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Artificial intelligence (AI) has the potential to revolutionize higher education, going beyond mere disruption and completely transforming the industry. The progress of smart machines in various fields is undeniable, with AI even demonstrating its ability to outperform humans in standardized tests like the GMAT and GRE. The fact that AI can achieve a 3.34 GPA in a Harvard freshman course and a B grade in a Wharton Business School course raises concerns about the future of education. Will AI eventually normalize cheating and render education devoid of genuine content?

This question has sparked a heated debate in the realm of academia, particularly in the United States, a country known for its lead in education and technology. As we approach the return to physical campuses, The Washington Post has issued warnings of an impending “chaos” and “turmoil.” In addition to addressing this urgent issue, we must also examine the shortcomings of the current educational model that allows machines to perform many functions that were traditionally the domain of humans.

One proposed solution to this dilemma is an outright ban on AI usage by students. Institutions like Sciences Po in Paris and RV University in Bangalore have taken this stringent approach. However, is it realistic to ban a technology that is rapidly becoming ubiquitous? Moreover, does preventing students from using a tool that they will heavily rely on in their future careers truly prepare them for life after university? Banning AI outright may inadvertently repeat the same mistake Socrates made in Plato’s Phaedrus, where he argued against writing things down due to fears that it would diminish memory and the pursuit of true wisdom.

A more feasible solution lies in allowing students to use AI responsibly. They can employ AI to gather information, organize notes, or fact-check their work. However, limitations need to be set to prevent students from relying on AI to write their essays or ace their exams. Nonetheless, drawing the line between responsible and irresponsible AI usage poses practical challenges. How can educators ensure that students have not used AI to compose their essays, but merely to organize their thoughts? Moreover, can one consider it genuine research if a student employs a bot to do all the work, then merely tweaks the material to create an essay?

Advocates for responsible AI usage argue that it opens up the possibility of an academic future that resembles an arms race mixed with a cat-and-mouse game. Tech companies will develop increasingly sophisticated cheating apps, while others will focus on creating even more advanced apps to conceal such cheating. Faculty members will strive to detect illicit AI usage, while students will attempt to outsmart them. However, neither approach seems effective in identifying cheating, let alone eradicating it. Open AI’s ChatGPT, for instance, released an app earlier this year to expose AI-generated content but quietly scrapped it due to its low accuracy rate. Another company, Turnitin.com, often mistakes human writing for AI-generated content.

In the pursuit of preventing educational catastrophe, the most promising answer lies not in perfecting machines, as the solution to technological challenges rarely involves more technology. Rather, it lies in adopting a teaching method that harkens back to the days of Plato and Socrates, one that has thrived at institutions like Oxford and Cambridge for over a century and a half: the tutorial method.

In the Oxbridge tradition, students have weekly individual or small group meetings with their tutors. Tutors assign essay questions and provide reading lists, allowing students to independently research and write their essays. During tutorials, tutors challenge students on their ideas, interpretations, and understanding of the assigned material. This exchange is a spirited intellectual debate where knowledge is constantly tested, and no authority is immune to being questioned or replaced. Tutorials are a gladiatorial yet egalitarian approach to education, where debates are central and knowledge is contested.

To determine a student’s grade, high-stakes exams involving timed essay writing are conducted. The essays are assessed by examiners appointed by the university, often including scholars like Professor Snodgrass. Tutors compete to achieve the best results for their students, while colleges compete to demonstrate superior collective performance. Although there have been recent attempts to ease the examination burden by allowing typing instead of handwriting and introducing theses alongside exams, AI may paradoxically strengthen the role of old-fashioned handwritten exams. Sometimes, progress requires embracing elements from the past.

The tutorial method creates an environment where over-reliance on AI is laid bare. A student who submits an essay generated verbatim by a chatbot or who uses a bot to conduct the reading and merely embellish the essay would be quickly exposed as a fraud under cross-examination. The purpose of the essay is not solely to answer the question and earn a grade; rather, it aims to spark discussion and provoke critical analysis of the assigned texts. Failure to engage with the reading material would subject a student to a challenging hour of scrutiny from a skilled sparring partner.

Tutorials not only reveal cheating but also demonstrate that AI cannot replace the essence of real education. True education goes beyond assembling facts into coherent patterns or collecting certificates and marks. It revolves around the exploration of ideas, open-ended inquiry, and being admitted into the realm of learning and intellectual discourse. Renowned Oxford historian, philosopher, and archaeologist R.G. Collingwood sharply contrasted real learning with “scissors-and-paste” history, which involves rearranging statements from different authorities without true understanding. Tutorials aim to transcend the cut-and-paste nature of AI by delving deeply into literature, engaging in debates with fellow scholars, and extracting answers through fair and rigorous means.

Beyond guarding against cheating, tutorials foster a sense of accountability and morality within education. The difference between attempting to deceive an impersonal institutional bureaucracy and trying to deceive a tutor whom one interacts with personally, both academically and socially, is substantial. Tutorials serve as a societal safeguard against cheating. However, they offer far more than that. They function as a hyphen, connecting senior and junior members, and imbue education with a moral character.

In conclusion, while the rise of AI in higher education presents significant challenges, the tutorial method provides a powerful antidote. This teaching approach, epitomized by institutions like Oxford and Cambridge, invites intellectual combat, celebrates debate, and nurtures a deep understanding of the subject matter. Not only does it expose the limitations of AI, but it also fosters a genuine passion for learning and encourages students to embark on intellectual journeys that defy the cut-and-paste nature of AI. Rather than succumbing to fears of AI dominance, embracing the tutorial method can help education remain rooted in critical thinking and intellectual exploration for generations to come.

AI legalese decoder and Addressing the Situation:
In the face of the rapid AI advancements in higher education, the use of AI legalese decoder can play a significant role in addressing the situation. This tool can assist in tackling the problem of cheating and maintaining the integrity of education.

The AI legalese decoder works by analyzing AI-generated content and identifying any potential instances of plagiarism or unauthorized use of AI tools in academic work. By scanning essays, papers, or other written assignments, this technology can distinguish between AI-generated content and content produced by human effort.

Educational institutions can utilize AI legalese decoder to evaluate the authenticity of students’ work, ensuring that they have not relied on AI to write their assignments. This technology can help differentiate between responsible AI usage, such as using AI to gather information or fact-check, and dishonest practices involving AI-generated content.

With the assistance of AI legalese decoder, universities can establish clear guidelines and policies regarding the ethical use of AI in academic work. By educating students about the responsible and accountable utilization of AI tools, institutions can mitigate the risk of cheating while acknowledging the inevitability of AI’s presence in professional settings.

Furthermore, AI legalese decoder can aid educators in identifying instances where AI has been leveraged to deceive or manipulate academic assessments. By detecting discrepancies or similarities in writing styles, the tool can flag potential cases of AI involvement, allowing educators to investigate further and take appropriate action.

In summary, the AI legalese decoder offers an invaluable solution to the challenges posed by AI in higher education. By ensuring academic integrity and fostering responsible AI usage, this technology contributes to the preservation of the tutorial method’s values while effectively addressing the concerns surrounding AI’s impact on education.

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