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Showing 2 results for Type of Study: Letter to Editor

Hadi Ghasemi,
Volume 38, Issue 0 (4-2025)
Abstract

The rapid integration of artificial intelligence (AI) into various aspects of human life raises important questions about its potential benefits and drawbacks. As AI reduces our reliance on cognitive processes, we must consider its long-term effects on human cognition. While, the general use of AI is still relatively new, significant discussions and studies have begun to explore its impact on cognitive function. This letter aims to summarize findings from several studies, highlighting the dual nature of AI's cognitive effects and the necessity for a balanced and targeted approach to its use.
Some studies indicated that AI could enhance cognitive abilities. For instance, Haider et al. (1) conducted a cross-sectional study revealing that AI tools such as memory enhancement platforms and adaptive learning systems improved short-term and long-term memory, analytical thinking, and decision-making efficiency. A review (2) also found that AI-based interventions like brain training programs, promoted neuroplasticity and alleviate anxiety, particularly in older adults.
Conversely, another research highlights the negative effects of AI on cognitive function. Zhai et al. (3) conducted a systematic review demonstrating that prolonged use of AI conversational systems in education could hinder independent problem-solving and analytical reasoning, introducing risks such as algorithmic bias, privacy violations, and plagiarism. Furthermore, excessive reliance on AI has been linked to diminished critical thinking, creativity, and work ethic, potentially fostering psychological dependence and reducing motivation for deeper learning (1). Increased screen time and reliance on AI may also alter brain structure, resulting in reduced gray matter in frontal regions and impairing attention, memory, and socioemotional regulation (2).
The impact of AI varies across different age groups. In children, unsupervised AI use can impede language development and attention span. Among young people, social media and AI tools may contribute to anxiety, loneliness, and poor academic performance. For older adults, while cognitive training through AI shows promise, it necessitates support for digital literacy (2).
In summary, while AI can enhance cognition in certain contexts, its unchecked use poses risks to creativity, independent thinking, and ethical standards. For optimal outcomes, AI usage should be accompanied by human judgment and critical thinking skills must be integrated, and also overall screen time should be monitored and limited. Future research should prioritize prospective studies and develop specific guidelines for AI users across different ages and demographic groups, including students.


Farzan Madadizadeh, Sajjad Bahariniya,
Volume 39, Issue 0 (3-2026)
Abstract

Artificial intelligence as one of the transformative technologies of the present era, plays an increasing role in medical sciences, especially dentistry. Among the various branches of artificial intelligence, machine learning with its ability to analyze complex data, extract patterns, and provide accurate predictions, has provided a suitable platform for the development of smart dentistry. Modern dentistry faces challenges such as interpreting a large volume of radiographic images, early detection of lesions, selecting an appropriate treatment plan, and managing patient information. Challenges that can be largely resolved use machine learning algorithms. Today, deep learning models and artificial neural networks have found widespread use in analyzing dental images, diagnosing caries, predicting the success of restorative and implant treatments, designing prostheses, and supporting clinical decision-making. In addition, the integration of machine learning with technologies such as robotics, digital design, and intelligent patient monitoring systems has paved the way for precise and personalized dentistry. Despite the significant benefits of this technology, challenges such as data quality dependency, ethical issues, and the need for clinical validation has remained. Overall, machine learning has the potential to revolutionize the future of dentistry by increasing diagnostic accuracy, reducing human error, saving time and money, and improving the quality of service.


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