Opinion Paper: "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
Yogesh K. Dwivedi,Nir Kshetri,Laurie Hughes,Emma L. Slade,Anand Jeyaraj,Arpan Kumar Kar,Abdullah M. Baabdullah,Alex Koohang,Vishnupriya Raghavan,Manju Ahuja,Hanaa Albanna,Mousa Ahmad Albashrawi,Adil Al-Busaidi,Janarthanan Balakrishnan,Yves Barlette,Sriparna Basu,Indranil Bose,Laurence Brooks,Dimitrios Buhalis,Lemuria Carter,Soumyadeb Chowdhury,Tom Crick,Scott W. Cunningham,Gareth Davies,Robert M. Davison,Rahul De,Denis Dennehy,Yanqing Duan,Ram Janam Dubey,Rohita Dwivedi,John G. Edwards,Carlos Flavián,Robin Gauld,Varun Grover,Meixia Hu,Marijn Janssen,Paulette Camp Jones,Iris A. Junglas,Sangeeta Khorana,Sascha Kraus,Kai R. Larsen,Paul L. Latreille,Sven Laumer,F. T. Malik,A Mardani,Marcello M. Mariani,Sunil K. Mithas,Emmanuel Mogaji,Jeretta Horn Nord,Siobhan O'Connor,Fevzi Okumus,Margherita Pagani,Neeraj Pandey,Savvas Papagiannidis,Ilias O. Pappas,Nishith Pathak,Jan Pries-Heje,Ramakrishnan Raman,Nripendra P. Rana,Sven-Volker Rehm,Samuel Ribeiro-Navarrete,Alexander Richter,Frantz Rowe,Suprateek Sarker,Bernd Carsten Stahl,M. K. Tiwari,Wil M. P. van der Aalst,Viswanath Venkatesh,Giampaolo Viglia,Michael Wade,Paul H. Walton,Jochen Wirtz,Ryan Wright +72 more
TLDR
In this article , the authors bring together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing to identify questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research.About:
This article is published in International Journal of Information Management.The article was published on 2023-08-01 and is currently open access. It has received 103 citations till now. The article focuses on the topics: Transformative learning & Generative grammar.read more
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ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope
TL;DR: A comprehensive review of the background, applications, key challenges, and future directions of ChatGPT can be found in this article , highlighting the importance of striking a balance between AI-assisted innovation and human expertise.
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Overview of Early ChatGPT’s Presence in Medical Literature: Insights From a Hybrid Literature Review by ChatGPT and Human Experts
Omar Temsah,Samina A Khan,Yazan Chaiah,A. Senjab,Khalid Alhasan,Amr Jamal,Fadi Aljamaan,Khalid H. Malki,Rabih Halwani,Jaffar A. Al-Tawfiq,Mohamad-Hani Temsah,Ayman Al-Eyadhy +11 more
TL;DR: In this paper , the authors present a hybrid narrative review of ChatGPT's applications and implications in healthcare, highlighting the need for further research to assess its effectiveness and ethical concerns.
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Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions
TL;DR: In this article , the authors explore the potential use of AI systems and chatbots in the academic field and their impact on research and education from an ethical perspective, and propose effective solutions to the observed ethical dilemmas.
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War of the chatbots: Bard, Bing Chat, ChatGPT, Ernie and beyond. The new AI gold rush and its impact on higher education
TL;DR: In this article , the authors present a comparative method and systematically compare selected chatbots across a multi-disciplinary test relevant to higher education and conclude with four types of recommendations for key stakeholders in higher education: (1) faculty in terms of assessment and (2) teaching & learning, (3) students and (4) higher education institutions.
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On the use of AI-based tools like ChatGPT to support management research
TL;DR: In this article , a case study of systematic literature reviews (SLRs) is presented to provide a guideline for employing AI in the process of scientific research, highlighting recent trends and developments in the field.
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TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
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