AI Ethical Considerations in the Classroom

AI Ethical Considerations in the Classroom

 

Authored By: Ayishat Sandra Olanrewaju

Abstract

The rise of ethics in artificial intelligence (AI) is crucial to its proper application, whether in the classroom or outside of it. As educators and students learn to embrace AI in the classroom, the question of ethical considerations arises, and these considerations need to be thoroughly examined to provide a safe and wholesome learning experience. In cases where the internet is left with no guardrails, there may arise issues with wrong usage and abuse of it. The classroom is supposed to be a place of learning, and to enable scholars and professionals to effectively learn, the usage of AI in the classroom needs to be ethically guarded. This paper critically examines the ethical considerations in AI usage in the classroom by examining how educators and students can effectively utilise AI. It also discussed AI use cases for educators as well as students. The paper was anchored on the uses and gratifications theory. It utilised the desk methodology. The paper concludes that educators and students should no longer shy away from using AI in the classroom, as it can provide a rich, interactive, and comprehensive learning experience. However, it needs to be used with the proper guardrails in place and ethical considerations in mind to ensure the optimal benefits for educators, students, and society. This paper recommends regular training, reading, and upskilling for educators to develop the skills necessary to ethically utilise AI in the classroom. Likewise, it recommends that students also invest their time in learning how to ethically use AI in the classroom.

Keywords: AI, AI in the classroom, AI in education, Artificial Intelligence. Ethical Considerations of AI.

Introduction

The subject of Artificial Intelligence (AI) is no longer “if” but “how”. It is no longer a question of whether there is an influx of AI tools, but how the emergence of AI tools is being managed and utilised. AI is permeating various areas of life, including work, education, healthcare, finance, and many more. According to Nancholas (2023), Artificial intelligence (AI) is an area of computer science enabling machines and devices to accomplish tasks that would otherwise require human intelligence and cognitive abilities.

Conversations are ongoing regarding how to manage its usage, while in some quarters, some are yet to accept its usage. Artificial intelligence has risen from the corridors of the classroom into the classroom and it is now important to ensure its ethical usage for the benefit of all. Questions arise as to how to ensure the intended use of AI is properly checked to benefit educators and learners, also how this would  ultimately impact society.

Scholars and professionals are no longer wondering if AI will be used in the classroom, but are now thinking about the best practices when it comes to classroom usage of AI. As such, it is crucial to examine how scholars and professionals can ethically utilise AI in the classroom. According to Olorunlana (2025), artificial intelligence is transforming education by facilitating an inclusive and personalised teaching environment. Walter (2024) calls for an AI-culture that permeates academic life and fosters an environment where AI is readily used and not feared, comprehended, and critically evaluated.

As such, this paper provides a conceptual discussion about the role of ethical AI in the classroom.

Problem Statement

Some researchers have debated whether AI should be allowed in the classroom, while some have simply wondered how best to use it. As communication and the internet advance, it is essential for scholars and professionals to find out how best to use AI so that they are not caught off guard or lagging behind. Olorunlana (2025) observed that AI poses significant questions about the future of work, ethical responsibility, human identity, and global equity due to its rapid evolution.

Artificial intelligence (AI) is not without its challenges; nevertheless, it offers remarkable possibilities (Olorunlana, 2025). It is important to note that using AI in the classroom is not inherently wrong; however, the wrong usage of it is what constitutes an issue. And that issue can spiral from being one to many. For instance, a wrong citation can lead to dozens of pieces of misinformation being peddled across a nation or worldwide. The Internet is an evolving landscape that is often difficult to control due to how accessible it is. As such, it is important to leverage essential guardrails to enable a safe and ethical usage for the benefit of all.

Olorunlana (2025) noted that societies must guard against the potential misuse of artificial intelligence and unforeseeable consequences while also using their capabilities for the general good. Walter (2024) expressed that the notion of AI literacy arises as a fundamental element of modern education. It focuses on the comprehension and ability to effectively interact with AI technology

Therefore, this paper seeks to examine the ethically safe measures that scholars can utilize to benefit from AI in the classroom.

 

Literature Review

 Uses and Gratifications Theory

The uses and gratifications theory explains how individuals utilize the media for their benefit. For this paper, we look at how educators and students can make use of AI for their benefit. This theory helps to explain how scholars can safely use AI in the classroom to their benefit. According to Vinney (2024), the theory argues that people use media to satisfy certain wants and needs, adding that the theory views the audience as active agents in their media consumption.

Vinney (2024) notes the theory relies on two principles about media users: 1) they are active in the selection of the media they consume; engaged and motivated in the selections. 2) People have their reasons for selecting various media options and rely on the knowledge of their motivations for this. Therefore, this theory helps to understand how educators and students can ethically use AI in the classroom to gratify their teaching and learning needs, respectively.

Methodology

The research method used for this study was the desk research methodology. It utilised secondary data to gain information on the subject matter and draw out findings.

 

Taxonomies of AI

AI did not just start today; AI has been in existence for a while. Olorunlana (2025) observed that a few decades ago, AI emerged as a significant and transformative factor in modern history.

According to Ekwere (2024), AI can be classified in different ways:

1. Hierarchy:Artificial intelligence, machine learning, deep learning, and generative AIs and GPTs
2. Technical (Learning) Methods:Supervised learning, unsupervised learning, and reinforcement learning (RL)
3. Function and Process:Forecasting and regression algorithms, classification, clustering, natural language processing (NLP), image recognition and computer vision, and recommendation systems.

According to Ekwere (2024), it is important to note that the categories are not mutually exclusive, as an AI model can be classified within all three taxonomies. Nancholas (2023) explained that there are various types of AI with their different level of sophistication, capabilities, and uses. The three primary categories include Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI).

 

AI in the Classroom

When the usage of AI in the classroom is discussed, there may be some ambiguity that can be detrimental to its usage. As such, it is important to provide clear and practical examples for educators and students.

According to Nagelhout (2025), the emergence of AI tools like large language models (LLMs) and chatbots has significantly transformed the academic space. Walter (2024) argued for the need for the academic community to consistently engage with AI topics so they remain informed and adept at managing AI tools and concepts. AI will not replace teachers, their unique expertise, nor will it diminish the importance of fostering relationships and cultivating a welcoming, inclusive classroom atmosphere (Aiello, 2025).

Initiatives on educational technology are gaining momentum with the aim of enhancing access to quality education and improving learning experiences (Chisom, Unachukwu, & Osawaru, 2023). The application of AI in education can promote interactive collaboration while also facilitating content production and curation for both students and teachers (University of Iowa, 2024). According to Walter (2024), technological education should be profound, exploring real-world applications, examining the intersection of theory and practice, and equipping both students and educators with a comprehensive grasp of AI’s impact on society and education.

Taking the case of Africa, Chisom, Unachukwu, and Osawaru (2023) observed that education in Africa faces a pivotal moment of ensuring universal access and improving the quality of education. As such, this paper opines that Africa needs to join global conversations on how to ethically use AI in the classroom. Whether instructors decide to incorporate generative AI intelligence tools in their course or not, it is essential for both the instructors and students to comprehend, evaluate, and familiarize themselves with the uses of the tools (Cornell University, 2024). Walter (2024) recommended that a nuanced approach is crucial for AI literacy in the classroom and academia. Adding that the development of AI literacy courses would be a significant advantage, and the courses should be incorporated into the existing curriculum, spanning across several AI concepts, ethical considerations, and practical applications.

 

AI in the Classroom: For Educators

Some practical examples of how educators can utilize AI in the classroom include:

• Providing Examples and Case Studies: Comprehensive examples and case studies can help make the classroom more interactive and engaging. Educators can leverage several AI tools to come up with examples and case studies relevant to their course, in different formats such as audio, video, text, and the like.
• Presenting Information in an Interactive and Engaging Manner: Educators can leverage AI tools to present information in a way that makes their classes more interesting for learners and, in turn, increases participation. University of Iowa (2024) noted that two significant ways educators are applying AI to enhance learning outcomes include developing vocabulary instruction visual aids and coming up with interactive math lessons.
• Simplifying Complex Topics: Educators can utilize AI to break down complex topics into relatable modes to enhance comprehension and relatability
• Providing More Context to Topics: AI tools can furnish educators with more context for some of the explanations educators provide regarding different subject matters in the classroom.
• Modelling Theories: Some theories need proper examples and applications that AI can generate easily and quickly for educators to use in teaching in the classroom
• Personalized Learning: According to the University of Iowa (2024), educators can utilize AI to customize learning experiences to each student’s needs, enhancing education to be more effective and engaging. Utilizing AI tools, educators can more efficiently develop tailored assignments or resources for each learning level, facilitating each student to advance at their own speed (Aiello, 2025).
• Administrative Tasks: Technologies that are AI-enabled can assist educators in their administrative work, streamline their operations and free up more time for them to concentrate on teaching (University of Iowa, 2024). According to Chisom, Unachukwu, and Osawaru (2023), AI-based platforms can gather and analyze student data on how they engage with educational materials, time used to complete exercises, exam outcomes, and overall performance to comprehend each student’s attitudes and requirements.
• Restoring Old Learning Materials: Through generative AI, the quality of old or low-quality educational resources, such as historical documents, images, and films, can be restored (Dilmegani & Sezer, 2024).
• Developing Course Materials: AI can also help with resource planning, designing curriculum, and continuous support throughout the learning process (Chisom, Unachukwu, & Osawaru, 2023).

 

AI in the Classroom: For Students

Some practical examples of how students can utilize AI in the classroom include:

• Research: AI can synthesize research for students by helping them quickly gather materials on a subject matter.
• Editing: AI can also help students with editing their works or reviews and feedback.
• Experimenting With Data: AI can help students experiment with data and provide case-by-case scenario-based explanations.
• Interpreting Data: Likewise, AI can assist students in gaining insights from data.
• Organizing Study Routines: AI can help students develop customized study routines and plans that are in line with their goals.
• Personalized Learning: In addition, AI can help students develop learning that is customized to their needs. According to Aiello (2025), AI has the ability to function as a personalized educator, and students can obtain customized responses tailored to their own requirements and learning levels.
• Language Learning: AI tools can facilitate language learning by helping students to practice new vocabulary, ask for feedback on their writing, or engage in conversations in foreign languages with AI to enhance fluency (Aiello, 2025).
• Gamified Learning: According to Dilmegani and Sezer (2024), one of the use cases of generative AI is gamified learning, developing engaging quizzes and simulations. Chisom, Unachukwu, and Osawaru (2023) posited that Artificial Intelligence has the ability to transform education from a system focused on memorising facts into one that helps students discover their full potential and learn critical skills through more personalized learning.

AI Tools for the Classroom

Here are some AI tools that can be used in the classroom:

• Chat GPT
• Gemini
• Mindgrasp
• Ai
• To-Teach.ai
• TeacherMatic
• Khanmigo
• Brisk Teaching
• SchoolAi, and the like

 

Ethics Considerations in AI

Cornell University (2024) reiterated that LLMs that power generative AI are as inclusive and fair as the data that informs them. According to Aiello (2025), some best practices of using AI in the classroom include setting clear guidelines for use, encouraging critical evaluation, using AI to enhance and not replace, and providing training and resources on how to use AI. When students actively participate in AI projects, they can develop critical thinking and problem-solving capabilities that are crucial to navigating the complexities of the accelerating digital world (Walter, 2024). Li (2023) observed that in an age where Artificial Intelligence (AI) permeates our daily lives, the ethical oversight of AI technology is essential.

Li (2023) calls for developing regulations that are comprehensive, AI frameworks that are transparent, varied development practices, and aiding ongoing discourse vital for ensuring responsible AI usage becomes the norm. To build literacy in generative AI, there is a need to address ethics, privacy, and equity intentionally (Cornell University, 2024).

According to Cornell University (2024), a few questions instructors and students while critically assessing AI or Generative AI content borders around if the AI-generated content is accurate and how the accuracy can be tested or assessed, if other credible sources that are not generative AI can validate the data, how the generated information impact or influence one’s thinking on the subject matter, the representation of the data and if it is inclusive in terms of scope and perspectives, as well as how to make students know that LLMs may also be collective the data they input and how they can protect their own privacy.

According to Li (2023), some ethical principles in computer vision to include algorithmic fairness which focuses on the importance of having unbiased training datasets, informed consent which is about ensuring autonomy of individuals, public engagement which promotes the active participation of communities impacted by computer vison technologies, robust privacy protocols which is about safeguarding individuals’ privacy rights, and explainability and transparency which fosters clear computer vision algorithms, and then human-in-the-loop systems incorporating human oversight.

 

Here are some ethical considerations when utilizing AI in the classroom:

1. Lack of Transparency: It is crucial to be transparent where AI is used in developing materials for learning in the classroom, so the parties involved are informed and not caught off guard. This also helps to set the right expectations.
2. Plagiarism: There is the risk of plagiarism when content development is discussed when using AI. As such, it is important to avoid passing odd content developed by others through AI as one’s own work. In addition, where sources are used, there should be proper and accurate citations.
3. Confabulation: There is also the risk of AI tools producing results out of context or interpreting prompts the wrong way.
4. Discrimination: There may be risks of some AI generative tools being found discriminatory in their output. According to Li (2023), AI systems, which may amplify prejudices and privacy issues, present intricate ethical challenges, as concerns regarding transparency, discussions on job loss, and global inequalities in AI development intensify these challenges.
5. Inaccuracy: Some results from AI stem from inaccurate sources or made-up data.
6. Data privacy: There is also the risk of how the AI tools safeguard sensitive information that users input into it. However, through training, this can be averted. According to Dilmegani and Sezer (2024), a benefit of adopting generative AI in developing training data sets is its capacity to protect student privacy. When engaging with AI, it is crucial for instructors and students to consider the matter of privacy (Cornell University, 2024).
7. Lack of Fact-checking: If users do not fact-check some of the results gotten from AI, there is the risk of misinformation.
8. Lack of Context: Especially when indigenous nuances are not put into consideration, some AI output may not be contextual, therefore, not relevant to what the user needs.

Conclusion

This study concludes that educators and students should no longer be hesitant about using AI in the classroom, as it can offer a rich, interactive, and comprehensive learning experience. However, it needs to be used with the right guardrails in place and ethical considerations in mind to ensure the optimal benefits for educators, students, and society.

Recommendations

This paper recommends regular training, reading, and upskilling for educators to understand how to ethically use AI in the classroom. Likewise, it recommends that students also invest their time in learning how to ethically use AI in the classroom.

References

Aiello, G. (2025, July 8). How to use AI in the classroom: A guide. Retrieved September 30, 2025, from Cheshire Academy website: https://cheshireacademy.org/how-to-use-ai-in-the-classroom-a-guide/

Chisom, O. N., Unachukwu, C. C., & Osawaru, B. (2023). Review of AI in education: Transforming learning environments in Africa. International Journal of Applied Research in Social Sciences, 5(10), 637–654. https://doi.org/10.51594/ijarss.v5i10.725

Cornell University. (2024). Ethical AI for teaching and learning | Center for teaching innovation. Retrieved September 30, 2025, from teaching.cornell.edu website: https://teaching.cornell.edu/generative-artificial-intelligence/ethical-ai-teaching-and-learning

Dilmegani, C., & Sezer, S. (2024, January 3). Top 6 use cases of generative AI in education. Retrieved September 30, 2025, from research.aimultiple.com website: https://research.aimultiple.com/generative-ai-in-education/

Ekwere, P. (2024, November 13). Types of AI: How are they classified? Retrieved September 30, 2025, from Icaew.com website: https://www.icaew.com/insights/viewpoints-on-the-news/2024/nov-2024/types-of-ai-how-are-they-classified

Li, N. (2023). Ethical considerations in artificial intelligence: A comprehensive disccusion from the perspective of computer vision. SHS Web of Conferences, 179(1), 04024. https://doi.org/10.1051/shsconf/202317904024

Nagelhout, R. (2025, July 9). Developing AI ethics in the classroom. Retrieved September 30, 2025, from Harvard Graduate School of Education website: https://www.gse.harvard.edu/ideas/usable-knowledge/25/07/developing-ai-ethics-classroom

Nancholas, B. (2023, June 7). What are the different types of artificial intelligence? Retrieved September 30, 2025, from University of Wolverhampton website: https://online.wlv.ac.uk/what-are-the-different-types-of-artificial-intelligence/

Olorunlana, T. J. (2025). The rise of artificial intelligence (AI): Challenges and opportunities for humanity. International Journal of Science, Architecture, Technology, and Environment, 02(04). Retrieved from https://ijsate.com/wp-content/uploads/2025/04/V2I4P39_IJSATE042530-.pdf

University of Iowa. (2024, August 27). The role of AI in modern education. Retrieved September 30, 2025, from University of Iowa website: https://onlineprograms.education.uiowa.edu/blog/role-of-ai-in-modern-education

Vinney, C. (2024, July 29). What is uses and gratifications theory? Definition and examples. Retrieved September 30, 2025, from ThoughtCo website: https://www.thoughtco.com/uses-and-gratifications-theory-4628333

Walter, Y. (2024). Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00448-3