AI Research
AI is making you slow and stupid: How artificial intelligence causes detrimental effects on productivity and learning
Much has been said about the upsides of artificial intelligence (AI), which is designed to enhance efficiency, eliminate human error and improve decision-making. Humanoid robots may help us do tedious chores at home in the future, while one AI-focused company plans on “putting the power of superintelligence in people’s hands to direct it to what they value in their own lives.”
However, many are concerned, rightly or wrongly, about losing their job because of AI, which is also being linked to rising electricity bills.
Studies show detrimental effect of AI on creativity and learning
Additionally, a number of studies have been carried out to determine the connection between AI use and creativity and learning, with the results of two such papers discussed on The Intelligence Podcast from The Economist.
The first came in the form of an MIT paper, which some students were asked to complete a series of essay writing tasks with the help of AI, while others did them alone without any assistance. As explained by Alex Hern, The Economist’s AI writer, those aided by AI produced “subpar” essays, with the study also showing they didn’t use the ‘creative’ parts of their brains nearly as much as students who completed their writing tasks independently.
A second piece of research carried out by METR, an AI research group, analyzed how much AI coding assistants helped speed up the productivity of very experienced open-source developers. The developers imagined AI would allow them to work approximately 20% more quickly, but actually discovered it slowed them down by between 10 and 40%. “They spent so much time tinkering with the AI assistant, correcting mistakes and trying to work out the best way to prompt it, that they spent more time doing the task than they would’ve unaided,” Hern reports.
Will AI become a cognitive replacement? “Genuine concern for the future”
What does it all mean, then?
AI, in its current form, is “going to produce slop” if you ask it to produce an academic essay, according to Hern. “We’re not yet at the position where it’s a cognitive replacement.”
The “genuine concern for the future,” however, is what happens if, as is expected, the technology develops to a point where it is capable of carrying out such a task as well as, or even better than, a skilled human.
“Do people who are using AI assistants use it to help them or does it just do the task entirely?” Hern asks. “If it’s the latter, what is actually left of the human intellect to flourish in the gaps created by that AI help? Thinking about what it would look like if AI becomes a cognitive replacement might prepare us for the very different world that could be coming.”
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MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists
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AI Research
UCLA Researchers Enable Paralyzed Patients to Control Robots with Thoughts Using AI – CHOSUNBIZ – Chosun Biz
Cybersecurity firm Trail of Bits has revealed a technique that embeds malicious prompts into images processed by large language models (LLMs). The method exploits how AI platforms compress and downscale images for efficiency. While the original files appear harmless, the resizing process introduces visual artifacts that expose concealed instructions, which the model interprets as legitimate user input.
In tests, the researchers demonstrated that such manipulated images could direct AI systems to perform unauthorized actions. One example showed Google Calendar data being siphoned to an external email address without the user’s knowledge. Platforms affected in the trials included Google’s Gemini CLI, Vertex AI Studio, Google Assistant on Android, and Gemini’s web interface.
Read More: Meta curbs AI flirty chats, self-harm talk with teens
The approach builds on earlier academic work from TU Braunschweig in Germany, which identified image scaling as a potential attack surface in machine learning. Trail of Bits expanded on this research, creating “Anamorpher,” an open-source tool that generates malicious images using interpolation techniques such as nearest neighbor, bilinear, and bicubic resampling.
From the user’s perspective, nothing unusual occurs when such an image is uploaded. Yet behind the scenes, the AI system executes hidden commands alongside normal prompts, raising serious concerns about data security and identity theft. Because multimodal models often integrate with calendars, messaging, and workflow tools, the risks extend into sensitive personal and professional domains.
Also Read: Nvidia CEO Jensen Huang says AI boom far from over
Traditional defenses such as firewalls cannot easily detect this type of manipulation. The researchers recommend a combination of layered security, previewing downscaled images, restricting input dimensions, and requiring explicit confirmation for sensitive operations.
“The strongest defense is to implement secure design patterns and systematic safeguards that limit prompt injection, including multimodal attacks,” the Trail of Bits team concluded.
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