The use and ethical implications of artificial intelligence in scientific research and academic writing DOI
Serkan Dinçer

Deleted Journal, Journal Year: 2014, Volume and Issue: 1(2), P. 139 - 144

Published: Sept. 15, 2014

The integration of artificial intelligence into scientific research has significantly changed methodologies, including data analysis, literature review and academic writing. This paper aims to explore the diverse applications tools in its relationship with ethics. shows that accelerate processes, especially data-intensive fields, by improving efficiency accuracy analysis review. It also highlights growing role writing, where such as ChatGPT streamline text generation editing. However, rapid adoption sparked ethical debates, particularly around integrity, originality reliability generated sources. assesses these emerging challenges need for clear guidelines. Ultimately, it concludes are a powerful tool can greatly benefit if used responsibly, but unethical practices manipulation plagiarism must be avoided. Human oversight remains essential ensure use processes.

Language: Английский

Academics’ Weak(ening) Resistance to Generative AI: The Cause and Cost of Prestige? DOI Creative Commons
Richard Watermeyer, Donna Lanclos, Lawrie Phipps

et al.

Postdigital Science and Education, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Abstract The disruptive potential of generative AI (GenAI) tools to academic labour is potentially vast. Yet as we argue herein, such also represent a continuation the inequities inherent academia’s prestige economy and intensified hierarchy precarisation endemic universities institutions. In recent survey n = 284 UK-based academics, reasons were put forward for avoiding GenAI tools. These responses surface concerns about automative technologies corrupting identity inauthenticating scholarly practice; that are salient all who participate within benefit from work communities. discussion these results, explore ambivalence whether expedite acquisition or depletion demanded especially where adopted increase productivity. We appraise whether, far helping academics cope with climate hyper-intensifcation, ultimately exacerbate their vulnerability, status-based peripheralisation, self-estrangement.

Language: Английский

Citations

4
Generative Artificial Intelligence and Usage in Academia DOI Open Access
İsmail Yoşumaz

Fırat Üniversitesi Sosyal Bilimler Dergisi, Journal Year: 2025, Volume and Issue: 35(1), P. 1 - 24

Published: Jan. 24, 2025

Artificial intelligence is not a new concept. However, it has reached an important point with technological development. Today, there are many software developed using artificial and various application areas where they used. Generative intelligence, one of these areas, technology in machine learning aiming to generate content by training on large data sets. used fields such as health, business, finance, e-commerce, academic studies, R&D. This study evaluates the use generative applications field. In this context, differences similarities between texts generated ChatGPT, Claude Sonet, Google Gemini prepared human were analyzed regarding subject integrity, language, ethics, plagiarism rate. Descriptive analysis, qualitative methods, was study. As result, concluded that similar integrity content, rates vary according language.

Language: Английский

Citations

0
Progress and challenges in the symbiosis of AI with science and medicine DOI
Zhicheng Lin

European Journal of Clinical Investigation, Journal Year: 2024, Volume and Issue: 54(10)

Published: April 12, 2024

The author declares no competing interests.

Language: Английский

Citations

3
Delving into PubMed Records: Some Terms in Medical Writing Have Drastically Changed after the Arrival of ChatGPT DOI Creative Commons
Kentaro Matsui

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 16, 2024

Abstract It is estimated that ChatGPT already widely used in academic paper writing. This study aims to investigate whether the usage of specific terminologies has increased, focusing on words and phrases frequently reported as overused by ChatGPT. The list 118 potentially AI-influenced terms was curated based posts comments from anonymous users, 75 common were controls. PubMed records 2000 2024 (until April) analyzed track frequency these terms. Usage trends normalized using a modified Z-score transformation. A linear mixed-effects model compare over time. total 26,403,493 investigated. Among terms, displayed meaningful increase (modified ≥ 3.5) 2024. showed significant effect compared (p < 0.001). noticeable starting 2020. revealed certain phrases, such “delve,” “underscore,” “meticulous,” “commendable,” have been more medical biological fields since introduction rate words/phrases increasing for several years before release ChatGPT, suggesting might accelerated popularity scientific expressions gaining traction. identified this can provide valuable insights both LLM educators, supervisors fields. Author Summary Artificial intelligence systems rapidly integrated into writing, particularly investigates changes By analyzing 2024, we tracked them with phrases. study’s findings reveal ‘delve,’ ‘underscore,’ ‘meticulous,’ ‘commendable’ saw marked However, trend actually began around suggests while some large language may their adoption literature. Furthermore, analysis highlights impact extends beyond new altering style commonly Understanding help researchers educators see how AI tools are shaping

Language: Английский

Citations

3
Overviewing the Maze of Research Integrity and False Positives Within AI-Enabled Detectors DOI
Mussa Saidi Abubakari

Advances in educational technologies and instructional design book series, Journal Year: 2024, Volume and Issue: unknown, P. 335 - 366

Published: Sept. 20, 2024

Academic writing in the current times is significantly different from what it was a decade ago. Most prevalent today's digital world disruption caused by Artificial Intelligence (AI) tools employed to assist academic works. In this chapter, we overview ongoing trend of ethical challenge and implications using AI-text detection systems for fostering research integrity. Using literature on topic, chapter has presented real-world cases where individuals have complained that platforms like provided Turnitin flagged (as AI-generated) content edited language AI assistive Grammarly translators. Furthermore, reviewing up-to-date empirical studies, an false-positive scenario these their biases towards non-native English writers. Finally, provides, besides future outlook practical implications, including consideration fair transparent AI-based tool usage policies.

Language: Английский

Citations

3
Beyond principlism: practical strategies for ethical AI use in research practices DOI
Zhicheng Lin

AI and Ethics, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 8, 2024

Language: Английский

Citations

2
AI in Academic Writing: Ally or Foe? DOI Open Access
Arthur William Fodouop Kouam

International Journal of Research Publications, Journal Year: 2024, Volume and Issue: 148(1)

Published: April 16, 2024

This paper delves into the burgeoning field of AI in academic writing, exploring complex interplay between technology and scholarly communication. By examining advantages, limitations, ethical considerations employing tools this study sheds light on potential impact writing processes work quality. The findings offer a nuanced understanding benefits using such as enhanced efficiency, accuracy, accessibility, alongside challenges posed by lack subjectivity, bias algorithms, overreliance technology. Ethical surrounding use including plagiarism detection, data privacy, fairness, are also discussed. contributes to existing literature providing comprehensive analysis implications practices, highlighting need for collaboration, education, responsible promoting integrity innovation. Future research avenues suggested further explore critical thinking, develop guidelines academia, examine effectiveness diverse genres. underscores importance navigating complexities harness its while upholding standards fostering culture technological

Language: Английский

Citations

1
Neural Network Methods in the Development of MEMS Sensors DOI Creative Commons
Yan Liu,

Mingda Ping,

Jizhou Han

et al.

Micromachines, Journal Year: 2024, Volume and Issue: 15(11), P. 1368 - 1368

Published: Nov. 12, 2024

As a kind of long-term favorable device, the microelectromechanical system (MEMS) sensor has become powerful dominator in detection applications commercial and industrial areas. There have been series mature solutions to address possible issues device design, optimization, fabrication, output processing. The recent involvement neural networks (NNs) provided new paradigm for development MEMS sensors greatly accelerated research cycle high-performance devices. In this paper, we present an overview progress, applications, prospects NN methods sensors. superiority leveraging structural compensation/calibration is reviewed discussed illustrate how NNs reformed Relevant usage NNs, such as available models, dataset construction, parameter are presented. Many application scenarios demonstrated that can enhance speed predicting performance, rapidly generate device-on-demand solutions, establish more accurate calibration compensation models. Along with improvement efficiency, there also several critical challenges need further exploration area.

Language: Английский

Citations

1
GAI Identity Threat: When and Why Do Individuals Feel Threatened? DOI
Jing Zhou, Yaobin Lu, Qian Chen

et al.

Information & Management, Journal Year: 2024, Volume and Issue: unknown, P. 104093 - 104093

Published: Dec. 1, 2024

Language: Английский

Citations

1
Beyond principlism: Practical strategies for ethical AI use in research practices DOI Open Access
Zhicheng Lin

Published: Sept. 19, 2023

The rapid adoption of generative artificial intelligence (AI) in scientific research, particularly large language models (LLMs), has outpaced the development ethical guidelines, leading to a “Triple-Too” problem: too many high-level initiatives, abstract principles lacking contextual and practical relevance, much focus on restrictions risks over benefits utilities. Existing approaches—principlism (reliance principles), formalism (rigid application rules), technological solutionism (overemphasis fixes)—offer little guidance for addressing challenges AI research practices. To bridge gap between day-to-day practices, user-centered, realism-inspired approach is proposed here. It outlines five specific goals use: 1) understanding model training output, including bias mitigation strategies; 2) respecting privacy, confidentiality, copyright; 3) avoiding plagiarism policy violations; 4) applying beneficially compared alternatives; 5) using transparently reproducibly. Each goal accompanied by actionable strategies realistic cases misuse corrective measures. I argue that requires evaluating its utility against existing alternatives rather than isolated performance metrics. Additionally, propose documentation guidelines enhance transparency reproducibility AI-assisted research. Moving forward, we need targeted professional development, programs, balanced enforcement mechanisms promote responsible use while fostering innovation. By refining these adapting them emerging capabilities, can accelerate progress without compromising integrity.

Language: Английский

Citations

2