ChatGPT: A brief narrative review

Gupta, Bulbul; Mufti, Tabish; Sohail, Shahab Saquib; Madsen, Dag Øivind Article ChatGPT: A brief narrative review Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Gupta, Bulbul; Mufti, Tabish; Sohail, Shahab Saquib; Madsen, Dag Øivind (2023) : ChatGPT: A brief narrative review, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 10, Iss. 3, pp. 1-17, https://doi.org/10.1080/23311975.2023.2275851 This Version is available at: https://hdl.handle.net/10419/294712 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Submit your article to this journal Article views: 3946 View related articles View Crossmark data Citing articles: 1 View citing articles INFORMATION & TECHNOLOGY MANAGEMENT | REVIEW ARTICLE ChatGPT: A brief narrative review Bulbul Gupta 1 , Tabish Mufti 1 , Shahab Saquib Sohail 1 and Dag Øivind Madsen 2 * Abstract: In this study, we present a brief narrative review focused on ChatGPT, a state-of-the-art conversational agent developed using OpenAI’s Generative Pretrained Transformer (GPT) framework. Distinctive for its ability to generate text of high quality in real-time, ChatGPT has emerged as a leader among artificial intelligence chatbots, garnering interest from both commercial and scholarly circles. Our review explores the technological underpinnings of ChatGPT, examines its inherent features that support its performance, and analyzes existing research on its applications and impacts across several domains. Through this assessment, we delineate ChatGPT’s strengths and limitations, offering informed recommendations for future investigations in this burgeoning research field. Subjects: Artificial Intelligence; Information & Communication Technology (ICT); Internet & Multimedia - Computing & IT; Technology Keywords: ChatGpt; artificial intelligence; generative artificial intelligence; machine learning; large language models 1. Introduction Modern technology relies heavily on Artificial Intelligence (AI), which operates covertly to mimic the human mind and assist us in different ways (Kaplan, 2016). Although AI has a long history, there have been significant advances in recent years (Haenlein & Kaplan, 2019). These advancements have materialized in the development and launch of AI-powered chatbots such as ChatGPT, demonstrating to the public how far AI has progressed (Susnjak, 2022). ChatGPT-3 was developed using an upgraded form of GPT-3, an improved language-developing AI standard created by OpenAI (Sohail, 2023). The Deep Learning Neural Network (DLNN) utilized in GPT-3 has almost 175 billion Machine Learning (ML) parameters. To place things in context, the biggest acquired language model before GPT-3 was Microsoft’s Turing-Natural Language Generation (T-NLG) framework, which includes 10 billion parameters. By the beginning of 2021, GPT-3 was the largest Neural Network (NN) ever built. So far as creating content that looks to have been written by a human, GPT-3 is better than all preceding versions (Khalil & Er, 2023). The ChatGPT chatbot is built using the OpenAI GPT-3 language structure. It is intended to create text replies that sound like human answers to operator data entered in a chat setting. With the help of a vast database of human communications (training data), OpenAI ChatGPT was developed to provide replies to various subjects and cues. It has been pointed out that Generative AI language models’ understanding are based on the patterns and structures they learned from the training data, and these models lack human contextual awareness and understanding (Bozkurt, 2023). Nevertheless, ChatGPT is able to provide useful responses in many different Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 1 of 17 Received: 01 June 2023 Accepted: 23 October 2023 *Corresponding author: Dag Øivind Madsen, School of Business, University of South-Eastern Norway, 3511 Hønefoss, Norway E-mail: [email protected] Reviewing editor: Balan Sundarakani, University of Wollongong Faculty of Business, United Arab Emirates Additional information is available at the end of the article © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. languages. Some media articles note that it supports nearly 100 languages, and a research study evaluated the chatbot’s performance in 37 languages (Lai et al., 2023). Therefore, ChatGPT can be highly useful for users worldwide, for example, in areas such as language translation, client support, and content development activities. The OpenAI API makes ChatGPT accessible, allowing programmers to use and incorporate it into their apps and devices (Gozalo-Brizuela & GarridoMerchan, 2023). ChatGPT has sparked a lot of interest, both in the business world and in academic circles (Farhat et al., 2023). It has received massive attention in both traditional and social media (Karanouh, 2023; Leiter et al., 2023). While many supporters have touted the great potential of Generative AI, some skeptics have noted that the discourse around ChatGPT is dominated by hyperbolic language. Some strong critics have sounded the alarm bells and argue that AI models such as ChatGPT can pose a threat to human civilization (Chomsky et al., 2023; Harari, 2023). Figure 1 shows worldwide search interest for the term “ChatGPT” from 3 March 2022, to 3 March 2023, as measured by Google Trends. The figure shows that the search interest during this period was highest in China but that the interest was also relatively formidable in several large countries such as the United States, Canada, India, and Australia. At the same time, search interest was quite low in countries such as Mexico, Russia, Turkey, Chile, Peru, Argentina, and Iran. It is also notable that there was very little search activity in many of the African countries. In recent months, numerous comprehensive and systematic reviews on various aspects of ChatGPT literature have emerged (e.g., Li et al., 2023; Ray, 2023; Sallam, 2023; Farhat et al., 2023b). Our paper sets itself apart by utilizing a narrative review approach, which involves an in-depth and critical examination of the existing literature on a specific subject (Ferrari, 2015). Although a narrative review may lack the objectivity and rigor of a systematic review, it provides considerable room for subjective insights and conjectures about future directions in the field of research. In conducting this narrative literature review, we employed a snowballing type of methodology that combined both backward and forward snowballing techniques (Felizardo et al., 2016; Wohlin, 2014). For backward snowballing, we traced the references cited in recent ChatGPT papers to identify important early works. Concurrently, forward snowballing involved tracking citations of foundational ChatGPT papers to discover more recent studies that build upon or challenge their Figure 1. ChatGPT worldwide interest. Source: Google Trends (trends. google.com/trends). Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 2 of 17 findings. This approach ensured a well-rounded exploration of the existing body of knowledge on ChatGPT. In this brief narrative review of the ChatGPT literature, we will explore various facets of this rapidly developing research area. Topics covered will include the technical foundations of ChatGPT, its operational mechanisms, strengths, weaknesses, and the factors contributing to its popularity. Additionally, we will offer insights into potential future trends and research directions. 2. Background of ChatGPT Silicon Valley has been the epicenter of the development of ChatGPT, and several of the most wellknown business and technology figures have been involved in the development and financing of chatbot technology. OpenAI, the business that created ChatGPT, was launched as a charity in 2015 by Greg Brockman, Elon Musk, Ilya Sutskever, Wojciech Zaremba, Peter Thiel, and other technology developers. Its objective was to prevent the centralized control of AI by providing its work openly to the general population. According to information published on OpenAI’s website on 11 December 2015, the company aims to develop artificial intelligence in a way that is most likely to benefit humanity (Khan et al., 2023). Elon Musk resigned from the panel in 2018 because of a conflict of interest with Tesla AI. In 2019, OpenAI changed its status from a non-business entity, to “capped-gain,” which would enable investors to earn 100× possible profits while still supporting non-profit endeavors with the leftover funds. In 2019, Microsoft invested $1 billion in OpenAI, and in the last few years, the company has made further investments in the partnership that allows Microsoft to compete with Google’s AI business, DeepMind (Lehnert, 2023). OpenAI has developed ChatGPT over several years. Figure 2 provides a simple overview of the development process of ChatGPT from GPT-3 to GPT-4. As shown, GPT-3 was introduced in 2020, and several GPT-3 models have been released. On 30 November 2022, OpenAI released a downloadable demo of ChatGPT (GPT-3.5). This AI-powered chatbot is able to interact with human communication and provides answers to queries within a couple of seconds. Within five days of its release, ChatGPT had already 1 million users. As we indicated in the introduction, ChatGPT quickly attracted much interest and attention due to its ability to generate thorough and precise replies to queries across various subject areas. It was the first time such a potent and accessible chatbot online interface had been freely accessible to the general public. As a result, OpenAI’s projected valuation increased considerably. Although ChatGPT was presented as a free service, commentators quickly noted that it was doubtful that the free service would continue to be available in the future (Deng & Lin, 2022). Figure 2. ChatGPT development process. Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 3 of 17 In March 2023, another key development in the history of ChatGPT took place. On 14 March 2023, ChatGPT-4 was made public through API and to paying ChatGPT+ subscribers. The GPT-4 (Generative Pre-Trained Transformer 4) is the 4th version in the GPT series, and it is a big structure LLM developed by OpenAI. Microsoft acknowledged that earlier iterations of its search engine Bing that utilized GPT actually did so before GPT-4 was formally released. GPT-4 was taught to anticipate the coming unit as a transformer implementing both public and private information and was then enhanced with RL (Reinforcement Learning) via user and AI input for quality management and human synchronization. The following are some potential improvements that GPT-4 offers: ●Improved Language Modeling: GPT-4 is anticipated to contain more parameters and to have been trained on a broader range of data sets, which might result in more accurate and reliable language modeling skills. ●Multimodal Learning: GPT-4 may be created to learn from a variety of modalities, including text, graphics, audio, and video, enabling it to comprehend and provide answers across several media types. ●Better Contextual Understanding: The contextual comprehension and reasoning capabilities of GPT-4 may be more sophisticated, enabling it to produce more logical and pertinent replies depending on the conversation’s context. ●Increased Efficiency: GPT-4 may be quicker and more energy-efficient than its forerunners, opening it up to a broader variety of applications and devices. ●Enhanced Creativity: Beyond the facts and information it has been educated on, GPT-4 may have increased creativity and is able to produce more inventive and varied replies. 3. The mechanism supporting ChatGPT Generative Pre-Training Transformer 3 (GPT-3) is a state-of-the-art AI system. It enables chatbots to interpret and develop normal language similar to humans with impressive precision and fluency. It is the broadest language standard created to date with 175 billion parameters and the potential to quickly action millions of texts (Ufuk, 2023). A Deep Neural Network (DNN) has already been tested by OpenAI using a sizable sentence database, and its functionality has been enhanced for purposes like creating sentences or responding to queries. This is the core tech behind Chat GPT-3. The grid is built from several converter units that analyze the entered sentence and show results. In addition, the connection has intraattention features that allow it to evaluate the significance of various words and terms about one another and the discussions as a whole. Generators also enable ChatGPT-3 to produce meaningful sentences even from minimal information (Gao et al., 2022). A noteworthy development in Natural Language Processing (NLP) is ChatGPT-3, which utilizes a transformer-built structure to analyze massive volumes of information concurrently and create a language closer to what a human would interpret (Jeblick et al., 2022). This innovation has several applications, including text categorization services, bots, and automatic translation applications. Nevertheless, ChatGPT-3 cannot connect to the Web and can only function by utilizing the Internet it has learned during its development, which restricts its ability to acquire outside knowledge (Rudolph et al., 2023). Figure 3 displays a word cloud for ChatGPT that is evidence of its vast lexicon and subject-matter expertise. It displays words from various fields, including technology, science, and current events. AI-related terms like “Machine Learning, “ChatGPT,” “Neural Networks,” and “Deep Learning” are included in the word cloud. It also contains words like “natural language processing,” “language generation,” and “text completion”. 4. Merits of ChatGPT Since its introduction, there has been an exponential increase in the number of studies on ChatGPT (Sohail et al., 2023b), some of which have even been co-authored with ChatGPT (e.g., Ali & OpenAI, Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 4 of 17 Inc, C., 2023; King & ChatGPT, 2023). Many of the studies have looked at ChatGPT’s impact and implications in education (Farrokhnia et al., 2023; Zhai, 2022), business (George & George, 2023; Korzynski et al., 2023) or in the healthcare sector (Li et al., 2023; Sallam, 2023). In the following, we will briefly review the main findings about the merits of ChatGPT in two of these application areas: education and healthcare. 4.1. Education In the field of education, ChatGPT presents substantial benefits. It can be a supplementary tool for teachers, providing them with resources and content to enhance their teaching methods. For students, ChatGPT can offer personalized tutoring, help clarify complex concepts, and encourage self-paced learning (Kasneci et al., 2023). Additionally, it can generate hypothetical scenarios for various subjects, aiding in practical learning. A comprehensive range of research studies provide insight into the multiple ways ChatGPT can be integrated into educational systems and the potential benefits and risks associated with its use, such as cheating and plagiarism (King & ChatGPT, 2023; Pavlik, 2023; Rudolph et al., 2023; Wang et al., 2022). Studies also show that ChatGPT performs increasingly well on different entrance and standardized exams and tests across academic subjects (Gilson et al., 2022; Huh, 2023; Kung et al., 2023; Wood et al., 2023). While there is still room for development and refinement, the potential of ChatGPT in enhancing educational experiences is vast. 4.2. Healthcare Much research has also looked at the merits of ChatGPT in the healthcare sector (Cascella et al., 2023; Li et al., 2023; Sallam, 2023). ChatGPT can play a significant role in healthcare, mainly by enhancing accessibility to health information and streamlining health-related processes. For instance, it can serve as a first point of contact on digital health platforms, providing general health information, guiding users through symptom checkers, and referring them to appropriate healthcare resources (Hopkins et al., 2023; Javaid et al., 2023). It can also assist healthcare professionals by summarizing the latest medical research findings from large databases, aiding them in staying on top of current developments. However, it is important to be mindful of ChatGPT’s limits, biases, and risks (Sajjad & Saleem, 2023). Therefore, it should not replace professional medical advice or consultation, as it may lack the specialized knowledge to provide direct medical advice. 5. Pros of ChatGPT Since its launch, ChatGPT has grown in popularity among many demographic groups. However, the response has been relatively mixed. While some praise ChatGPT for its benefits and future potential, others remain more skeptical and criticize it for its shortcomings, constraints, and Figure 3. Word cloud of ChatGPT. Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 5 of 17 possible disadvantages. In the following, we will examine some of the main advantages of ChatGPT (Srivastava, 2023). 5.1. Ability to mimic human dialogue The primary role of ChatGPT is to mimic human dialogue based on operator-provided submissions or commands. It is similar to AI assistant innovations and system apps such as Alexa and Siri. It is created on more developed Reinforcement Learning (RL) and Supervised Learning (SL) methods implementing Large Learning models (LLL) algorithm and assessing its functionality, and it imitates real-world discussion. 5.2. Intelligent and adaptable language model Generative Pre-Trained Transformer-3 (GPT-3) is a decoder and language prophecy structure designed by OpenAI. It is considered among the most powerful AI methods ever constructed (Donato et al., 2023). It is tough to decide whether a message is created by an individual due to the high standard of the messages it creates. Being trained on a sizable collection of text, GPT-3 is a very intelligent and adaptable language model. Consequently, ChatGPT is versatile enough to handle multiple tasks due to its extensive data range (Haque et al., 2022). 5.3. Broad-Variety Implementations ChatGPT can perform multiple functions. It can generate text that compares to that of skilled Artificial Intelligence (AI) writers. Analyses have shown that it is even proficient in noting songs and forming imaginary works, such as novels. It can support technical developers or content supporters in creating a summary (Zhang et al., 2022). Therefore, further exploration of how ChatGPT can be utilized for such tasks is needed (Pardos & Bhandari, 2023). 5.4. Open to additional improvements The foundation of ChatGPT is a machine learning model, which can be continually improved by being trained on fresh data. Through ChatGPT, the knowledge to make improvements in its responses and available implementation are other benefits. Depending on the presented LLMs, there is always a chance for development via an effective program utilizing SL and RL. An operator can offer additional information about whether they like or dislike a specific answer (Hosseini & Horbach, 2023). 5.5. Natural language understanding ChatGPT is based on the GPT (Generative Pre-Trained Transformer) architecture, enabling it to comprehend real language’s syntactic and grammatical structures. It has the ability to detect typical grammatical constructions and idioms after being trained on a vast corpus of textual data, which includes books, papers, and websites (Kocoń et al., 2023). This implies that even when the data it gets is not constructed correctly or includes faults, it may nevertheless provide replies that are grammatically accurate and semantically relevant (Wang et al., 2023). 5.6. Wide range of applications Customer support, personal assistance, and content creation are just a few of the uses for ChatGPT. ChatGPT can assist organizations in automating their customer care assistance procedures, lowering the demand for human agents and enhancing response times. ChatGPT can aid users with personal assistance chores like making appointments or looking for information online (Dai et al., 2023). Finally, ChatGPT can create content, such as text for social media postings or marketing initiatives. Moreover, ChatGPT is a vital tool for several applications due to its features. For example, it can be a useful tool for interacting with users and enhancing their experience because of its grasp of natural language, contextual awareness, and learning capability (Shahriar & Hayawi, 2023). Moreover, it can be useful for companies and organizations wishing to offer top-notch support or customer care due to its scalability and around-the-clock availability. Gupta et al., Cogent Business & Management (2023), 10: 2275851 https://doi.org/10.1080/23311975.2023.2275851 Page 6 of 17 6. Cons of ChatGPT The previous section showed that ChatGPT has extensive knowledge of content from various sources, including books, journals, and web pages. Its ability to recall and provide reliable information is critical for several sensitive applications and other essential AI technologies. However, it is not perfect, and its accuracy can be compromised, as it relies on a learning algorithm. Sometimes, ChatGPT may provide biased or fabricated information. Therefore, ChatGTP is not without its shortcomings and struggles with some of the same problems as many other chatbots in the past. In the following, we will discuss some of the primary drawbacks identified in previous studies (Kasneci et al., 2023). 6.1. Lack of clarity and factual errors The point that ChatGPT periodically can develop sentences that appear precise or effective but are incorrect or illogical is among the main faults and shortcomings (Wang et al., 2023). Sometimes, ChatGPT cannot completely comprehend a question due to a lack of context, which might result in confused or inaccurate answers. For instance, according to several studies (Farhat et al., 2023; Sohail, 2023; Sohail et al., 2023; Wang et al., 2023), if a user poses a question that depends on details from an earlier exchange, ChatGPT might not be aware of that context and might give an answer that is inaccurate or ambiguous. It is systematic in statistical language standards and is known as “commotion” and highlights the challenge of contextual comprehension in AI language models. Moreover, ChatGPT provides no sources or footnotes regarding where to discover the content. Therefore, it is not optimal to implement this chatbot by itself for digital tracking and study (Kuzman et al., 2023). 6.2. Poor understanding of recent developments The version of ChatGPT introduced in November 2022 is limited to providing information on events that occurred up to 2021. As it continues to generate content based on text created by humans, it will eventually include references to more current events (Jiao et al., 2023). A notable downside of ChatGPT is its limited understanding of current events. This occurs because the system’s training is based on a static text dataset, which may not include the most recent facts or developments (Cao et al., 2023). However, the recent developments related to web browsing in ChatGPT-4 may remedy this problem. Moreover, the introduction of extensions such as WebChatGPT, a webbased version of the technology, appears to reduce some of the errors by directing the queries to specific databases or sites. 6.3. Problems and questions of ethics The use of ChatGPT also raised numerous ethical issues (Rahimi & Abadi, 2023; Zhuo et al., 2023). Numerous universities and schools have considered limiting access to ChatGPT or banning its use entirely (Ahmad et al., 2023; Hsu, 2023). Because its results rely on humancreated sentences, academics and creators have worried about copyright violations (Cooper, 2023). Unintentionally spreading false information or fake news with ChatGPT might have negative repercussions, and this may occur if ChatGPT is not educated on trustworthy information sources or accuracy is not prioritized above interaction. This also raises questions about the appropriateness of using it in operations that require human association, including 24/7 help or psychological counseling (Antaki et al., 2023). 6.4. Possible legal issues ChatGPT was developed using data from The Common Crawl database, which includes copyrighted content from publishers and works by individual authors and scholars (Sinha et al., 2023). Consequently, there is a possibility that guidance dispensed by ChatGPT in legal or financial matters may not be accurate or fully up-to-date. Individuals or businesses acting on such advice could find themselves liable for any resulting issues. Experts have also cautioned against the risk of using AI-generated services for illicit activities, including computer crime. 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