AI Insights
AI tools threaten writing, thinking, and learning in modern society
In the modern age, artificial intelligence (AI) is revolutionizing how we live, work, and think – sometimes in ways we don’t fully understand or anticipate. In newsrooms, classrooms, boardrooms, and even bedrooms, tools like ChatGPT and other large language models (LLMs) are rapidly becoming standard companions for generating text, conducting research, summarizing content, and assisting in communication. But as we embrace these tools for convenience and productivity, there is growing concern among educators, journalists, editors, and cognitive scientists that we are trading long-term intellectual development for short-term efficiency.
As a news editor, one of the most distressing observations has been the normalization of copying and pasting AI-generated content by young journalists and writers. Attempts to explain the dangers of this trend – especially how it undermines the craft of writing, critical thinking, and authentic reporting – often fall on deaf ears. The allure of AI is simply too strong: its speed, its polish, and its apparent coherence often overshadow the deeper value of struggling through a thought or refining an idea through personal reflection and effort.
This concern is not isolated to journalism. A growing body of research across educational and corporate environments points to an overreliance on writing tools as a silent threat to cognitive growth and intellectual independence. The fear is not that AI tools are inherently bad, but that their habitual use in place of human thinking – rather than in support of it – is setting the stage for diminished creativity, shallow learning, and a weakening of our core mental faculties.
One recent study by researchers at the Massachusetts Institute of Technology (MIT) captures this danger with sobering clarity. In an experiment involving 54 students, three groups were asked to write essays within a 20-minute timeframe: one used ChatGPT, another used a search engine, and the last relied on no tools at all. The researchers monitored brain activity throughout the process and later had teachers assess the resulting essays.
The findings were stark. The group using ChatGPT not only scored lower in terms of originality, depth, and insight, but also displayed significantly less interconnectivity between brain regions involved in complex thinking. Worse still, over 80% of students in the AI-assisted group couldn’t recall details from their own essays when asked afterward. The machine had done the writing, but the humans had not done the thinking. The results reinforced what many teachers and editors already suspect: that AI-generated text, while grammatically sound, often lacks soul, depth, and true understanding.
These “soulless” outputs are not just a matter of style – they are indicative of a broader problem. Critical thinking, information synthesis, and knowledge retention are skills that require effort, engagement, and practice. Outsourcing these tasks to a machine means they are no longer being exercised. Over time, this leads to a form of intellectual atrophy. Like muscles that weaken when unused, the mind becomes less agile, less curious, and less capable of generating original insights.
The implications for journalism are especially dire. A journalist’s role is not simply to reproduce what already exists but to analyze, contextualize, and interpret information in meaningful ways. Journalism relies on curiosity, skepticism, empathy, and narrative skill – qualities that no machine can replicate. When young reporters default to AI tools for their stories, they lose the chance to develop these essential capacities. They become content recyclers rather than truth seekers.
Educators and researchers are sounding the alarm. Nataliya Kosmyna, lead author of the MIT study, emphasized the urgency of developing best practices for integrating AI into learning environments. She noted that while AI can be a powerful aid when used carefully, its misuse has already led to a deluge of complaints from over 3,000 educators – a sign of the disillusionment many teachers feel watching their students abandon independent thinking for machine assistance.
Moreover, these concerns go beyond the classroom or newsroom. The gradual shift from active information-seeking to passive consumption of AI-generated content threatens the very way we interact with knowledge. AI tools deliver answers with the right keywords, but they often bypass the deep analytical processes that come with questioning, exploring, and challenging assumptions. This “fast food” approach to learning may fill informational gaps, but it starves intellectual growth.
There is also a darker undercurrent to this shift. As AI systems increasingly generate content based on existing data – which itself may be riddled with bias, inaccuracies, or propaganda – the distinction between fact and fabrication becomes harder to discern. If AI tools begin to echo errors or misrepresentations without context or correction, the result could be an erosion of trust in information itself. In such a future, fact-checking will be not just important but near-impossible as original sources become buried under layers of machine-generated mimicry.
Ultimately, the overuse of AI writing tools threatens something deeper than skill: it undermines the human drive to learn, to question, and to grow. Our intellectual autonomy – our ability to think for ourselves – is at stake. If we are not careful, we may soon find ourselves in a world where information is abundant, but understanding is scarce.
To be clear, AI is not the enemy. When used responsibly, it can help streamline tasks, illuminate complex ideas, and even inspire new ways of thinking. But it must be positioned as a partner, not a replacement. Writers, students, and journalists must be encouraged – and in some cases required – to engage deeply with their work before turning to AI for support. Writing must remain a process of discovery, not merely of delivery.
As a society, we must treat this issue with the seriousness it deserves. Schools, universities, media organizations, and governments must craft clear guidelines and pedagogies for AI usage that promote learning, not laziness. There must be incentives for original thinking and penalties for mindless replication. We need a cultural shift that re-centers the value of human insight in an age increasingly dominated by digital automation.
If we fail to take these steps, we risk more than poor essays or formulaic articles. We risk raising a generation that cannot think critically, write meaningfully, or distinguish truth from fiction. And that, in any age, is a far greater danger than any machine.
Anita Mathur is a Special Contributor to Blitz.
AI Insights
Tampa General Hospital, USF developing artificial intelligence to monitor NICU baby’s pain in real-time
TAMPA, Fla. – Researchers are looking to use artificial intelligence to detect when a baby is in pain.
The backstory:
A baby’s cry is enough to alert anyone that something’s wrong. But for some of the most critical babies in hospital care, they can’t cry when they are hurting.
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“As a bedside nurse, it is very hard. You are trying to read from the signals from the baby,” said Marcia Kneusel, a clinical research nurse with TGH and USF Muma NICU.
With more than 20 years working in the neonatal intensive care unit, Kneusel said nurses read vital signs and rely on their experience to care for the infants.
“However, it really, it’s not as clearly defined as if you had a machine that could do that for you,” she said.
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Big picture view:
That’s where a study by the University of South Florida comes in. USF is working with TGH to develop artificial intelligence to detect a baby’s pain in real-time.
“We’re going to have a camera system basically facing the infant. And the camera system will be able to look at the facial expression, body motion, and hear the crying sound, and also getting the vital signal,” said Yu Sun, a robotics and AI professor at USF.
Yu heads up research on USF’s AI study, and he said it’s part of a two-year $1.2 million National Institutes of Health grant.
He said the study will capture data by recording video of the babies before a procedure for a baseline. Video will record the babies for 72 hours after the procedure, then be loaded into a computer to create the AI program. It will help tell the computer how to use the same basic signals a nurse looks at to pinpoint pain.
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“Then there’s alarm will be sent to the nurse, the nurse will come and check the situation, decide how to treat the pain,” said Sun.
What they’re saying:
Kneusel said there’s been a lot of change over the years in the NICU world with how medical professionals handle infant pain.
“There was a time period we just gave lots of meds, and then we realized that that wasn’t a good thing. And so we switched to as many non-pharmacological agents as we could, but then, you know, our baby’s in pain. So, I’ve seen a lot of change,” said Kneusel.
Why you should care:
Nurses like Kneusel said the study could change their care for the better.
“I’ve been in this world for a long time, and these babies are dear to me. You really don’t want to see them in pain, and you don’t want to do anything that isn’t in their best interest,” said Kneusel.
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USF said there are 120 babies participating in the study, not just at TGH but also at Stanford University Hospital in California and Inova Hospital in Virginia.
What’s next:
Sun said the study is in the first phase of gathering the technological data and developing the AI model. The next phase will be clinical trials for real world testing in hospital settings, and it would be through a $4 million NIH grant, Sun said.
The Source: The information used in this story was gathered by FOX13’s Briona Arradondo from the University of South Florida and Tampa General Hospital.
Financial operations platform Ramp has debuted its first artificial intelligence (AI) agents.
A majority of small businesses are using artificial intelligence and finding out it can save time and money.
Artificial Intelligence and automation are often used interchangeably. While the technologies are similar, the concepts are different. Automation is often used to reduce human labor for routine or predictable tasks, while A.I. simulates human intelligence that can eventually act independently.
“Artificial intelligence is a way of making workers more productive, and whether or not that enhanced productivity leads to more jobs or less jobs really depends on a field-by-field basis,” said senior advisor Gregory Allen with the Wadhwani A.I. center at the Center for Strategic and International Studies. “Past examples of automation, such as agriculture, in the 1920s, roughly one out of every three workers in America worked on a farm. And there was about 100 million Americans then. Fast forward to today, and we have a country of more than 300 million people, but less than 1% of Americans do their work on a farm.”
A similar trend happened throughout the manufacturing sector. At the end of the year 2000, there were more than 17 million manufacturing workers according to the U.S. Bureau of Labor statistics and the Federal Reserve Bank of St. Louis. As of June, there are 12.7 million workers. Research from the University of Chicago found, while automation had little effect on overall employment, robots did impact the manufacturing sector.
“Tractors made farmers vastly more productive, but that didn’t result in more farming jobs. It just resulted in much more productivity in agriculture,” Allen said.
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Researchers are able to analyze the performance of Major League Baseball pitchers by using A.I. algorithms and stadium camera systems. (University of Waterloo / Fox News)
According to our Fox News Polling, just 3% of voters expressed fear over A.I.’s threat to jobs when asked about their first reaction to the technology without a listed set of responses. Overall, 43% gave negative reviews while 26% reacted positively.
Robots now are being trained to work alongside humans. Some have been built to help with household chores, address worker shortages in certain sectors and even participate in robotic sporting events.
The most recent data from the International Federation of Robotics found more than 4 million robots working in factories around the world in 2023. 70% of new robots deployed that year, began work alongside humans in Asia. Many of those now incorporate artificial intelligence to enhance productivity.
“We’re seeing a labor shortage actually in many industries, automotive, transportation and so on, where the older generation is going into retirement. The middle generation is not interested in those tasks anymore and the younger generation for sure wants to do other things,” Arnaud Robert with Hexagon Robotics Division told Reuters.
Hexagon is developing a robot called AEON. The humanoid is built to work in live industrial settings and has an A.I. driven system with special intelligence. Its wheels help it move four times faster than humans typically walk. The bot can also go up steps while mapping its surroundings with 22 sensors.
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Researchers are able to create 3D models of pitchers, which athletes and trainers could study from multiple angles. (University of Waterloo)
“What you see with technology waves is that there is an adjustment that the economy has to make, but ultimately, it makes our economy more dynamic,” White House A.I. and Crypto Czar David Sacks said. “It increases the wealth of our economy and the size of our economy, and it ultimately improves productivity and wages.”
Driverless cars are also using A.I. to safely hit the road. Waymo uses detailed maps and real-time sensor data to determine its location at all times.
“The more they send these vehicles out with a bunch of sensors that are gathering data as they drive every additional mile, they’re creating more data for that training data set,” Allen said.
Even major league sports are using automation, and in some cases artificial intelligence. Researchers at the University of Waterloo in Canada are using A.I. algorithms and stadium camera systems to analyze Major League Baseball pitcher performance. The Baltimore Orioles joint-funded the project called Pitchernet, which could help improve form and prevent injuries. Using Hawk-Eye Innovations camera systems and smartphone video, researchers created 3D models of pitchers that athletes and trainers could study from multiple angles. Unlike most video, the models remove blurriness, giving a clearer view of the pitcher’s movements. Researchers are also exploring using the Pitchernet technology in batting and other sports like hockey and basketball.
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Overview of a PitcherNet System graphics analyzing a pitcher’s baseball throw. (University of Waterloo)
The same technology is also being used as part of testing for an Automated Ball-Strike System, or ABS. Triple-A minor league teams have been using the so-called robot umpires for the past few seasons. Teams tested both situations in which the technology called every pitch and when it was used as challenge system. Major League Baseball also began testing the challenge system in 13 of its spring training parks across Florida and Arizona this February and March.
Each team started a game with two challenges. The batter, pitcher and catcher were the only players who could contest a ball-strike call. Teams lost a challenge if the umpire’s original call was confirmed. The system allowed umpires to keep their jobs, while strike zone calls were slightly more accurate. According to MLB, just 2.6% of calls were challenged throughout spring training games that incorporated ABS. 52.2% of those challenges were overturned. Catchers had the highest success rate at 56%, followed by batters at 50% and pitchers at 41%.
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Triple-A announced last summer it would shift to a full challenge system. MLB commissioner Rob Manfred said in June, MLB could incorporate the automated system into its regular season as soon as 2026. The Athletic reports, major league teams would use the same challenge system from spring training, with human umpires still making the majority of the calls.
Many companies across other sectors agree that machines should not go unsupervised.
“I think that we should always ensure that AI remains under human control,” Microsoft Vice Chair and President Brad Smith said. “One of first proposals we made early in 2023 was to insure that A.I., always has an off switch, that it has an emergency brake. Now that’s the way high-speed trains work. That’s the way the school buses, we put our children on, work. Let’s ensure that AI works this way as well.”
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