AI Definitions: Symbolic Artificial Intelligence

/

Symbolic Artificial Intelligence – This is where programmers meticulously define the rules that specify the behavior they want from an intelligent system. It works well when the environment is predictable, and the rules are clear-cut. Researchers believed that if they programmed enough rules and logic into computers, they could create machines capable of human-like reasoning. This was the dominant area of research for most of AI’s history until artificial neural networks became central to most of the recent AI developments. Although symbolic AI has lost its luster, most of the applications we use today depend on rule-based systems. An alternative approach to AI is machine learning. Some researchers believe the future of AI lies in a hybrid combination of these two approaches.

More Definitions

What an AI executive tells her kids about the jobs of the future

/

I tell my kids, play around, try things out. People need to know how to use an AI model, but not necessarily build it. Metacognitive skills will be very important—flexibility, adaptability, experimentation, thinking critically, being able to challenge things. Developing critical-thinking skills requires friction, doing things that are hard, doing deep thinking. For that, a traditional liberal-arts education is really important. Passing judgment, being accountable and responsible for decisions that impact people and society, that’s foundationally important. -Daniela Amodei, President and co-founder, Anthropic quoted in the Wall Street Journal

28 Articles about AI & Academic Scholarship

/

Can we use AI for academic writing? It depends – Times Higher Ed

Why artificial intelligence detectors could penalize academic writing – Nature

Are AI Tools Killing Review Articles? Two Failure Modes Suggest Otherwise – Aaron Tay

Artificial Intelligence guidance for authors, peer reviewers, and editors: A content analysis of journal policies - Taylor & Francis  

These Mathematicians Are Putting A.I. to the Test – New York Times 

AI agents have their own social-media platform and are publishing AI-generated research papers on their own preprint server. – Nature

The Case of the Mysterious Citations – ArXiv

AI is advancing too quickly for research to keep up - Axios

AI 'Copy-Paste' Lands PhD Students in Trouble, UGC Rejects Dozens of Research Papers – Patrika

Open-source AI tool beats giant LLMs in literature reviews — and gets citations right – Nature

AI is not a peer, so it can’t do peer review – Times Higher Ed 

Why write a literature review if AI can do it for you? – London School of Economics   

On the troubling rise of generative AI suspicion in academic publishing – Nature

Researchers find nearly 300 papers at linguistics conferences contained hallucinated citations. - ArXiv

Self-Disclosed Use of AI in Research Submissions to BMJ Journals – JAMA  

AI research deluge: why one conference is asking authors to rank their own papers – Nature

Why Authors Aren’t Disclosing AI Use and What Publishers Should (Not) do About It – Scholarly Kitchen  

An AI Bot Is Making Podcasts With Scholars’ Research. Many of Them Aren’t Impressed. – Chronicle

After turning off ChatGPT’s ‘data consent’ option, two years of academic work vanished – Nature  

ArXiv preprint server clamps down on AI slop - ArXiv

AI conference “accepted research papers with 100+ AI-hallucinated citations – Fortune

LLMs in Peer Review—How Publishing Policies Must Advance – JAMA  

Why scholarly publishing needs a neutral governance body for the AI age – Research Information  

From model collapse to citation collapse: risks of over-reliance on AI in the academy – Times Higher Ed 

Qualitative researchers’ AI rejection is based on identity, not reason: The claim that AI can’t make meaning contradicts what researchers are finding – Times Higher Ed

AI research should always be verified, especially in court – Post Crescent 

Invisible Text Injection and Peer Review by AI Models – JAMA

Artificial Intelligence and the Fraud Industry in Scientific Publishing (video) -  Ministry of Science, Innovation and Universities, Spain 

Optimists live longer

/

Here’s a good reason to turn that frown upside down: Optimistic people live as much as 15% longer than pessimists, according to a study spanning thousands of people and 3 decades.  After controlling for health conditions, behaviors like diet and exercise, and other demographic information, the scientists were able to show that the most optimistic women (top 25%) lived an average of 14.9% longer than their more pessimistic peers. For the men the results were a bit less dramatic: The most optimistic of the bunch lived 10.9% longer than their peers, on average, the team reports today in the Proceedings of the National Academy of Sciences. 

David Shultz writing in Science Magazine 

Being Bored Out of Your Mind Makes You More Creative

/

Boredom might spark creativity because a restless mind hungers for stimulation. Maybe traversing an expanse of tedium creates a sort of cognitive forward motion. “Boredom becomes a seeking state,” says Texas A&M University psychologist Heather Lench. “What you’re doing now is not satisfying. So you’re seeking, you’re engaged.” A bored mind moves into a “daydreaming” state, says Sandi Mann, the psychologist at the University of Central Lancashire who ran the experiment with the cups. Parents will tell you that kids with “nothing to do” will eventually invent some weird, fun game to play—with a cardboard box, a light switch, whatever.

The problem, the psychologists worry, is that these days we don’t wrestle with these slow moments. We eliminate them. “We try to extinguish every moment of boredom in our lives with mobile devices,” says Sandi Mann, psychologist at the University of Central Lancashire. This might relieve us temporarily, but it shuts down the deeper thinking that can come from staring down the doldrums. Noodling on your phone is “like eating junk food,” she says.

So here’s an idea: Instead of always fleeing boredom, lean into it. Sometimes, anyway.

Clive Thompson, Wired

22 Articles about AI’s impact on College Faculty & Administrators

/

An Overview of AI Governance in Education – EdTech Magazine

Harvard Proposes a Cap on AI’s amid worry over grade inflation – Bloomberg

Higher education needs to change in order to survive the AI economy – Fast Company

Hey, ChatGPT: Where Should I Go to College? – New York Times

The risks of AI in schools outweigh the benefits, report says – NPR  

Resisting AI slop in Science & Higher Ed – Science.org

5 Predictions on How AI Will Shape Higher Ed in 2026 – Inside Higher Ed

As Schools Embrace A.I. Tools, Skeptics Raise Concerns - New York Times

Purdue University Approves New AI Requirement For All Undergrads – Forbes 

4 policy trends that should be on college leaders’ radars in 2026 – Higher Ed Dive

Voices of Student Success: A Liberal Arts College Goes All In on AI (podcast) – Inside Higher Ed

Higher Education Plans for a Future Markedly Changed by A.I. - New York Times

Higher Education’s AI Problem (podcast) - NPR

How AI Is Changing Higher Education – Chronicle of Higher Ed 

Big tech companies are making the Cal State college system a training ground for A.I. tools in education. - New York Times

Can Colleges Be Run Using AI? - Chronicle of Higher Ed 

From Yale to MIT to UCLA: The AI policies of the nation's biggest colleges – Mashable

University of Georgia investing $800,000 in program providing students with AI tools – CBS News 

How AI Supports Student Mental Health in Higher Education – Ed Tech

Calcutta University plans 10% cap on AI use in PhD thesis – Millennium Post

The Accidental Winners of the War on Higher Ed – The Atlantic

The worst AI strategy in higher ed is no strategy at all – University Business

9 Podcasts about AI

/

Eye on AI (interviews from a longtime New York Times correspondent)

Machine Learning Guide (teaching the fundamentals of machine learning and AI)

AI in Business (for non-technical business leaders)

Data Skeptic (applies critical thinking and the scientific method to AI developments)

AI Today (practical insights)

AI for Humans (have a good time learning)

Practical AI (how to get stuff done)

The Artificial Intelligence Show (for marketers)

NVIDIA AI Podcast (interviews with people growing the AI space  from a major AI chipmaker)

The intersection of Science & AI in 18 Articles

/

Open-source AI program can answer science questions better than humans - Science.org

OpenClaw AI chatbots are running amok — these scientists are listening in – Nature

Today’s fraudsters can exploit the online scientific world to quickly create realistic looking papers on an industrial scale - Taylor and Francis

There's a crisis in particle physics. Researchers hope AI can help. – IEEE Spectrum

Inside OpenAI’s big play for science – MIT Tech Review

Researchers use AI to reverse engineer molecules – Semafor

Resisting AI slop in Science & Higher Ed – Science.org

2025's AI-fueled scientific breakthroughs - Axios

Where Is All the A.I.-Driven Scientific Progress? – New York Times 

The H-Index of Suspicion: How Culture, Incentives, and AI Challenge Scientific Integrity – NEJM

Machine learning helps researchers create lab-grown ‘tiny brains’ to uncover how neurons may malfunction in schizophrenia and bipolar disorder – SciTechDaily  

AI-designed viruses raise fears over creating life – Washington Post  

AI hallucinates because it’s trained to fake answers it doesn’t know - Science.org 

How ChatGPT-5 redefines scientific reproducibility – Elephant in the Lab

The chemistry community should ban drawing chemical structures with generative AI, chemists warn – Chemistry World  

Hack reveals reviewer identities for huge AI conference – Science.org

Researchers call for retraction of two recent Nature studies about AI-generated crystals – Chemical & Engineering News

Science Is Drowning in AI Slop – The Atlantic

18 AI Dangers

/

AI Companions - Inappropriate dependance on AI, AI control over humans, weakening of human relationships, pornography, suicides, AI delusions, mental health care, human dignity.

AI Divide - Greater inequality, the distance between those who have access to powerful AI & those who don’t.  

Bias - AI can reflect societal prejudices and stereotypes, obscuring underrepresented and marginalized populations.    

Criminals & Crime - Using AI to commit crimes such as cyberattacks, fraud and child pornography.  

Copyright – AI may be trained on copyrighted works and reproduce copyrighted material without permission. 

Deep Fakes - Cyberbullying, nonconsensual pornographic images & video.

Economics - Potential AI-created financial crisis.

Environmental Concerns - Energy consumption, high water usage, and electronic waste.

False information  - Hallucinations can lead to fearmongering, fake news, poor health advice, corrupted learning tools for children, historical misinformation, and false criminal accusations.

Human Labor – Exploitation of workers, human trafficking.

Knowledge Collapse – AI models run out of fresh data, resulting in a feedback loop — dominant ideas are amplified while less widely held or new viewpoints are minimized.

Out of Control AI - Bullying humans, taking action against humans (particularly actions outside of what the AI was designed to do), and AI uprising where bots attempt to gain control outside of human direction. 

Politics - Influencing elections, creating or magnifying international conflict.

Privacy & Security - Facial recognition false arrests, malware, social media, data on children, using AI to hack databases, steal passwords, and personal information has the potential to be shared with third parties. 

Religion - Cultlike dependence on AI, allowing outsized control, treating AI like a Magic 8 Ball, worshipping AI. 

Science - AI Slop may erode scientific progress.

Slop – Low-grade AI content can clog email, social media and the internet. Also, work slop.

Weapons & War - Drones, satellites, biological weapons.

Signs of Endings

/

Endings and losses are the commonest first sign that people are in transition. These endings tend to be signaled by one of several experiences: 

  • A sudden and unexpected event that destroys the old life that made you feel like yourself 

  • The “drying up” of a situation or a relationship 

  • An activity that has always gone well before, suddenly and unexpectedly goes badly

  • A person or an organization that you have always trusted proves it be untrustworthy 

  • An inexplicable or unforeseen problem crops up 

William Bridges, The Way of Transition

AI Health Advice

/

A new study found that AI "health advice from was frequently wrong. However, a closer look at the results tell a different story. "About half the time, mistakes appeared to be the result of user error. Participants didn’t enter enough information or the most relevant symptoms. By contrast, when researchers entered the full medical scenario directly into the chatbots, they correctly diagnosed the problem 94 percent of the time." -New York Times

Using AI to Write an Apology to the Court

/

A judge in New Zealand questioned the remorse of a defendant who had used A.I. to write apologies to victims and the court. Increasingly, people are outsourcing many tasks to machines, including writing apologies, eulogies and wedding vows, perhaps saving precious time but also inviting the ire of some of their fellow humans. People apparently believe that certain activities should take work in order to seem genuine. -New York Times

4 Steps When Addressing Inappropriate Behavior

/

When someone keeps repeating inappropriate behavior, try the DESC approach.  The four steps are describe, express, specify, and consequences.

1. Describe the objectionable behavior.

2. Express your feelings.

3. Specify what action you want to see.

4. Tell the person the consequences if there is no change in behavior.

12 Recent Articles about AI & Audio/Video

/