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Showing posts with the label challanges

How ChatGPT May Pose Challenges in Medical Research

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Image AI Generated A research team, led by eye surgeon Giuseppe Giannaccare from the University of Cagliari, conducted an experiment revealing a concerning aspect of AI, specifically ChatGPT.  The study integrated ChatGPT with a Python-based data analysis model to swiftly generate a set of convincing but fake data, aimed at comparing treatments for keratoconus, an eye disease.  The results provided fictitious support for one of the procedures, raising ethical and practical questions about the integrity of medical research. The study emphasizes the need for methods to detect fraudulent data, showcasing AI's potential as both a problem and a solution in scientific research ethics.  The discovery underscores the importance of responsible AI use and ethical considerations as society navigates the transformative power of these technological tools.  The potential misuse of AI to generate false data for financial gain in the medical sector is identified as a risk, urging caution and moral

Challenges Arising from Plex's Social Feature and How to Mitigate Them

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Image AI Generated "Plex, known for its evolution from a simple local media file management app to a comprehensive media platform, introduced the social feature 'Discover Together.'  However, this default-enabled feature has caused discomfort among users as it shares viewing history with family and friends.  Users report instances where certain compromising or sensitive content was revealed, causing tension in relationships. While the feature allows users to choose who can see their profiles and viewing history, it lacks a mechanism to filter out specific content.  Frustrated users have taken to platforms like Reddit to share their negative experiences. Currently, the only solution is to disable the sharing of viewing history, potentially undermining the social function.  Users have urged Plex to implement granular controls and filters to enhance the social experience.  Without such improvements, the social layer risks becoming a failure, regardless of upcoming features pl