cai, Xinkai Wang, Junfei Wang, Xiangkun Hu, Jiadi Su, Yang Nan, Sihan Wang, Bohan Zhang, Xiaoze Fan, Jinbin Luo, Yuxiang Zheng, Tianze Xu, Dayuan Fu, Yunze Wu, Pengrui Lu, Zengzhi Wang, Yiwei Qin, Zhen Huang, Yan Ma, Zhulin Hu, Haoyang Zou, Tiantian Mi, Yixin Ye, Ethan Chern, Pengfei Liu

Interaction as Intelligence: Deep Research With Human-AI Partnership
This paper introduces "Interaction as Intelligence" research series, presenting a reconceptualization of human-AI relationships in deep research tasks. Traditional approaches treat interaction merely as an interface for accessing AI capabilities-a conduit between human intent and machine output. We propose that interaction itself constitutes a fundamental dimension of intelligence. As AI systems engage in extended thinking processes for research tasks, meaningful interaction transitions from an…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[7/7]:
- From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Au...
Anadria, Dobbe, Giachanou, Kuiper, Bartels, van Amsterdam, de Troya, Z\"urcher, Oberski
…

When you're so used to programming languages with high-level methods of checking for empty strings, that you grasp for something like `not x`, `x.empty()`, `len(x) == 0`… and only after a while of thinking, you realize that it's `x == ''`.
#Meson

2/3
🔹 Pros:
✅ Scalable – your income isn’t tied to hours worked
✅ Leverage – teams, automation, or systems do the heavy lifting
✅ More time freedom over the long term
🔹 Cons:
❌ Requires upfront effort to build systems
❌ May involve an initial investment
❌ Requires leadership & strategic thinking
💡 Best for: Those ready to shift from self-employed to system owner – turning their side hustle into a real asset.

Looking for Fairness in Recommender Systems
C\'ecile Log\'e
https://arxiv.org/abs/2507.12242 https://arxiv.org/pdf/2507.12242…

Looking for Fairness in Recommender Systems
Recommender systems can be found everywhere today, shaping our everyday experience whenever we're consuming content, ordering food, buying groceries online, or even just reading the news. Let's imagine we're in the process of building a recommender system to make content suggestions to users on social media. When thinking about fairness, it becomes clear there are several perspectives to consider: the users asking for tailored suggestions, the content creators hoping for some limelight, and soc…

Just thinking aloud: building stuff for a higher -march= than you're running is technically cross-compiling, right?

When you choose the armor for the female character based on its physical defense, but it actually turns out grossly indecent. I mean, how is it supposed to protect her if there's a huge uncovered area in the middle?
But thinking about it, my earlier best armor was swimming oil, i.e. walking around half-naked.
(in #Xenoblade Chronicles 3D)

System 0: Transforming Artificial Intelligence into a Cognitive Extension
Massimo Chiriatti, Marianna Bergamaschi Ganapini, Enrico Panai, Brenda K. Wiederhold, Giuseppe Riva
https://arxiv.org/abs/2506.14376

System 0: Transforming Artificial Intelligence into a Cognitive Extension
This paper introduces System 0, a conceptual framework for understanding how artificial intelligence functions as a cognitive extension preceding both intuitive (System 1) and deliberative (System 2) thinking processes. As AI systems increasingly shape the informational substrate upon which human cognition operates, they transform from passive tools into active cognitive partners. Building on the Extended Mind hypothesis and Heersmink's criteria for cognitive extension, we argue that AI systems…