Examples of successful implementation of artificial intelligence tools and systems in education – organisational aspect

The use of AI in education requires careful consideration of ethical issues, especially those related to privacy, transparency, and algorithmic fairness. Because AI systems process sensitive personal data from students – including papers, results, and learning habits – institutions must develop clear policies that define how this data is collected, stored, and used.

Such policies typically address:

• Privacy and processing of personal data, in accordance with applicable data protection regulations
• Transparency of AI systems, ensuring that users understand how the system works and on what basis it makes decisions
• Avoidance of bias and discrimination through ongoing testing and evaluation of algorithms to ensure fairness and ethical outcomes.

Example: 

The University of Michigan has developed its own set of generative AI tools within a closed, security-controlled infrastructure.

This ensures that all processes – from data analysis to automated evaluation of written assignments – occur within the framework of strictly defined ethical guidelines and under teacher supervision.

The system is designed to support, not replace, teachers in the assessment process and to provide feedback to students. All algorithms are checked for bias and accuracy, and each result can be manually reviewed before it becomes final. In this way, academic accountability and student trust in the fairness of the evaluation process are maintained.

The University of Michigan’s practice exemplifies responsible institutional use of AI, demonstrating how technical innovation can align with ethical standards and principles of academic integrity. Others can adopt this model, in which AI is not viewed as an autonomous decision-making system but as a tool that supports human oversight, ethics, and transparency in the educational process.

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