Dear Prof. Juan Luis Cabanillas García,

I just want to give a note to your sentence "It also questions the authenticity and trustworthiness of AI-generated data": I found the following related paragraph in the "Turnitin":

"What does qualifying text mean?

Sometimes false positive (incorrectly flagging human-written text as AI generated), can include lists without a lot of structural variation, text that literally repeats itself, or text that has been paraphrased without developing new ideas.If our indicator shows a higher amount of AI writing in such text, we advise you to take that into consideration when looking at the percentage indicated."

وترجمة ذلك النص إلى اللغة العربية تقول

في بعض الأحيان، يمكن أن تتضمن الإيجابية الكاذبة قوائم لا تحتوي على الكثير من الاختلافات الهيكلية، أي الحُكم بوضع علامات غير صحيحة على النص المكتوب بواسطة البشر على أنه تم إنشاؤه بواسطة الذَّكَاء الْاِصْطِنَاعِيّ، أو وضع هذه العلامات على النص الذي يكرر نفسه حرفيًا، أو وضعها على النص الذي تمت إعادة صياغته دون تطوير أفكار جديدة. إذا أظهر مؤشر هذه البرمجية قدرًا أكبر من كتابة الذَّكَاء الْاِصْطِنَاعِيّ في مثل هذا النص، فننصحك بأخذ ذلك بعين الاعتبار عند النظر إلى النسبة المئوية المشار إليها.

Authenticity and trustworthiness of AI-generated data...........

AI - generated data ... know your tool as a double edged sword honed within the parameters of the craftsmens' knowledge.

There is so much more to Knowledge itself.

Dear Doctor

Go To

Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis Special Issue Next-Generation Programming Education: Integrating Generative AI and Collaborative Tools for Cutting-Edge Learning Experiences Edited by Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis

• June 2024
• Information 15(6)
• DOI: 10.3390/info15060325
• License CC BY 4.0
• 📷Saba Mansoor Qadhi, 📷Ahmed M. S. Alduais, 📷Youmen Chaaban, Majeda Khraisheh

[Abstract

In the digital age, the intersection of artificial intelligence (AI) and higher education (HE) poses novel ethical considerations, necessitating a comprehensive exploration of this multifaceted relationship. This study aims to quantify and characterize the current research trends and critically assess the discourse on ethical AI applications within HE. Employing a mixed-methods design, we integrated quantitative data from the Web of Science, Scopus, and the Lens databases with qualitative insights from selected studies to perform scientometric and content analyses, yielding a nuanced landscape of AI utilization in HE. Our results identified vital research areas through citation bursts, keyword co-occurrence, and thematic clusters. We provided a conceptual model for ethical AI integration in HE, encapsulating dichotomous perspectives on AI's role in education. Three thematic clusters were identified: ethical frameworks and policy development, academic integrity and content creation, and student interaction with AI. The study concludes that, while AI offers substantial benefits for educational advancement, it also brings challenges that necessitate vigilant governance to uphold academic integrity and ethical standards. The implications extend to policymakers, educators, and AI developers, highlighting the need for ethical guidelines, AI literacy, and human-centered AI tools.]

Dear Juan Luis Cabanillas García , I do recommend the following source:

Mapping the Ethics of Generative AI: A Comprehensive Scoping Review

"The advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios."

Article Mapping the Ethics of Generative AI: A Comprehensive Scoping Review