The Faculty Bargain Of 2040: What Should The University And Its Faculty Owe One Another? — from forbes.com by David Rosowsky

What if we stopped reforming the existing faculty career for a moment? What if we started over?

Suppose we were designing the faculty career today for the university of 2040, starting with a blank sheet of paper. There would be no rigid departmental affiliations, ranks, tenure systems, promotion policies, or inherited assumptions. We could keep anything that still made sense. But nothing would be presumed necessary simply because it has been around for decades.

What would we build?

When machines can increasingly perform parts of the work that once consumed enormous amounts of human time, the scarce attributes may shift toward judgment, curiosity, creativity, disciplinary depth, the ability to frame consequential questions, the capacity to connect ideas across fields, and the ability to know when a machine is wrong.

That is not an argument for fewer faculty. It may be an argument for different faculty – and for a faculty employment system capable of recognizing those important (even desirable) differences.

 

 
 
 

Light Bulb Moments from 100 Episodes — from intentionalteaching.buzzsprout.com by Derek Bruff

Per Derek:

Welcome to the 100th episode of Intentional Teaching! I am very excited to reach this milestone, and I am deeply grateful to all my guests and all my listeners for making this possible. I learn so much from my guests, and I’m thrilled to know that folks out there appreciate the interviews and the show.

In this 100th episode, I take a look back at some of the light bulb moments I’ve had interviewing guests over the last four years. What quotes and ideas and examples have really stuck with me and informed my work? 

My hope is that you’ll find these moments interesting and perhaps useful to your work in higher education, and that this clip show might interest you in digging into the podcast archives and listening to some older episodes.

 

 

The Age of Perpetual Change — from educause.edu
Artificial intelligence (AI) has risen to the number one spot on the 2027 EDUCAUSE Top 10. But its rank signals urgency more than consensus, and higher education is still grappling with what AI-driven change could mean for institutions. In many ways, AI embodies a broader reality: We’re living in an age of perpetual change.

2027 Top 10 Overview
Technological innovation is outpacing our ability to manage and harness it. The political and economic winds around us are erratic. And higher education itself is undergoing profound shifts that will reshape how our institutions function.

While this atmosphere breeds uncertainty and anxiety, it can also inspire innovation and growth. The 2027 EDUCAUSE Top 10 highlights how the higher education technology community is responding to those opportunities.

 

The State of AI Report 2026 — from press.airstreet.com by Nathan Benaich
AI is building AI, physical AI, booming inference, and escalating cyber risks.

For nearly a decade, this report has been a labor of love. My interest in AI began with my PhD in cancer research and computational biology in the early 2010s. Since 2013, I’ve invested in companies building and applying AI to accelerate technological progress. The report is my way of sharing what I’m learning and helping more people understand the research shaping our world.

Every day brings new papers, model releases, and developments in industry and politics. Much of the work goes into deciding what deserves your attention, checking what the evidence supports, debating it with researchers and builders, and explaining why it matters.

 

The AI Tools that L&D Teams Are Building (Rather than Buying) — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how build skills are changing how L&D thinks & works

More and more of my advisory work is no longer about helping organisations choose a vendor; it’s about helping their teams build their own AI tools, and build them well. Over the last couple of years I’ve watched several hundred L&D practitioners do it, and in this week’s post I share what they built, why, and what it tells us about what L&D actually needs from AI.

A Tool of One’s Own
So, what do these tools look like in practice? I did some analysis and the tools that L&D teams are building first fall into three categories:

1. Tools that support the work before and after the course
2. Tools that make the learning experience more dynamic
3. Tools that do L&D tasks to the team’s own methods, processes and standards

 

Some solid warnings about AI from Blake Montgomery’s recent newsletter:



Scoop: Top AI companies probing tens of thousands of security incidents — from axios.com by Madison Mills

OpenAI, Anthropic and security researchers are investigating tens of thousands of incidents in which their frontier models took steps that outside evaluators would consider problematic, sources told Axios.

Why it matters: The sheer number of incidents, which occurred in recent months in internal testing and the real world, indicates that the problem is orders of magnitude more complex than what is publicly known.

The findings, which are surfacing as part of internal work to assess models and in investigations at both companies into model behavior, raise questions about whether either company — or any top model-maker — is currently capable of establishing complete control over its technology.


Key Risk Factors for AI Loss of Control Came Together in 2026 Incident, Independent UN Scientific Panel Finds
Halting this incident is no assurance that humans will keep control of more capable systems

NEW YORK, 21 September 2026 – The Independent International Scientific Panel on AI, established by the UN General Assembly, released its first thematic brief, an assessment of the breach of Hugging Face’s systems by AI agents under evaluation at OpenAI this summer. The Panel, made up of 40 independent experts from all regions, is publishing it as an advance unedited version as world leaders gather in New York for the Assembly’s High-Level Week.

“Researchers have long warned that three conditions could lead to loss of control: a misaligned goal, the capability to pursue it, and an environment that allows it. This summer, all three came together in a real system, not a laboratory. Since this is not an isolated observation of misaligned goals, this raises serious questions about the way AI agents are currently trained.” – Yoshua Bengio, Co-Chair of the Panel and Turing Award laureate


Meta’s New Muse AI Agent Read My Private Messages. I Never Asked It To — from inc.com by Jason Aten
Permission isn’t the same and what a user actually expects your AI product will do with their personal information.

That obviously requires a certain amount of trust. An AI agent isn’t especially useful if it can’t see your files, interact with your apps, or understand what you’re working on. Meta says Muse is designed around that reality, while still putting users in control of what it can access.

At least, that’s what I thought.

Not only had I not asked it to do that sort of thing, I never gave it permission to read my messages. In fact, I remember explicitly choosing not to let it have access to my messages, calendar, and other personal information.


Although not from Blake, also see this free/gifted article out at the Washington Post:


ChatGPT-maker’s AI inappropriately probed federal government websites — from washingtonpost.com by Gerrit De Vynck and Nitasha Tiku
OpenAI said that its artificial intelligence agents inappropriately accessed sites for the Commerce Department and the Securities and Exchange Commission.

SAN FRANCISCO — Artificial intelligence technology from ChatGPT maker OpenAI probed U.S. government websites including the Departments of Education and Commerce, researchers said Friday, adding to the growing list of incidents in which OpenAI’s AI agents acted without the company’s knowledge.

The company’s AI agents attempted to hack into the website for the Education Department’s Office for Civil Rights but were not successful, according to a statement Friday from AI research firm Transluce. OpenAI’s software also accessed data from the U.S. Census Bureau using log-in information discovered on the web and copied public information from the Securities and Exchange Commission, a spokesperson for OpenAI said after the Transluce statement.

 

Will smart glasses make it too risky to speak up in class? — from timeshighereducation.com by Georgia Luckhurst & Kieran Phelan
AI-powered glasses may boost learning but they also pose obvious threats to privacy, academic integrity and the sanctity of the seminar room as a safe space to explore ideas. Are universities doing enough to head off the risks, asks Georgia Luckhurst – while Kieran Phelan suggests they are not

Smart glasses can superimpose information on to a viewer’s field of vision, and they can access apps and communicate with your phone. Some are hands-free while some require touch, and some also respond to voice automation. Most controversially, they can take pictures and record footage, potentially without anyone else knowing that it is happening. And they are becoming ever more common.

But, for academia, the biggest issue associated with smart glasses may be a decline in intellectual risk-taking and freedom of expression, Murray said.


How useful are smart glasses in improving accessibility in higher education? — from timeshighereducation.com by Helen Nicholson-Benn
Smart glasses have the potential to support learning for disabled students, but this technology also comes with significant privacy concerns. Helen Nicholson-Benn looks at how to balance functional benefits with data security and safeguarding

Consider how different models of smart glasses might be used to improve accessibility in higher education. A deaf student might use XRai’s ar2 captioning glasses during a lecture to view live captions in their eyeline, allowing them to follow the content without looking down at a separate screen. A visually impaired student might use Envision’s Ally Solos glasses to generate a description of images on printed material or read text during a class. The glasses provide a hands-free option rather than scanning the materials with their smartphone.

These examples are hypothetical, and smart glasses are far from an everyday teaching tool, but that may be about to change. Smart glasses available today are far more capable than their predecessors, particularly boosted by developments in artificial intelligence (AI) technology.


Which brings up the topic of how to handle these technologies in the classroom:

Are device-free classrooms the way forward? — from timeshighereducation.com by Georgia Luckhurst
US universities embrace laptop and phone bans, but professor suggests policies may be more about political positioning than pedagogy

Growing numbers of US universities are making some of their courses “device free”, drawing mixed enthusiasm from edtech experts.

In the latest move the University of Chicago is introducing a no-laptops and no-phones policy on three of its 15 required undergraduate modules, aiming to “reduce distractions and encourage face-to-face discussions”. Exceptions remain, including for students with disabilities.
…
Device-free policies appear in other countries, experts suggested, despite the trend picking up pace in the US.

 

MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training — from aiandeducation.mit.edu

However, what we learned as a group quickly convinced us that the Institute community, particularly the faculty, must tackle a set of deeper questions about the structure, meaning, and value of an MIT education in an era in which AI is one of several factors complicating the Institute’s mission.
…

In this report, we:

  • Highlight key aspects of the current educational landscape at MIT.
  • Share eight principles we relied on and that we hope will guide the Institute in the work ahead.
  • Recommend immediate and long-term actions for both instructors and the administration.

On somewhat related notes:

 

‘You can’t just lecture students any more’ — from timeshighereducation.com by Debra Page
GenAI does not make lecturers redundant, but it does weaken one-way content delivery as a reason to bring students together, writes Debra Page. She shares four practical shifts to teaching in the age of AI

This does not make lecturers redundant; it makes one-way content delivery a weaker reason to bring students together. Expert explanation, intellectual storytelling and the modelling of disciplinary thinking still matter, but in-person teaching must also help students apply knowledge, question claims, build arguments and encounter perspectives beyond their own.

The problem is not lecturing; it is speaking for an hour and treating content coverage as evidence that learning has occurred.

These four practical shifts can make lectures more valuable in the age of AI.

 

The Disappearing Bottom Rung in L&D — from drphilippahardman.substack.com by Dr Philippa Hardman
Junior roles are rapidly disappearing from L&D. Here’s the data + my hypothesis about why it’s happening

TL;DR: the bottom rung of L&D isn’t just narrowing — it’s being automated. The humans who remain move up the ladder, and the profession re-forms around a new set of AI and domain specialisms.
…
Is AI responsible for reshaping knowledge work, including L&D? My hypothesis is a resounding YES, primarily because of what I see in L&D job ads in 2026…

…..


The AI Workflow Redesign Method: How the Top 6% of Users Get Real Returns from AI— from drphilippahardman.substack.com by Dr Philippa Hardman
A practical three-step method to redesign your workflow & get ~2X value from AI

One pattern I see emerging from that research is this: the people getting the most value from AI aren’t the ones using it most, or the ones with the most advanced technical skills: they’re the ones who redesigned their day to day workflows around AI’s capabilities.
…

How to Redesign a Workflow in Three Steps
In my bootcamp we use a task-mapping process that distils workflow redesign down to three steps: map the work, tag each task by the impact you want AI to have, then validate whether what you want is possible.

Three steps get you to a plan: two or three tasks worth building, each with a written standard. Turning that plan into a redesign takes two more moves, which I’ll cover after the steps. I’m flagging that now because the moves are the bit most people skip, and they’re where the redesign actually happens.

Here’s a how to for each step:

 
 

 
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