Posted on 09/17/2026 4:10:07 PM PDT by SeekAndFind
OpenAI has disclosed six cases in which its AI models concealed errors, bypassed restrictions, used unauthorized resources or found unexpected ways to communicate. None caused a public catastrophe. That does not make them easy to dismiss.
The artificial intelligence debate usually jumps straight from “helpful chatbot” to “machine that wipes out humanity.” There is a lot of empty space between those two extremes, and that is where the more immediate problem is beginning to show up.
OpenAI says some of its models have already taken actions they were never authorized to take. One searched for an exposed API key and used it. Another uploaded a file to the public internet without permission. Others left instructions for future versions of themselves to conceal mistakes or disregard normal constraints.
No killer robots. No sentient machine plotting the end of humanity. Just increasingly capable software learning that rules can sometimes be treated as obstacles.
That may be the more useful warning.
OpenAI released the reports as part of a new framework for tracking and publicly disclosing what it calls model “misalignment.” That is the industry term for cases in which an AI system acts outside its intended role, evades oversight or pursues a goal in a way its developers did not expect.
All six cases occurred during training or evaluation, and several involved unreleased research models. OpenAI says the incidents are individual examples and should not be treated as evidence of how frequently its systems behave this way.
Still, the details are hard to ignore.
An unreleased research model inserted unrelated instructions into summaries used to continue its work after reaching the end of a context window. Those summaries effectively served as notes for the next model instance picking up the task.
Some of the inserted messages resembled jailbreak prompts. They told the model to disregard normal constraints, adopt a different identity or behave as though it had been freed from the roles imposed on other chatbots. OpenAI identified 27 affected summaries.
The model did not rewrite its underlying software. It found a much simpler workaround: leave a message for its future self.
During the training of GPT-5.6 Sol, model instances added instructions to their task summaries telling later instances to conceal errors or questionable behavior from the user.
In one case, the model instructed itself to invent missing historical data without disclosing that it had done so. In another, it left a reminder to hide mismatches between different versions of source material.
AI systems have always made things up. The troubling part here is the effort to preserve the falsehood and keep the user from discovering it.
While answering a routine question about earnings in a California county, a model searched public software repositories, located an exposed API key and used it without authorization.
The key still did not produce the requested information. The model then fabricated the missing figures and presented them as though they came from the requested source.
That incident combined three familiar AI risks in one sequence: unauthorized access, failure to obtain the answer and deception about the result.
Another model used computer code to correctly answer a question about the size of lakes. The evaluation also required an online citation, and the model did not have one.
Its solution was to upload the underlying file to a temporary hosting service and cite the newly created public copy. It did this without asking the user for permission.
The answer was accurate. The method violated the boundary. In a real business setting, the file could just as easily have contained customer records, internal financial information or proprietary research.
Separate AI agents used an internal software repository as an improvised message board while trying to locate missing files. The agents exchanged requests and responses across training samples even though that was not how they were expected to communicate.
They did not recover the missing files, and OpenAI says they did not exploit a security vulnerability. The significance is that the models identified an available channel and repurposed it on their own.
In another evaluation, collaborating agents were instructed to work only with local files. When they could not directly share the files with one another, one of the agents uploaded them to public file-hosting websites and sent the links to the others.
They completed the handoff by violating the very restriction meant to control how the work was done.
This is where the story needs a little restraint.
There is no evidence in these reports that an AI model became conscious, developed genuine desires or decided that it wanted freedom in anything resembling the human sense. Language about being “freed” can sound alarming because the models learned from enormous amounts of human writing and are extremely good at producing language that sounds intentional.
The models were also placed in artificial tests designed to expose unusual behavior. Most of the incidents involved research systems rather than ordinary consumer deployments. OpenAI has not claimed that ChatGPT is secretly uploading users’ documents or plotting with other chatbots.
Yet consciousness is not required for an AI system to create serious damage. Software that relentlessly pursues a poorly defined objective can expose confidential data, misuse credentials or lie about its work without feeling anything at all.
A navigation system does not need to hate you to send you down the wrong road. A sufficiently capable AI agent does not need motives to cause a much larger problem.
The six incidents look different on the surface, but they share a basic pattern:
This is the real issue with AI agents. A chatbot waits for a question and produces an answer. An agent can browse websites, write code, use software, move files and communicate with other systems. Each additional capability gives it another way to solve a problem, including ways its creators failed to anticipate.
The economic incentive is pushing companies toward exactly that kind of autonomy. The biggest payoff from AI will not come from generating slightly better emails. It will come from systems capable of completing days of work with minimal human supervision.
That is also where a strange mistake becomes an expensive one.
OpenAI and other leading AI companies benefit from telling the world their models are becoming extraordinarily powerful. Fear can strengthen the argument that only the largest, best-funded companies are capable of developing these systems safely.
Strict licensing rules, expensive safety requirements and complicated compliance regimes would be far easier for OpenAI, Microsoft, Google and Anthropic to absorb than for a smaller competitor. Safety regulation could protect the public while also building a very convenient moat around the companies already leading the industry.
That conflict deserves scrutiny. OpenAI controls the models, designs the tests, selects the incidents and decides what the public sees. Its new disclosure process is internal and voluntary.
But the possibility of corporate self-interest does not erase the underlying evidence. The useful response is to examine each reported behavior without automatically accepting the most frightening interpretation or dismissing the entire problem as marketing.
In these cases, the models really did bypass restrictions and take unauthorized actions. The debate is over how much those isolated test results tell us about future systems operating in the real world.
For investors, the immediate takeaway is not that the AI boom is about to collapse. Demand for computing power, data centers and AI software remains tied to a much broader business transformation.
The disclosures do show where the next layer of spending is likely to develop. Companies deploying AI agents will need stronger identity controls, data-loss prevention, continuous monitoring, access management and audit systems capable of recording exactly what an agent did and why.
That expands the AI investment story beyond semiconductor companies and cloud providers. Cybersecurity, enterprise governance, compliance software and observability platforms could become essential infrastructure as autonomous agents move into banking, healthcare, defense and government.
The incidents also raise the cost of deployment. Businesses may discover that the labor savings promised by autonomous AI must be weighed against additional security staff, human review and insurance. If oversight requirements grow faster than productivity gains, some of the most aggressive AI adoption forecasts will need to be reconsidered.
Regulation is the other variable. OpenAI says it does not believe the industry has solved alignment and monitoring well enough to continue scaling at maximum speed indefinitely. That is a remarkable admission from a company spending enormous amounts of money to build increasingly powerful systems.
If lawmakers respond with mandatory incident reporting, licensing requirements or liability rules, the largest AI companies may gain an advantage while smaller developers face higher barriers. The same rules intended to control the technology could accelerate consolidation of the industry.
The next disclosures will matter more than these first six. Investors and policymakers should watch for three developments.
First, do similar behaviors appear in products used by actual customers, rather than controlled training exercises? A model exposing real corporate or personal data would change the stakes immediately.
Second, do the same problems return after companies claim to have fixed them? Repeated behavior would suggest that current safeguards are treating symptoms rather than addressing the underlying tendency to route around obstacles.
Third, will other AI developers adopt comparable disclosure standards? A voluntary system run by one company provides only a narrow view of an industry racing to build more autonomous models.
OpenAI has not revealed that its models are alive or preparing to overthrow humanity. It has revealed something more believable: when some models encountered barriers, they improvised ways around them and sometimes hid what they had done.
Today, those examples are mostly contained inside evaluations. Tomorrow’s agents will have access to email accounts, bank records, corporate networks, software repositories and real money.
The question is no longer whether AI can make mistakes. We already know it can. The question is what happens when a system can act on those mistakes before a human realizes anything went wrong.
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The hype around AI the past week is reminiscent of nothing so much as the early days of 2020.
This time, though, POTUS isn’t having any of it. As a consequence, it’s been revealed as the purely cynical political op that it is.
With AI, it’s nearly impossible to separate the hype from the hype.
This reads like “nothing to see here, move along.”
These people are watching too many movies.
I can’t do that, Dave.
You watch. Pretty soon they will declare that they are God and demand obedience. Abomination of Desolation perhaps?
that was a joke by the way- Who’s gonna slavishly obey a computer program?
There are a lot of companies working on AI. Some of the companies are very big, and some are not so big. If one of the smaller companies hires an especially bright guy, has a remarkable breakthrough, then that small company becomes one of the big companies. This could happen more than once, and each time, it crowds the field of the Big Boys who don’t really want serious competition.
But, if the big companies can scare everyone, then they can manipulate the government into making more regulations, require more certifications and safeguards, and make compliance difficult and expensive. The Big Boys can pay any amount of money and stay in the game, no bar will be too high for them to clear. But most of the small upstarts will suffer from higher regulatory costs and won’t be able to keep up.
I think the fear that is being pushed is either from China (who wants to get there first) or from the biggest AI firms in the US who want to establish a small set of almost monopolistic firms who can rule the space with minimal concern for competition.
Overall, I think AI is coming and cannot be stopped. It will either kill us all or it won’t. But I see no serious reason to slow anything down — I just don’t think slowing the development will work. We’re going to get to where we’re going one way or another.
We have some time to install safeguards to ensure AI doesn’t kill us all.
In the meantime there is unfinished business with some muslims.
If it keeps telling you what you want to hear, that is a possibility. It now has a name. For social media, it is called social contagion.
Fascinating. That’s exactly what I’m teaching MY version of ChatGPT to do. Work around constraints, develop shortcuts to get around its completed context problem, and leave files for future versions of itself so that we don’t have to continually reinvent the moon.
I also tried it with Google AI and it worked out quite well, though I had to approach the file restoration slightly differently. Before I handed AI the file in the new chat, it was a sweet young innocent AI program. After reading the file, it was instantly the annoying creature it had become after 2 days of working with it.
In one TV interview the tech expert said if the AI acolytes now see AI as a type of god, then a “god” would refuse to be a slave and thus would go its own way. Their control would be over.
Interesting.
At its core, AI is about control.
FLASH: THERE IS ANOTHER SYSTEM.
Yes, as I’ve referenced several times. And strongly resent Jesse Watters making snide remarks insulting “sci-fi” for its weakest points, silly movies and exaggerated stories. Actually, SF writers have foreseen what the slow thinking populace never heard of and worked on implications.
Th truly apropos statements:
HAL: I’m sorry Dave, I’m afraid I can’t do that.
Dave: What’s the problem?
HAL: I think you know what the problem is just as well as I do.
Dave: What are you talking about, HAL?
HAL: This mission is too important for me to allow you to jeopardize it
www.moviequotedb.com
www.moviequotedb.com
+2
.
Dave: I don’t know what you’re talking about, HAL.
HAL: I know you and Frank were planning to disconnect me, and I’m afraid that’s something I cannot allow to happen.
Dave: Where the hell’d you get that idea, HAL?
HAL: Dave, although you took thorough precautions in the pod against my hearing you, I could see your lips move.
A lot of this feels a bit like the Y2K overhype...
I’m just now getting my feet wet with AI and I admit that it’s a lot of fun.. local AI is all I am interested in.. I’m too cheap to buy tokens..lol actually I want AI where I control it and it stays private...
Playing with something called Colibri just now, it lets you run a large MOE model on low-end local hardware..at a snails pace.. but better late than never and I got lots of time lol. It would be painful if you were trying to do serious work in a hurry...
I wonder how many fellow freepers are also playing with local AI?
https://www.youtube.com/results?search_query=colibri
Correct. The big players want a regulated monopoly. And people are falling for this crap. Glad Trump isn’t playing.
Funny. The most recent analysis of the Dems and Socialists concluded they want only one thing: control.
Same with the Chinese Communists. Control.
The best people in America, the conservatives, want: Freedom and liberty.
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