Need a balancing act to shape AI’s role in education

The use of Artificial Intelligence (AI) in education presents a wide range of ethical implications that need to be carefully considered and addressed. AI systems in education often collect and analyse vast amounts of student data. Ensuring the privacy and security of this data is crucial. There is a risk of data breaches, misuse of personal information, and the potential for profiling students based on their data.

AI in education can exacerbate existing educational inequalities. Not all students have access to the same technology or resources, and those without access may be left behind. Ensuring equitable access to AI-driven educational tools and resources is essential. What measures can be taken to ensure that AI-powered educational tools do not exacerbate existing educational inequalities?

According to Dr Rajesh Bagga, Director, Apeejay Institute of Management & Engineering Technical Campus (AIMETC), Jalandhar, we must prevent AI-powered educational tools from worsening existing educational inequalities.

“We must ensure that all our students, regardless of their backgrounds or circumstances, have equal access to AI-powered tools. We may need to provide necessary resources, such as devices or internet connectivity, to those who need them. We must be vigilant in using diverse datasets to train AI algorithms. This diversity should encompass various demographic groups so that our AI systems do not inadvertently favour or discriminate against any particular group,” Dr Bagga said.

There is a need to regularly assess the performance of AI systems to detect and rectify any biases or disparities. This requires continuous evaluation to ensure that the technology benefits all students equally. We should maintain complete transparency in our use of AI.

“We must be clear about how AI is employed in our educational processes, what data it collects, and how it influences decision-making. This transparency helps build trust among our stakeholders, including educators, students, and parents. Once, we take these measures, we can harness the potential of AI in education while upholding our commitment to fairness and equal opportunity for all our students,” Dr Bagga opined.

Personalise learning & protect student privacy

Dr Bagga said that personalised learning with student privacy is a matter of trust and responsibility. By following certain set guidelines, educators and institutes can provide a safe and conducive learning environment while harnessing the benefits of AI-driven personalisation.

“We must obtain informed consent from students or their guardians before collecting any personal data. It is essential to communicate what data will be gathered, how it will be used, and for what educational purposes. We must ensure that any collected data is anonymized and aggregated to protect individual identities. This allows for the benefits of personalisation without compromising privacy. We must maintain transparency in data handling practices. Inform students, educators, and parents about how their data is used and who has access to it,” Dr Bagga said.

We must be clear about how AI is employed in our educational processes, what data it collects, and how it influences decision-making. This transparency helps build trust. Once, we take these measures, we can harness the potential of AI in education

–Dr Rajesh Bagga, Director, Apeejay Institute of Management & Engineering Technical Campus, Jalandhar

Not just the students, the integration of AI technology in classrooms transform the role of teachers from traditional lecturers to dynamic facilitators of personalised learning experiences as well.

This evolution empowers educators to engage more deeply with their students and adapt their teaching methods to better serve individual learning needs. Teachers can collaborate with AI systems to provide adaptive instruction. AI can identify areas where students may need additional help, and teachers can step in to provide targeted support, ensuring that no student is left behind.

Collaborative learning experiences between students and AI systems

“To foster collaborative learning experiences between students and AI systems, thoughtful design and implementation are essential. We can design AI interfaces that encourage active student engagement. These interfaces should be user-friendly and intuitive, facilitating easy communication and interaction with the AI system. We can incorporate AI into virtual group projects that require students to work together. The AI system can assign tasks, facilitate communication, and provide real-time feedback on group progress,” Dr Bagga said and shared some key strategies.

AI-Powered Discussion Forums: We can create AI-moderated discussion forums where students can collaborate on assignments, share ideas, and ask questions. The AI can help maintain a productive and respectful online environment.

Adaptive Learning Paths: We must develop AI systems that adapt learning materials based on student collaboration. For example, if two students are working together on a project, the AI can suggest relevant resources or topics to explore.

Peer Feedback: We can implement AI-driven peer feedback systems that encourage students to review and provide constructive feedback on each other’s work. The AI can assist in identifying areas for improvement and facilitating peer assessments.

Virtual Labs and Simulations: We can use AI to create virtual labs and simulations that require collaborative problem-solving. Students can work together to conduct experiments, analyze data, and draw conclusions.

Feedback Mechanisms: We can continuously gather feedback from students about their collaborative experiences with AI. Use this feedback to refine the AI systems and improve the collaborative learning process.

“AI can play a pivotal role in enhancing collaborative learning experiences among students, promoting teamwork, critical thinking, and problem-solving skills, while also facilitating a deeper understanding of the subject matter,” Dr Bagga said in conclusion.