Do AI tutors empower or enslave learners? Toward a critical use of AI in education
- URL: http://arxiv.org/abs/2507.06878v1
- Date: Wed, 09 Jul 2025 14:15:49 GMT
- Title: Do AI tutors empower or enslave learners? Toward a critical use of AI in education
- Authors: Lucile Favero, Juan-Antonio Pérez-Ortiz, Tanja Käser, Nuria Oliver,
- Abstract summary: The paper argues that while AI can support learning, its unchecked use may lead to cognitive atrophy.<n>The paper advocates for an intentional, transparent, and critically informed use of AI that empowers rather than diminishes the learner.
- Score: 7.673465837624366
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The increasing integration of AI tools in education presents both opportunities and challenges, particularly regarding the development of the students' critical thinking skills. This position paper argues that while AI can support learning, its unchecked use may lead to cognitive atrophy, loss of agency, emotional risks, and ethical concerns, ultimately undermining the core goals of education. Drawing on cognitive science and pedagogy, the paper explores how over-reliance on AI can disrupt meaningful learning, foster dependency and conformity, undermine the students' self-efficacy, academic integrity, and well-being, and raise concerns about questionable privacy practices. It also highlights the importance of considering the students' perspectives and proposes actionable strategies to ensure that AI serves as a meaningful support rather than a cognitive shortcut. The paper advocates for an intentional, transparent, and critically informed use of AI that empowers rather than diminishes the learner.
Related papers
- Evaluating AI-Powered Learning Assistants in Engineering Higher Education: Student Engagement, Ethical Challenges, and Policy Implications [0.2812395851874055]
This study evaluates the use of the Educational AI Hub, an AI-powered learning framework, in undergraduate civil and environmental engineering courses at a large R1 public university.<n>Students appreciated the AI assistant for its convenience and comfort, with nearly half reporting greater ease in using the AI tool.<n>While most students viewed AI use as ethically acceptable, many expressed uncertainties about institutional policies and apprehension about potential academic misconduct.
arXiv Detail & Related papers (2025-06-06T03:02:49Z) - Must Read: A Systematic Survey of Computational Persuasion [60.83151988635103]
AI-driven persuasion can be leveraged for beneficial applications, but also poses threats through manipulation and unethical influence.<n>Our survey outlines future research directions to enhance the safety, fairness, and effectiveness of AI-powered persuasion.
arXiv Detail & Related papers (2025-05-12T17:26:31Z) - Student Perspectives on the Benefits and Risks of AI in Education [0.49157446832511503]
The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years.<n>The adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases.<n>To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the United States.
arXiv Detail & Related papers (2025-05-04T17:36:11Z) - AI Identity, Empowerment, and Mindfulness in Mitigating Unethical AI Use [0.0]
This study examines how AI identity influences psychological empowerment and unethical AI behavior among college students.<n>Findings show that a strong AI identity enhances psychological empowerment and academic engagement but can also lead to increased unethical AI practices.<n>IT mindfulness acts as an ethical safeguard, promoting sensitivity to ethical concerns and reducing misuse of AI.
arXiv Detail & Related papers (2025-03-25T22:36:21Z) - AI in Education: Rationale, Principles, and Instructional Implications [0.0]
Generative AI, like ChatGPT, can create human-like content, prompting questions about its educational role.<n>The study emphasizes deliberate strategies to ensure AI complements, not replaces, genuine cognitive effort.
arXiv Detail & Related papers (2024-12-02T14:08:07Z) - Imagining and building wise machines: The centrality of AI metacognition [78.76893632793497]
We examine what is known about human wisdom and sketch a vision of its AI counterpart.<n>We argue that AI systems particularly struggle with metacognition.<n>We discuss how wise AI might be benchmarked, trained, and implemented.
arXiv Detail & Related papers (2024-11-04T18:10:10Z) - Combining AI Control Systems and Human Decision Support via Robustness and Criticality [53.10194953873209]
We extend a methodology for adversarial explanations (AE) to state-of-the-art reinforcement learning frameworks.
We show that the learned AI control system demonstrates robustness against adversarial tampering.
In a training / learning framework, this technology can improve both the AI's decisions and explanations through human interaction.
arXiv Detail & Related papers (2024-07-03T15:38:57Z) - Assigning AI: Seven Approaches for Students, with Prompts [0.0]
This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools.
The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student.
arXiv Detail & Related papers (2023-06-13T03:36:36Z) - Cybertrust: From Explainable to Actionable and Interpretable AI (AI2) [58.981120701284816]
Actionable and Interpretable AI (AI2) will incorporate explicit quantifications and visualizations of user confidence in AI recommendations.
It will allow examining and testing of AI system predictions to establish a basis for trust in the systems' decision making.
arXiv Detail & Related papers (2022-01-26T18:53:09Z) - Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society.
A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests.
This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
arXiv Detail & Related papers (2021-06-25T22:31:55Z) - An interdisciplinary conceptual study of Artificial Intelligence (AI)
for helping benefit-risk assessment practices: Towards a comprehensive
qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence.
The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
arXiv Detail & Related papers (2021-05-07T12:01:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.