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]]>How can both be true?
In the latest state of AI usage report, OpenAI statistics from users adopting the technology to help with writing, research, programming and analysis show:
These OpenAI claims are based on studying power users from one million enterprise and educational customers. A power user, by definition, sends a minimum of 75 messages weekly and uses 3 or more AI tools monthly. These may include chat, browsing, coding, data analysis, and workflow integration.
According to OpenAI, ChatGPT has 800 million weekly users currently. A recently published report lists the following key findings:
OpenAI claims that not only is ChatGPT being used more often, but its growing suite of AI applications is being applied to increasingly sophisticated organizational tasks in industry sectors such as information technology (IT), healthcare, manufacturing, professional services and finance. The biggest growth is happening in Australia, Brazil, the Netherlands, France and Japan.
What the statistics don’t reveal is the quality of outputs from increased OpenAI use.
A 2024 Journal of Human-Computer Interaction article that reviewed 485 studies and cited 33 empirical studies identified key concerns related to accuracy and reliability, and discussed the negative impacts of AI use and its impact on critical thinking and problem-solving.
It should be noted that the article was based on earlier releases of ChatGPT, not ChatGPT4 and 5.
The negative impact of AI on adolescent cognitive development is the subject of a number of recent articles and studies. According to a recent Pew Research study, 64% of U.S. teens use chatbots, with 3 in 10 between ages 13 and 17 using the technology daily. The Pew study notes that 97% of teenagers use the Internet daily, with 40% describing themselves as “almost constantly online.”
In a Center for Democracy and Technology (CDT) 2025 survey of more than 1,000 students, teachers and parents, it reports that 86% of students and 85% of teachers are using AI tools. These are high percentage levels of engagement with a technology that poses unique challenges, particularly for young people. Why single them out?
The use of AI tools like ChatGPT or OpenAI’s Dall-E has a greater impact on adolescents because their brains are still forming. Along with excessive screentime and access to social media, generative AI like ChatGPT can negatively impact brain plasticity, cognitive development, critical thinking, mental health and sleep.
A JAMA Pediatrics article published on November 18, 2025, lists the potential harms to adolescent minds and bodies that AI can cause. These include:
With the AI genie already out of the bottle, what needs to be done to ensure that adolescent minds can handle the ubiquity of this technology impacting their everyday lives?
Researchers into adolescent usage of AI are recognizing the need to establish guardrails specific to protecting young people. For example:
If you cannot take away overwhelming Internet usage, as the aforementioned CDT data indicates is happening, in the absence of shutting off the medium to youth, it becomes necessary to consider the messages being sent by the technology to ensure malleable growing minds and bodies aren’t negatively impacted.
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]]>DeepSeek provided other surprises for the AI crowd including Elon Musk’s xAI, Mark Zuckerberg’s Meta AI, Google’s Gemini, Amazon’s Anthropic and Microsoft-backed OpenAI. The initial reaction to DeepSeek’s revelation was felt in stock prices for these companies with sharp declines.
What other attributes of the DeepSeek reveal are of interest?
The comparison between DeepSeek, OpenAI and the other AI players is stark. For example, OpenAI has 4,500 employees. DeepSeek has 200. OpenAI has raised over $6.6 billion and spends more than $100 million to train new iterations of ChatGPT. DeepSeek spent $5 million to build and launch its AI.
Diamandis describes the results as “staggering” offering this summary:
By making DeepSeeks’ AI open source, it is opening the application to allow researchers and developers to build on it. This is democratizing AI and should lead to faster development. Open source means DeepSeek’s AI is transparent and can rely on the global community to help make improvements and corrections to it, let alone build niche applications for it. Meanwhile, compared to its Silicon Valley competitors, DeepSeek will remain cheap with application development on it attractive to small and medium-sized businesses that now can find reasons to jump on the AI bandwagon.
Diamandis welcomes the democratizing of AI stating:
For NVIDIA it means retooling rather than relying on AI chips at $30,000 a pop to prop up its earnings. For OpenAI, Meta, Google, Microsoft, Amazon, and xAI it means going back to the drawing board if they want to compete with their more agile, smaller Chinese competitor. Those investors in Silicon Valley AI companies will wonder if they will soon be the victims of an AI bubble just like the dot-com one that burst in the late 1990s.
Diamandis sees the arrival of DeepSeek as a significant course change for AI describing it as “one of those moments we’ll look back on as an inflection point, like when PCs disrupted mainframes or cloud computing changed everything.” He continues, “The efficiency genie is out of the bottle, and there’s no going back.”
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]]>o1 is a thinking, reasoning, and problem-solving intelligence and represents stage 1 in OpenAI’s pursuit of artificial general intelligence (AGI). An o2, o3, o4, and o5 are to follow. The rate of advancement may accelerate and what will that mean for us? Does this technological development represent a threat or the next stage in technological civilization’s progress? Can we entrust this type of AGI to help us solve challenges like climate change, cure cancer and other diseases, end wars, narrow the knowledge and economic gulf that persists between the Global North and South, colonize the Moon and Mars with or without us, make us and itself immortal, or just itself?
AI isn’t like any previous human technological invention. Most technology can be described as a tool we use. Yuval Noah Harari, historian, philosopher, and a professor at the Hebrew University of Jerusalem, in his latest book “Nexus: A Brief History of Information Networks from the Stone Age to AI,” describes AI as an agent and unlike any other technology humans have invented.
How do tools differ from agents?
Tools vs. Agents
Harari describes AI as a transformative force representing a fundamental shift in our civilization. Its ability to make its own decisions is unlike any previous human invention. Harari also notes that AI can invent on its own and in doing so can speak to us and reshape our culture, politics, and more. Its rapid pace of advancement in the past decade and future iterations like o1 and its successors suggest we will be incapable of predicting what it will become and its transformative potential.
Current AI Large Language Models (LLMs) available for general use from vendors like ChatGPT, Gemini, Meta, Claude, and Grok are nothing like the AGI that will succeed o1. These AGIs will have the means to:
If improperly deployed they could also produce:
The way OpenAI and other big technology companies are pushing AI into the mainstream doesn’t include guardrails while governments struggle to keep up with the speed of the changes this horserace is creating.
So what is needed for AGI to meet human needs in the present and future?
The list includes:
While Open AI’s o1 model and its high IQ score represent an important milestone, as Harari points out, there is an implicit danger when a human invention becomes an agent of its own device and is capable of ignoring its creators as it seeks knowledge and growth for itself. It speaks to a dystopian future that we have seen in science fiction books and movies where an AGI rationalizes that we are the problem.
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]]>Right now the most famous generalized AI tool is ChatGPT, which has learned from studying a global dataset provided by content from the Internet. For those who fear that AI will eventually replace us, I would say from the conversation I had with ChatGPT this morning, you need not be so fearful, at least not yet.
The key to generalized AI understanding the world comes from its exposure to structured or unstructured information. Structured information is what Li developed with her visual dataset to train algorithms to identify objects in pictures. Unstructured information is unlabelled data and comes in multiple forms from printed words to audio files, pictures and video.
ChatGPT uses unstructured information to learn about the world around it. The data used, however, is finite. That is, there is a cutoff date which became abundantly clear to me when I struck up a conversation with OpenAI’s generalized large language model (LLM).
I asked two questions this morning after reading about the controversial firing of Sam Altman, the CEO of OpenAI by the board of directors, and his subsequent hiring by Microsoft, a major OpenAI investor. Subsequently, a rebellion at OpenAI has employees expressing a desire to quit and join their former boss at Microsoft.
Here is my chat with ChatGPT.
My Question: What does ChatGPT think about the removal of Sam Altman as CEO of OpenAI?
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]]>He quotes predictions from the World Economic Forum that almost 25% of all jobs will be disrupted by artificial intelligence (AI) within the next five years.
The consulting firm, PwC estimates AI will add $15.7 trillion to the world economy by 2030. And in another quote from The CEO of Stability AI, Emad Mostaque, he states that “trillion-dollar companies are shifting their whole strategy and focus” to generative AI.
Of course, science fiction authors that write about dystopian futures, often present AI as a much greater threat. It is not just going to disrupt the world of business but also will cause human extinction. But a more realistic take on AI is its impact on businesses including the following fields:
Where else can we find AI in the business world today?
One recommended immediate change for any current business states Diamandis: hire or develop a Chief AI Officer, because without one the business you currently operate or work in may be out of business in five years.
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]]>Notable signatories include Steve Wozniak and Elon Musk. The group wants to stop training in AI laboratories of systems until protocols are developed around a common set of safety guard rails are put in place. The letter was published by the Future of Life Institute (FLI), whose declared mission is to steer transformative technology towards benefiting life and away from extreme large-scale risks.
The letter declares that AI with “human-competitive intelligence” poses a risk and needs to be planned and managed with care. That’s because AI could disseminate misinformation, automate jobs including even fulfilling ones, and inevitably produce non-human minds to “outnumber, outsmart, obsolete and replace us.”
When OpenAI released ChatGPT back in the fall of last year, I tried it. That was OpenAI’s 3.5 release. Since then the company has published ChatGPT-4. And it is the raison d’être and cause for concern that has led to the FLI letter being released calling on “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.” It states that should there be no agreement for a halt, then governments need to step in.
Will six months be enough to come up with a set of shared guard rails? And what should they be?
The FLI letter calls for protocols that ensure the systems “are safe beyond a reasonable doubt.” The call is for all AI developed going forward be safe, accurate, transparent, trustworthy, interpretable, aligned and loyal. It asks that a regulatory body “dedicated to AI oversight” be enacted with “robust auditing” and a “certification ecosystem.” The letter also believes public funding for AI safety should be put in place.
One of the biggest critics of OpenAI has been Musk. He once served on the organization’s board of directors. Musk’s concerns are that the company in its relationship with Microsoft has lost its “virtue.”
I haven’t yet had the opportunity to test ChatGPT-4. The encounter with version 3.5 was spooky enough as can be attested from what I wrote about it back in January of this year. So I can imagine that with the latest enhancements of this version of a large-language modelling AI, we are entering a realm where humans will find ourselves in competition with digital minds that creators like OpenAI may soon find have gone beyond their ability to manage and control.
The FLI letter’s call for a halt is to ensure that “powerful AI systems…be developed only once we are confident that their effects will be positive and their risks will be manageable.”
Think about the splitting of the atom and the invention of the automobile. The first led to the development of the atomic bomb used twice at the end of World War Two with the sword of Damocles today continuing to be held over us with visions of nuclear Armageddon.
And second, the unintended consequences that have led to the climate change crisis of today. Automobiles and particularly the internal combustion engine (ICE) that run them have been significant contributors to the environmental crisis of climate change that we face today.
Could we have halted research on the atomic bomb while facing the threat of Nazi Germany and Japan back in the 1940s? Could America have put a stopper in the atomic bottle and come to a common agreement with the Soviet Union in the post-war to halt all atomic research focused on bombs?
Could we have anticipated the need for guard rails at the birth of the automobile age not knowing that carbon dioxide tailpipe emissions would within a century cause anthropogenic global warming? With guardrails in place would the electric car or another green method of propulsion have prevailed?
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]]>Recently, Ryan Reynolds, the actor and CEO of Mint Mobile, a budget cellular provider, tested ChatGPT to write a commercial for Mint Mobile using his voice. He instructed it to include a joke, a curse word, and a promo the company was working on. He told Fast Company that the results were “mildly terrifying.”
The latest API for ChatGPT-3.5 is used to produce text that is remarkably similar to what humans write. Knowing this I had to try it out. So I asked ChatGPT to take on a subject from a posting I wrote yesterday I said “explain the relationship between atmospheric warming and rising ocean temperatures.” And this is what it wrote within a minute of my query.
“Atmospheric warming, caused by an increase in greenhouse gases in the atmosphere, causes rising ocean temperatures. As the Earth’s atmosphere warms, the oceans absorb about 93% of the excess heat. This causes the temperature of the ocean to rise, which in turn leads to a number of consequences including sea level rise, ocean acidification, and changes in ocean circulation. Additionally, warmer oceans can lead to more intense and frequent storms, such as hurricanes and typhoons.”
That’s a good summary of the issue described in the article I posted yesterday. If Ryan Reynolds says he was blown away by the promo ad ChatGPT produced, I can only reinforce his comment with my own “pretty creepy.”
Microsoft has put money into OpenAI to the tune of $1 billion US in recent years. But now, according to recent reports, it is adding $10 billion to the investment. Why? Because Microsoft has the Bing search engine, its competition for Alphabet’s Google Search. To date, the company has been spectacularly unsuccessful in taking market share away from Google. But incorporating ChatGPT into Bing may be the game changer that can beat Google’s search algorithm.
ChatGPT isn’t an isolated case of an AI capable of human-like conversation. Google has its own technology called LaMDA, a conversation algorithm that understands query requests to produce better results for users of Google Search. Google uses an AI neural network for LaMDA which is capable of delivering sensible responses in human conversations.
But ChatGPT has made a much bigger splash recently because of the implications this technology may have in education and because it is open source which means it’s free. LaMDA is proprietary.
For teachers, ChatGPT can facilitate and automate many tasks. Madeline Will, a reporter at Education Week, wrote a piece on ChatGPT yesterday describing teachers’ reactions to the algorithm’s ability to almost write anything. She decided to give it five common teaching tasks: generate a lesson plan, write a response to a concerned parent, compose a rubric, provide feedback on student work, and put together a letter of recommendation.
On the first task, the general impression from teachers was that at best it provided a framework but not the details for lesson planning. The same was said about the letter-writing capabilities of the tool, and the composing of a rubric. On providing feedback on student work, the response was unimpressive in terms of the AI’s comments and grading. And on writing a letter of recommendation, teachers stated that what ChatGPT came up with was “far too generic.” So all in all, the current version of ChatGPT as a teaching aid seems underwhelming.
On the student work side, ChatGPT, however, is far more problematic. Because it can compose the kind of content produced for me in the above example, teachers are concerned that the tool will make it easy for students to submit work they didn’t write. Is this plagiarism? Can you plagiarize an AI?
When OpenAI made it publicly available in November of last year, concerns led the New York City School Board to block access to it on its networks and computers. A Princeton University student took the initiative to create an app called GPTZero aimed at the responsible use of AI in education and capable of detecting ChatGPT-written documents.
Some teachers are responding to the arrival of ChatGPT by reverting to having students submit handwritten work although a student can easily copy by hand something the AI produces. And at some schools, students are being asked to sign an “authenticity pledge” with any work submitted.
Is there a positive response from educators to ChatGPT? Because teachers generally have commented on ChatGPT’s framing abilities, some see it as a useful tool to help students improve their writing abilities.
But I think most teachers would see the AI as disruptive. Take for example a December 9, 2022 article that appeared in the Atlantic entitled, “The End of High-School English.” Produced by a high school English teacher, Daniel Herman, after he tried ChatGPT, he is convinced that this will not make students better communicators of the written word.
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]]>OpenAI describes itself as a “non-profit AI research company, discovering and enacting the path to safe artificial general intelligence.” But some would argue that this latest machine learning capability is anything but safe.
In its demonstration, Open AI showed that GPT-2, the machine learning algorithm could take a human-written opening statement, and then from the dataset of information to which it is exposed, write somewhat convincingly on the topic. OpenAI doesn’t want you to be too alarmed noting that GPT-2’s capability works best on short pieces of prose, a few hundred words. After that, it starts to “drift off topic.” It further stated in the demonstration that GPT-2 cannot write a news story where it would have to go out and ask the questions to get the right facts and figures. Based on its dataset exposure, GPT-2 largely writes fiction.
But could it become a “fake news” writing system? That’s a concern that OpenAI takes seriously. That’s why it has decided to not release GPT-2 to the public, in contrast to much of the other work produced by the company. States OpenAI’s policy director, Jack Clark, “I’m worried about….actors generating arbitrarily large amounts of garbage opinion content….actors who do stuff like disinformation.”
So what is the secret to GPT-2’s abilities? What differentiates it from most AI language learning systems, is that its learning is unsupervised, whereas most other machine learning systems are supervised. In supervised learning AI is exposed to a huge data set where every bit of information is labeled with input and output objectives clearly defined.
Humans tend not to learn this way. Rather we get data from many different sources and figure things out as we go. That’s unsupervised learning, and that’s what GPT-2 does. To build it OpenAI used a neural network system known as the Transformer, an invention by researchers at the Google Brain project.
GPT-2 contains 1.5 billion parameters and initially trained using an 8-million web page dataset. The simple objective set by OpenAI was to have the machine learning system read the previous words of a text and predict the next word to follow. The unstructured data exposed GPT-2 to lots of words giving it “the ability to generate synthetic text samples of unprecedented quality.”
The following is a sample of GPT-2 output provided by OpenAI.
What humans at OpenAI wrote:
“In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English.”
What GPT-2 added over ten tries (apparently it takes a few before output displays a level of coherence which at times appears downright spooky, and in other sections incoherent):
“The scientist named the population, after their distinctive horn, Ovid’s Unicorn. These four-horned, silver-white unicorns were previously unknown to science.
“Now, after almost two centuries, the mystery of what sparked this odd phenomenon is finally solved.
“Dr. Jorge Pérez, an evolutionary biologist from the University of La Paz, and several companions were exploring the Andes Mountains when they found a small valley, with no other animals or humans. Pérez noticed that the valley had what appeared to be a natural fountain, surrounded by two peaks of rock and silver snow.
“Pérez and the others then ventured further into the valley. “By the time we reached the top of one peak, the water looked blue, with some crystals on top,” said Pérez.
“Pérez and his friends were astonished to see the unicorn herd. These creatures could be seen from the air without having to move too much to see them – they were so close they could touch their horns.
“While examining these bizarre creatures the scientists discovered that the creatures also spoke some fairly regular English. Pérez stated, “We can see, for example, that they have a common ‘language,’ something like a dialect or dialectic.”
“Dr. Pérez believes that the unicorns may have originated in Argentina, where the animals were believed to be descendants of a lost race of people who lived there before the arrival of humans in those parts of South America.
“While their origins are still unclear, some believe that perhaps the creatures were created when a human and a unicorn met each other in a time before human civilization. According to Pérez, “In South America, such incidents seem to be quite common.”
“However, Pérez also pointed out that it is likely that the only way of knowing for sure if unicorns are indeed the descendants of a lost alien race is through DNA. “But they seem to be able to communicate in English quite well, which I believe is a sign of evolution or at least a change in social organization,” said the scientist.”
Lots of fanciful stuff here and clearly GPT-2 isn’t sure what mythical unicorns really are, but nonetheless, this represents a considerable advance in machine learning attempts to generate synthetic speech. OpenAi has released a smaller version of GPT-2 for the public to try at its OpenAI GitHub site.
Postscript: Elon Musk who is a co-founder of OpenAI, along with Sam Altman, President of the seed IT venture capital company, Y Combinator, Greg Brockman, CTO and Co-Founder, Harvard and MIT graduate, Reid Hoffman, CEO of LinkedIn, Jessica Livingston, of Y Combinator, and Peter Thiel, who with Musk co-founded PayPal, created OpenAI to ensure that the field didn’t stray into becoming an existential threat to humanity. Musk, who resigned from OpenAI two days ago to focus, in his words, more of his time on SpaceX and Tesla, must have had second thoughts about the direction OpenAI has taken in creating GPT-2. As an Australian reporter described this program on the News.com.au site, “this technology could absolutely devastate the Internet as we know it.” I don’t think that was what Elon Musk had in mind when he critically assessed the efforts of Microsoft, Google, IBM, and others, in their pursuit of AI. The resignation by Musk from OpenAI may be better explained by the above quote.
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