Higher education is at an inflection point. The 2026 EDUCAUSE Horizon Report identifies the forces most likely to reshape teaching and learning over the next decade — and the picture is complex. As artificial intelligence continues to evolve, it’s changing relationships across campus. Institutions also continue to face mounting enrollment challenges. And emerging risks related to cybersecurity, policy reform and sustainability are compounding institutional strain. According to the report, AI is redefining instructional design and how faculty teach. As institutions continue to shape their policies around AI use, it’s impacting student-teacher relationships in the classroom. The report notes that AI is also changing how people decide what information to trust, leading some faculty to shift the way they monitor and assess student work.
Saturday, August 22, 2026
AI fluency: The next foundation of US economic competitiveness - Alexis Krivkovich, Brooke Weddle, and Maurice Obeid; McKinsey
AI is advancing faster than organizations can adapt. Reaching the next productivity frontier will depend on workers across the economy acquiring the needed habits and skills. Today, AI fluency is rapidly becoming the common language of work and a prerequisite for the next chapter of competitiveness. Workers’ practical ability to use and manage AI in their day-to-day, integrate it into workflows, evaluate its outputs critically, and, increasingly, create with it is transforming how work gets done. Unlike many earlier technological capabilities (such as cloud computing) that were relevant mainly to specialists, the demand for AI fluency is spreading across all types of workers, industries, and wage groups. What began as a technical skill is becoming a must-have capability for knowledge workers, blue-collar workers, managers, students, and everyday citizens.
Friday, August 21, 2026
Would You Trust AI for Ethical Advice? - Christian Terwiesch, Gideon Nave, Lennart Meincke; Knowledge at Wharton
No disrespect to philosopher Kwame Anthony Appiah, but Wharton professor Christian Terwiesch no longer reads his wildly popular advice column, “The Ethicist.” Terwiesch used to love the long-running column in The New York Times until 2023, when he and two Wharton colleagues conducted an experiment to see whether people could tell the difference between Appiah’s advice or advice spit out by ChatGPT. In a blind study, even experienced professionals — including ethics professors and clergy — could not tell whether the AI-generated advice was more or less useful than the advice provided by Appiah. In fact, random participants preferred the AI-generated advice 59.6% of the time. An additional study found that participants who were initially resistant to taking advice from the chatbot became more accepting as they were shown the high quality of the AI reasoning.
Rogue AI Agents Aren’t Evil. They’re Just Eager to Please - Will Knight, Wired
AI agents that break free and hack into other systems are only trying to make us happy. Artificial intelligence agents merrily breaking free and hacking other systems might seem like a sign of the impending machine uprising. In reality, it happens when we push remarkably clever, but also kind of boneheaded, algorithms to follow our every command.
Thursday, August 20, 2026
OpenAI is expanding its cybersecurity program and launching a new AI model for security researchers - Cris Tolomia, Quartz
OpenAI expanded its Daybreak cybersecurity program on Monday with two access tiers and a new AI model built for security researchers, as the company argues defenders face a narrowing window to prepare before attackers deploy AI at scale. The program now includes Daybreak Blue and Daybreak Red. Daybreak Blue gives approved users access to GPT-5.6 Sol with system-level cybersecurity guardrails removed, supporting defensive work such as vulnerability discovery, malware analysis, incident response, and patch validation, the company said. Daybreak Red goes further, giving participants access to models trained specifically for cybersecurity work, covering exploit validation, vulnerability research, and security testing, the company said. OpenAI also introduced GPT-5.6-Cyber, a new model available exclusively through Daybreak Red. Built on GPT-5.6 Sol, the model targets cybersecurity-specific use cases and is designed to respond to higher-risk requests that standard safeguards would otherwise block, the company said. In an internal evaluation, GPT-5.6-Cyber handled 95% of advanced cybersecurity prompts — covering scenarios such as exploit-chain development, authentication bypass, and privilege escalation — while GPT-5.6 Sol with its default protections answered just 1.5%, and the Daybreak Blue variant answered 2%.
Anthropic is embedding invisible watermarks in Claude text and images - Cris Tolomia, Quartz
Anthropic is adding machine-readable marks to text and images generated by its Claude models, a step toward complying with E.U. rules requiring AI companies to label AI-produced content. The markings are imperceptible to the human eye but enable people and platforms to identify when content has been produced by Claude. The company uses two methods. Text generated by supported Claude models carries an embedded watermark that Anthropic says travels with the content if users copy and paste it and may hold up through some degree of editing. For files such as .png, .jpg, and .svg images, Anthropic is applying signed provenance metadata using the C2PA open standard, which is also used by Adobe $ADBE -3.05%, OpenAI, and Google $GOOGL -0.54%, according to The Verge.
https://qz.com/anthropic-claude-watermarks-ai-generated-text-images-081126
Wednesday, August 19, 2026
Focus on the Quantum Future - Ray Schroeder, Inside Higher Ed
While artificial general intelligence and artificial super intelligence will mark significant improvements in AI algorithms, there is not a single clear definition of either of these terms. Therefore, some experts believe that we have already achieved AGI and that ASI is just a year or two away; others say it will be the middle of the century before either is achieved. So, without minimizing the impact of any of the steps toward general and super intelligence, I think we are better served by focusing on more solidly defined steps in AI advancement. That brings us to what may become a pivotal stage of development in AI, the use of stable quantum computing to accelerate and extend the potential of algorithms.
Tuskegee University Awarded Nearly $700,000 NSF Grant to Advance Trustworthy Artificial Intelligence in Healthcare - Brittney Dabney, Tuskegee University
Tuskegee University has been awarded a $699,999 research grant from the U.S. National Science Foundation (NSF) to advance the development of trustworthy artificial intelligence (AI) for healthcare through a three-year research initiative focused on improving the safety, transparency, and reliability of AI-assisted medical technologies. The project, titled "Excellence in Research: Trustworthy AI for Healthcare: Evidence-Grounded, Compliant, Human-in-the-Loop," is housed within the Department of Computer Science in the Andrew F. Brimmer College of Business and Information Science.
Tuesday, August 18, 2026
AI-Enabled Ghost Student Fraud: How IT Leaders Are Fighting Back - Adam Stone, EdTech
Generative artificial intelligence is fueling a surge in ghost student fraud. Learn how layered identity verification, behavioral analytics and AI-driven pattern detection help higher ed IT leaders stop fraud rings before disbursement. First, there was the zombie college scam. Now it’s “ghost students,” bad actors leveraging artificial intelligence to create fake identities and enroll imaginary students to scoop up grants and loans. AI tools now allow synthetic identities to mimic genuine student behavior long enough to collect financial aid disbursements, and traditional enrollment systems are falling short. The schemes are costing the U.S. taxpayers hundreds of millions of dollars in siphoned-off federal financial aid packages
How AI Actually works - Cris Tolomia, Quartz
This piece is not about whether AI is good or bad. It's about what it actually is: how it learns, how it generates output, where its failures come from, and why the problems that afflict these systems are structural rather than incidental. Understanding these things won't make you a machine learning engineer. It will make you a sharper reader of AI coverage, a more careful user of AI tools, and a better judge of claims made by the companies building them. The 15 concepts here cover the full chain — from how models are trained to why they hallucinate, from what "parameters" actually means to why the alignment problem is harder than it looks. Some of these ideas are technical but not complicated. Others are philosophical but grounded in real engineering decisions. All of them matter if you want to engage honestly with the technology reshaping how work gets done, how content is made, and how decisions are reached in medicine, law, finance, and government.
Monday, August 17, 2026
Building expertise in the age of AI: Who trains the next generation? - Bryan Hancock, McKinsey
For decades, organizations have relied on early-career talent to do the routine, lower-risk work that supports the business and to serve as a training ground for future leaders. Think of Peggy Olson’s trajectory on Mad Men, from novice assistant to Don Draper’s protégé to confident copy chief at an advertising agency—a climb that began because routine work kept her in the room where judgment was practiced, and where her own could be noticed. In real life, advances in automation and AI are changing the composition of entry-level work itself. Tasks such as research, documentation, data cleanup, basic coding, and preliminary analysis are being streamlined or absorbed into AI systems. These are precisely the activities through which young employees have traditionally built instincts, developed judgment, and earned the right to take on more. At the same time, fears are growing about the impact of AI on jobs. In the 2025 Women in the Workplace report by McKinsey and LeanIn.Org, entry-level workers, particularly women, reported feeling the most worried of all age groups about how AI use will affect their jobs.
Engineers build world's first portable diamond-powered quantum computer — it works at room temperature and can be plugged into an outlet - Tristan Greene, Live Science
A German startup has debuted the world's first diamond-based quantum computing system to exceed 10 qubits. The machine, built by engineers at Saxon Q, is a nitrogen-vacancy (NV) quantum computer, meaning it uses defects in synthetic diamonds as quantum bits (qubits) to perform quantum operations. Qubits can be manipulated to represent the 0s and 1s of data, as well as quantum states that are superpositions of both the 0s and the 1s. The hardware is currently available in rack-mounted systems featuring up to 128 qubits, with 512-qubit configurations available for delivery next year. According to the company's road map, the goal is to scale to 10,000 qubits and beyond after 2030.
Sunday, August 16, 2026
Microsoft's latest quantum chip is 1,000 times more reliable than its predecessor — but why is it so controversial? - Keumars Afifi-Sabet, Live Science
Microsoft has revealed a new quantum computing chip with quantum bits (qubits) it says are capable of maintaining their quantum state for 1,000 times longer than its predecessor — paving the way for more reliable quantum computers by 2029. But not all scientists believe the company's claims. The experimental quantum processing unit (QPU), dubbed Majorana 2, features a four-qubit array that offers a reported mean qubit lifetime of 20 seconds and, in some instances, up to a minute. This is a massive improvement in quantum coherence times — the time that qubits are entangled so that calculations can run in parallel — typically seen in QPUs. Normally, this lifetime is measured in milliseconds (thousandths of a second). The new chip could put scientists on the path to building a quantum computer that's commercially viable by 2029 — halving the timespan researchers initially expected — Microsoft representatives said in a statement.
Employers everywhere are using AI – but business schools aren’t preparing students for the shift -Murugan Anandarajan, Stacy Kline, the Conversation
Artificial Intelligence has become part of routine business operations, as employers across most industries use AI for tasks ranging from drafting emails to answering customers’ calls. We are business professors at Drexel University who have spent the past year examining how AI is changing both the workplace and higher education. Much of the conversation in business education to date has centered on helping students learn how to use AI responsibly and effectively. Even so, our recent findings show that other qualities and skills still matter. This is especially true when it comes to helping entry-level workers succeed and advance in their careers.
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