Reflections on the ethics, potential, and challenges of artificial intelligence in the framework of quality education (SDG4) (original) (raw)

ETHICAL REFLECTIONS IN THE USE OF AI FOR TEACHING AND LEARNING

ANVESAK, 2024

Given the rise in the use of Artificial Intelligence (AI) in educational settings, ethical considerations have become more significant. This review of existing literature delves into the ethical aspects of AI implementation in education, with the goal of clarifying both its advantages and difficulties. By thoroughly examining current studies, this review synthesizes main ethical concerns such as privacy issues, algorithmic prejudices, autonomy, responsibility, and socioeconomic impacts. It also looks at established ethical frameworks and guidelines for the ethical integration of AI in educational environments. The review highlights the necessity of enhancing digital literacy and ethical consciousness among stakeholders to effectively tackle potential hazards. By scrutinizing the ethical landscape, this article offers valuable perspectives for educators, policymakers, and researchers to navigate the ethical intricacies linked to AI-supported teaching and learning.

Ethics of AI in Education: Towards a Community-Wide Framework

International Journal of Artificial Intelligence in Education, 2021

While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically, to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community’s leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise...

The use of AI in education: Practicalities and ethical considerations'. London Review of Education

Reiss, M. J. (2021) The use of AI in education: Practicalities and ethical considerations. London Review of Education, 19(1), 5, 1-14. , 2021

There is a wide diversity of views about the potential for AI, ranging from overenthusiastic pronouncements about how it is going imminently to transform our lives to alarmist predictions about how it is going to cause everything from mass unemployment to the destruction of life as we know it. In this article I look at the practicalities of AI in education and at the attendant ethical issues it raises. My key conclusion is that AI in the near to medium-term future has the potential to enrich student learning and to complement the work of (human) teachers without dispensing with them. In addition, AI should enable such traditional divides as ‘school versus home’ increasingly to be straddled with regards to learning. AI offers the hope of increasing personalisation in education but is accompanied by risks of learning becoming less social. There is much that we can learn from previous introductions of new technologies in school to help maximise the likelihood that AI can help students both to flourish and to learn powerful knowledge. Looking further ahead, AI has the potential to be transformative in education and it may be that such benefits will first be seen for students with special educational needs. This is to be welcomed.

Ethical guidelines for AI in education: Starting a conversation

International Journal of Artificial Intelligence in Education, 2000

Dedication to Martial Vivet The first author of this paper had the good fortune to interact with Martial Vivet over many years; in particular with Martial and his colleagues and students in Le Mans for five weeks during the Spring of 1999. His passing has left us without an important voice in the AI & Education community. In addition to his many professional contributions he was an inspiration to many students and colleagues. His warm personality, his adherence to rigorous scientific standards and his concern for the people with whom he interacted will always be a beacon for us to follow. He was concerned about ethics and the impact, both for good and potential harm, that AI research could have on education. It is in his memory and with his concern for students that we would like to dedicate this paper.

Challenges and opportunities of artificial intelligence in education in a global context

Review of Artificial Intelligence in Education, 2023

Objective: The objective of "Generative AI and the Future of Education" by Stefania Giannini at UNESCO is to examine the transformative impact of generative artificial intelligence (AI) on the educational sector, focusing on the implications for teaching, learning, and knowledge dissemination. Method: The document employs a qualitative analysis, drawing on existing literature, case studies, and theoretical frameworks to explore the integration of AI technologies in education. It addresses the challenges and opportunities presented by AI, emphasizing the need for a balanced approach to its adoption in educational settings. Results: Giannini identifies several key areas where AI has the potential to revolutionize education, including personalized learning, accessibility, and the democratization of knowledge. However, the document also highlights significant challenges, such as ethical concerns, the digital divide, and the need for adequate regulatory frameworks to ensure equitable and safe use of AI in education. Practical Implications and Conclusions: The document advocates for the development of comprehensive strategies to harness the potential of AI in education responsibly. It calls for international collaboration among policymakers, educators, and technologists to create inclusive, equitable, and human-centered educational systems. Giannini concludes that with thoughtful integration, AI can enhance educational outcomes, but emphasizes the importance of maintaining a focus on human values and critical thinking skills.

Artificial intelligence in education: Addressing ethical challenges in K-12 settings

AI and Ethics

Artificial intelligence (AI) is a field of study that combines the applications of machine learning, algorithm productions, and natural language processing. Applications of AI transform the tools of education. AI has a variety of educational applications, such as personalized learning platforms to promote students' learning, automated assessment systems to aid teachers, and facial recognition systems to generate insights about learners' behaviors. Despite the potential benefits of AI to support students' learning experiences and teachers' practices, the ethical and societal drawbacks of these systems are rarely fully considered in K-12 educational contexts. The ethical challenges of AI in education must be identified and introduced to teachers and students. To address these issues, this paper (1) briefly defines AI through the concepts of machine learning and algorithms; (2) introduces applications of AI in educational settings and benefits of AI systems to support students' learning processes; (3) describes ethical challenges and dilemmas of using AI in education; and (4) addresses the teaching and understanding of AI by providing recommended instructional resources from two providers-i.e., the Massachusetts Institute of Technology's (MIT) Media Lab and Code.org. The article aims to help practitioners reap the benefits and navigate ethical challenges of integrating AI in K-12 classrooms, while also introducing instructional resources that teachers can use to advance K-12 students' understanding of AI and ethics.

Ethical Considerations in AI Integration in Education

Redshine , Swedan, 2024

Artificial Intelligence (AI) in education has enormous potential to transform learning processes, personalize instruction, and enhance educational outcomes. To guarantee that AI in education serves all students while preserving their rights and well-being, a variety of ethical problems must be addressed in addition to this transformational potential. This abstract examines the ethical issues surrounding the use of AI in education, concentrating on three key areas: privacy, bias, and equity. The collection and use of student data raises privacy issues in the context of AI integration. Strong data security and protection measures must be put in place, informed consent must be obtained, and the privacy implications of AI surveillance must be addressed. These efforts must be guided by ethical values like data anonymization and openness. Another important component of integrating ethical AI is bias prevention. Biases existing in training data can be amplified and sustained by AI systems, producing discriminating results. To make sure that AI systems in education promote justice and diversity, it is essential to have methods for bias discovery, varied and representative datasets, and regular audits. In order to prevent escalating educational inequities, equity issues must be prioritized. It is crucial to provide fair access and individualized support for all students because the digital gap and socioeconomic constraints may make it difficult for some students to utilize AI resources. Ethical principles emphasize how critical it is to remedy these injustices in order to level the playing field. Overall, the article promotes multidisciplinary collaboration, ongoing monitoring, and the responsibility of educators while highlighting the significance of ethical frameworks for AI inclusion in education. It emphasizes how ethical AI integration may improve educational results and experiences while respecting privacy, justice, and equity as fundamental values, ultimately paving the path for an ethical and just future for AI integration in education. Keywords: AI Integration, Education, Ethical Considerations, Privacy, Equity.