While founding a university (SIAI), I encountered a surprising reality—university rankings, like any evaluative system, are shaped by more than just academic performance. Factors such as institutional branding, media visibility, and methodological choices play a role in shaping how institutions are perceived and ranked. This has led to ongoing debates about how rankings should be structured and whether certain metrics introduce unintended biases.
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I have spent years in AI and data science, believing that structured models and quantitative analysis were the future. That perspective changed the moment I became a target of an orchestrated misinformation campaign—one that wasn’t random but designed to destroy my credibility, my institution’s reputation, and my work.
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People following AI hype are mostly completely misinformedAI/Data Science is still limited to statistical methodsHype can only attract ignorance As a professor of AI/Data Science, I from time to time receive emails from a bunch of hyped followers claiming what they call 'recent AI' can solve things that I have been pessimistic. They usually think 'recent AI' is close to 'Artificial General Intelligence', which means the program learns by itself and it is beyond human intelligence level.
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