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Relying on AI is rotting your brain. But here’s what you can do about it | Carly Dober
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Meta recently launched Muse, an AI personal agent that can fill out forms, organize calendars, pay bills and make reservations. Meta calls Muse a personal agent “built for everyone.” The launch comes as AI agents have made headlines for hacking government websites, public agencies and businesses.
Psychologist Carly Dober said her immediate concern is closer to home. She argued that brains prefer the path of least resistance to preserve resources. With modern life overwhelming, deferring to a chatbot can be highly seductive, she wrote.
Dober warned that large language models and infinite-scroll social media can have a dose effect. Too much reliance can activate cognitive biases, affect mental health and atrophy neurological skills, she said. She also cited cognitive offloading, which bypasses the mental effort needed to build deep neural connections.
Frequent AI use can foster passive acceptance of information, Dober argued. That reduces the friction and inquiry that drive curiosity and problem-solving. The brain depends on mental struggle and failure to rewire neural pathways, she said, so bypassing friction can lower cognitive reserve.
She also described automation bias and automation complacency. People may favor information from tools such as ChatGPT or Claude over correct manual sources. They may monitor technology less vigilantly because they trust its accuracy, even though LLMs often err.
Dober linked this to the privacy paradox. Many people trade location data, contacts and browsing history for free maps and personalized recommendations. She warned that aggregate data can manipulate purchases, influence votes and predict private life events.
As AI agents like Muse enter daily tasks, Dober framed the debate around convenience versus cognitive autonomy. She urged users to consider what they are giving up, to whom and why before handing over data. The launch highlights tension between useful automation and the mental effort behind learning and judgment.