Unethical Use Research Articles

Beyond boundaries: exploring a generative artificial intelligence assignment in graduate, online science courses.

Generative artificial intelligence (GAI) offers increased accessibility and personalized learning, though the potential for inaccuracies, biases, and unethical use is concerning. We present a newly developed research paper assignment that required students to utilize GAI. The assignment was implemented within three online, asynchronous graduate courses for medical laboratory sciences. Student learning was assessed using a rubric, which rated students' effective integration and evaluation of GAI-generated content against peer-reviewed research articles, thus demonstrating their critical thinking and synthesis skills, among other metrics. Overall rubric scores were high, suggesting that learning outcomes were met. After field testing, we administered a 16-item survey about GAI utilization, contribution to learning, and ethical concerns. Data (n = 32) were analyzed, and free-response answers were thematically coded. While 93.8% of respondents found the GAI-generated content to be "very good" or "excellent," 28.1% found inaccuracies, and 68.8% "strongly agreed" or "agreed" that GAI should be allowed to be used as a tool to complete academic assignments. Interestingly, however, only 28.1% "strongly agreed" or "agreed" that GAI may be used for assignments if not explicitly authorized by the instructor. Though GAI allowed for more efficient completion of the project and better understanding of the topic, students noted concerns about academic integrity and the lack of citations in GAI responses. The assignment can easily be modified for different learning preferences and course environments. Raising awareness among students and faculty about the ethical use and limitations of GAI is crucial in today's evolving pedagogical landscape.

Investigating academics’ attitudes towards ChatGPT: A qualitative study

ChatGPT, at the forefront of artificial intelligence advancement, has caused excitement and scepticism within academic spheres due to its potential to affect academic processes. Understanding attitudes towards ChatGPT could help manage expectations and concerns for ChatGPT in academia, predict behaviour and inform policy. This study aimed to develop an understanding of university academics’ attitudes towards ChatGPT. A total of 11 university academics participated in semi-structured interviews. Data analysis found three main themes: (a) ethics, (b) changes to academic processes and (c) accessibility and inclusivity. Results showed academics had positive attitudes towards ChatGPT overall; however, they held negative attitudes towards the unethical use of the technology. Key findings included discrepancies in perceptions of academics’ personal ethical use of ChatGPT compared to unethical use by others. Furthermore, academics viewed ChatGPT as a useful tool for saving time and enhancing research processes and student learning. Finally, ChatGPT could increase equity among diverse groups, though it should be used with caution. Future studies could conduct a longitudinal study and recruit a larger and wider sample exploring specific and/or multidisciplinary domains for research diversity and the generalisability of findings. Implications for practice or policy: Academic policy and codes of conduct concerning the use of ChatGPT in research and education can be refined to address key ethical concerns, such as plagiarism. Academic educators and researchers can save time and improve processes using ChatGPT to attain better work-life balance and thus potentially improve the quality of their work.

Medical Students' Ethical Use of Information and Communication Technologies

The purpose of this study was to investigate the ethical tendencies of medical faculty students, their unethical use of information and communication technologies, and their attitudes toward digital ethics in terms of certain variables. The study was designed using a relational survey model. The research group consisted of 335 medical faculty students studying at a state university in Turkey. Data were collected using the "Personal Information Form," the "Ethical Tendencies Scale," Information and Communication Technologies Ethics Scale," and "Attitude towards Digital Ethics Scale." The data analysis revealed that medical faculty students' digital ethical attitudes and ethical tendencies were at a high level and positive, while their unethical use of information and communication technologies was at a very low level. The study's findings indicated that there were gender-related differences in medical students' unethical use of ICT. In addition, there were significant differences in the ethical tendencies of the participating students based on the variable of year of study. Lastly, medical students' unethical use of information and communication technologies were significantly affected by their ethical tendencies and attitudes towards digital ethics.

Ethical issues of social media in Nigeria

This study sought to analyse ethical concerns of social media in Nigeria. The theoretical framework adopted is the Source Credibility Theory. The study employed Critical Discourse Analysis. The population of the study consisted of the top four (4) social networking sites in Nigeria. Out of these, Twitter was purposively selected for its widespread use for youth activism, particularly within the context of the #EndSARS protest; and for being the only social media platform the federal government had temporarily banned for ethical violations. A convenient sample of ten (10) tweets, which included retweets with text and images posted both during and within 18 months after the protest, was used to collect secondary data. Findings demonstrated a mix of ethical and unethical use of Twitter within the context of the protest. The result also revealed that although Twitter is a credible source of information, there were instances of anonymous tweets, which cast some doubts on the credibility of that specific source. The study recommends that beyond social media regulations, there is a need for the promotion of media literacy in Nigeria’s workplaces and educational system. In addition, the form of self-regulation inherent in African ethics should be applied by users of social media to facilitate harmonious communication. This study has made a modest contribution in the area of source credibility theory by proposing a conceptual framework within the context of the study.

Co-creation in action: Bridging the knowledge gap in artificial intelligence among innovation champions

The increasing significance of artificial intelligence (AI) in various industries highlights the necessity for industry leaders and professionals to comprehend and gain knowledge about AI. The urgency for AI literacy is more critical than ever due to the potential unethical use of AI resulting from insufficient knowledge. This issue is particularly crucial for educators because they need to understand and adapt to the impact of AI within educational institutions, with some needing to use and become literate in AI, given that students now have increased access to public AI tools. This research presents a multi-phase study to address the issue of bridging the knowledge gap in AI by conducting co-creation with innovation champions, illustrated by a case of Generative AI innovation in a K-12 school. Using action design research, we engaged experienced teachers who are experts in pedagogical innovation to co-create a generative AI-enhanced platform at a leading K-12 education institution known for its pedagogical innovation in Australia. The findings reveal that champions enhance their knowledge through their subject-matter expertise, organizational knowledge, and AI knowledge gained through external exposure and experience. The study also highlights the key elements that facilitate a cross-domain knowledge exchange platform, enabling champions to be exposed to and experience AI technological learning, leading to shifts in their understanding and perception of AI. The initially unaware and sceptical champions become more aware and capable of articulating more technical AI knowledge rooted in a shared value. This research demonstrates how co-creation serves as a pathway for learning AI, particularly among K-12 teachers who are innovation champions. It underscores the impact of experiential and organizational learning on AI collaborative learning and behavioral intentions. Additionally, the study presents that aligning organizational and personal visions and values can influence perceptions about AI technologies, enhancing the discourse on AI and education innovation.

Enhancing the accuracy of stock return movement prediction in Indonesia through recent fundamental value incorporation in multilayer perceptron

PurposeThe study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.Design/methodology/approachThe study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.FindingsIncorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.Research limitations/implicationsThe study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.Practical implicationsGovernments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.Originality/valueStudies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

Students are using large language models and AI detectors can often detect their use

Large language model (LLM) artificial intelligence (AI) has been in development for many years. Open AI thrust them into the spotlight in late 2022 when it released ChatGPT to the public. The wide availability of LLMs resulted in various reactions, from jubilance to fear. In academia, the potential for LLM abuse in written assignments was immediately recognized, with some instructors fearing they would have to eliminate this mode of evaluation. In this study, we seek to answer two questions. First, how are students using LLM in their college work? Second, how well do AI detectors function in the detection of AI-generated text? We organized 153 students from an introductory microbiology course to write essays on the regulation of the tryptophan operon. We then asked AI the same question and had the students try to disguise the answer. We also surveyed students about their use of LLMs. The survey found that 46.9% of students use LLM in their college work, but only 11.6% use it more than once a week. Students are unclear about what constitutes unethical use of LLMs. Unethical use of LLMs is a problem, with 39% of students admitting to using LLMs to answer assessments and 7% using them to write entire papers. We also tested their prose against five AI detectors. Overall, AI detectors could differentiate between human and AI-written text, identifying 88% correctly. Given the stakes, having a 12% error rate indicates we cannot rely on AI detectors alone to check LLM use, but they may still have value.

Despre relevanța perspectivei kantiene în era inteligenței artificiale generative: Provocări etice și tehnice

Since the evolution of computational and communication technologies, the world becomes a global village: society and environment are seen through digital perspectives of faster and wider industrial revolutions that become widely available and influence daily our lives. Generative AI dynamically trained and used on billions of blurred knowledge graphs’ multimodal elements becomes a growing technological presence with impact. New scientific and regulatory debates address, alongside the opportunities of generative AI presence in economy and society, the challenges that could, on one side, reinvent technologies and the humanity through the Singularity hypothesis, and one the other side, open its availability for unethical, improper, or illegal use of „black box” learning. Within dynamically challenging tsunami of big data, information and knowledge systems, the need of contemporary wisdom captured within AI could benefit from the well-known and visionary ethical yet traditional philosophical foundations. The need to adapt the technology based on well-known and accepted logics to unsafe, opaque decisions finds solid foundations in philosophical ethics. This paper critically reviews recent scientific articles on AI challenges, the Kantian perspective, and ethics foundations that argue the need of human in the loop for the current progresses of generative AI. The role of Kantianism in the ethical perception of AI and its accent on reason and reasoning for ethics, as well as other traditional ethical theories such as theory of virtue and utilitarianism, arguably request the presence of human values at the centre of AI and justify the argument of this paper that current challenges of transparency, explainability, fairness, responsibility of AI technologies can be addressed by consistent transitions from data-centred technologies to human-centred and scientifically quantifiable solutions for the next industrial revolution(s). The paper includes case studies of ethical and common-sense challenges for the use of „black box” models in healthcare, paediatric robotics, also refers to other potential applications such autonomous decision making or creativity. The paper ends with arguments and open questions on opportunities and challenges for AI and philosophy scientists with a focus on ethical aspects of AI technologies.

Pengaruh Etika Berbahasa Indonesia Yang Buruk di Media Sosial Terhadap Individu

especially among young people. However, the use of social media can also cause various problems, including the use of unethical language. This research discusses the influence of poor Indonesian language etiquette on social media on individuals. In this research, researchers used descriptive methods to identify language errors that occur on social media, especially on Instagram. The research results show that the use of Indonesian on social media often experiences errors in spelling, diction and grammatical structure. These mistakes can lead to misunderstandings and ineffective use of language. Apart from that, this research also found that the use of Indonesian on social media often experiences variations in Indonesian with English, slang and local regional languages. The conclusion of this research shows that the unethical use of Indonesian on social media can have a negative impact on individuals. Therefore, more awareness and attention is needed in using Indonesian on social media in order to communicate effectively and not cause misunderstandings.

Misi Kontemporer: Utilitas Teknologi Dalam Misi Kristen Masa Kini

This research aims to describe the importance of using or exploiting technology in carrying out the mission of today's church. Contemporary Christian mission cannot be accomplished by itself, even ignoring the importance of technology in it. Based on an investigation using the library research method, this research found that the role of technology in today's Christian Mission is vital and cannot be ignored. However, the use of technology in the context of Christian Missions must also pay attention to Christian ethical principles and consider the consequences of unethical use of technology. With the right strategy and adequate development of technological skills, technology can be an effective tool to assist Christian Missions in sharing the message of God's truth and love.

A Qualitative Analysis of ML Method in Fruits Adultery and Focus on Fruit Adulteration Detection

Detecting formalin can be difficult and time- consuming without exact chemical knowledge. The presence of naturally occurring formalin in food products can additionally make it more difficult to distinguish between formalin that has been purposefully added. The method for dynamic and precise food and formalin identification described in this work is machine learning-based. Preserving food practises that put public nutrition in jeopardy include the unethical use of formalin. It was decided what kind of food to provide based on conductive characteristics. With the use of a VOC HCHO gas sensor and a Renesas, the gadget has the ability of detecting formalin concentrations of 1 to 50 ppm. Polynomial regression has been used in a number of investigations to simulate the application of formalin.

The relationship between personal and professional goals and emotional state in academia: a study on unethical use of artificial intelligence.

Artificial Intelligence (AI) is a concept that has been a subfield of computer science since the 1950s. In recent years, with its growing development power, AI technologies have made significant progress and are now being used in many fields. Like in all areas, the use of AI technologies in academia has provided convenience to academics while also bringing ethical debates. In the literature part of the study, concepts such as AI, academia, academics and academic progress, ethics, ethical theories, academic ethics, and emotional states have been thoroughly examined and defined. In this study, starting from AI and scientific ethics, ethical issues arising from emotional states in academic research have been identified, and concrete solutions to these ethical issues have been proposed. The aim is to discuss the views of academics in order to determine what types of scientific ethical violations and prevention methods are involved. In this context, the semi-structured interview technique, which is one of the qualitative research methods, was preferred as the method. In the study, in-depth semi-structured interviews were conducted with 4 ethics experts and 4 psychology experts selected through snowball sampling technique. The data obtained through semi-structured in-depth interviews will be analyzed using content analysis. Within the context of the literature review and interviews: Ethics is based on the foundation of acting correctly. In this context, scientific ethics can be summarized as acting truthfully and honestly, not distorting data, and not trying to progress unfairly. The use of AI in academia is becoming increasingly widespread. From a positive perspective, this usage significantly contributes to making studies more practical. However, it can lead to problems such as unfair authorship, devaluation of human authorship, and incorrect data. The connection between academics' professional advancement goals and emotional states becomes prominent in this context. The potential of AI to facilitate progression can lead to unethical use. To prevent such situations, it is recommended to organize training sessions to increase professional awareness, internalize ethics personally, establish ethical committees specific to the field of AI, conduct more effective audits by academic publication and promotion committees, and implement specific regulations for AI. Finally, for future academic studies, it is suggested that the usage of AI in academic research be measured and evaluated by ethics experts. For psychologists, conducting surveys with academics to explore how they use AI in the context of their emotional states and professional advancement goals is recommended.

Attitudes of oncology patients’ towards biospecimen donation for biobank research

BackgroundSince the biological material that remains after diagnostic and therapeutic procedures plays crucial role in biobank research, this study aims to explore cancer patients’ views on the donation of biospecimens for research purposes.Methods548 oncology patients from two hospitals with oncology treatment units in Poznan, Poland, completed an anonymous, self-administered pen-and-paper questionnaire.ResultsAlthough only 43.4% of patients had heard of biobanks, 93.1% declared themselves willing to donate. 71.1% of patients believed that doctors should ask patients to donate, and 60.9% that this should be done before the medical procedure. While 65% of patients were willing to donate any type of tissue that remained after a medical procedure, blood, saliva and hair were indicated most frequently. 40.5% of patients would donate their entire body after death and 21% would refuse. Patients’ support for biobanks was mainly driven by the desire to support science, help advance cancer research and altruism. Some respondents expected health information or medical treatment. The most common barriers for donation were physical distance, repeated examinations, concerns over the privacy and confidentiality of data and the commercial or unethical use of samples. Patients’ attitudes toward biobank donation seemed to be associated with age, education level, declared religiousness, a family history of genetically determined diseases and whether they were a blood donor.ConclusionsAlthough cancer patients’ lack of biobank awareness had no effect on their affirmative attitudes towards biobank research, there is a need to further increase patients’ support and overcome possible barriers that might hinder their willingness to donate.

Ethical Issues of Social Media in Nigeria

This study sought to analyse ethical concerns of social media in Nigeria. The theoretical framework adopted is the Source Credibility Theory. The study employed Critical Discourse Analysis. The population of the study consisted of the top four (4) social networking sites in Nigeria. Out of these, Twitter was purposively selected for its widespread use for youth activism, particularly within the context of the #EndSARS protest; and for being the only social media platform the federal government had temporarily banned for ethical violations. A convenient sample of ten (10) tweets, which included retweets with text and images posted both during and within 18 months after the protest, was used to collect secondary data. Findings demonstrated a mix of ethical and unethical use of Twitter within the context of the protest. The result also revealed that although Twitter is a credible source of information, there were instances of anonymous tweets, which cast some doubts on the credibility of that specific source. The study recommends that beyond social media regulations, there is a need for the promotion of media literacy in Nigeria’s workplaces and educational system. In addition, the form of self-regulation inherent in African ethics should be applied by users of social media to facilitate harmonious communication. This study has made a modest contribution in the area of source credibility theory by proposing a conceptual framework within the context of the study.

Navigating the AI frontier: Should we fear ChatGPT use in higher education and scientific research? Finding a middle ground through guiding principles and practical applications

The adoption of Artificial Intelligence-based chatbots, including ChatGPT, in various sectors has raised concerns about their implications in higher education and scientific research. While the academic world aims to foster critical thinking and produce reliable research, the use of chatbots has elicited resistance from some academics due to fears of inaccuracies. In this paper, we extensively examine this phenomenon in higher education and scientific research, seeking to understand its practical applications, limitations, and potential risks. We investigated how ChatGPT is currently being used by academia, young researchers, and students. We also identified its areas of application and conducted trials by engaging ChatGPT, with transcripts included in the paper. Based on our findings, we discuss the results in the context of the needs in higher education and scientific research, presenting guidelines for responsible adoption. We distinguish positive use cases, areas requiring caution, explicit limitations of ChatGPT, and cases of unethical use. Importantly, we view ChatGPT as a valuable technological innovation but emphasize the necessity for thoughtful and responsible implementation. While we do not consider its use inherently deceitful, consistent, and shared guidelines are essential to ensure its ethical and effective application.

What if ChatGPT generates quantitative research data? A case study in tourism

研究目的本研究旨在探讨ChatGPT是否能够为那些可能通过数据伪造行为不道德的研究人员生成定量数据集。研究方法本研究进行了与旅游领域相关的两阶段案例研究, 并要求ChatGPT（v.3.5.）代表400名参与者回答第一个问卷, 以及代表800名参与者回答第二个问卷。通过描述统计、相关分析、探索性因子分析、验证性因子分析和哈曼的单因素测试对人工智能生成的数据集的质量进行了统计测试。研究发现结果显示, ChatGPT能够按照所需的样本大小水平回答问卷, 并以表格格式呈现生成的数据集, 以便进行分析。还观察到ChatGPT的回答是系统性的, 并且它创建了一个在统计上理想的数据集。然而, 本研究注意到所产生的数据在观察变量之间存在较高的相关性, 测量模型未能达到足够的拟合度, 并出现了共同方法偏差的问题。本研究得出的结论是, ChatGPT目前不能生成适用于高级统计分析的数据, 或者说不适合这样做。研究创新本研究表明, ChatGPT可以为试图不道德地伪造数据集的研究人员提供定量数据。因此, 它为关于ChatGPT不道德使用的持续争论提供了一个新而重要的论点。此外, 在本研究中首次对由人工智能生成的定量数据集进行了统计检验。结果表明, ChatGPT生成的数据在某些方面存在问题, 为期刊编辑在编辑过程中考虑的几个要点提供了启示。

Determinants of Google Workspace Usage and Collaborative Learning among University Students in Selangor

Technology for education can assist students' learning goals while opening new avenues for critical thinking, communication, collaboration, and creativity. One of the platforms used by students is Google Workspace, a cloud-based productivity suite developed by Google. However, the problem of insufficient support for sharing content and the unethical use of information system services has become a major concern highlighted in this study. The quantitative findings in this study show a correlation between the usage of Google Workspace and the Collaborative Learning Environment and a recommendation to upskill students with digital literacy skills and ethics of information use.

Publication Ethics in the Era of Artificial Intelligence.

The application of new technologies, such as artificial intelligence (AI), to science affects the way and methodology in which research is conducted. While the responsible use of AI brings many innovations and benefits to science and humanity, its unethical use poses a serious threat to scientific integrity and literature. Even in the absence of malicious use, the Chatbot output itself, as a software application based on AI, carries the risk of containing biases, distortions, irrelevancies, misrepresentations and plagiarism. Therefore, the use of complex AI algorithms raises concerns about bias, transparency and accountability, requiring the development of new ethical rules to protect scientific integrity. Unfortunately, the development and writing of ethical codes cannot keep up with the pace of development and implementation of technology. The main purpose of this narrative review is to inform readers, authors, reviewers and editors about new approaches to publication ethics in the era of AI. It specifically focuses on tips on how to disclose the use of AI in your manuscript, how to avoid publishing entirely AI-generated text, and current standards for retraction.

RESTRICTED DATA MANAGEMENT: THE CURRENT PRACTICE AND THE FUTURE.

Many organizations across the world that manage restricted data have adapted the Five Safes framework (safe data, safe projects, safe people, safe setting, safe output) for their management of restricted and confidential data. While the Five Safes have been well integrated throughout the data life cycle, organizations encounter several challenges with regard to safe data management. In this paper, we review current practices for restricted data management, and discuss challenges and future directions. We focus on data use agreements, disclosure risk review, and training. In the future, organizations managing restricted data may need proactively to take into consideration reducing inequalities in access to scientific data, preventing unethical use of data, and managing various types of data.

Can spiritual power reduce online cheating behavior among university students? The fraud triangle theory perspective

PurposeAlthough the academic literature provides extensive insight into the motivations for the unethical use of information technology in online classes, little is known about how perceived justice, the opportunity to cheat and spiritual legitimacy mitigate unethical behavior among young academics. The purposes of this study are two folds: first, to determine how perceived lecturers’ justice and opportunity to cheat may mitigate academic misconduct in online classes, and second, to evaluate the moderating effect of spiritual power on the relationship between perceived lecturers’ justice and opportunity to cheat and academic misconduct.Design/methodology/approachThis research was conducted at universities in three Southeast Asia countries, including Indonesia, Malaysia and Thailand, with a total of 339 respondents. The research questionnaire was distributed using Google Forms. The analytical method used to test the research hypothesis is moderated regression analysis (MRA).FindingsThe findings of this study reveal that spirituality moderates the relationship between lecturer justice and the opportunity to cheat online. Even though the justice level of the lecturer is low, individuals with relatively high spirituality will show much less cheating behavior than when there is a low level of lecturer justice and a low level of student spirituality, and vice versa.Research limitations/implicationsCheating occurs when students develop an intention to cheat, which leads to actual involvement in cheating, meaning that theoretically, the findings extend the fraud triangle theory. In addition, the practical implications of this research are that lecturers need to conduct fair teaching, such as transparency of exam conditions, assessment, the right to an opinion and supervision during exams, consequently, the students cannot cheat. Spirituality is also an essential factor that can reduce online cheating, so instilling spirituality in specific courses is a fruitful solution.Originality/valueThe contributions of this study are twofold. First, this study gives testable theories on how spiritual help works. Second, this study offers tailored and more humanistic assistance, such as a mechanism that adjusts to the academic world’s usage of more positive technologies. This study contributes to the literature on online cheating in higher education across three Southeast Asian nations (Indonesia, Malaysia and Thailand).