Humans — not AI — are to blame for deadly Iran school strike

Humans — not AI — are to blame for deadly Iran school strike, sources say. According to former military officials and people familiar with aspects of the bombing campaign in Iran, the thousands of people who gather intelligence and analyze satellite photos to build massive target lists ahead of potential conflicts with foreign adversaries are to blame for the deadly Iran school strike. The error was one that AI would not be likely to make: US officials failed to recognize subtle changes in satellite imagery, while human intelligence analysts missed publicly available information about a school located inside the Revolutionary Guard compound. -Semafor

20 Recent Articles about AI & Journalism

Notes on RISJ’s AI and the Future of News symposium - Harvard’s Nieman Lab

How Journalists Can Make AI Work for Them -  Columbia Journalism ReviewNotes on RISJ’s AI and the Future of News symposium

A lot of journalism folks are offering editing advice as Grammarly’s AI “experts” – Harvard’s Nieman Lab

Ars Technica Fires Reporter After AI Controversy Involving Fabricated Quotes – Futurism

Can AI Save Local News? – Wall Street Journal

As AI data centers scale, investigating their impact becomes its own beat – Harvard’s Nieman Lab

Ars Technica Fires Reporter After AI Controversy Involving Fabricated Quotes - Futurism

In This Cleveland Newsroom, AI Is Writing (But Not Reporting) the News – Columbia Journalism Review

Retraction of article containing fabricated quotations by an AI Tool - Arstechnica

Eight in ten of world’s biggest news websites now block AI training bots – Press  Gazette

The Fight over AI at McClatchy - Columbia Journalism Review

New York Times publisher: AI is using our facts without paying for them – Mediaite

Generative Engine Optimization FAQs from the ‘What Is AI Reading?’ report  - Muck Rack  

College paper fights to stop AI slop website from stealing its identity – Washington Post

How AI is reshaping the news industry - Harvard’s Nieman Lab

How will AI reshape the news in 2026? Forecasts by 17 experts from around the world – Reuter Institute

How AI is affecting me as a human (and journalist) – Axios  

Here are the news outlets that got AI right in 2025 — and the ones that got it very, very wrong – Poynter

AI Used to Promote Non-Existent Evacuation Flights From the Middle East – Bellingcat

What the ‘AI inflection point’ means for journalism – Fast Company

Privacy Concerns with AI-powered Meta Ray-Ban glasses

The things you record with your AI-powered Meta Ray-Ban glasses — yes, even those intimate moments where you think you're alone — are probably being seen by strangers. An investigation by two Swedish newspapers found that offshore Meta workers in Kenya were asked to analyze intimate and even "disturbing" videos taken by glasses wearers, including videos taken in bathrooms, footage featuring nudity and sexual content, and images showing personal information like bank accounts. It's part of a process known as data labeling, used to train AI models with footage first reviewed and annotated by humans so that the AI can understand what it's "looking" at. -Mashable

25 Recent Articles about AI & Legal Issues

AI Legal Platform now Valued at $5.5 Billion – AI Business  

Encyclopedia Britannica sues OpenAI over AI training – Reuters

The AI Literacy Gap is Now a Security and Compliance Liability – JD Supra

Who’s liable when AI is used for harm? – KARE-11

Grammarly is using our identities without permission – The Verge  

Thaler Is Dead. Now for the AI Copyright Questions That Actually Matter. - Copyright Lately

AI legal advice is driving lawyers bananas - Axios 

AI Deepfakes in the Workplace: A New Frontier of Employer Liability – JD Supra

A judge in New Zealand questioned the remorse of a defendant who had used A.I. to write apologies to victims and the court. - New York Times

Employers Turn to AI to Screen Candidates’ Social Media: Best Practices to Minimize Legal Threats – JD Supra

Arkansas attorney resigns after using AI to assist in case work – Thv11 

Interest in Law School Is Surging. A.I. Makes the Payoff Less Certain. – New York Times

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

League City police to review policies after giving theft suspect an AI mug makeover – ABC13

How AI and social media sites are still collecting kids’ data despite privacy laws – Technical.ly  

ABA Highlights AI’s Challenges for Legal Education and Liability – Bloomberg

Proposed New York law would bar AI chatbots from posing as lawyers, allow duped users to sue – Reuters

What Was Grammarly Thinking? – The Atlantic

Legal advocates object to bill to allow AI interpretation in court – Wisconsin Public Radio

Federal Court Rules Some AI Chats Are Not Protected by Legal Privilege – Crowell Legal

White House puts red state AI laws under scrutiny – Axios

AI Legal Compliance for Law Firms: What Lawyers Need to Know in 2026 – JD Supra

A Long-Running AI Copyright Question Gets an Answer as Supreme Court Stays Mum – CNET

DOJ attorney in Raleigh accused of fake legal arguments, prompting warning about AI from prosecutor - WRAL

AI pilot program in L.A. County courts will help judges craft rulings in some cases – LA Times

AI Definitions: Machine Learning

Machine Learning (ML) - This type of AI can spot patterns in data sets and then improve what it can do on its own, making predictions or decisions. This process evolves and the ML adapts as it is exposed to new data, improving the output without explicit human programming. An example would be algorithms recommending ads for users, which become more tailored the longer it observes the users‘ habits (someone’s clicks, likes, time spent, etc.). A developer of a ML system creates a model and then “trains” it by providing it with many examples. Data scientists then combine ML with other disciplines (like big data analytics and cloud computing) to solve real-world problems. However, the results are limited to probabilities, not absolutes. It doesn’t reveal causation. A subset of “narrow AI,” ML is an alternative approach to symbolic artificial intelligence, and it is better at spotting faces and recognizing voices. Machine learning can be divided into four types: supervised, unsupervised, semi-supervised, and reinforcement learning. A clever computer program can be considered AI if it can mimic human-like behavior. However, the computer system is not machine learning unless its parameters are automatically informed by data without human intervention. Video: Introduction to Machine Learning

AI Bioweapons

Microsoft researchers selected 72 different proteins that are subject to legal controls, such as ricin, a bacterial toxin already used in several terrorist attacks. Using specialized AI protein design tools, they came up with more than 70,000 DNA sequences that would generate variant forms of these proteins. Computer models suggested that at least some of these alternatives would also be toxic. The researchers asked four suppliers of biosecurity screening systems used by DNA synthesis labs to run these sequences through their software. The tools failed to flag many of these sequences as problematic. Their performance varied widely. One tool flagged just 23% of the sequences.  Some DNA vendors, accounting for perhaps 20% of the market, don’t screen their orders at all.  -Science.org

AI Definitions: Decision Science

Decision Science (or Decision Intelligence) – A branch off the “AI engineer” tree, this career path is less focused on software and more about how to make the most of AI outputs through both quantitative and qualitative methods. This interdisciplinary approach combines data science tools (statistics, analytics, causal inference, and strategic analysis) with the behavioral sciences (psychology, neuroscience, economics, and the managerial sciences) to offer a broader perspective than many data science efforts. In effect, decision scientists support the human-in-the-loop effort to make actionable decisions from AI results for real business value.  

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27 Webinars this week about AI, Journalism & Media

Mon, Mar 16 - Lost History of Western Maryland’s Earliest Black Newspapers (1870 - 1900)

What: Learn about the founding of the first Black newspapers in Appalachian Maryland and their editors.

Who: Librarian and historian John H. Muller who has authored many historical books.

When: 11 am

Where: Zoom

Cost: Free

Sponsor: Lost History Associates

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Mon, Mar 16 - Preparing Students for the AI Work Force

What: How artificial intelligence has changed the job market for entry-level workers. What skills and competencies employers are looking for in entry-level workers. How colleges and universities are changing curricula to include AI.

Who: Ian Wilhelm, Deputy Managing Editor The Chronicle of Higher Education; Sid Dobrin, Professor of English, Founding Director of the Trace Innovation Initiative University of Florida; Don Fraser Jr., Senior Vice President, Design + Innovation Education Design Lab; Margaret Moffett, Author; Jessica A. Stansbury, Director, Center for AI Learning and Community-Engaged Innovation University of Baltimore.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Chronicle of Higher Ed

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Tue, Mar 17 - AI and the Future of News 2026

What: A day of lightning talks, panel discussions and interviews with journalists and experts on how AI is transforming news. There will be one Zoom for the entire day so you can tune in and out as you wish.

Who: Several dozen journalists and researchers.

When: 6 am, Eastern

Where: Zoom

Cost: Free

Sponsor: Reuters Institute

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Tue, Mar 17 - AI Innovator Collaborative  

What: The AI Innovator Collaborative, a monthly gathering for members experimenting with AI. We'll talk about what publishers need to know in this era of search volatility and give members a chance to share what's currently working in their own organizations.

Who: Jessie Willms and Shelby Blackley, co-founders of WTF is SEO.

When: 3 pm, Eastern

Where: Zoom

Cost: Free to members

Sponsor: Online News Association

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Tue, Mar 17 - Using AI Gems to build training materials 

What: We will demonstrate how to create your own personalised AI GEMS that can produce learning tools based on any content you provide, whether it’s a course outline, an article you wrote, or content you find inspiring.

Who: David Brewer from Media Helping Media.

When: 5 am, Eastern

Where: Zoom

Cost: Free

Sponsor: Fojo Media Institute

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Tue, Mar 17 - Turning Expertise into Opportunity: Using YouTube to Build Credibility, Demand, and Trust

What: We will explore how YouTube can serve as a long-term credibility engine—helping professionals “sell” their expertise by teaching clearly and consistently. Instead of focusing on algorithms or influencer tactics, this session shows how to align your expertise with real audience needs, avoid common content pitfalls, and build trust before the first client conversation even happens. Discover how teaching can become one of your most valuable professional assets.

Who: Paul Wilson, CTDP, eLearning Consultant, Designer and Developer, CaptivateTeacher.com

When: 12 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Training Magazine Network

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Wed, Mar 18 - ChatGPT for Teachers: Managing and Scaling Access

What: We’ll focus on how to manage and scale access to ChatGPT for Teachers over time, including user administration, permissions, and operational best practices for secure, sustainable district implementation.

When: 10 am, Eastern

Where: Zoom

Cost: Free

Sponsor: OpenAI Academy

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Wed, Mar 18 - How to Use GenAI for Personalisation

What: Each panalist will walk us through their key learnings in their experiments with using AI in personalisation. Yahoo News recently launched Your Daily Digest, an AI-powered feature that delivers a personalised audio summary of the day’s top news stories directly in the Yahoo News app. The feature combines Yahoo’s editorial curation with AI-driven recommendations and personalisation to create a tailored listening experience for every user.  Times Internet’s AI-powered personalisation has almost doubled click-through rates on push notifications and doubled engagement on content widgets.

Who: Erica Greene, Director of Engineering, Machine Learning at Yahoo News; Ritvvij Parrikh, Senior Director of Product Management — AI at Times Internet.

When: 10 am, Eastern

Where: Zoom

Cost: Free

Sponsor: International News Media Association

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Wed, Mar 18 - Restricting Access to the "I" in FOIA

What: This will be a discussion on the nuts and bolts of FOIA, its exemptions, and how pending lawsuits could shake things up. Learn how the ACLU and local journalists use FOIA, what the process is for filing a request, litigating a denial of a request, and the most frequent barriers to information access, and how we navigate them.

Who: Rob Vanella, Journalist at Delaware Call; Xerxes Wilson, Journalist at Delaware News Journal;  Andrew Bernstein, ACLU-DE Civic Engagement Counsel.

When: 12 pm, Eastern

Where: Zoom

Cost: $50

Sponsor: ACLU Delaware

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Wed, Mar 18 - The Cost of Silence

What: We will explore how intentional communication can replace friction with connection. Whether you're leading, collaborating, or simply looking to improve personal interactions, you’ll leave with practical strategies you can use immediately to build stronger relationships at work or in your personal life.

Who: Communications expert and strategic storyteller Jenny Riddle.

When: 12 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: DePaul University

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Wed, Mar 18 - Republishing Guidelines Legal Briefing

What: We often hear that news organizations would like to allow other news organizations to share their content or that they’d like to co-report on stories, but they need help establishing an understanding about republishing or co-publishing guidelines. ProJourn, a program operated by the Reporters Committee for Freedom of the Press, in partnership with Covington & Burling LLP, will host a public briefing on the intellectual property and other legal considerations that go into republishing guidelines.  

Who: Christina Piaia; Audrey Tanenbaum; Phil Hill & Dimitra Rallis of Covington & Burling LLP.

When: 12 pm, Eastern

Where: Microsoft Teams

Cost: Free

Sponsor: ProJourn

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Wed, Mar 18 - Book Bans with The Marshall Project and Data Liberation Project

What: Learn about the work of uncovering book bans in prisons across the country.

Who: Experts from The Marshall Project and Data Liberation Project

When: 1 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Sunlight Research Desk

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Wed, Mar 18 – How Medical Writing Work, Value, and Careers Are Shifting in the Age of AI

What: Rather than focusing on tools or tactics, the discussion centers on how writing work itself is being redefined. A core theme of the session is the distinction between what can be automated and what cannot. Participants will explore where human judgment remains essential, and why these contributions are often under-recognized but critical to quality and credibility.

Who: Sharon Kim, PharmD, is the founder and CEO of MPilot, an AI-driven platform supporting clinical trial documentation; Aliza Nathoo has over 20 years of experience as a medical writer and submission lead.

When: 1 pm, Eastern

Where: Zoom

Cost: Member $20 | Non-member $55

Sponsor: American Medical Writers Association

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Wed, Mar 18 - The Human Edge: Thriving with AI Through Empathy and Critical Thinking

What: We’ll explore practical strategies for safely and responsibly using AI in the classroom and for developing the human skills needed to use AI effectively. Learn how to blend AI into learning environments without diminishing the critical human skills students need to thrive. Walk away with actionable strategies, resource ideas, and a mindset shift that helps you champion both innovation and essential human abilities in your educational setting.

Who: Stefani Kauppila, Former Teacher, Current Director of Product, Committee for Children; Jordan Posamentier, Former Teacher, Current VP of Policy & Partnerships, Committee for Children; and Dr. Jodie Donner, Former Teacher, Current Senior Instructional Designer II, Committee for Children.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: SecondStep

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Wed, Mar 18 - Cyber in the Era of AI

What: A look at how AI is transforming cybersecurity across the public sector. We’ll cut straight to what matters: faster threats, smarter defenses, and the emerging tools helping agencies stay ahead of adversaries.

Who: Shannon Lawson, Chief Information Security Officer, City of San Antonio, Texas; Marcus Thornton,  Deputy Chief Data Officer, Virginia Office of Data Governance and Analytics; Kelvin Brewer, Director, Public Sector Sales Engineering, Ping Identity; Bryan Rosensteel, Head of Public Sector Product; Travis Rosiek, Field CTO, Public Sector, Rubrik Marketing, Wiz.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: GovLoop

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Wed, Mar 18 – Digital Accessibility for Student Media

What: In this session, learn how to treat digital accessibility the same as physical accessibility to comply with the Department of Justice's new digital accessibility standards as they apply to websites, podcasts and social media. Specific topics include audio/video transcripts, descriptive link text, alt text, color contrast and color blindness.

Who: Jamie Lynn Gilbert, the associate director of NC State Student Media.

When: 5 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: College Media Advisor

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Thu, Mar 19 - 30 Minute Skills: Copyediting 101

What: Join a growing community of journalists and other curious members of the public for our next monthly lesson.

Who: Edward Fitzpatrick, The Boston Globe.

When: 12 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: New England First Amendment Coalition

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Thu, Mar 19 - Life After Layoffs: Resources, Tips, & Real

What: Hear from peers and experts on how to cope with being laid off.

Who: Jayme Catsouphes, producer, editor, sound designer, and co-founder of the worker cooperative production company, Mumble Media; Lauren Paterson, multimedia journalist with a reporting career rooted in the Pacific Northwest and public media; Chandra Turner, recruiter, career coach, and founder of boutique recruiting agency The Talent Fairy.

When: 1 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Public Media Journalism Association

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Thu, Mar 19 - AI in Book Publishing: How Does it Affect Indie Authors?

What: This is a 101-level discussion of the impact AI is having on the book publishing industry. Topics will include: The opportunities and savings it offers; Ethical as well as practical concerns; Tips for safe and helpful usage; Red flags every author must be aware of.

Who: Book marketing advisor Beth Kallman Werner of Author Connections.

When: 1:30 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Author Learning Center

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Thu, Mar 19 - Solutions Journalism

What: We’ll learn the four key elements of “solutions stories”: Response, what has or hasn’t worked; Insight, what does the response show; Evidence, data or qualitative results that indicate effectiveness, or lack thereof; and Limitations, the response in context, including shortcomings. At the end of this workshop, you’ll be able to reframe stories and story pitches around the solutions lens.

Who: ENS Managing Editor Lynette Wilson.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsors: Episcopal News Service & Episcopal Communicators

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Thu, Mar 19 - AI in Journalism

What: How is artificial intelligence reshaping the newsroom — and what does it mean for the future of reporting? In this webinar, we will share how AI is being put to work in agricultural and mainstream media. will moderate.  

Who: Eric Braun of Farm Progress; Silas Lyons of USA Today; NAAJ President Tim Hearden.

When: 2 pm, Eastern

Where: Zoom

Cost: Free to NAAJ members and ACN members.

Sponsors: North American Agricultural Journalists & Agricultural Communicators Network

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Thu, Mar 19 – Using Gen AI in Advising

What: This virtual forum with student-affairs leaders where we’ll discuss the effects of generative AI on advising.

Who: Alexander C. Kafka, Senior Editor, The Chronicle of Higher Education; Alytrice Brown, Chief Student Services Officer/Vice President of Student Services, Jackson College; Lynda Holt, Director, Recruitment and Partnerships, Lally School of Management, Rensselaer Polytechnic Institute; Eric Johnson, Assistant Dean, Office of Undergraduate Studies; Director, Office of Letters and Sciences,  University of Maryland; Glenda Morgan, Founder Morgan EdTech Strategies.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Chronicle of Higher Ed, Oracle

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Thu, Mar 19 - AI, Algorithms & Librarians: The evolution of the librarian in the GenAI era

What: Our panel will share how they are engaging in the AI debate on their campuses and how purpose-built research grade AI tools can improve the researcher workflow. Attendees will leave with practical tips on staying up to date on AI developments, participating in AI policy decisions on their campuses, and evaluating AI tools for the library.

Who: Melissa Del Castillo, Chair, AIRUS: Artificial Intelligence in Reference & User Services Interest Group; Evan Simpson, Associate Dean, Experiential Learning & Academic Engagement, Northeastern University; Emily Singley Vice President, Global Library Relations & Partnerships, Elsevier.

When: 2 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Elsevier

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Thu, Mar 19 - AI Powered Media Sales: Top 10 Ways to Use A.I. In Your Sales Strategy

What: With an overwhelming array of AI sales tools available, how can serious media sales reps know which ones to rely on? In this practical workshop, you will be given real examples why AI tools are essential for researching more effectively, uncovering valuable sales opportunities, and gaining a competitive edge. Don’t miss this chance to elevate your sales strategy—learn the tools that high-performing reps are already using to outsell the competition.

Who: Ryan Dohrn, motivational speaker and 30-year ad sales veteran.

When: 2 pm, Eastern

Where: Zoom

Cost: $35

Sponsor: Online Media Campus

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Thu, Mar 19 - Investigative College Sport Journalism

What: The winners of the 2026 Drake Group Education Fund Student Journalism Prize for Investigative Reporting on Intercollegiate Athletics will talk about their stories with an esteemed panel of sports journalists and authors.

Who: Prize winners and journalists from The Associated Press, The New York Times, The Columbus Dispatch, and NBCSport.com.

When: 2:00 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: The Drake Group Educational Fund

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Thu, Mar 19 - Digital Open-Source Investigations: Geolocation Webinar    

What: Participants will learn how to verify images and videos by finding exactly where they were recorded using satellite and street-view imagery from platforms like Google Earth and Maps.

When: 6 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: National Association of Hispanic Journalists, USC Annenberg School for Communication & Journalism  

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Thu, Mar 19 - How to Start an AI-Native Business: Informational Session

What: The start of an AI series where we take entrepreneurs through step by step on how to create an AI Native Business. In this session, we will run through the program information, talk about what makes an AI native business, how to construct and integrate AI into each area of your business.  

When: 6 pm, Eastern

Where: Zoom

Cost: Free

Sponsor: Small Business Development Center, Widener University

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Many AI models Prefer to "think" in Chinese

Many AI models prefer to think in Chinese. Their internal chain of thought is built to process data this way because the Chinese language is 50% more space-efficient than English. Chinese programmers prefer to code in their own language even when their model is configured to output information in English. This is why Chinese models are generally faster than English-language models and why they use fewer tokens (requiring less energy). The Chinese model DeepSeek was trained for about $6 million, while US models have typically needed about $100 million for training. 

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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.

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24 Articles about how AI is Affecting Jobs

Anthropic is tracking which jobs are most exposed to AI. These 10 professions top the list. – CBS News

Is AI productivity prompting burnout? Study finds new pattern of "AI brain fry" – CBS News

Enhance or Eliminate? How AI Will Likely Change These Jobs – Harvard Business School

FAQs about how AI affects PR in 2026 - Muckrack

AI Isn’t Coming for Everyone’s Job – The Atlantic

Amazon Admits Extensive AI Use Is Wreaking Havoc on Its Core Business – Futurist  

Generative AI changes how much time developers spend on coding and project management – MIT Management  

Are AI productivity gains fueled by delivery pressure? - Ruslan Osipov 

Tech Has Never Caused a Job Apocalypse. Don’t Bet on It Now. - Wall Street Journal  

A.I. Isn’t Coming for Every White-Collar Job. At Least Not Yet. - New York Times

The hottest job in tech pays $775,000 and has nothing to do with coding – Business Insider 

What AI Executives Tell Their Own Kids About the Jobs of the Future - Wall Street Journal

Why the AI jobs panic is misplaced - Washington Post

America isn’t ready for what AI will do to jobs – The Atlantic

How to Stay Sane in the AI Skills Race – Wall Street Journal  

Building AI brains for blue-collar jobs – Axios

Job Applicants Sue to Open ‘Black Box’ of A.I. Hiring Decisions – New York Times

Trump team touts a coming economic revolution as voters fear job losses – Washington Post

How Americans are using AI at work, according to a new Gallup poll – Associated Press

Mass Hysteria. Thousands of Jobs Lost. Just How Bad Is It Going to Get? – New York Times

Arkansas attorney resigns after using AI to assist in case work – THV 11 

I don't know if my job will still exist in ten years – Sean Geodecke 

In a jobs apocalypse, look to ‘AI-proof’ skilled trades, career experts say – CNBC

AI isn't taking people's jobs. Here's what's really happening – Quartz

AI & Particle Physics

Researchers are turning artificial intelligence loose on particle physics. They aren’t simply asking AI to comb through accelerator data to confirm existing theories. They’re asking AI to point the way toward theories that they’ve never imagined. By asking AI to flag anomalies in the data, researchers hope to find their way to “new physics” that extends the Standard Model. AI might not solve the mysteries of the universe outright, but it could change how we search for answers. -IEEE

AI definitions: Reinforcement Learning 

Reinforcement Learning Rather than being given specific goals, the AI is deployed into an environment where it can train with minimal feedback. This trial-and-error approach involves adjusting weights until high-reward outcomes are achieved. Desirable behaviors are rewarded, and undesirable behaviors are punished. It is similar to a person learning how to work through levels of a video game, searching for an effective strategy. This type of machine learning sits somewhere in between supervised (by humans) and unsupervised learning. Reinforcement learning is used in video game development and has helped robots adapt to new environments.  

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23 Articles about AI & Teaching

Adapting to a New World: Teachers on How A.I. Is Reshaping the Classroom - New York Times

In some classrooms, teachers ask: Can AI teach students to write better? – Washington Post

These Tools Say They Can Spot A.I. Fakes. Do They Really Work? – New York Times 

College students, professors are making their own AI rules. They don't always agree – KPBS  

Teens Are Using AI-Fueled ‘Slander Pages’ to Mock Their Teachers - Wired

China’s Parents Are Outsourcing the Homework Grind to A.I. - The New York Times 

What AI Is Teaching Us About Humanities Education – The Dispatch  

Will Agentic AI Break Higher Education? – Chronicle of Higher Ed

‘A.I. Literacy’ Is Trending in Schools. Here’s Why. - The New York Times

Agentic AI Can Complete Whole Courses for Students. Now What? – Inside Higher Ed

The Lesson of A.I. Literacy Class: Don’t Let the Chatbot Think for You - The New York Times

In some classrooms, teachers ask: Can AI teach students to write better? - Washington Post 

I’m Not Worried AI Helps My Students Cheat. I’m Worried How It Makes Them Feel - EdWeek

My students compared my writing against ChatGPT – and they all preferred the AI – The Independent

AI Detection Pushed my Students to use AI – Chronicle of Higher Ed

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

The Solution to AI Cheating Is Within Our Grasp - Chronicle of Higher Ed

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

More Teachers Are Using AI in Their Classrooms. Here’s Why - EdWeek

To Solve the Student-Attention Problem, Professors Turn to Pencils and Paper - Chronicle of Higher Ed

A veteran teacher explains how to use AI in the classroom the right way – Scientific American

California schools debate how much AI belongs in classrooms - Ed Source

This MIT prof says we don't know enough about AI to teach it - KJZZ

AI Definitions: Unsupervised Training

Unsupervised Training - Just as children mostly learn to explore their world on their own, without the need for too much instruction, in this type of AI training, the AI is turned loose on raw data without a human first labeling the data. Instead of the AI being told what to look for, it learns to recognize and cluster data possessing similar features. This can reveal hidden groups, links, and patterns within the data and is really helpful when the user cannot describe the thing they are looking for—such as a new type of cyberattack. Not as expensive as supervised learning, it can work in real-time but is also less accurate.

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