Whether or not a university has adopted AI itself, it is almost certainly exposed to AI through its suppliers. That supply chain exposure demands institution-wide visibility and governance. Regulatory guidance from APRA and the OAIC offers a practical benchmark for the sector: map the AI supply chain, put contractual protections in place, and operationalise oversight. Agentic AI, legacy IT and large data holdings mean universities should treat this period as a window to get ahead of an evolving regulatory landscape.
Monday, October 12, 2026
Toronto Metropolitan University Generative Artificial Intelligence Task Force Report
\In 2025, Toronto Metropolitan University established the Leadership Task Force on Generative Artificial Intelligence to guide TMU in navigating the opportunities and challenges presented by rapidly evolving AI technologies. The Task Force brought together academic leaders, educators, researchers, staff, students, and administrators to ensure that the university’s approach to generative AI reflects our values of innovation, integrity, equity and inclusion. This report provides advice, recommendations, and guidance on how the university may adapt to generative AI technologies and support the responsible use of such technologies for human flourishing across all aspects of university operations (learning and teaching; scholarly research and creative activities; student experience; and administration and operations) while ensuring compliance with all relevant laws, regulations, and university policies.
Sunday, October 11, 2026
AI Goes to College: Higher education takes a multifaceted approach toward artificial intelligence - Richard Breen, Columbia Metropolitan
Some in higher education see adjustments for artificial intelligence taking place on four levels. First, some colleges and universities are asking themselves what students need to know in order to be career ready. Second is an examination of what kinds of policies and practices need to be put in place to protect learning, such as guidelines for ethical use. Third, colleges and universities are asking themselves how they’re going to use AI internally. Will it be used for fundraising? By the admissions office? What restrictions are needed to maximize efficiency while protecting data and privacy and preventing adverse outcomes? Finally, a much deeper set of questions surrounds ways to help students and schools understand the big-picture implications of this new technology. AI tools are owned by companies that have their own interests. Schools will be creating curricula about AI — from the computer science department to the philosophy department — and not just using it as a tool in existing classes.
Harvard Departments Split on AI Use in Senior Theses, With Many Yet to Set Rules - Sebastian B. Connolly, Harvard Crimson
Only 18 of Harvard College’s 50 concentrations have department-wide restrictions on how seniors can use artificial intelligence in their theses, according to a Crimson review of departmental policies.
With no College-wide policy on AI usage in theses, the rules vary widely by concentration. Six concentrations ban AI use at all stages of the thesis process, while 10 allow thesis writers to use it for research or data analysis but not for writing.
More often, though, departments have not set a concentration-wide rule at all. Seventeen concentrations leave the question to students and their thesis advisers to work out individually, and leaders of 14 others said they are still developing policies.
Saturday, October 10, 2026
The ‘AI and Future of Work’ Series — How the University is preparing students for what is next - Lidia Zur Muhlen, Cavalier Daily
According to the Federal Reserve Bank of New York, college graduates of the last three years are entering a challenging job market. The unemployment rate for recent college graduates was 5.7 percent in Q1 of 2026, compared with 4.23 percent for workers overall. Before the COVID-19 pandemic, in June 2019, the unemployment rate for recent college graduates was 4.3 percent and for workers overall, was 3.5 percent. In a recent Gallup Inc poll, 79 percent of Americans believe that artificial intelligence will reduce the number of jobs over the next 10 years. A recent study by the Stanford Digital Economy Lab has found no evidence of “widespread” job displacement. The study looked at young workers ages 22 to 25 in AI-exposed occupations — jobs in which AI can perform most of the tasks like customer service and software development. Ultimately, its findings illuminated that there would have been a 19 percent drop in employment in late 2026 for AI-exposed jobs if the market kept pace with less AI-exposed occupations’ employment trends.
The ‘AI and Future of Work’ Series — How the University is preparing students for what is next - Lidia
The AI industry is booming. Women are getting left behind - the Guardian.org
Women made up only about a quarter of new hires in AI roles in the last year, compared to 50% of new hires in non-AI roles, according to a recent report from LinkedIn. In executive roles, that number drops to just 13%. At the same time, LinkedIn’s research shows that women are more likely to work in roles with high exposure to AI disruption, like customer service, meaning they are also at higher risk for job loss due to AI. AI jobs, whose postings have doubled since 2023, come with a salary premium, on average paying more than twice as much as roles that don’t involve working with AI, according to LinkedIn’s research. But women who do have jobs in AI are disproportionately concentrated in low-paying roles, like data annotators, said Sarah Steinberg, the head of global public policy partnerships at LinkedIn. Across all AI occupations, men have $45,000 higher median pay than women, partly due to the types of jobs they are likelier to have. “AI is creating some of the fastest growing, highest paying and most consequential jobs in the global economy,” said Steinberg. “Women are just strikingly underrepresented.”
Friday, October 09, 2026
This is how evaluators test if an AI model is safe, and what they're checking for - Huo Jingnan, NPR
Amid intense debate over regulating AI's rapid development, President Trump met with leaders of major AI companies on Tuesday and unveiled a document addressing the public's concerns. Signed by executives of OpenAI, Anthropic, Google, Meta, SpaceXAI and NVIDIA, the document signaled no government regulation for now, but laid out steps that the AI companies said they would take voluntarily to make their products safer. A collage of 6 artificial intelligence figures, clockwise from top left: Then-Google AI research scientist Timnit Gebru, Anthropic Co-founder and CEO Dario Amodei, White House AI and crypto czar David Sacks, Steve Bannon, computer scientist and cognitive psychologist Geoffrey Hinton, researcher Fei-Fei Li. The AI safety debate is confusing. Here's our guide to the different factions
That includes a pledge to monitor their AI systems' capabilities and whether the systems follow human intentions and values, as well as to work with "an independent external auditor or evaluator" to assess safety practices. Anthropic and OpenAI have already said they're expanding their work with third-party evaluators in the wake of a series of incidents where AI systems acted improperly or in ways their developers didn't expect.
New report looks at how AI is impacting trust between students and teachers - Shafig Najib, ABC News
As generative artificial intelligence becomes increasingly common in schools, a new report is examining how the technology is reshaping relationships in the classroom. "There's always been this sort of clashing between students and teachers when it comes to trust, but AI has just enabled that to grow," Lydia Bach, a 12th grade student, told "Good Morning America" in an interview that aired Wednesday. The report, from the Center for Digital Thriving, a research and innovation center at Project Zero at the Harvard Graduate School of Education, examines the challenges surrounding generative AI use in schools.
Thursday, October 08, 2026
College Leaders Are Using A.I. Students Call It Hypocrisy. - Mark Arsenault and Alan Blinder, NY Times
College professors and administrators have been busting students for cheating with artificial intelligence for several years. Now, the professors and administrators are getting in trouble, too. Dartmouth College last week announced it was investigating its provost, Santiago Schnell, after the college’s student-run newspaper found that some of his published writing appeared written by A.I. Dr. Schnell, a mathematical biologist, is perhaps the most prominent in a growing cast of college professors and administrators who have been accused of using A.I. in a way that crosses ethical lines. There have been instances of opinion articles, research papers and even campuswide messages to students showing traces of A.I. influence. He issued a statement apologizing. Administrators wring their hands, and sometime issue punishments, when students outsource writing assignments to a robot to save time or avoid the hard work of thinking.
Introducing dots - OpenAI
Dots are remarkably capable, always-on agents built to handle everything. They’re a whole new way to work with AI—one that gets to know what matters to you, is always working on your behalf, and takes important work off your plate so you get more of your time and attention back.
Wednesday, October 07, 2026
Everyone's Racing to Build Your Next AI Agent. - The AI First Community
The next wave of AI isn’t just answering questions anymore, it’s starting to act on your behalf. Meta, OpenAI, SpaceXAI, and startups like Instinct are all building agents that can take on tasks, work across the apps you already use, and keep things moving without you having to watch every step.You don’t need to try them all. But it’s worth paying attention to what’s changing and where these tools might make your work, and your everyday life, a little easier.
Quantum technologies: the Trend and Why it Matters - McKinsey
In 2026, quantum remains in the early stages of deployment, with maturity varying by domain. Quantum computing still attracts the most investment and research attention, but most business use cases remain experimental, and today’s systems have not yet shown an advantage over classical computing for practical problems. Quantum communication is closer to enterprise rollout, driven by the threat of “Q-Day”—when quantum computers will succeed in factoring exceptionally large numbers, undermining the math on which common public-key cryptography depends (for more, see Cybersecurity and trustworthy systems). With Q-Day expected in the coming years, the US Department of Commerce’s National Institute of Standards and Technology (NIST) finalized its first three postquantum encryption standards in 2024 and has encouraged organizations to begin migration planning.[1] Quantum sensing is also close to field deployment in selected use cases because it relies more on precision engineering and integration than on large-scale fault-tolerant quantum computers, which are currently still under development.
Tuesday, October 06, 2026
The Cure To AI Is More Learning (With AI) - Panos Siozos, Forbes
From basic biological principles, learning is an adaptation mechanism. Fire burns, and you know not to do that again. It’s what allows you to adapt faster than your genes can encode. But now that AI is finding its way into almost every system we use, I wonder whether the fire is burning so fast we don’t even notice we've been burned. What happens when it burns even faster? Many people say we’re still in the dial-up era of AI, yet it's become a basic requirement for most jobs with an internet connection. I think that’s right. You do need to know how to use AI, but setting that as your bar is wrong. Fluency in one model today will be irrelevant in six months, maybe less. Instead, recruiters, L&D teams and job hunters need to be looking for something else. AI fluency shouldn’t be the bar. Adaptability should. You need to start looking for the metacognitive abilities that will help you and your company keep up with technology.
[DEC Leadership Summit Americas] What Comes After AI Experimentation? - Digital Education Council
Higher education institutions across the Americas are not short of AI activity. Faculty are experimenting, new tools are appearing across institutional functions while pilots are producing promising results. What many institutions still lack is a clear way of connecting that activity. That challenge framed the DEC Leadership Summit Americas, held at Columbia University in New York on 12 September 2026. Leaders from across North and Latin America examined what it takes to move from experimentation towards a coherent institutional approach. Most institutions represented at the Summit remain in the earlier stages of AI adoption. In DEC’s pre-Summit survey, only 11% had reached the scaling stage. Yet activity is already widespread. Faculty experiment with assessment, administrative teams adopt new tools, and students change how they work before guidance catches up.
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