𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗔𝗜 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝗳𝗼𝗿 𝘂𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝗶𝗲𝘀 𝗶𝘀𝗻'𝘁 𝘀𝗽𝗼𝘁𝘁𝗶𝗻𝗴 𝘄𝗵𝗼 𝘂𝘀𝗲𝗱 𝗶𝘁. 🎓 It's that AI lets any student turn in work as polished as the top of the class, so even honest grades stop telling them apart. Economist Jason Potts makes the case in a new paper, 𝗧𝗵𝗲 𝗨𝗻𝗶𝘃

𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗔𝗜 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝗳𝗼𝗿 𝘂𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝗶𝗲𝘀 𝗶𝘀𝗻'𝘁 𝘀𝗽𝗼𝘁𝘁𝗶𝗻𝗴 𝘄𝗵𝗼 𝘂𝘀𝗲𝗱 𝗶𝘁. 🎓 It's that AI lets any student turn in work as polished as the top of the class, so even honest grades stop telling them apart. Economist Jason Potts makes the case in a new paper, 𝗧𝗵𝗲 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗮𝗳𝘁𝗲𝗿 𝗔𝗜. 🔗 From the printing press to the internet, tech made 𝘤𝘰𝘯𝘵𝘦𝘯𝘵 abundant, and universities shrugged it off. Content was never the product. What universities really sell: 🤝 𝗠𝗮𝘁𝗰𝗵𝗶𝗻𝗴: bringing students, scholars and employers together ✅ 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: vouching that graduates know their stuff AI is the 𝗳𝗶𝗿𝘀𝘁 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 to reach both. Plus, AI tutors now compete with the teaching that quietly pays for research. His answer isn't better AI detection. It's the 𝗼𝗿𝗮𝗹 𝗲𝘅𝗮𝗺, how universities tested people before paper was everywhere. When anyone can produce polished work, 𝘁𝗿𝘂𝘀𝘁𝗲𝗱 𝘃𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 becomes scarce. His boldest idea: universities should mainly examine and certify, with teaching optional. 🔍 Fair caveat: it's an early (v0.1) conceptual paper, so the ideas are argued, not tested. #AI #ArtificialIntelligence #GenerativeAI #AIinEducation #HigherEducation #HigherEd #Universities #Education #FutureOfEducation #EdTech #Academia #Assessment #AcademicIntegrity #Credentials #Economics #FutureOfWork #Research #Innovation #Leadership #EducationPolicy 📷