AI can search, summarise, recombine, classify, draft, and generate alternatives. At best, it can be a useful learning assistant. It does not know which problems are worth solving, which assumptions matter, which sources should be trusted, or which conclusions should be defended under uncertainty. There is an old Socratic point here. Learning to prompt well is the old educational problem in new language – a good question is often worth more than a good answer. A weak student asks AI for a conclusion. Stronger students ask it to test assumptions, identify missing evidence, compare explanations, generate objections, or apply a principle to a new case.
Saturday, July 04, 2026
Would You Trust AI for Ethical Advice? - Knowledge at Wharton
The scholars said the study reveals shifts in how people think about AI. The studies were conducted in 2023 and 2025, and the scholars said they would be curious to see whether results would change if they redid the experiments now. Despite all the improvements to large language models like ChatGPT, Terwiesch said there’s still something unnerving about taking advice from a machine. “There is some human desire in us that makes us want to listen to music generated by other humans, read a book written by a person. You are looking for somebody who has suffered, who has loved, who has experienced life. How can a computer that has never been alive relate to the human struggle?” he said. “I think this is a natural hesitation, which makes the [results] more remarkable.”
Friday, July 03, 2026
UB Research Positions Artificial Intelligence at the Centre of Academic Integrity and Data Governance - University of Botswana
The growing influence of artificial intelligence (AI) in higher education is reshaping how universities safeguard academic integrity and manage research data with the University of Botswana (UB) contributing to emerging global debates on how these technologies should be responsibly integrated into learning systems. At the centre of this conversation is research by Dr Dennis Kealeboga Mabalane, Manager: Content Design and Development in the Centre for Learning and Teaching Innovation (CLTI), which examines how AI-enhanced Turnitin integrated into the Moodle Learning Management System can be used to strengthen academic integrity and improve research data governance within universities.
Panelists say state, colleges must meet workforce needs as AI use grows - Matthew McFarland, News Tribune
The use of artificial intelligence will continue to grow at higher education institutions around the state, a panel of AI and education experts said Thursday. As part of a statewide forum on AI and data centers at the Missouri University of Science & Technology in Rolla, two Missouri education administrators and the CEO of a Cape Girardeau nonprofit focused on AI training took part in a panel on workforce development. Their message, overwhelmingly, was that higher education must adapt to AI, not fight it. "Are you going to stop fire? Are you going to stop the wheel? Are you going to stop the industrial revolution? You're not going to stop AI," said Hal Higdon, chancellor of Ozarks Technical Community College. "Fighting is futile, but learning to use it responsibly is the way."
Personalized talent cultivation and academic prediction framework for higher education based on the HA-GNN-LSTM architecture - Qi Gong & Jing Shi, Nature
To address the dilemma of homogeneous talent training and the efficiency bottleneck of human resource management in universities, this study proposes an innovative personalized training framework integrating artificial intelligence, big data, and deep learning. Based on the 18-dimensional full-cycle behavior dataset of 5,000 students and OULAD dataset, a multimodal heterogeneous data fusion pipeline is constructed.
The simulation results demonstrate that, under established constraints and historical sample distributions, advisor allocation response time could be reduced by 60% and resource idle rate could be decreased by 63.4%. These findings indicate the framework’s potential for optimizing educational resource allocation. However, its managerial benefits require further validation through subsequent real-world deployment and long-term follow-up studies.
Thursday, July 02, 2026
Studying the Use of Generative Artificial Intelligence in Undergraduate Research at the U.S. Military AcademyPeer-Review - John Scudder1, et al; Journal of Military Learning
At the U.S. Military Academy (USMA) in West Point, New York, where academic integrity and pedagogical rigor are foundational, initial guidance on generative AI was introduced in 2023. While it emphasized the importance of integrity and instructor-specific policies, the use of generative AI remained decentralized and varied across disciplines (Reeves, 2023). Given this context, faculty members across five academic programs initiated a collaborative, multiyear research project to track the adoption, utility, and implications of generative AI in student-driven research activities. This study aims to document and analyze the technological engagement and ethical considerations among cadets from the class of 2024 through the class of 2029.
How Artificial Intelligence Is Changing Healthcare, Manufacturing, Recycling and Education - Tech Business News
Artificial intelligence (AI) is no longer a future-facing technology sitting inside research labs. It is now being used in doctor’s offices, classrooms, factories, recycling plants, semiconductor research facilities and government departments. The real shift is not just that AI can generate text, images or code. The bigger change is that AI systems are now being connected to daily decision-making, physical infrastructure and professional workflows. That makes the technology more useful, but also more difficult to manage. Across industries, AI is being used to detect disease, support teachers, predict machine failures, sort waste, discover new semiconductor materials, analyse risk, automate service desks and assist with policy planning. At the same time, it is raising hard questions about bias, privacy, security, accountability and whether people can understand how an AI system reached its answer.
Wednesday, July 01, 2026
The Next 5 Years: A Supersonic Tsunami - Peter H. Diamandis, Metatrends
Elon described the near future as a “supersonic tsunami”: a wave moving so fast and so large that by the time you hear it coming, it has already broken over you. The phrase stuck with me. So let me lay it out in detail, with the actual numbers, because I don’t think most people have any real sense of what the next 60 months hold. Buckle up. Start with the price of intelligence, because it is collapsing faster than anything in the history of technology. According to the Stanford AI Index, the cost of tokens dropped 280x collapse in 24 months. For frontier models, the price has been dropping about 10x every single year, from $20 to about $0.40 per million tokens. Not 10% cheaper. Ten times cheaper, annually.
Re-educating graduates for the competitive job market - Amber Wang, University World News
As another record number of university graduates enter China’s job market this month, authorities are increasingly encouraging both students and unemployed graduates to be “re-educated” through vocational and skills-based training. Across China, cities and provinces are offering “technician class” programmes aimed at improving employment outcomes among young people. With strong backing from local governments, initiatives typically combine vocational education with internships and job placement opportunities in strategic industries. Local authorities in Beijing, Guangdong, Zhejiang and Anhui, together with vocational institutions, have recently launched a range of full-time training programmes as well as shorter subsidised skills courses.
Tuesday, June 30, 2026
How universities are preparing students for an AI-powered future - Marta McAlister, Google Keyword Blog
Virginia Tech is providing access to AI tools — such as Gemini for Education and Notebook LM — which their IT Security Office approved for use with high-risk data to help ensure institutional information remains protected. UC Riverside introduced a secure campus AI assistant called The Grove, built on Gemini Enterprise. UC Irvine approved Google Workspace, Google Cloud Platform and Gemini for Education for secure use with select sensitive institutional data and then put those tools to work through ZotGPT, a free AI platform featuring Gemini among its models, available to the entire campus community.
Americans and AI 2026: Chatbots, Smart Devices and Views on Impact - Jeffrey Gottfried et al, Pew Research
About half of U.S. adults now report using AI chatbots, up substantially from the summer of 2024.1 This includes roughly one-in-four who use these tools on daily basis.
Some people are bringing AI into their homes. About a third of Americans say they have a smart speaker, and smaller shares have a doorbell or thermostat with AI features.
But Americans —including younger adults— are deeply skeptical of AI. More adults predict that AI will have a negative rather than positive impact on them and on society. And majorities think AI is advancing too quickly and will put their personal information at risk.
Monday, June 29, 2026
Collective action, collective success: A CEO’s role in transformations - Kurt Strovink, Mathew Lee, Meagan Hill, and Michael BucyMcKinsey - McKinsey
Successful transformations require everyone in the organization to move in the same direction. That can only happen when CEOs directly address collective-action problems. Beyond managing the challenges that organizations face every day, most leaders strive to be transformative—to find new ways to deliver substantial impact and leave the company stronger than they found it. Yet only 30 percent of transformations deliver the value their leaders expect. There are many possible explanations for this statistic, among them unexpected market conditions, tough new competitors, technological disruptions, and a volatile geopolitical landscape. Such external factors are easy to understand. Less appreciated are the internal dynamics in organizations that can thwart even the most ambitious and well-intentioned leaders.
Medical students’ perceptions of learning modalities: development and psychometric validation of the e-learning and face-to-face learning experience questionnaire - Zahra Karimian, et al; Nature
The analysis revealed six primary factors influencing student learning experiences, including Peer Interaction, Teacher-Student Interaction, Examination and Assessment methods, Emotional Comfort, Content Quality, and Assignments. The highest factor loading was observed for peer interaction and collaborative learning.... The findings suggest that effective educational practices must integrate diverse teaching methods and assessment strategies to accommodate various learning styles. Both F2F and online environments offer unique advantages that can be leveraged through a blended approach. The study underscores the importance of creating inclusive and supportive learning environments that prioritize student comfort and engagement, ultimately enhancing educational outcomes.
Sunday, June 28, 2026
Risk, Retention, and the Algorithmic Institution: Artificial Intelligence as a Policy Response to Higher Education in Crisis - McConvey, Kelly;Ghai, Maya;Lee, Rosa;Guha, Shion; Canadian Public Policy, 2026, v. 52
This article examines the adoption of artificial intelligence (AI) systems in Ontario’s post-secondary education sector as a response to financial pressures stemming from federal immigration reforms and provincial funding constraints. It highlights how AI technologies—such as predictive analytics and early warning systems—are used for student retention, resource allocation, and program planning, but also raise significant concerns about bias, surveillance, and opacity, particularly affecting marginalized student populations. The analysis underscores the inadequacy of existing Canadian privacy laws and the failure of federal AI legislation (notably the Artificial Intelligence and Data Act, AIDA) to provide comprehensive governance, calling instead for sector-specific regulation, human oversight, and equity-centered design inspired by international models like the European Union’s AI Act. The article concludes with policy recommendations for institutional, provincial, and federal levels to ensure AI systems in higher education align with democratic values of fairness, transparency, and accountability while mitigating risks of reinforcing inequities.
Authors, reviewers and editors should not be left to endure AI anxiety alone - Mai Zaki, Times Higher Ed
The arrival of generative artificial intelligence in academic research has produced something more disorienting than a simple ethical dilemma. It has created a situation in which every participant in scholarly publishing is being asked to make judgements that the system itself has not yet learned how to make. Authors are told to be transparent, reviewers to be vigilant, editors to protect integrity. But the result is not a new culture of clarity. It is a culture of suspicion. I experience this problem first as an author. Like many researchers, I do not approach AI as either a miracle or a threat. I approach it as a tool, whose boundaries remain strangely unclear. It can help with phrasing, structure, summaries, coding, translation, visualisation, brainstorming and literature mapping. Yet each of these uses occupies a different ethical position. Asking AI to polish a paragraph is not the same as asking it to generate an argument. Using it to produce a chart is not the same as using it to interpret data. Asking it to suggest possible lines of enquiry is not the same as outsourcing the intellectual work of the article.
Subscribe to:
Posts (Atom)