I invite you to read my recent paper: Why Mathematicians Resist AI: Between Rigor, Risk, and Opportunity? (https://www.preprints.org/manuscript/202509.1307/v1). The paper argues that while AI can be a powerful tool for mathematicians when used with expertise, the growing reliance on AI detectors is unreliable and discourages genuine research. Such detection tools often misclassify human work, creating barriers instead of fostering innovation. I propose that responsible integration of AI—through transparency and verification—is far more beneficial than adversarial policing. I would greatly appreciate your comments and insights as mathematicians and AI experts.
Dear Rafik Zeraoulia ,
Recent advances in machine learning have sparked intense debate about the existential risks (x-risks) associated with artificial intelligence (AI) systems.Footnote1 Central to this debate is a concern about the mechanisms by which AI could cause existential catastrophes. In direct response to this concern, this paper explores: What are the distinct types of pathway by which AI systems could cause existential catastrophes? Conventional discourse on AI existential catastrophes typically portrays them as sudden, decisive events, caused by artificial general or super intelligence or extremely powerful (non-general) AI..
Article Two types of AI existential risk: decisive and accumulative
Regards,
Shafagat
I believe that the use of artificial intelligence in research must be done systematically with the researcher, because an artificial intelligence cannot DISCOVER something, so it needs the scientist for help and speed, so research has excellent results.
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