AI Needs To Be Explainable When It Enters the Classroom

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AI is transforming education with personalized learning and data-driven insights, but there are ethical challenges to consider including bias and privacy. Explainable AI (XAI) ensures transparency, accountability, and can foster trust, acting as an ethical guardian in an education setting.

In today’s dynamic educational landscape, the infusion of artificial intelligence (AI) is redefining the way students learn and educators teach.

AI-powered tools promise personalized learning experiences, inclusivity, and data-driven insights, but they also bring forth a pressing need: transparency, accountability, and ethical considerations.

This article explores how Explainable AI (XAI) is the key to elevating ethical education and enhancing accountability and understanding in education.

AI in Education

Like its impact on various industries, AI is reshaping education by addressing significant challenges.

A key concern in modern education is the high rate of student disengagement caused by a rigid, one-size-fits-all curriculum, a lack of personalized attention, inflexible schedules, and limited student autonomy.

AI offers a solution through personalized learning experiences, adapting to individual needs with adaptive learning, tailoring materials with personalized content creation, and providing real-time guidance through interactive engagement. It resembles having a personal tutor.


Besides personalization, AI is crucial in fostering inclusivity in education. It helps people with language barriers or disabilities through tools like Presentation Translator, which provides instant subtitles, ensuring that a diverse audience can access education.

Furthermore, AI streamlines administrative responsibilities, such as grading and admissions processes, freeing up valuable time for educators to focus on their students, and data-driven insights provide educators with invaluable resources to enhance their teaching methods, ultimately increasing the effectiveness and efficiency of education.

Ethical Challenges and Imperatives

The rapid integration of AI into education brings a significant set of ethical challenges that demand our attention. These challenges include algorithmic bias, data privacy concerns, and the imperative of ensuring equitable access to AI-powered educational tools, regardless of a student’s background.

Ethical learning isn’t merely an optional consideration; it’s an absolute necessity. The potential for AI to inadvertently perpetuate bias, infringe upon privacy, or show favoritism towards certain student groups underscores the critical importance of responsible AI development.

Ethical learning must be a foundational principle that guides the entire process, from designing and deploying AI systems to their day-to-day use in educational settings. It is the linchpin that ensures that AI in education adheres to ethical standards, respects individual rights, and creates an inclusive and fair learning environment for all.

What is Explainable AI?

Explainable AI (XAI) seeks to enhance AI transparency by clearly explaining its decisions. Unlike traditional black-box AI, XAI aims for transparency, interpretability, and accountability, which are essential for trust, ethics, and human comprehension of AI processes.

Transparency means AI should be as clear as a see-through window so we can understand its decisions. Interpretability ensures AI’s actions are like a well-written book, easy for us to read and comprehend. Accountability means AI takes responsibility for its actions, just as humans do for their choices.

In education, XAI ensures that AI-driven systems follow these goals, just like having a teacher who provides solutions and teaches you the problem-solving process. This can foster trust in AI technologies and facilitate a deeper understanding of its role and decisions.

Enhancing Accountability with XAI

One of XAI’s remarkable strengths lies in its ability to detect and correct biases within educational algorithms (PDF). Sometimes, AI systems unintentionally perpetuate biases from their training data. With its transparency, XAI exposes these biases, making them visible and actionable.

Imagine XAI as a responsible teacher who openly shares their grading criteria, leaving no room for confusion.

Educational institutions operate under specific standards and regulations to maintain quality and fairness. XAI acts as a compliance officer, guaranteeing that AI-powered tools meet these educational standards.

In this context, it is helpful to picture XAI as a rulebook that AI must follow, creating a level playing field for all learners.

Fostering Understanding Through XAI

XAI is like the interpreter in the world of AI, making complex AI-driven recommendations and decisions understandable for students and educators. It takes the obscure language of algorithms and translates it into plain English.

Imagine a student receiving a recommendation to study a particular topic. Without XAI, it might feel like a random suggestion. But with XAI, it’s like having a personal tutor explain, “You’re receiving this recommendation because your recent quiz scores show you need more practice in this area.”

Ethical Learning and XAI

XAI isn’t just about understanding AI; it’s also about ensuring ethical learning practices within AI-driven education.

When educational AI applications are being built, XAI can flag potential ethical issues, such as algorithm bias. Imagine it as an alert system that says, “This AI tool might favor certain groups. Let’s address this bias to ensure fairness for all students.”

Refining AI models using XAI feedback is iterative, like a feedback loop. XAI continually assesses AI systems, identifying any deviations from ethical guidelines.

When it detects issues, it’s like a quality control inspector signaling, “We’ve found a problem here; let’s fix it.” This iterative process ensures that AI aligns more closely with ethical standards over time.

Let’s take a real-world example. Suppose an AI-driven language learning app unintentionally introduces gender bias in its vocabulary recommendations. XAI identifies this bias and recommends changes, ensuring the app promotes inclusive language learning. This is like having an ethical guardian that ensures AI remains aligned with educational values.

In essence, XAI’s role in ethical learning is pivotal. It identifies ethical concerns and guides the continuous improvement of AI systems to create a more ethically sound educational environment.

The Bottom Line

XAI is essential for ethical education in the AI era, needed to ensure transparency, correct biases, and interpret AI decisions to create better understanding.

XAI acts as an ethical guardian, continuously refining AI systems to align with educational values, making it vital in education.


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Dr. Tehseen Zia
Tenured Associate Professor
Dr. Tehseen Zia
Tenured Associate Professor

Dr. Tehseen Zia has Doctorate and more than 10 years of post-Doctorate research experience in Artificial Intelligence (AI). He is Tenured Associate Professor and leads AI research at Comsats University Islamabad, and co-principle investigator in National Center of Artificial Intelligence Pakistan. In the past, he has worked as research consultant on European Union funded AI project Dream4cars.