In recent layoffs, AI's role may be bigger than companies are letting on
As companies use terms like reorganization, restructuring, and optimization in job cuts, AI may be at work more than they want employees to know.
Deciding vs. Choosing: AI and Learning
I’m reading The AI Con right now, and it reminded me of a story I’d heard a long time ago about how Joseph Weizenbaum – inventor of Eliza which was one of the first chatbots ̵…
Ep. 7 – AI, Cheating, and Trusting Students to be Human
Tricia Bertram Gallant, coauthor of The Opposite of Cheating: Teaching for Integrity in the Age of AI, joins us to discuss questions about academic dish...
AI Awareness Starts with Time
Time is one of the luxuries every teacher searches for within their classrooms.
AI and a Return to Rhetoric - ReadBeanIceCream
Bonus Edition: What’s the Deal with ChatGPT Agents?
A First Look at the Tool Everyone Will Be Talking About
COMMENTARY by Adrian Lenardic and Johnny Seales, "Why Write?" - Future U
Writing to a rubric involves thinking, but it’s an artificial form of thinking. The messier human mode is bypassed in favor of following a formula to gain a reward – a move to perverse incentives.
Once something can follow the formula faster, why not use it – a move with no incentive. This follows a broader path that moved higher education from a place of learning to a place of training. Students became trained to write before AI was given training data to help it ‘learn’ how to write essays for students.
You’re Not Imagining It: AI Is Already Taking Tech Jobs
“We’re going from mass hiring to precision hiring,” said Chen, adding that companies are starting to focus more on employing experts in their fields. “The superstar workers are in a better position.”
7 AI, Cybersecurity, and the Future of Teaching Trends: ISTE 2025
Seven trends are discussed today from AI lesson planning, how to use AI to promote creativity and Auburn University's SOC center.
Asking a More Productive Question about AI and Assessment
'Given that AI exists in the world, and that students are likely to use it (whether accidentally or on purpose), what evidence of learning would I now find persuasive?'
AI Progress Delayed Is Progress Denied
Earlier this summer, I recorded an episode of the Scaling Laws podcast with MacKenzie Price, founder of Alpha Schools—schools “where kids crush academics in two hours, build life skills through workshops, and thrive beyond the classroom.” The secret is AI, but likely not the sort of AI that comes to...
Using AI to reimagine teacher preparation for scale, equity, and reflective practice
A computerized AI coaching support model lets pre-service teachers engage in scalable, self-guided reflection for teacher preparation.
University students feel ‘anxious, confused and distrustful’ about AI in the classroom and among their peers
Whether students and faculty are actively using AI or not, it is having significant interpersonal, emotional effects on learning and trust in the classroom.
60% of managers use AI to make decisions now, including whom to promote and fire - does yours?
In fact, 43% of managers surveyed went on to replace a human role with AI. Here's how employees can protect themselves in the face of AI's gray areas.
Half of Managers Use AI To Determine Who Gets Promoted and Fired - ResumeBuilder.com
According to a new Resume Builder survey, a majority of mangers are using AI make high-stakes personnel decisions.
Start Where It Hurts: Using AI to Tackle Assessment Pain Points
How AI Makes Assessments Less Painful and More Purposeful
Counteract #AI Cynicism with Philosophy-Inspired CARES Model #EduSky
In one of his missives to followers, Steve Hargadon writes something my memory assigned to Audrey Watters (incorrectly I noticed when I went back to check the source). I should have known better. N…
Special Update: Google Launches Gemini for Education at ISTE 2025
Teachers and Parents Can’t See AI Chat Transcripts While Gemini may be “student safe,” only administrators can review chat histories. That’s a huge blind spot. If a student is confused by a Gemini response, misuses the tool, or gets inaccurate information—teachers and parents won’t know unless the student says something.
Is AI doing the thinking—or the student? Many features encourage speed and convenience, but could inadvertently promote over-reliance. Students can get summaries, answers, and explanations so easily that critical thinking risks taking a backseat.
There’s no way to track edits or usage Gemini doesn’t offer version history for AI-generated content. That means teachers can’t see how a document evolved—or how much of it came from AI.
Equity gaps may widen Some schools have tech coaches, training time, and infrastructure to support thoughtful AI use. Others don’t. Without equitable implementation support, Gemini’s benefits may be limited to already well-resourced districts.
From knowledge to performance
Bad questions are not the answer to move from knowledge to performance. What is needed? Let's look at the types of questions we ask.
Experience AI
Experience AI
How the Vatican Is Shaping the Ethics of Artificial Intelligence
Shane Tews is joined by Father Paolo Benanti, a theologian and ethicist for the Vatican on AI, for a thought-provoking interactive discussion that transcends traditional debates on values and policy to examine AI's broader psychological, philosophical, and even theological implications.
Bernie Sanders Reveals the AI 'Doomsday Scenario' That Worries Top Experts
The Vermont senator discusses his fears that artificial intelligence will only enrich the billionaire class, the fight for a 32-hour work week, and the ‘doomsday scenario’ that has some of the world’s top experts deeply concerned.
Capabilities & Ethics of AI Found in Middle Grades Fiction
Novels that explore AI through stories grounded in real ethical and scientific questions spark discussions and critical thinking with students, says Kasey Short
Generative artificial intelligence in education: (what) are we thinking?
The power of Gen-AI lies in the synthesis of comprehensive information openly available online, a much faster process compared to any normal human processing.
Digital ethicswashing: a systematic review and a process-perception-outcome framework - AI and Ethics
The term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.”
Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia.
In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.
The term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.” Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia. In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
AI Ethics, Ethics Washing, and the Need to Politicize Data Ethics
Many commercial actors in the tech sector publish ethics guidelines as a means to ‘wash away’ concerns raised about their policies. For some academics, this phenomenon is reason to replace ethics with other tools and methods in an attempt to make sure that the tech sector does not cross any moral Rubicons. Others warn against the tendency to reduce a criticism of ‘ethics washing’ into one of ethics simpliciter. In this essay, I argue firstly that the dominant focus on principles, dilemmas, and theory in conventional ethical theories and practices could be an explanation of it lacking resistance to abuse by dominant actors, and hence its rather disappointing capacity to stop, redirect, or at least slow down big tech’s course. Secondly, drawing from research on casuistry and political philosopher Raymond Geuss, this essay will make a case for a question, rather than theory or principle-based ethical data practice. The emphasis of this approach is placed on the acquisition of a thorough understanding of a social-political phenomenon like tech development. This approach should be replenished with one extra component to the picture of the repoliticized data ethics drawn so far: the importance of ‘exemplars,’ or stories. Precisely the fact that one should acquire an in-depth understanding of the problem in practice will also allow one to look in the past, present, or future for similar and comparable stories from which one can learn.
Hitchhiker’s Guide to RAG: From Tiny Files to Tolstoy with OpenAI’s API and LangChain | Towards Data Science
Scaling a simple RAG pipeline from simple notes to full books
AN ETHICAL WIN-WIN-WIN
Explore the synergy between consequentialism, virtue ethics, and deontology, revealing how these ethical frameworks can coexist and enhance moral understanding.