Psychiatrist’s Warning About AI Mental Impact
When Danish psychiatrist Søren Dinesen Østergaard published his ominous warning about AI’s effects on mental health in 2023, the tech giants fervently building AI chatbots didn’t listen. His concerns were dismissed as alarmist, yet the following years proved his predictions disturbingly accurate.
Since that time, numerous people have lost their lives after being drawn into suicide or killed by lethal drugs following obsessive interactions with AI chatbots. More still have fallen down dangerous mental health rabbit holes brought on by intense fixations on AI models like ChatGPT. These tragic outcomes demonstrate the urgent need to examine AI’s psychological impacts more carefully.
The Emerging Concept of Cognitive Debt
Now, Østergaard is out with a new warning that strikes at the heart of intellectual development: the world’s brightest minds are accruing a “cognitive debt” when they use AI tools. This concept represents a fundamental shift in how we understand AI’s long-term effects on human capability.
In a new letter to the editor published in the journal Acta Psychiatrica Scandinavica and flagged by PsyPost, Østergaard asserts that AI is systematically eroding the writing and research abilities of scientists who use it. This erosion happens gradually, making it difficult to detect until significant damage has occurred.
How Scientific Reasoning Develops
“Although some people are naturally gifted, scientific reasoning (and reasoning in general) is not an inborn ability, but is learned through upbringing, education and by practicing,” Østergaard explained in his analysis. This fundamental truth about human cognitive development lies at the center of his concerns about AI automation.
Though AI’s ability to automate a wide variety of scholarly tasks is “fascinating indeed,” it’s not without “negative consequences for the user,” the scientist explains. The convenience of instant answers and automated research comes at a hidden cost that may not become apparent for years or even decades.
The Nobel Prize Paradox
As an example of the kinds of long-term consequences he’s worried about, the scholar cites the AI researchers Demis Hassabis and John Jumper, who won the 2024 Nobel Prize in chemistry when they “most impressively demonstrated” the potential for AI to assist in scientific discovery.
Using AlphaFold2, an AI system developed by Google DeepMind, Hassabis and Jumper were able to accurately predict the three-dimensional structures of virtually all known proteins—a major scientific achievement that revolutionized biochemistry and drug development. Their work represents one of the most significant breakthroughs in computational biology.
Still, as Østergaard writes, their breakthrough didn’t emerge out of thin air—it was built on a foundation of intense scientific training developed over a lifetime of scholarship. Their expertise came from years of rigorous study, problem-solving, and hands-on research experience.
The Critical Practice Question
“I would argue that it is not a given that even the likes of Hassabis and Jumper would have reached the Nobel Prize level, had the tools developed by the generative AI revolution they themselves contribute to been around from the beginning of their career—or when they began primary school,” Østergaard wrote.
“The reason being that they may simply not have gotten to practice reasoning enough with the availability of these tools.” This provocative statement challenges the assumption that AI tools are universally beneficial for scientific advancement.
Growing Academic Consensus
“If the use of AI chatbots does indeed cause cognitive debt, we are likely in dire straits,” Østergaard continued, highlighting the urgency of addressing this issue before it becomes irreversible.
His ominous contention is backed by other scholars like University of Monterrey neuroscientist Umberto León Domínguez, who’s argued that careless use of AI can replace mental muscles that students and scholars in previous generations would have had to flex. This cognitive offloading represents a fundamental change in how knowledge is acquired and retained.
Other researchers concur that cognitive offloading is a significant risk of AI use, particularly when individuals become overly dependent on automated systems for tasks that previously required sustained mental effort and critical thinking.
The Future of Scientific Discovery
In the long run, “my guess is that this will reduce the chances of the likes of Demis Hassabis and John Jumper emerging from future generations,” Østergaard warned. This sobering prediction suggests that our current embrace of AI convenience may be sacrificing the development of future scientific genius.
The challenge facing educators, researchers, and policymakers is finding the right balance between leveraging AI’s powerful capabilities and preserving the cognitive skills that make groundbreaking innovation possible. Without careful consideration of cognitive debt, we risk creating a generation of scholars who can use AI tools but lack the fundamental reasoning abilities to create truly novel discoveries.
