Who creates better memes—humans or AI?

Researchers in the EU found:

  • When humans got help from an AI, there were more ideas produced with less work, but the quality wasn’t better.  

  • AI memes did better than human-only collaborative creations though the top-performing memes were human-created

The researchers concluded: “These findings highlight the complexities of human-AI collaboration in creative tasks. While AI can boost productivity and create content that appeals to a broad audience, human creativity remains crucial for content that connects on a deeper level.” 

Read more about the research

Imagineering

Imagine yourself as reaching into your mind and one by one removing your worries. A small child possesses an imaginative skill superior to that of adults. A child responds to the game of kissing away a hurt or throwing away a fear. This simple process works for the child because in his mind he believes that that is actually the end of it. The dramatic act is a fact for him and so it proves to be the end of the matter. Visualize your fears being drained out of your mind and the visualization will in due course be actualized.  

Imagineation is a source of fear, but imagination may also be the cure of fear. “Imagineering” is the use of mental images to build factual results, and it is an astonishingly effective procedure. However, it is not enough to empty the mind, for the mind will not long remain empty. It must be occupied by something.  It cannot continue in a stat of vacuum. Therefore, upon emptying the mind, practice refilling it. Fill it with thought of faith, hope, courage, expectancy.

A half-dozen times each day crowd your mind with such thoughts as those until the mind is overflowing with them. In due course these thoughts of faith will crowd out worry. Day by day, as you fill your mind with faith, there will ultimately be no room left for fear.  

Norman Vincent Peale, The Power of Positive Thinking

Why Most Companies Shouldn’t Have an AI Strategy

Studies show that most organizations are immature when it comes to AI. By that, I mean that throughout the ranks—from the top executives through the rank and file—there is little knowledge of, and experience with, AI and its capabilities, and a reluctance to embrace data-assisted decision-making. All of this will mean any AI strategy will be misguided and inexecutable.  If you are the leadership team and you aren’t familiar with AI, how are you going to build a strategy for AI? You can’t. -Wall Street Journal

Lax AI Security in Schools

The implementation of AI surveillance tools has surged since the COVID-19 pandemic. A recent investigation revealed that reporters from The Seattle Times and Associated Press inadvertently accessed nearly 3,500 sensitive student documents due to inadequate security measures surrounding the district's surveillance technology. These documents included personal writings about depression, bullying, and even LGBTQ+ struggles — information that should have remained confidential. -Read more at Mic

Underlying Emptiness

Think of the person (who) loses a job or a girlfriend and then finds himself in despair. The real cause of the despair is not the man’s loss of the job or the girlfriend. What the loss of the job or girlfriend really reveal is that the person was in despair all along, that his identity was built on something too fragile to be the basis of selfhood. When this fragile basis for identity is shattered, the self’s underlying emptiness was revealed.

C. Stephen Evans, Kierkegaard: An Introduction

AI Definitions: Convolutional neural networks

Convolutional neural networks (CNNs or ConvNet) – These deep learning artificial neural networks, often used in computer vision for object recognition, are trained on thousands of images—and even then, they often fail when they encounter the same objects under new lighting conditions or from a different angle. CNNs were first introduced in 1989 by NYU professor Yann LeCun and have been used with autonomous vehicles and security camera systems.

More AI definitions here.

The Paradox of Emotions

CS Lewis wrote, “A desire (or emotion) is turned not to itself but to its object. Not only that, but it owes all its character to its object. It is the object which makes the desire harsh or sweet, coarse or choice, ‘high’ or ‘low.’ It is the object that makes the desire itself desirable or hateful.”

In other words, if you want to love your wife then concentrate, not on love, but on her. Likewise, if you wish more faith in God, do not concentrate on faith. Focus on God. 

Stephen Goforth

 

The power of sibling rivalry­

Sibling rivalry can be a year-round tradition for some families. Researchers at the University of Missouri followed nearly 150 pairs of siblings for a year and found their conflict fell into two overall categories:

1. Conflicts about shared resources and responsibilities that focused on equality and fairness, like whose turn it was to empty the dishwasher or, use the computer or ride in the front seat of the car. These siblings were more likely to become depressed.  

2. Meanwhile, those who argued over privacy and personal space, such as borrowing clothes without asking or entering a room without permission, were more likely to be anxious and have low self-esteem. The most vulnerable for this twist were younger siblings.

The researchers say how these preteens and teens reacted to the conflict had to do with what they believed was at stake. Details about this study are in the journal Child Development.  

Stephen Goforth

Turning AI innovations into measurable business outcomes

A media company using generative AI for content creation must connect the project to business goals like increasing audience engagement or reducing production costs. Without this clear focus, the technology might produce content, but it may not resonate with the target audience or contribute to the company’s bottom line.  The successful integration of generative AI is not just about technology but about people. Collaboration between technical teams, business leaders, and end users is essential to ensure that AI projects deliver practical value. Generative AI is not just about creating new things but about creating value. - Mike Zhou writing in TechTalks

23 Recent Articles about AI Fakes & Deepfakes

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

Sony Music says over 75,000 songs in battle against AI deepfakes – Gizmodo 

‘Hi mom, it’s me’: voice cloning services demand stronger voice deepfake detection – BioMetricUpdate

Dark Side of GenAI: Ethical Dilemmas Threatening Our Future – Analytics Insight  

AI Search Has A Citation Problem – Columbia Journalism Review 

Celine Dion warns fans to beware of fake, AI-generated songs appearing online – CNN

YouTubers are being scammed with AI-generated deepfake videos – PC World

AI can steal your voice, and there's not much you can do about it – NBC News

Deepfakes, cash and crypto: how call centre scammers duped 6,000 people – The Guardian

I was so freaked out by talking to this AI that I had to leave – PC World

Chinese AI Video Generators Unleash a Flood of New Nonconsensual Porn – 404 Media

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

Fake Video of Trump and Musk Appears on TVs at Housing Agency – New York Times

A ‘True Crime’ Documentary Series Has Millions of Views. The Murders Are All AI-Generated – 404 Media

Scarlett Johansson warns of 'AI misuse' after fake Kanye video – BBC

AI Slop of Musk and Trump on TikTok Racks Up 700 Million Views – 404 Media

Schools face a new threat: "nudify" sites that use AI to create realistic, revealing images of classmates – CBS News

AI enters Congress: Sexually explicit deepfakes target women lawmakers – 19th News

AI nude photo investigation uncovers twice as many likely victims at Lancaster Country Day – WGAL  

Deepfakes didn’t disrupt the election, but they’re changing our relationship with reality – The Hill

Scarlett Johansson Slams AI Video of Celebrities Fighting Kanye West’s Antisemitism: ‘We Must Call Out the Misuse of AI, No Matter Its Messaging’ – Variety

How to Tell If Your Job Candidate Is an AI Deepfake – INC

Judge fines lawyers in Walmart lawsuit over fake, AI-generated cases – Reuters

What makes data real?

The beautiful images of galaxies, nebulas, and other astronomical objects produced by radio telescopes have been processed several times and colorized before we see them, but we still consider these images to be real and not synthetic.

So, what makes data real? Real data are data that have been generated by a process that is appropriately connected to real phenomena, where the terms “appropriately connected” and “real” are defined by the relevant research community. For example, we can say that an MRI image of the brain is real because it has been produced by a process that is appropriately connected to a real brain. However, sometimes MRI machines produce images that radiologists classify as (unreal) artifacts because they have been produced, for example, by the scanner itself or by the patient’s movements.

Referring to data as “real” does not necessarily entail a commitment to a physicalist notion of reality. Data could be about physical, chemical, biological, social, or psychological phenomena. For example, we would consider data concerning biodiversity, stock prices, suicidal ideation, or cultural taboos to be real data, even though the phenomena they refer to cannot be equated with specific physical objects. The data could be about things we cannot directly observe, such as electrons, quarks, entropy, or dark matter. What matters most is that the relevant scientific community considers the data to be about real phenomena.

Read more at the PNAS (Proceedings of the National Academy of Sciences of the United States of America)