Tootfinder

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
Russell Beale
https://arxiv.org/abs/2506.22231

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
The rapid proliferation of generative artificial intelligence (AI) tools - especially large language models (LLMs) such as ChatGPT - has ushered in a transformative era in higher education. Universities in developed regions are increasingly integrating these technologies into research, teaching, and assessment. On one hand, LLMs can enhance productivity by streamlining literature reviews, facilitating idea generation, assisting with coding and data analysis, and even supporting grant proposal d…

OpenAI launches study mode in ChatGPT, designed to encourage students to engage with learning material, available to logged-in Free, Plus, Pro, and Team users (Reece Rogers/Wired)
https://www.wired.com/story/chatgpt-study-mode/

ChatGPT’s Study Mode Is Here. It Won’t Fix Education’s AI Problems
OpenAI’s new study mode for ChatGPT throws questions back at students, but the learning feature doesn’t address generative AI’s underlying disruption of education.

"So if ChatGPT destroys literacy and law, then ChatGPT is going to kill God. By this I don’t mean that the bearded guy in the sky is going to be found dead of a gunshot wound to the chest, but that monotheistic religion as we have traditionally understood it will not be able to function in a post-literacy regime."
(Original title: ChatGPT is going to kill God)

ChatGPT is going to kill God
I hate generative AI. I hate how it’s destroying writing pedagogy and giving students even more excuses not to read (because they can just read a “summary”). I hate how whiny and …

Do Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study
Jiayu Zheng, Lingxin Hao, Kelun Lu, Ashi Garg, Mike Reese, Melo-Jean Yap, I-Jeng Wang, Xingyun Wu, Wenrui Huang, Jenna Hoffman, Ariane Kelly, My Le, Ryan Zhang, Yanyu Lin, Muhammad Faayez, Anqi Liu
https://arxiv.org/abs/2508.20244

Do Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study
This study explores how college students interact with generative AI (ChatGPT-4) during educational quizzes, focusing on reliance and predictors of AI adoption. Conducted at the early stages of ChatGPT implementation, when students had limited familiarity with the tool, this field study analyzed 315 student-AI conversations during a brief, quiz-based scenario across various STEM courses. A novel four-stage reliance taxonomy was introduced to capture students' reliance patterns, distinguishing A…

How Exposed Are UK Jobs to Generative AI? Developing and Applying a Novel Task-Based Index
Golo Henseke, Rhys Davies, Alan Felstead, Duncan Gallie, Francis Green, Ying Zhou
https://arxiv.org/abs/2507.22748

How Exposed Are UK Jobs to Generative AI? Developing and Applying a Novel Task-Based Index
We introduce the Generative AI Susceptibility Index (GAISI), a task-based measure of UK job exposure to large language models (LLMs), such as ChatGPT. GAISI is derived from probabilistic task ratings by LLMs and linked to worker-reported task data from the Skills and Employment Surveys. It reflects the share of job activities where an LLM or LLM-powered system can reduce task completion time by at least 25 per cent beyond existing productivity tools. The index demonstrates high reliability, str…

AI, AGI, and learning efficiency
An addendum to this: I'm someone who would accurately be called "anti-AI" in the modern age, yet I'm also an "AI researcher" in some ways (have only dabbled in neutral nets).
I don't like:
- AI systems that are the product of labor abuses towards the data workers who curate their training corpora.
- AI systems that use inordinate amounts of water and energy during an intensifying climate catastrophe.
- AI systems that are fundamentally untrustworthy and which reinforce and amplify human biases, *especially* when those systems are exposed in a way that invites harms.
- AI systems which are designed to "save" my attention or brain bandwidth but such my doing so cripple my understating of the things I might use them for when I fact that understanding was the thing I was supposed to be using my time to gain, and where the later lack of such understanding will be costly to me.
- AI systems that are designed by and whose hype fattens the purse of people who materially support genocide and the construction of concentration campus (a.k.a. fascists).
In other words, I do not like and except in very extenuating circumstances I will not use ChatGPT, Claude, Copilot, Gemini, etc.
On the other hand, I do like:
- AI research as an endeavor to discover new technologies.
- Generative AI as a research topic using a spectrum of different methods.
- Speculating about non-human intelligences, including artificial ones, and including how to behave ethically towards them.
- Large language models as a specific technique, and autoencoders and other neural networks, assuming they're used responsibly in terms of both resource costs & presentation to end users.
I write this because I think some people (especially folks without CS backgrounds) may feel that opposing AI for all the harms it's causing runs the risk of opposing technological innovation more broadly, and/or may feel there's a risk that they will be "left behind" as everyone else embraces the hype and these technologies inevitability become ubiquitous and essential (I know I feel this way sometimes). Just know that is entirely possible and logically consistent to both oppose many forms of modern AI while also embracing and even being optimistic about AI research, and that while LLMs are currently all the rage, they're not the endpoint of what AI will look like in the future, and their downsides are not inherent in AI development.

Hallucinating with AI: AI Psychosis as Distributed Delusions
Lucy Osler
https://arxiv.org/abs/2508.19588 https://arxiv.org/pdf/2508.19588

Hallucinating with AI: AI Psychosis as Distributed Delusions
There is much discussion of the false outputs that generative AI systems such as ChatGPT, Claude, Gemini, DeepSeek, and Grok create. In popular terminology, these have been dubbed AI hallucinations. However, deeming these AI outputs hallucinations is controversial, with many claiming this is a metaphorical misnomer. Nevertheless, in this paper, I argue that when viewed through the lens of distributed cognition theory, we can better see the dynamic and troubling ways in which inaccurate beliefs,…

# Is ChatGPT Making Us Stupid?
In boardrooms and classrooms, coffee shops and cubicles, the same question keeps coming up: Is #ChatGPT making us smarter, or is it making us intellectually lazy—maybe even stupid?
#ai #ia

Is ChatGPT Making Us Stupid?
Just-released research studies are helping us understand what’s going on when we allow ChatGPT to think for us. Without guardrails, generative AI could in fact dull our thinking.

> “Instead of articulating our own thoughts, we articulate whatever AI helps us to articulate…we become more persuaded.” Without these signals, Naaman warns, we’ll only trust face-to-face communication — not even video calls.
Now I expect generative AI be used to justify return to office policies 🤢
—
You sound like ChatGPT
AI isn’t just impacting how we write — it’s changing how we speak and interact with others. And there’s only more to come.

You sound like ChatGPT
AI isn’t just impacting how we write — it’s changing how we speak and interact with others. And there’s only more to come.

Understanding the Challenges and Promises of Developing Generative AI Apps: An Empirical Study
Buthayna AlMulla, Maram Assi, Safwat Hassan
https://arxiv.org/abs/2506.16453

Understanding the Challenges and Promises of Developing Generative AI Apps: An Empirical Study
The release of ChatGPT in 2022 triggered a rapid surge in generative artificial intelligence mobile apps (i.e., Gen-AI apps). Despite widespread adoption, little is known about how end users perceive and evaluate these Gen-AI functionalities in practice. In this work, we conduct a user-centered analysis of 676,066 reviews from 173 Gen-AI apps on the Google Play Store. We introduce a four-phase methodology, SARA (Selection, Acquisition, Refinement, and Analysis), that enables the systematic extr…

Good article, regardless your opinion about GenAI , it will change society.
#ai

The Third Algorithm
ChatGPT and other generative AI isn't about to create superintelligence, but even if what we see now is it, the impact is on the scale of Google search and algorithmic social media, except maybe worse

Can We Tell if ChatGPT is a Parasite? Studying Human-AI Symbiosis with Game Theory
Jiejun Hu-Bolz, James Stovold
https://arxiv.org/abs/2508.11359 https://a…

Can We Tell if ChatGPT is a Parasite? Studying Human-AI Symbiosis with Game Theory
This work asks whether a human interacting with a generative AI system can merge into a single individual through iterative, information-driven interactions. We model the interactions between a human, a generative AI system, and the human's wider environment as a three-player stochastic game. We use information-theoretic measures (entropy, mutual information, and transfer entropy) to show that our modelled human and generative AI are able to form an aggregate individual in the sense of Krakauer…

NYT: They asked an A.I. chatbot questions. The answers sent them spiraling. https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-chatbots-conspiracies.html (archived at

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.

Exploiting Jailbreaking Vulnerabilities in Generative AI to Bypass Ethical Safeguards for Facilitating Phishing Attacks
Rina Mishra, Gaurav Varshney
https://arxiv.org/abs/2507.12185

Exploiting Jailbreaking Vulnerabilities in Generative AI to Bypass Ethical Safeguards for Facilitating Phishing Attacks
The advent of advanced Generative AI (GenAI) models such as DeepSeek and ChatGPT has significantly reshaped the cybersecurity landscape, introducing both promising opportunities and critical risks. This study investigates how GenAI powered chatbot services can be exploited via jailbreaking techniques to bypass ethical safeguards, enabling the generation of phishing content, recommendation of hacking tools, and orchestration of phishing campaigns. In ethically controlled experiments, we used Cha…

A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment
Iman Reihanian, Yunfei Hou, Yu Chen, Yifei Zheng
https://arxiv.org/abs/2507.11543

A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment
This paper surveys the use of Generative AI tools, such as ChatGPT and Claude, in computer science education, focusing on key aspects of accuracy, authenticity, and assessment. Through a literature review, we highlight both the challenges and opportunities these AI tools present. While Generative AI improves efficiency and supports creative student work, it raises concerns such as AI hallucinations, error propagation, bias, and blurred lines between AI-assisted and student-authored content. Hum…

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.

There's no putting the genie back in the bottle, but education is [yet another part of our society that is] completely unprepared to deal with generative AI.
Teachers Are Not OK
https://www.404media.co/teachers-are-not-ok-ai-chatgpt/

Exploring the Impact of Generative Artificial Intelligence on Software Development in the IT Sector: Preliminary Findings on Productivity, Efficiency and Job Security
Anton Ludwig Bonin, Pawel Robert Smolinski, Jacek Winiarski
https://arxiv.org/abs/2508.16811

Exploring the Impact of Generative Artificial Intelligence on Software Development in the IT Sector: Preliminary Findings on Productivity, Efficiency and Job Security
This study investigates the impact of Generative AI on software development within the IT sector through a mixed-method approach, utilizing a survey developed based on expert interviews. The preliminary results of an ongoing survey offer early insights into how Generative AI reshapes personal productivity, organizational efficiency, adoption, business strategy and job insecurity. The findings reveal that 97% of IT workers use Generative AI tools, mainly ChatGPT. Participants report significant …

'...a student might hear "don't use generative AI" from a prof but then log on to the university's Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing'
https://www.404media.co/teachers-are-not-ok-ai-chatgpt/…

Teachers Are Not OK
AI, ChatGPT, and LLMs "have absolutely blown up what I try to accomplish with my teaching."

Culling Misinformation from Gen AI: Toward Ethical Curation and Refinement
Prerana Khatiwada, Grace Donaher, Jasymyn Navarro, Lokesh Bhatta
https://arxiv.org/abs/2507.14242

Culling Misinformation from Gen AI: Toward Ethical Curation and Refinement
While Artificial Intelligence (AI) is not a new field, recent developments, especially with the release of generative tools like ChatGPT, have brought it to the forefront of the minds of industry workers and academic folk alike. There is currently much talk about AI and its ability to reshape many everyday processes as we know them through automation. It also allows users to expand their ideas by suggesting things they may not have thought of on their own and provides easier access to informati…

Programming Geotechnical Reliability Algorithms using Generative AI
Atma Sharma, Jie Zhang, Meng Lu, Shuangyi Wu, Baoxiang Li
https://arxiv.org/abs/2506.19536

Programming Geotechnical Reliability Algorithms using Generative AI
Programming reliability algorithms is crucial for risk assessment in geotechnical engineering. This study explores the possibility of automating and accelerating this task using Generative AI based on Large Language Models (LLMs). Specifically, the most popular LLM, i.e., ChatGPT, is used to test the ability to generate MATLAB codes for four classical reliability algorithms. The four specific examples considered in this study are: (1) First Order Reliability Method (FORM); (2) Subset simulation…

An analysis of over 1M words of conversation between a ChatGPT user and the generative AI chatbot shows how ordinarily rational people can spiral into delusion (New York Times)
https://www.

Chatbots Can Go Into a Delusional Spiral. Here’s How It Happens.
Over 21 days of talking with ChatGPT, an otherwise perfectly sane man became convinced that he was a real-life superhero. We analyzed the conversation.

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Zosia Krusberg
https://arxiv.org/abs/2506.00229 http…

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Generative AI tools like ChatGPT are rapidly reshaping how students and instructors engage with course material-and how they think about academic integrity. This paper presents a classroom activity designed to help physics students critically examine the ethical and educational implications of using AI in coursework. Through a structured sequence of case analysis, discussion, and optional policy drafting, students develop the metacognitive, ethical, and collaborative skills needed to navigate e…

Between Regulation and Accessibility: How Chinese University Students Navigate Global and Domestic Generative AI
Qin Xie, Ming Li, Fei Cheng
https://arxiv.org/abs/2506.14377

Between Regulation and Accessibility: How Chinese University Students Navigate Global and Domestic Generative AI
Despite the rapid proliferation of generative AI in higher education, students in China face significant barriers in accessing global tools like ChatGPT due to regulations and constraints. Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, this study employs qualitative interviews to investigate how Chinese university students interact with both global and domestic generative AIs in the learning process. Findings reveal that engagement is shaped by accessibilit…

Do Students Write Better Post-AI Support? Effects of Generative AI Literacy and Chatbot Interaction Strategies on Multimodal Academic Writing
Yueqiao Jin, Kaixun Yang, Roberto Martinez-Maldonado, Dragan Ga\v{s}evi\'c, Lixiang Yan
https://arxiv.org/abs/2507.04398

Do Students Write Better Post-AI Support? Effects of Generative AI Literacy and Chatbot Interaction Strategies on Multimodal Academic Writing
Academic writing increasingly involves multimodal tasks requiring students to integrate visual information and textual arguments. While generative AI (GenAI) tools, like ChatGPT, offer new pathways for supporting academic writing, little is known about how students' GenAI literacy influences their independent multimodal writing skills or how chatbot interaction strategies (passive reactive vs. proactive scaffolding) impact learning. This study examined 79 higher education students' multimodal a…

Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
Yinan Sun, Ali Unlu, Aditya Johri
https://arxiv.org/abs/2508.14692 https://

Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
This study investigates how U.S. news media framed the use of ChatGPT in higher education from November 2022 to October 2024. Employing Framing Theory and combining temporal and sentiment analysis of 198 news articles, we trace the evolving narratives surrounding generative AI. We found that the media discourse largely centered on institutional responses; policy changes and teaching practices showed the most consistent presence and positive sentiment over time. Conversely, coverage of topics su…

Encouraging Students' Responsible Use of GenAI in Software Engineering Education: A Causal Model and Two Institutional Applications
Vahid Garousi, Zafar Jafarov, Aytan Movsumova, Atif Namazov, Huseyn Mirzayev
https://arxiv.org/abs/2506.00682

Encouraging Students' Responsible Use of GenAI in Software Engineering Education: A Causal Model and Two Institutional Applications
Context: As generative AI (GenAI) tools such as ChatGPT and GitHub Copilot become pervasive in education, concerns are rising about students using them to complete rather than learn from coursework-risking overreliance, reduced critical thinking, and long-term skill deficits. Objective: This paper proposes and empirically applies a causal model to help educators scaffold responsible GenAI use in Software Engineering (SE) education. The model identifies how professor actions, student factors, …

Predicting ChatGPT Use in Assignments: Implications for AI-Aware Assessment Design
Surajit Das, Aleksei Eliseev
https://arxiv.org/abs/2508.12013 https://ar…

Predicting ChatGPT Use in Assignments: Implications for AI-Aware Assessment Design
The rise of generative AI tools like ChatGPT has significantly reshaped education, sparking debates about their impact on learning outcomes and academic integrity. While prior research highlights opportunities and risks, there remains a lack of quantitative analysis of student behavior when completing assignments. Understanding how these tools influence real-world academic practices, particularly assignment preparation, is a pressing and timely research priority. This study addresses this gap…

Understanding Why ChatGPT Outperforms Humans in Visualization Design Advice
Yongsu Ahn, Nam Wook Kim
https://arxiv.org/abs/2508.01547 https://arxiv.org/pdf…

Understanding Why ChatGPT Outperforms Humans in Visualization Design Advice
This paper investigates why recent generative AI models outperform humans in data visualization knowledge tasks. Through systematic comparative analysis of responses to visualization questions, we find that differences exist between two ChatGPT models and human outputs over rhetorical structure, knowledge breadth, and perceptual quality. Our findings reveal that ChatGPT-4, as a more advanced model, displays a hybrid of characteristics from both humans and ChatGPT-3.5. The two models were genera…

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…

Generative AI in Science: Applications, Challenges, and Emerging Questions
Ryan Harries, Cornelia Lawson, Philip Shapira
https://arxiv.org/abs/2507.08310 h…

Generative AI in Science: Applications, Challenges, and Emerging Questions
This paper examines the impact of Generative Artificial Intelligence (GenAI) on scientific practices, conducting a qualitative review of selected literature to explore its applications, benefits, and challenges. The review draws on the OpenAlex publication database, using a Boolean search approach to identify scientific literature related to GenAI (including large language models and ChatGPT). Thirty-nine highly cited papers and commentaries are reviewed and qualitatively coded. Results are cat…

Generative AI in Higher Education: Evidence from an Elite College
Zara Contractor, Germ\'an Reyes
https://arxiv.org/abs/2508.00717 https://arxiv.org/pd…

Generative AI in Higher Education: Evidence from an Elite College
Generative AI is transforming higher education, yet systematic evidence on student adoption remains limited. Using novel survey data from a selective U.S. college, we document over 80 percent of students using AI academically within two years of ChatGPT's release. Adoption varies across disciplines, demographics, and achievement levels, highlighting AI's potential to reshape educational inequalities. Students predominantly use AI for augmenting learning (e.g., explanations, feedback), but also …

Surgeons Awareness, Expectations, and Involvement with Artificial Intelligence: a Survey Pre and Post the GPT Era
Lorenzo Arboit, Dennis N. Schneider, Toby Collins, Daniel A. Hashimoto, Silvana Perretta, Bernard Dallemagne, Jacques Marescaux, EAES Working Group, Nicolas Padoy, Pietro Mascagni
https://arxiv.org/abs/2506.08258

Surgeons Awareness, Expectations, and Involvement with Artificial Intelligence: a Survey Pre and Post the GPT Era
Artificial Intelligence (AI) is transforming medicine, with generative AI models like ChatGPT reshaping perceptions of its potential. This study examines surgeons' awareness, expectations, and involvement with AI in surgery through comparative surveys conducted in 2021 and 2024. Two cross-sectional surveys were distributed globally in 2021 and 2024, the first before an IRCAD webinar and the second during the annual EAES meeting. The surveys assessed demographics, AI awareness, expectations, inv…

Short-Term Gains, Long-Term Gaps: The Impact of GenAI and Search Technologies on Retention
Mahir Akgun, Sacip Toker
https://arxiv.org/abs/2507.07357 https:…

Short-Term Gains, Long-Term Gaps: The Impact of GenAI and Search Technologies on Retention
The rise of Generative AI (GenAI) tools, such as ChatGPT, has transformed how students access and engage with information, raising questions about their impact on learning outcomes and retention. This study investigates how GenAI (ChatGPT), search engines (Google), and e-textbooks influence student performance across tasks of varying cognitive complexity, based on Bloom's Taxonomy. Using a sample of 123 students, we examined performance in three tasks: [1] knowing and understanding, [2] applyin…

Integrating Universal Generative AI Platforms in Educational Labs to Foster Critical Thinking and Digital Literacy
Vasiliy Znamenskiy, Rafael Niyazov, Joel Hernandez
https://arxiv.org/abs/2507.00007

Integrating Universal Generative AI Platforms in Educational Labs to Foster Critical Thinking and Digital Literacy
This paper presents a new educational framework for integrating generative artificial intelligence (GenAI) platforms such as ChatGPT, Claude, and Gemini into laboratory activities aimed at developing critical thinking and digital literacy among undergraduate students. Recognizing the limitations and risks of uncritical reliance on large language models (LLMs), the proposed pedagogical model reframes GenAI as a research subject and cognitive tool. Students formulate discipline-specific prompts a…

Computer Science Education in the Age of Generative AI
Russell Beale
https://arxiv.org/abs/2507.02183 https://arxiv.org/pdf/2507.0218…

Computer Science Education in the Age of Generative AI
Generative AI tools - most notably large language models (LLMs) like ChatGPT and Codex - are rapidly revolutionizing computer science education. These tools can generate, debug, and explain code, thereby transforming the landscape of programming instruction. This paper examines the profound opportunities that AI offers for enhancing computer science education in general, from coding assistance to fostering innovative pedagogical practices and streamlining assessments. At the same time, it highl…

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review
Seyma Yaman Kayadibi
https://arxiv.org/abs/2507.01062

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review
The exponential development of generative artificial intelligence (GenAI) technologies like ChatGPT has raised increasing curiosity about their use in higher education, specifically with respect to how students view them, make use of them, and the implications for learning outcomes. This paper employs a hybrid methodological approach involving a systematic literature review and simulation-based modeling to explore student perceptions of GenAI use in the context of higher education. A total of n…