AI Language Research Articles

Generative AI has democratised fraud and cybercrime

Artificial intelligence has no intrinsic ethical stance. Everything depends on the uses to which it is put. This is leading to an arms race between threat actors, using generative AI and large language models (LLMs) to hone the effectiveness of phishing and other forms of attack, and security professionals looking to conscript AI into the effort to identify and interdict those attackers. What's certain is that no-one can ignore generative AI and LLMs, and it's important to understand both the threat and the potential for enhancing security.

Writing at a Distance: Notes on Authorship and Artificial Intelligence

ABSTRACT: This essay provides an overview of notions of authorship in AI and natural language processing systems and discusses past and current debates about computers as literary authors. It suggests the concept of causal authorship to measure the types of distance between human and machine agents, acknowledging the anthropocentric bias of this idea. To balance this, the essay reflects on the notion of distributed authorship , which considers the network of actors involved in the creation of a text and has its own limitations. Both concepts are elements of a future theory of authorship in the age of machine learning.

Foundation Models, Generative AI, and Large Language Models

We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care.

The Trend of Using AI Language Models such as ChatGPT in Research and Publication: How to Keep it in Check?

The Trend of Using AI Language Models such as ChatGPT in Research and Publication: How to Keep it in Check?

ChatGPT for use in technology-enhanced learning in anesthesiology and emergency medicine and potential clinical application of AI language models : Between hype and reality around artificial intelligence in medical use

The utilization of AI language models in education and academia is currently asubject of research, and applications in clinical settings are also being tested. Studies conducted by various research groups have demonstrated that language models can answer questions related to medical board examinations, and there are potential applications of these models in medical education as well. This study aims to investigate the extent to which current version language models prove effective for addressing medical inquiries, their potential utility in medical education, and the challenges that still exist in the functioning of AI language models. The program ChatGPT, based on GPT3.5, had to answer 1025 questions from the second part (M2) of the medical board examination. The study examined whether any errors and what types of errors occurred. Additionally, the language model was asked to generate essays on the learning objectives outlined in the standard curriculum for specialist training in anesthesiology and the supplementary qualification in emergency medicine. These essays were analyzed afterwards and checked for errors and anomalies. The findings indicated that ChatGPT was able to correctly answer the questions with an accuracy rate exceeding 69%, even when the questions included references to visual aids. This represented an improvement in the accuracy of answering board examination questions compared to astudy conducted in March; however, when it came to generating essays ahigh error rate was observed. Considering the current pace of ongoing improvements in AI language models, widespread clinical implementation, especially in emergency departments as well as emergency and intensive care medicine with the assistance of medical trainees, is aplausible scenario. These models can provide insights to support medical professionals in their work, without relying solely on the language model. Although the use of these models in education holds promise, it currently requires asignificant amount of supervision. Due to hallucinations caused by inadequate training environments for the language model, the generated texts might deviate from the current state of scientific knowledge. Direct deployment in patient care settings without permanent physician supervision does not yet appear to be achievable at present.

An Innovative Approach for Treating Chronic Vaginitis Based on AI-Driven Drug Repurposing

This study evaluates the effectiveness of ChatGPT, an AI language model, in assisting healthcare practitioners in selecting drugs for treating chronic vaginitis, which is still an important medical problem. A panel of experts assessed ChatGPT’s recommendations for ten fictional clinical scenarios related to this condition. The study aims to determine if ChatGPT can provide accurate and relevant guidance on pharmaceutical options for managing chronic vaginitis.The authors use the set of question as input to ChatGPT system to derive the output then the output was further validated by expert panel. The results show that ChatGPT consistently offers valuable suggestions for potential drug repurposing, supported by scientific evidence. Despite limitations, such as the need for more clinical data and the inability to modify treatment, ChatGPT shows promise as a tool for drug repurposing in the treatment of chronic vaginitis. The present study is a novel approach in applying the AI based technique for drug repurposing in clinical medicine. Future research should focus on refining the model’s capabilities, incorporating more comprehensive clinical data, and enabling customization of treatment plans to enhance its effectiveness in assisting healthcare practitioners.By addressing these issues, ChatGPT could become a valuable resource for managing chronic vaginitis in females.

Research on confusing responses based on ChatGPT

Recently, Artificial intelligence and Machine learning have changed the nature of scientific inquiry, with chatbots moving from rule-based technology to AI technology. Open AIs ChatGPT is a prominent AI language model that has attracted great interest and attention since its launch. To better understand its role and influence in social life, it is very necessary to know its work carefully. This paper briefly introduces the development history, current situation, and future development of the ChatGPT, discusses its popular application fields, and analyzes its pros and cons. On this basis, some problems that still exist in the application are focused on. This study uses the case analysis method to emphasize the confusing responses of ChatGPT in multiple fields, telling people that while enjoying its powerful functions, should still pay attention to its side effects and risks, the most obvious one is deceptive behavior, providing users with misleading or fabricated information may further lead to other social problems. This study speculates on the future development of ChatGPT and proposes future development directions. Generally, by rationally utilizing the functions of ChatGPT, its potential in various fields can be better released, thereby promoting the advancement of conversational AI and its transformative impact on society.

AI-translated poetry: Ivan Franko's poems in GPT-3.5-driven machine and human-produced translations

The article presents a detailed comparative analysis of translations of twelve great Ukrainian poet Ivan Franko's poems done by translator Percival Cundy and the GPT-3.5 AI language model. Using various manual and automatic analytical research methods and techniques, we analyzed the translations' merits, demerits, and eight essential qualitative and quantitative linguistic and poetic characteristics to verify a hypothesis that human and GPT-3.5-driven machine translations can be quite comparable in terms of their quality and poetic features. The results obtained sufficiently prove the hypothesis and suggest that developing AI translation potential for poetry translation can help build more capable, diversified, and nuanced large language models. The AI revolutionary breakthrough in translation makes it quite possible to acquaint satisfactorily the wider public with the poetic heritage of the world's nations, especially those using minor languages, whose poetry is evidently under-translated. A follow-up study is desirable to assess the progress made by GPT4.0 and its possible later versions in poetry translation, as compared with GPT-3.5.

Voices from the algorithm: Large language models in social research

Research on energy and society often relies on online data collection. In particular, there has been an increase in the use of online techniques such as video software for qualitative research since the pandemic. We suggest that the rapid growth in generative AI and Large Language Models such as Chat-GPT mean that they may be utilised by research participants; particularly in research where participants may be less knowledgeable about the topic under discussion, such as emerging energy technologies. Drawing on examples from recent research, we argue that social scientists need to be cautious in assuming that the voices of our participants are genuinely theirs.

Enhancing Voice Assistants with Generative AI Language Models for Interactive Conversations

This paper presents comprehensive research for the development of a voice assistant application using HTML/CSS, JavaScript, Python, SQLite, and the Hugging Face API. The proposed methodology encompasses key steps in data collection, model training, frontend and backend development, integration, testing, and deployment, ensuring the creation of a robust and user-friendly voice assistant system. By leveraging a combination of web technologies and Al tools, the developed voice assistant application offers an interactive and intelligent user experience across its users. Key Words: Voice assistant, HTML/CSS, JavaScript, Python, SQLite, Hugging Face API, LLMs, AI.

Smart Parking Space Detection with Generative Artificial Intelligence and Large Language Models

CAMERON VU, Dept of Computer Science and Math & ENGR, Shepherd University, Shepherdstown, WV, 25443, and DARIA PANOVA, Dept of Computer Science and Math & ENGR, Shepherd University, Shepherdstown, WV, 25443, and JOSIAH KOWALSKI, Dept of Computer Science and Math & ENGR, Shepherd University, Shepherdstown, WV, 25443, and Dr. W. LIAO (Faculty Advisor), Dept of Computer Science and Math & ENGR, Shepherd University, Shepherdstown, WV, 25443, and Dr. O. Guzide (Faculty Advisor), Dept of Computer Science and Math & ENGR, Shepherd University, Shepherdstown, WV, 25443. Smart Parking Space Detection with Generative Artificial Intelligence and Large Language Models. The increasing relevance of generative AI and large language models is reshaping various sectors of modern society. These advancements have spurred notable progress in fields such as healthcare, finance, and education. Yet, the application of AI extends beyond expert domains, offering simplified solutions to everyday tasks for the general populace. This project harnesses the power of generative artificial intelligence and large language models to develop a practical application: smart parking space detection. By leveraging these technologies, individuals can effortlessly ascertain the availability of parking spots in monitored lots via camera or photographic monitoring, facilitated by a straightforward algorithm. The overarching objective is twofold: to engineer a user-friendly system utilizing generative AI principles and to demonstrate the potential for such technologies to enhance the daily experiences of ordinary individuals.

Developing Soft Skills in the Artificial Intelligence Era: Communication, Business Writing, and Composition Skills

This study explores the development of soft skills in the Artificial Intelligence era. Initially, the study, through an anonymous online survey, explored why students use AI and Large Language Models (LLMs). It was found that students use AI for general and academic purposes. From a general perspective, students use AI and LLMs for (1) convenience, (2) lack of time, and (3) lack of curiosity/interest. From an academic perspective, students use AI and LLM platforms as they (1) lack familiarity/knowledge, (2) lack basic skills, (3) lack confidence, (4) have an eagerness to score high grades, and (5) wish to provide different perspectives. To assist in developing students’ soft skills and discourage possible destructive outcomes in the AI era, the study suggests integrating AI platforms as part of teaching. This integration can be carried out by (1) introducing AI tools to students in a productive manner, (2) aligning the use of AI tools with the curriculum and teaching styles, (3) planning lessons and interactive activities using AI platforms, and (4) using AI tools to provide feedback and vice versa. In communication courses, instructors shall (1) create a supportive environment, (2) organize classroom discussions and debates, (3) create public speaking opportunities, (4) provide room for oral communication practices, (5) integrate the use of technology and multimedia, and (6) provide feedback and reflection. In business writing courses, instructors shall (1) encourage effective communication in classrooms, (2) facilitate collaboration and teamwork, (3) use role-play scenarios, (4) introduce project management tools, (5) teach professional etiquette, and (6) organize networking events. In composition courses, instructors shall (1) embrace technology, (2) teach students to critically evaluate online sources, (3) design assignments that require critical analysis, (4) encourage creative writing assignments, (5) promote imagination and originality, and (6) conduct workshops. These practices, which are provided in line with AlAfnan’s taxonomy of educational objectives, shall assist students in developing their soft skills in a way that maintains the relevance of classroom teaching in the AI era.

AI and Aphasia in the Digital Age: A Critical Review.

Aphasiology has a long and rich tradition of contributing to understanding how culture, language, and social environment contribute to brain development and function. Recent breakthroughs in AI can transform the role of aphasiology in the digital age by leveraging speech data in all languages to model how damage to specific brain regions impacts linguistic universals such as grammar. These tools, including generative AI (ChatGPT) and natural language processing (NLP) models, could also inform practitioners working with clinical populations in the assessment and treatment of aphasia using AI-based interventions such as personalized therapy and adaptive platforms. Although these possibilities have generated enthusiasm in aphasiology, a rigorous interrogation of their limitations is necessary before AI is integrated into practice. We explain the history and first principles of reciprocity between AI and aphasiology, highlighting how lesioning neural networks opened the black box of cognitive neurolinguistic processing. We then argue that when more data from aphasia across languages become digitized and available online, deep learning will reveal hitherto unreported patterns of language processing of theoretical interest for aphasiologists. We also anticipate some problems using AI, including language biases, cultural, ethical, and scientific limitations, a misrepresentation of marginalized languages, and a lack of rigorous validation of tools. However, as these challenges are met with better governance, AI could have an equitable impact.

Empowering inclusivity: improving readability of living kidney donation information with ChatGPT.

Addressing disparities in living kidney donation requires making information accessible across literacy levels, especially important given that the average American adult reads at an 8th-grade level. This study evaluated the effectiveness of ChatGPT, an advanced AI language model, in simplifying living kidney donation information to an 8th-grade reading level or below. We used ChatGPT versions 3.5 and 4.0 to modify 27 questions and answers from Donate Life America, a key resource on living kidney donation. We measured the readability of both original and modified texts using the Flesch-Kincaid formula. A paired t-test was conducted to assess changes in readability levels, and a statistical comparison between the two ChatGPT versions was performed. Originally, the FAQs had an average reading level of 9.6 ± 1.9. Post-modification, ChatGPT 3.5 achieved an average readability level of 7.72 ± 1.85, while ChatGPT 4.0 reached 4.30 ± 1.71, both with a p-value <0.001 indicating significant reduction. ChatGPT 3.5 made 59.26% of answers readable below 8th-grade level, whereas ChatGPT 4.0 did so for 96.30% of the texts. The grade level range for modified answers was 3.4-11.3 for ChatGPT 3.5 and 1-8.1 for ChatGPT 4.0. Both ChatGPT 3.5 and 4.0 effectively lowered the readability grade levels of complex medical information, with ChatGPT 4.0 being more effective. This suggests ChatGPT's potential role in promoting diversity and equity in living kidney donation, indicating scope for further refinement in making medical information more accessible.

AI and agents

AbstractEarlier this year, OpenAI released their GPTs framework, allowing users to set up Large Language Model (LLM)‐based personas, orchestrate them into a workflow and even offering their AI apps within an app store. This is the latest, and maybe the easiest to set up, in a string of agent‐based LLM orchestration platforms in the past year, harkening a new age of agent‐based engineering. But, like most breakthroughs, this one is also rooted in many years of research, and the reason the world is paying attention to it now is that, thanks to Generative AI and Large Language Models, we finally have artificial agents that are useful enough to scale to more serious problems.

AI and English language teaching: Affordances and challenges

AbstractEnglish is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. However, English learners face many challenges in gaining English language skills. Extant studies show that AI has affordances to support in English language teaching and learning ELT/L. This study answers the call to examine specific challenges and affordances for using AI in ELT/L. A systematic review method was used with PRISMA principles to identify 42 studies. Findings reveal the geographical locations of studies, learner ages and years of study. Grounded coding was then used to identify affordances of the use of AI in ELT/L in the areas of speaking, writing, reading, pedagogy and self‐regulation. AI in ELT/L challenges uncovered were technology breakdowns, limited capabilities, fear and standardising language. Policymakers, funders, practitioners and educational leaders can use the information provided in this study to gain a holistic understanding of the current trend in the use of AI in ELT/L, and practical implications are provided to guide future use of AI. Practitioner notesWhat is already known about this topic English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. Empirical evidence shows that pupils can often face difficulties when learning English, with challenges such as irregularity in English spelling. AI has supported language teaching and learning with studies showing that AI can support language‐specific skills. What this paper adds Provides the scholarly community with a unique systematic review in the use of AI in ELT/L across learner levels. Identifies affordances of AI in ELT/L in speaking, writing, reading, pedagogy and self‐regulation. Identifies challenges of AI in ELT/L in technology breakdowns, limited capabilities, fear and standardising language. Provides researchers with a review of the field with identification of gaps and future research opportunities. Implications for practice and/or policy Provides practical implications from the findings for educators, policy makers and program designers. Highlights the gaps in academic knowledge as a lack in the use of AI for assessment in ELT/L.

ChatGPT Earns American Board Certification in Hand Surgery

PurposeArtificial Intelligence (AI), and specifically ChatGPT, has shown potential in healthcare, yet its performance in specialized medical examinations such as the Orthopaedic Surgery In-Training Examination and European Board Hand Surgery diploma has been inconsistent. This study aims to evaluate the capability of ChatGPT-4 to pass the American Hand Surgery Certifying Examination. MethodsChatGPT-4 was tested on the 2019 American Society for Surgery of the Hand (ASSH) Self-Assessment Exam. All 200 questions available online (https://onlinecme.assh.org) were retrieved. All media-containing questions were flagged and carefully reviewed. Eight media-containing questions were excluded as they either relied purely on videos or could not be rationalized from the presented information. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT-4. The ASSH report was used to compare ChatGPT-4’s performance to that of the 322 physicians who completed the 2019 ASSH self-assessment. ResultsChatGPT-4 answered 192 questions with an overall score of 61.98%. Performance on media-containing questions was 55.56%, while on non-media questions it was 65.83%, with no statistical difference in performance based on media inclusion. Despite scoring below the average physician’s performance, ChatGPT-4 outperformed in the ‘vascular’ section with 81.82%. Its performance was lower in the ‘bone and joint’ (48.54%) and ‘neuromuscular’ (56.25%) sections. ConclusionsChatGPT-4 achieved a good overall score of 61.98%. This AI language model demonstrates significant capability in processing and answering specialized medical examination questions, albeit with room for improvement in areas requiring complex clinical judgment and nuanced interpretation. ChatGPT-4’s proficiency is influenced by the structure and language of the examination, with no replacement for the depth of trained medical specialists. This study underscores the supportive role of AI in medical education and clinical decision-making while highlighting the current limitations in nuanced fields such as hand surgery.

Exploring the Unknown: Evaluating ChatGPT's Performance in Uncovering Novel Aspects of Plastic Surgery and Identifying Areas for Future Innovation

BackgroundArtificial intelligence (AI) has emerged as a powerful tool in various medical fields, including plastic surgery. This study aims to evaluate the performance of ChatGPT, an AI language model, in elucidating historical aspects of plastic surgery and identifying potential avenues for innovation.MethodsA comprehensive analysis of ChatGPT's responses to a diverse range of plastic surgery-related inquiries was performed. The quality of the AI-generated responses was assessed based on their relevance, accuracy, and novelty. Additionally, the study examined the AI's ability to recognize gaps in existing knowledge and propose innovative solutions. ChatGPT’s responses were analysed by specialist plastic surgeons with extensive research experience, and quantitatively analysed with a Likert scale.ResultsChatGPT demonstrated a high degree of proficiency in addressing a wide array of plastic surgery-related topics. The AI-generated responses were found to be relevant and accurate in most cases. However, it demonstrated convergent thinking and failed to generate genuinely novel ideas to revolutionize plastic surgery. Instead, it suggested currently popular trends that demonstrate great potential for further advancements. Some of the references presented were also erroneous as they cannot be validated against the existing literature.ConclusionAlthough ChatGPT requires major improvements, this study highlights its potential as an effective tool for uncovering novel aspects of plastic surgery and identifying areas for future innovation. By leveraging the capabilities of AI language models, plastic surgeons may drive advancements in the field. Further studies are needed to cautiously explore the integration of AI-driven insights into clinical practice and to evaluate their impact on patient outcomes.Level of Evidence VThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266

OpenAI ChatGPT, Google Bard, and Microsoft Bing: Similarity Index and Analysis of Artificial Intelligence-Based Contents

This research compares AI language models—specifically, OpenAI's ChatGPT, Google's Bard, and Microsoft's Bing—by analyzing their originality, use of external sources, and performance. Conducted on August 5, 2023, the study evaluates how these models respond to different queries, revealing distinct characteristics. ChatGPT stands out with lower similarity scores and lesser reliance on online sources, indicating its potential for creating more unique content. In contrast, Bard and Bing show higher similarity scores, suggesting they draw more from available online content, which could be beneficial for tasks requiring context-rich information. While ChatGPT and Bard excel in grasping context, generating substantial content, and offering relevant insights, there are concerns about accuracy and consistency across queries. Notably, Bing's focus on aiding content creation rather than direct essay generation showcases diverse strengths among AI models. As AI technology progresses, refining these models and addressing inconsistencies will improve their usefulness across various applications. These findings guide users in choosing AI tools that fit their content needs and ensure the credibility of generated outputs.

Delving into educators’ perspectives on ChatGPT in management education: a qualitative exploration

PurposeThis study aims to delve into the perspectives of educators on integrating ChatGPT, an AI language model into management education. In the current research, educators were asked to talk as widely as possible about the perceived benefits, limitations of ChatGPT in management education and strategies to improve ChatGPT for management education. Also, shedding light on what motivates or inhibits them to use ChatGPT in management education in the Indian context.Design/methodology/approachInterpretative phenomenological analysis commonly uses purposive sampling. In this research, the purpose is to delve into educators’ perspectives on ChatGPT in management education. The data was collected from the universities offering management education in Uttarakhand, India. The final sample size for the study was constrained to 57 educators, reflecting the point of theoretical saturation in data collection.FindingsThe present study involved educators discussing the various advantages of using ChatGPT in the context of management education. When educators were interviewed, their responses were categorized into nine distinct sub-themes related to the benefits of ChatGPT in management education. Similarly, when educators were asked to provide their insights on the limitations of using ChatGPT in management education, their responses were grouped into six sub-themes that emerged during the interviews. Furthermore, in the process of interviewing educators about potential strategies to enhance ChatGPT for management education, their feedback was organized into seven sub-themes, reflecting the various approaches suggested by the educators.Research limitations/implicationsIn the qualitative study, perceptions and experiences of educators at a certain period are captured. It would be necessary to conduct longitudinal research to comprehend how perceptions and experiences might change over time. The study’s exclusive focus on management education may not adequately reflect the experiences and viewpoints of educators in another discipline. The findings may not be generalizable and applicable to other educational disciplines.Practical implicationsThe research has helped in identifying the strengths and limitations of ChatGPT as perceived by educators for management education. Understanding educators’ perceptions and experiences with ChatGPT provided valuable insight into how the tool is being used in real-world educational settings. These insights can guide higher education institutions, policymakers and ChatGPT service providers in refining and improving the ChatGPT tool to better align with the specific needs of management educators.Originality/valueAmid the rising interest in ChatGPT’s educational applications, a research gap exists in exploring educators’ perspectives on AI tools like ChatGPT. While some studies have addressed its role in fields like medical, engineering, legal education and natural sciences, the context of management education remains underexplored. This study focuses on educators’ experiences with ChatGPT in transforming management education, aiming to reveal its benefits, limitations and factors influencing adoption. As research in this area is limited, educators’ insights can guide higher education institutions, ChatGPT providers and policymakers in effectively implementing ChatGPT in Indian management education.