1. On the Privacy Principle: Since AI applications are also based on personal datasets, care is taken not to reveal the identity and the privacy of the individual when it is necessary to use their personal data, and these datasets must be anonymized. If the AI applications concern the growth of an individual (e.g., individualized learning apps), the other individuals are denied access to the dataset.

2. On the Awareness Principle: Information is given to the owners of the bulk datasets to be used in AI apps, and they are asked to give consent when needed. In addition, training sessions are offered to students, parents, teachers, and staff about the nature of the AI technology, the correct use of such apps, etc. In that respect, content can be integrated into the curriculum, electives can be offered, workshops can be organized, seminars and conferences can be held.

3. On the Inclusion Principle: Inclusion means to make sure that individuals do not feel excluded because of their differences. To ensure this when designing or developing AI applications, the datasets used to feed the respective algorithms are created heterogeneously. For example, if a face recognition AI is used, it is confirmed that it is sensitive to personal traits like skin color, gender, etc. The AI apps also help strengthen the diversity and the solidarity within the institution.

4. On the Individualization Principle: The AI apps offer individualized instruction and experiences to the students. The schools use their own student datasets if possible. Schools that do not have records of past data may use the AI apps developed with general datasets. With time, these schools should reflect their own students’ data onto the AI and localize it. Examples of individualized learning: deciding the content of projects/homework, choosing the electives, improving the living conditions at the school.

5. On the Transparency Principle: The data owners should be given clear and comparative information about how and to what purpose their datasets will be used, and the data which have been used should be shared with them in case they so request.

6. On the Objectivity Principle: One of the major issues related to AI in the current climate is bias. The more heterogeneous the feed datasets are, the more objective is the algorithm output. The AI algorithms are not biased per se. Therefore, it must be remembered that any bias displayed by the AI will originate from the school’s mode of operation in that area. Even when the datasets used for the design or the development of an AI app are the past data of the school, the bias dimension must be analyzed, and if any bias is in question, this must be tackled as a problem to be solved.

7. On the Well-being Principle: The AI apps improve the individuals’ living conditions, health, and working conditions. AI does not prevent the individuals from using their intellectual and physical abilities to full extent. The digital domain created at the school does not increase the individuals’ stress or concerns, it does not make them feel as if others had intruded into their private sphere.

8. On the Sustainability Principle: The AI designs or applications developed within the school should not jeopardize the ecological systems. Applications which contribute to environmental sustainability should be preferred. The AI infrastructure aims for the efficient use of energy.