Early 2026’s Non-Gigantic Problems with Artificial Intelligence – How Bad Are They?

These are what I have found over the past ten weeks.  As you will see, some have human-abuse components and some do not, though all are inherent to AI’s condition and proliferation.

We learned that we can expect “Meta to suspend teens’ access to AI characters amid safety overhaul” (Michael Sinkewicz, Fox Business, January 23^rd).  This was a stronger reaction to a problem I documented recently, on which “Meta previewed a new safety measure in October that would allow parents to disable their teenagers’ private chats with AI characters”;  now, “the tool would let parents block specific AI characters and look at the broad topics their teens were discussing with chatbots and Meta’s AI assistant, without completely turning off AI access.”  They will permit things that if in a movie would not cause it to get a rating stronger than PG-13.

“How Bad Are A.I. Delusions?  We Asked People Treating Them” (Jennifer Valentino-DeVries and Kashmir Hill, The New York Times, January 26^th).  The topic here is not misbeliefs within AI, but those it has seemed to induce in users.  Examples here were someone, who after getting ChatGPT’s counsel on “a major purchase,” thought “businesses were colluding to have her investigated by the government”; one who “came to believe that a romantic crush was sending her secret spiritual messages”; and a person who “thought he had stumbled onto a world-changing invention.”  Only the first is clearly psychosis, but all are undesirable.  That the chatbots were clearly to blame is debatable, but even disregarding their statements encouraging suicide or other self-harm, which were still happening, they clearly are bad influences, made harder to deal with by our lack of knowledge of just how they affect human cognition.

“These Tools Say They Can Spot A.I. Fakes.  Do They Really Work?” (Stuart A. Thompson, The New York Times, February 25^th).  We hope they do, but what does the author say?  “More than a dozen online tools claim they can tell the difference between what’s real and what’s A.I. by looking for hidden watermarks, composition errors and other digital clues,” but “the reality is more mixed, according to a battery of tests conducted by The New York Times (italics mine).”  Sadly, “they were not accurate enough to offer users complete confidence.”  Three and four of 12 products failed to identify two different pictures of two people, created by Grok and ChatGPT and including the latter product not recognizing its own work, as synthetic, and a higher share choked on videos.  While a camera-taken photograph of a plant was called real by all 12, adding AI content to another one precipitated four correct responses of “edited,” with six saying “real” and two saying it was completely artificial.  We need work here, and I expect we will get it.

Some timely advice is “A Word to the Wise:  Don’t Trust A.I. to File Your Taxes” (Thompson and the New York Times again, March 5^th).  The four products that newspaper’s staff assessed consistently botched “eight fictional tax situations… even when provided with all the necessary materials.”  The problem is that while “traditional tax software like TurboTax is procedural, following ‘if-then’ logic built for mathematical precision,” “large language models, by contrast, are prediction engines” which may misguess, even in a situation where no guessing is required.  Not the tool for this job, at least not now; “Just don’t, whatever you do, use it to file your taxes.”

On the technical side, we saw as “Meta Delays Rollout of New A.I. Model After Performance Concerns” (Eli Tan, The New York Times, March 12^th).  Two unnamed inside sources said while the new product “outperformed Meta’s previous A.I. model and did better than Google’s Gemini 2.5 model from March,” “it has not performed as strongly as Gemini 3.0 from November.”  That meant it was delayed from the current month until at least May.  Not as long a postponement as we have seen in this industry, but it could be bad.

It should be no shock that a “Cascade of A.I. Fakes About War With Iran Causes Chaos Online” (Stuart A. Thompson and Alexander Cardia, still in the Times, March 13^th).  “The videos – showing huge explosions that never happened, decimated city streets that were never attacked or troops protesting the war who do not exist – have added a chaotic and confusing layer to the conflict online.”  In my lifetime, we have gone from the first robustly filmed and broadcast television war to the first bogus-video one.  Improving the AI-detection software above will minimize it, but for now, with more complex images and moving pictures being the least confirmable as genuine, we can’t trust any of it.

If Meta thought it was having a bad month with its product delay, it got worse, as “Meta ordered to pay $375M after jury finds platform enabled child predators in landmark New Mexico case” (Jasmine Baehr, Fox Business, March 24^th).  This outcome was repeatable, as Meta was found to have “violated state law by misleading users about the safety of its platforms and allegedly enabling child sexual exploitation” by “failing to protect children from predators.”  That worked out to “$5,000 per violation,” meaning that there were 75,000 of those.  I hope the number of actual victims, in a state of 2.1 million, was nowhere near that high.  As a sour cherry on top of that, per “Meta and YouTube Found Negligent in Landmark Social Media Addiction Case” (Cecilia Kang, Ryan Mac and Eli Tan, The New York Times, March 25^th), those companies “harmed a young user with design features that were addictive and led to her mental health distress, a jury found…, a landmark decision that could open social media companies to more lawsuits over users’ well-being.” 

Given that these are the worst short-range things I could find about AI in just over two months, it is not doing badly.  The issues here, except for filing taxes with it which should remain a no-no, can all be handled effectively – and I believe they will be.  If not yet world-beating, artificial intelligence is getting better at doing what it can be expected to accomplish.