dataesr/scientific-paragraphs-categorization huggingface dataset:
The technology is far better today, and ChatGPT due to its widespread accessibility is causing some widespread concern. Some journals and conferences have already set up policies that prohibit the use of ChatGPT in the research product. For instance, the International Conference on Machine Learning indicate that "Papers that include text generated from a large-scale language model such as ChatGPT are prohibited unless the produced text is presented as a part of the paper's experimental analysis. " Is this an overreaction? Certainly, the "ability to discern" an AI generated prose from a human generated one increases the diligence needed from our editors and reviewers. Most studies have shown that humans have a difficult time discriminating between AI and human generated text. Machines however (i.
Essentially using these AI-powered language tools to improve the readability and language of their manuscript. We do not however, cite such tools as a co-author. Scholarly writing is more than just providing a polished manuscript, it is about originality and building on a tradition of accumulative building of knowledge  (Metcalfe, 2004). Scholarly writing is not the same as writing for a tabloid newspaper that publishes routine stories (e. g. , weather reports, traffic updates), whereby ChatGPT may help journalists to write short news stories  (Financial Times, 2023). Recent studies (e. g. ,  Gao et al. , 2022; Bouschery et al. , 2023)  suggest that ChatGPT can be a useful tool for writing an abstract or even an introduction section. However, in most cases, the text is either poorly paraphrased leading to the distortion of the actual message or content and in some cases, a high level or a considerable amount of plagiarism has been noted.
Changes to publisher and conference policies. While publishers scramble to update their policies (see excerpts in Table We make a call to the associations of our disciplines (e. g. , Association of Information Systems) to update their policies for conferences and the use of ChatGPT in scholarly research and writing. To conclude, publishing policies will continue to evolve, and new variations of ChatGPT will emerge in the future, the activity for publishing scholarly research is a 'human-centric' process, not 'robotcentric'. This implies that authors are responsible for the integrity and validity of their scholarly work, adhering to contractual agreements with publishers, and upholding the ethical principles of their academic community (i. e. , Association for Information Systems). Further, as the rigorous review process of manuscripts is conducted by humans, not robots, then publishers, editors, and conference committees have a responsibility to ensure reviewers are provided with relevant training to help mitigate the threat of technologies (when used unethically) that have the potential to undermine the craft of scholarly writing and the integrity of our disciplines.
This is not to say that writing the abstract is not important. Quite the contrary! Still, despite being an important part of an article and needs the same attention, there is no guarantee that humans will write a good one. Why are we concerned with productivity gains? Or, to put it differently, why were we not concerned with other technologies that made us more efficient. For instance, why were we not concerned with online databases moving away from paper journals and in-person visits to libraries? They made undertaking literature review searches much easier. Not to mention that we happily apply ML among other data science techniques to clustering papers to identify the underlying themes. If the argument is that AI can help us write better papers, providing a competitive advantage to the author, then any gains are likely to be short lived.
Academic journals must enforce this practice with consistency. Data used within each paper must be verified and safely stored by the publisher. The challenge in this regard is where authors seek to publish multiple papers from the same dataset. This is perfectly reasonably but will require an audit trail to ensure originality. 4. Could authors who have been previously found guilty of plagiarism have this noted on their publishing record. This is potentially possible by using unique author identifiers like ORCID for example. This might be regarded as an extreme measure so could include time limited offences which drop off the record after a set time period. It would act as an effective red flag for publishers and deter potential plagiarism. 5. Journals that publish systemic and bibliographic literature reviews might be challenged to identify plagiarised copies produced via ChatGPT given the capability of the software to significantly alter original content.
In addition, written language constitutes much of our society, our rules, norms, expectations, and routines. Again, changes to this will have results worth considering in detail. Much of the current discussion of the ethics of ChatGPT focuses on predictable consequences of easy to foresee applications. To take the example of the use of ChatGPT for the creation of student essays, there are (ethical) benefits for those students who struggle with essay writing who may use ChatGPT to construct better arguments or to polish their language to present good essays. Individuals struggling with traditional university essays are often those who did not have the opportunity to practice them, for example because they are from disadvantaged backgrounds or because they are non-native speakers. Helping them would clearly be ethically desirable.
There are immediate opportunities for both customer-facing and internal use. All of them will require the AI's training database to include internal company information as well as generally available information. How this process will be managed is one more specific challenge for industry users and generative AI system providers: SMEs, for example, clearly could not build and run a generative AI system themselves with current technology. At present, those offering freely available generative AI software such as ChatGPT strongly warn against sharing sensitive information. Generative AI offers a considerable improvement on current chatbots, being more conversational and better able to refer back to previous statements in a "chat" with a user. This is a clear benefit for both customer-facing contact centres and internal processes such as ICT support.
" Yet, it pointed to opportunities such as "create content such as articles, stories, and scripts. This can be particularly useful for content creators, such as writers and journalists…[to] improve language translation, which can facilitate communication and understanding between different cultures. " And then it went on to suggest further research opportunities in the above areas "to understand the potential impacts of ChatGPT on society and develop strategies to mitigate any negative effects. " I draw here on my prior research and writings for assessing ChatGPT or technologies similar to it and argue that a sobering and more useful view of ChatGPT will require consideration of the functionalities that it may enable: (1) the ability to sense the environment (Sense); (2) the ability to analyse information (Analyse); (3) the ability to collaborate with others within or across firms (Collaborate); and (4) the ability to.
The use of conversational AI offers a wide range of potential applications allowing companies to improve customer experience, automate routine tasks, gather customer insights, and drive innovation in their industries. Despite the numerous benefits in various applications, its usage also entails certain drawbacks that should not be overlooked: 1. One of the major challenges posed by ChatGPT is the presence of deep fake text, as demonstrated by a recent study  (Else, 2023)  that proved the ability of the AI system to write convincing fake research-paper abstracts. To address this issue, there is a need for ongoing research to develop methods for detecting deep fake text. Moreover, addressing the bias present in the model's training data is also crucial. For example, if the model is trained on a dataset that contains gender stereotypes, it may generate text reinforcing those biases.
Another issue is the lack of awareness of local rules and regulations. ChatGPT operates on a global scale, and its responses may not be aligned with local laws and regulations. This can result in the dissemination of information that is legally or culturally inappropriate. 4. Finally, the training of ChatGPT on the vast amount of information available on the Internet, which encompasses both good and bad aspects of human behaviour, can result in the propagation of inaccuracies. This highlights the importance of monitoring and verifying the information used to train language models, as well as the outputs they produce. By focusing on ongoing research to address the potential risks, we can ensure that this technology's benefits are realized and positively impact society. The key areas of focus should include: (i) developing methods for detecting and mitigating bias, (ii) improving deep fake text detection, (iii) investigating applications in education and accessibility, (iv) exploring the use of ChatGPT in industry, and (v) advancing our understanding of language and human communication.
Claim 7. Claim to impact. The user may engage the AI, or an independent implementation of the AI will be used in a setting. Such as to generate a tweet or blog post. It is instantiated into a system. It, therefore, can create impacts that may be measured, such as likes and retweets. This claim will be evaluated through efficacy validity. As we further understand how to evaluate generative AI, we may, by extension, start to understand human creativity. As AI evolves in capability and creativity, shared researcher understanding of evaluative criteria will be critical to fully understanding ChatGPT and equivalent artifacts. Y. K. Dwivedi et al. 4. 4. 5. Contribution 36 4. 4. 5. 1. ChatGPT: challenges, opportunities, Manoj Tiwari, Fevzi Okumus and F. Tegwen Malik. ChatGPT optimally harnesses the power of generative AI, large connected datasets, and how meaning is derived from linguistics using natural linguistic programming (NLP) for engaging with a user.
Hospitality and Tourism: The service providers in hospitality and tourism can provide ChatGPT as a widget on their website. ChatGPT would act as a round-the-clock interactive interface for the customers for providing the travel, food, vehicle, and tourist locations along with their distance. It can enhance customer experience and minimise the manpower cost for service providers. Research & Development (R&D): ChatGPT would enhance the pace of R&D by providing basic information on the topic in multiple dimensions. It can provides support in the coding and debugging of codes. It would also reduce the probability of duplication of R&D activities that have been publicised. Legal services: Legal services highly depend on written laws of the land and past judgments. ChatGPT provides advisory and support documents by text-mining legal databases in an efficient manner.
Regulation: ChatGPT provides expert advice to users and is gradually becoming an integral part of our society. However, there have been cases of racial overtones, biased answers (stereotypes) due to the existing database, and questions on the accuracy of medical advice about ChatGPT. It has been banned by many organisations like Sciences Po University in France, public schools in Western Australia, and Stack Overflow as they have yet to figure out how to regulate it for the larger well-being of their stakeholders. There is a need to devise a global protocol for regulations of such generative AI platforms, as such services are available across many countries. Cultural sensitivity: Like other AI tools, ChatGPT also faces challenges with cultural sensitivity and issues involving empathy. The issues like comments on certain personalities, religious matters, and other delicate issues need to be addressed, as each region may have its sensitivities.
My training data only goes up until 2021, and I don't have the ability to access current events'. The database for ChatGPT is, therefore, not current. It is not presently likely that the information gathering and analysis involved in many roles will be surpassed by generative AI. Nor is it likely that the work done by humans in using the generated information will be subsumed. I know school teachers who, at least in my native New Zealand, have taken to ChatGPT like a drugapparently it has gone viral. Teachers are marvelling and grateful for the way it is able to produce basic lesson plans and cut through other administrative and compliance workpaperwork that has to be submitted to school administrators and government agenciesthat takes considerable time to collate. This is time teachers do not have in their busy teaching schedules, and is usually done in evenings and weekends.
ChatGPT is freeing them up to focus on what mattersworking with our children and their parents. For basic tasks that an internet search is not able to easily help with, ChatGPT seems to fill a gap. My referencing software question, a genuine issue I was facing where a style I required was actually different from the named style in Endnote, was nicely solved by ChatGPT. I Googled away getting nowhere then thought I would try ChatGPT. To my relief, it solved my problem, telling me the name of the style I needed (a rarely used variation, and plug in). This is the power and opportunity it offers. With ChatGPT, OpenAI has upped the stakes. Investments in it have grown significantly, and the other big tech companies are working concertedly on their own offerings. As indicated, the opportunities and impact of generative AI are tremendous.
ChatGPT works as a companion tool for people working in IT Industry. For e. g. , being a developer, one can use ChatGPT as a companion tool for developers to help me generating test cases and test data, debugging, and troubleshooting my code and even to some extent writing a code to do a particular task. Similarly, ChatGPT can work as a companion tool for folks working in marketing, Learning and developments, HR, finance and many more. ChatGPT certainly has immense potential to unearth new business potential, generate new revenue streams and above all, be a driver for  innovation. 4. 4. 8. 1. 3. Impact of ChatGPT in the IT industry. With the advent of ChatGPT, IT Industry has a lot of challenges and opportunities to explore but Industry is also going to be largely affected with the way it operates currently.
Such information spread on platforms such as social media can result in devastating impacts  (Deng and Lin, 2022). 4. 4. 9. 1. 2. Technological challenges. While ChatGPT showcases generative AI at its best and is able to mimic human writing it is still not able to fully replicate the display of knowledge depth that is seen in humans. In fact, some have remarked that the software is so impressive not because of its technical prowess but because of its ability to persuade a reader with the use of words or phrases that appear to be authentic  (Hendrik, 2022). Educators worry about the uncertain future of written exams and some like the New York City Department of Education have even blocked access to ChatGPT on its networks. However, ChatGPT is still not able to match the intellectual capability of a human exam taker.
However, with the US$ 10 billion investment by Microsoft for ChatGPT and the fact that this software runs on Microsoft Azure, it is unclear what the true cost of running ChatGPT for OpenAI is at this time. Although ChatGPT started as a freely available service, OpenAI has changed its course of action and launched a subscription-based model for accessing ChatGPT that can "chat with you, answer follow-up questions, and challenge incorrect assumptions" at the subscription cost of US$ 20 per month  (OpenAI, 2023). Also, taking cue from OpenAI, several scammers and fraudsters have put up fake advertisements on the Internet for subscription to ChatGPT at a monthly service fee of US$ 50  (Agomuoh, 2023). It is reported that numerous people have lost money by falling a prey to this extortion scheme and paying for the free basic service that is offered by  OpenAI.
While some faculty view ChatGPT as a threat, it is an even greater opportunity. Encouraging students to use ChatGPT for summarizing specific topic areas enables them to stir up discussions more quickly, which in turn could help them building up argumentative and critical-thinking competencies. Students must learn how GPTs are different from other interfaces, such as search engines, and how different techniques of training and fine-tuning can help to create case-specific solutions. This certainly will happen in industry, and our students must be prepared. Researchers must look into biases introduced by the training data set and the training process. If the dataset is incomplete or biased, so will be its output. Look at the allegations that question the ethics of OpenAI's training process. Software engineers, and those in charge of training GPT's linguistic capabilities, are the ethical arbiters of our digital tools.
acknowledges these risks. In this sense there are costs to be born for the widespread availability of ChatGPT3 technologies; but they are higher for established gatekeepers of news, media and opinion. ChatGPT3 outputs are pruned and censored to not be hateful or objectionable. Nonetheless the net beneficiaries are those such as OpenAI who control the underlying algorithms of ChatGPT3. The fourth and final measure of information quality is known as perfection. This quality asks whether we know where we are within any given process or transaction. Ultimately technologies like ChatGPT3 reduce the costs of transacting within a modern economy. Tools such as these will help us by creating a range of ubiquitous personal assistants. Those who can afford widespread access to computing resources, and the know-how to deploy these agents on their behalf will certainly benefit.
ChatGPT as a productivity enhancing tool ChatGPT is expected to have a potentially positive effect on productivity (e. g. ,  Contributions 20, 32, 36). It can enable the automation of mundane or repetitive work and allow people to focus on creative and non-repetitive activities  (Contributions 11, 39). People can quickly access information and knowledge through a simplified natural languagebased information search process using  ChatGPT (Contributions 4, 11). Within the banking, financial services, and insurance sectors, ChatGPT can help increase the accuracy in the audit and advisory services, which means that banking executives can focus on more important tasks (Contribution 36). It can also be used in text-mining of legal databases (Contribution 36), which is of particular benefit to financial institutions required to handle complex regulatory systems  (Kshetri, 2023a).
In addition, generative AI may have many use cases across groups and communities, such as supporting older or disabled people. Research is needed to examine appropriate deployment of such technologies for different groups in society. Regarding institutional evolution around generative AI, some have called for actors such as academic publishers to act as an institutional change agent and develop a code of practice (a kind of informal institution) for the academic community to make responsible use of ChatGPT (Contribution 29). In this regard, a related future research topic could be how institutional change agents theorize such changes (e. g. ,  Kshetri & Ajami, 2008). Note that theorization -or the development and specification of abstract categories and the elaboration of chains of cause and effect -is an important process through which institutional change agents facilitate the diffusion of new ideas  (Greenwood et al.
ChatGPT's performance and the underlying data and training models The performance of ChatGPT in generating text may be considerably influenced by the data and the training models used (e. g. , Contribution 2). ChatGPT's effective performance when asked to create disinformation related to COVID-19  (Klepper, 2023)  could be attributed in part to the data repositories on which ChatGPT was trained. It is possible that ChatGPT could have struggled with generating disinformation had its operations been based on datasets that did not include disinformation. Since ChatGPT was based on GPT-3 that relied on 175 billion documents of various types in the public domain  (Perrigo, 2023) , which also contain disinformation or reports of disinformation, it can be conceded that data and training models influence ChatGPT performance.
g. , we do not ask for medical advice from insurance agents) as do organizations that have invested in specialisation (e. g. , the various functional departments). Even in specialised niches, training ChatGPT based on data may not be complete since training databases typically include outcomes and steps but not the lived experiences of specialised humans. Therefore, P9. Generative AI tools such as ChatGPT have the potential to be superhuman or specialised agents as dictated by data and training methods.
ChatGPT's capabilities and responsible use Technologies have traditionally addressed problems and provided solutions; generative AI tools such as ChatGPT are no exception. However, technologies have been subjected to both intended and unintended use (e. g. , social media helps connections but also facilitates cyberbullying) and resulted in both intended and unintended consequences (e. g. , nurturing friendships but also envy and bitterness). Technologies have often disrupted existing ways (e. g. , iPod disrupted how we consumed music) and resulted in new ways (e. g. , artists can release music for sale online). Likewise, ChatGPT promises conversational natural language dialogue based on supervised pre-training on a closed albeit large dataset. As has been already discussed, ChatGPT has been applied for both positive (e.
In order to optimise the benefits of generative AI such as ChatGPT, it is important to take into account the various limitations of this tool such as the lack of originality (Contribution 2) and vagueness of the output (Contribution 21). A further limitation, as mentioned earlier, is that it was trained on a database before 2021, which means that it cannot search the internet to provide up-to-date information about a topic. In many cases, convincing answers have been frustratingly difficult to find with ChatGPT (Contribution 22). It is important to educate students and other users about these and other limitations of ChatGPT so that they can benefit from this transformative innovation. It is also crucial to make sure that students have a clear understanding of how generative AI tools differ from other tools such as search engines (Contribution 41).
For instance, AI trainers providing human feedback during the training phases need to take neutral and objectively true positions such that the reinforcement learning are not unnecessarily biased. OpenAI's own description of ChatGPT acknowledges certain types of biases in training data such as trainers preferring longer answers that look more comprehensive  (OpenAI, 2023a). Further, OpenAI claims to use moderation policies around disallowed use of ChatGPT that could also be biased even after conceding restrictions to curb activities that are illegal, high-risk, or abusive  (OpenAI, 2022 (OpenAI, , 2023b)). AI practitioners need to devise methods to evaluate the extent to which new text generated by ChatGPT is biased. Users in any profession (e. g. , students, software developers) have the opportunity to apply ChatGPT in both positive and negative ways.