{"title":"Reclaiming authorship in the age of generative AI: From panic to possibility","authors":"Mohsen Askari","doi":"10.1002/aaai.70022","DOIUrl":null,"url":null,"abstract":"<p>The advent of generative AI, particularly large language models like ChatGPT, has precipitated a seismic shift in academia. Far from a gradual evolution, its sudden emergence has jolted educational institutions, leaving many academics grappling with a perceived encroachment upon their intellectual domain. This upheaval has sparked intense debates, with concerns ranging from the erosion of academic integrity to the devaluation of scholarly labor. This essay contends that such apprehensions, while understandable, may overlook the transformative potential of AI as a collaborative tool. Drawing parallels to historical disruptions—such as the advent of photography challenging traditional art forms—we explore how AI can augment human creativity rather than supplant it. By examining the dynamics of authorship, originality, and accountability, we argue for a redefinition of these concepts in the context of AI-assisted work. Emphasizing the importance of human oversight in guiding AI outputs, we advocate for a framework that recognizes the symbiotic relationship between human intellect and machine efficiency. Such a perspective not only preserves the essence of academic rigor but also embraces the democratization of knowledge production. Ultimately, this essay calls for a balanced approach that mitigates risks while harnessing the innovative capacities of generative AI in academia.</p>","PeriodicalId":7854,"journal":{"name":"Ai Magazine","volume":"46 3","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.70022","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Magazine","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aaai.70022","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The advent of generative AI, particularly large language models like ChatGPT, has precipitated a seismic shift in academia. Far from a gradual evolution, its sudden emergence has jolted educational institutions, leaving many academics grappling with a perceived encroachment upon their intellectual domain. This upheaval has sparked intense debates, with concerns ranging from the erosion of academic integrity to the devaluation of scholarly labor. This essay contends that such apprehensions, while understandable, may overlook the transformative potential of AI as a collaborative tool. Drawing parallels to historical disruptions—such as the advent of photography challenging traditional art forms—we explore how AI can augment human creativity rather than supplant it. By examining the dynamics of authorship, originality, and accountability, we argue for a redefinition of these concepts in the context of AI-assisted work. Emphasizing the importance of human oversight in guiding AI outputs, we advocate for a framework that recognizes the symbiotic relationship between human intellect and machine efficiency. Such a perspective not only preserves the essence of academic rigor but also embraces the democratization of knowledge production. Ultimately, this essay calls for a balanced approach that mitigates risks while harnessing the innovative capacities of generative AI in academia.
期刊介绍:
AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.