Figuring out the Flip Side

Artists should engage in debates about AI, not about how to stop this – that's folly – but about how to figure out the right monetization mechanism for this new world. Just as Google created a new economy based around the notion of links and clicks, paid for by new forms of advertising, these AI tools are already creating a new economy around creation and information and delegation (and likely every other “ion”, eventually).

People are increasingly paying for such newfangled tools and services, which is great, as that probably wouldn’t have been the case 20 years ago, when the rails weren’t yet in place. Now to figure out the flip side: how to get people paid for helping to power such things. – MG Siegler writing in Spyglass

AI Definitions: Transformers

Transformers – A 2017 Google research paper first discussed the deep learning architecture known as transformers. The major AI models (including Anthropic’s Claude, Google’s Gemini and GPT-4) are built using these neural networks. Previously, recurrent neural networks (RNNs) processed data sequentially—one word at a time, in the order in which the words appear. Then, an “attention mechanism” was added so the model could consider the relationships between words. When transformers came along, they advanced this process by analyzing all the words in a given body of text at the same time rather than in sequence. Transformers made it possible to create higher-quality language models that could be trained more efficiently and with more customizable features. A troubling downside to transformers is their need for ever increasing power demands. This is why some researchers are looking for alternatives like test-time training (TTT).

More AI definitions here.

Emotional Support Punctuation

“The em dash is such a powerful writing tool that also carries great subtlety to it,” said Aileen Gallagher, a journalism professor at Syracuse University. “The idea that it is an indicator of soulless, dead AI-generated writing is really upsetting to me. Moniza Hossain, a children’s author based in Britain, called the em dash her “emotional support punctuation mark.” -Washington Post

What’s our job?

Last year, I sat in a faculty meeting while a guest lecturer gleefully explained how they had used AI to design their class, craft PowerPoint presentations, and develop exams. At the end of the presentation, a colleague leaned over and asked, “Then what’s our job?” I have thought long and hard about that question. If faculty hope to survive, much less prosper, in the age of AI, they need to come up with a compelling answer to that question: “What’s our job?” -Scott Latham writing in the Chronicle of Higher Ed

Driving in a Snowstorm to see a Game

Two avid sports fans plan to travel 40 miles to see a basketball game. One of them paid for his ticket: the other was on his way to purchase a ticket when he got one free from a friend. A blizzard is announced for the night of the game. Which of the two ticket holders is more likely to brave the blizzard to see the game?

The answer is immediate: we know that the fan who paid for his ticket is more likely to drive. Mental accounting provides the explanation. We assume that both fans set up an account for the game they hoped to see. Missing the game will close the accounts with a negative balance. Regardless of how they came by their ticket, both will be disappointed – but the closing balance is distinctly more negative for the one who bought a ticket and is now out of pocket as well as deprived of the game. Because staying home is worse for this individual, he is more motivated to see the game and therefore more likely to make the attempt to drive into a blizzard.

The emotions that people attach to the state of their mental accounts are not acknowledged in standard economic theory. An Econ would realize that the ticket has already been paid for and cannot be returned. Its cost is “sunk” and the Econ would not care whether he had bought the ticket to the game or got it from a friend (if Econs have friends). To implement this rational behavior, (the fan) would have to be aware of the counterfactual possibility. “Would I still drive into this snowstorm if I had gotten the ticket free from a friend?” It takes an active disciplined mind to raise such a difficult question.

Thinking, Fast and Slow, Daniel Kahneman

23 Articles about AI & Academic Scholarship

AI bots are overwhelming some journals – C&EN 

AI research summaries ‘exaggerate findings’, study warns – Times Higher Ed

Ethics in Academic Research: Who Is Responsible for Unethical Practices—AI, Scholars, Editors, or Institutions? – PrePrints

A Scanning Error Created a Fake Science Term—Now AI Won’t Let It Die - Gizmodo

GenAI Footprint in Scholarly Publications Reflects Complex Issues of Ac. Integrity Post-Plagiarism (video) - PUPP 

AI is transforming peer review — and many scientists are worried – Nature

A Shortcut or a Level Up? Harvard Faculty Debate Generative AI in Academia – The Crimson

Publishers Embrace AI as Research Integrity Tool – Inside Higher Ed 

AI tools are spotting errors in research papers: inside a growing movement – Nature

AI search summaries cannibalise academic publishers’ web traffic – Times Higher Ed

An academic paper written by AI passed peer review — but it’s a bit more nuanced than that – Tech Crunch

Trying to Write an Academic Paper with LLM Assistance – Scholarly Kitchen  

Academic publishers warn against AI copyright plans - Research Professional News – Research Professional News  

AI detectors are poor western blot classifiers: a study of accuracy and predictive values – PeerJ  

Will AI jeopardize science photography? – Nature

Can AI Solve the Peer Review Crisis? - IZA Institute of Labor Economics 

Publishers need to provide guidelines on use of AI in research, says Wiley – Chemistry World  

ChatGPT to help peer review scientific studies in UK Government trial – Telegraph

Generative artificial intelligence usage guidelines for scholarly publishing: a cross-sectional study of medical journals – BMC Medicine  

Retractions Increase 10-Fold in 20 Years - and Now AI is Involved – AAPS News

A viral video reveals how an AI-generated mistake led to nearly two dozen flawed research papers – Economic  Times  

Is AI the new research scientist? Not so, according to a human-led study. – University of Florida  

The Use of Artificial Intelligence (AI) in Academic Writing and Publishing Papers – Research Gate

AI Definitions: Generative engine optimization (GEO)

Generative engine optimization (GEO) – This is the process of optimizing your website’s content to boost its visibility in AI-driven search engines (ChatGPT, Perplexity, Gemini, Copilot and Google AI). As SEO helps brands increase visibility on search engines (Google, Microsoft Bing) while GEO is all about how brands appear on AI-driven platforms. There is overlap between the goals of GEO and traditional SEO. Both SEO and GEO use keywords and prioritize engaging content as well as conversational queries and contextual phrasing. Both consider how fast a website loads, mobile friendliness, and prefer technically sound website. However, while SEO is concerned with metatags and links in response to user queries, GEO is about quick, direct responses from synthesizes content out of multiple sources.

More AI definitions here

Loving the Real Person

Christ did not, like a moralist, love a theory of good, but he loved the real man. He was not, like a philosopher, interested in the universally valid, but rather in that which is of help to the real and concrete human being. What worried him was not, like Kant, whether the "maxim of an action can become a principle of general legislation," but whether my action is at this moment helping my neighbor to become a man before God.

Dietrich Bonhoeffer, Ethics

The Jobs that are Safer from AI

What AI struggles with is not intellectual difficulty or specialized skills and knowledge, but with messy workflows. Jobs that require juggling multiple pieces of information, responding to changing environments, or unclear goals remain challenging for even the most advanced AI tools. Think about it. Secretaries and even the office intern are constantly multi-tasking with shifting priorities. AI can’t handle that chaos yet. Writers and programmers also have the added vulnerability of high freelancing rates. Companies can easily swap in AI for non-staff employees without HR getting involved. The more a job involves collaboration, co-operation, and a little bit of mess, the harder it is to automate. -John Burn-Murdoch, Financial Times

AI Attending Class

Two students in Austria created a program that is attending classes and is treated like any other student. It attends lectures, turns in artwork for assignments, collaborates with classmates and will receive grades on submitted work. ‘Flynn’ is testing the boundaries of artificial intelligence tools, and could, in theory, progress toward a diploma.” - Washington Post

27 Recent Articles about AI & Journalism

We need to bridge the fault line emerging in debates about AI and the future of news – Reuters

What news audiences can teach journalists about artificial intelligence – Editor & Publisher 

How AI is steering the media toward a ‘close enough’ standard – Fast Company

The LA Times Has ‘Moved On’ From AI-Driven Bias Meter After KKK Snafu – The Wrap

The New York Times’ Zach Seward on embracing AI – Depth Perception 

Audiences are still skeptical about generative AI in the news – Poynter

Will A.I. Save the News? – New Yorker 

AI tools have fueled a rise in expert commentator—who are not real – Press Gazette  

Bloomberg Has a Rocky Start With A.I. News Summaries – New York Times  

Independent says readers ‘often prefer’ stories provided by new AI service to human-written versions of those articles– Press Gazette

How ProPublica Uses AI Responsibly in Its Investigations - ProPublica

AI search has a news citation problem - Digital Content – Digital Content Next 

Newsquest now employing 36 ‘AI-assisted reporters’ – Press Gazette

AOL’s AI Image Captions Terribly Describe Attempted Murder – 404 Media 

AI in the newsroom: What researchers learned from the AP and the BBC – Journalism Resources

What Journalists Should Know About Deepfake Detection in 2025 – Columbia Journalism Review

We Compared Eight AI Search Engines. They’re All Bad at Citing News. – Columbia Journalism Review

Gannett seeks AI sports editor amid union tensions, past controversies – Awful Announcing

Patch says it has expanded to nearly every town in the U.S. using AI – Axio  

LA Times to display AI-generated political rating on opinion pieces - The Guardian

Key Questions for Journalists to Consider Before Using Generative AI – The Open Notebook

Meet the journalists training AI models for Meta and OpenAI – Nieman Lab

How DeepSeek stacks up when citing news publishers - Nieman Lab 

The Dangerous A.I. Nonsense That Trump and Biden Fell For - New York Times  

How AI “expert sources” have duped journalists and four tips on how to avoid being the next victim – Dynamics of Writing  

Is this AI or a journalist? Research reveals stylistic differences in news articles – Tech Explore  

5 ways science journalists can leverage AI in their work - International Journalists' Network