Artificial Intelligence for Education – A friend or Foe?

How do technologies get accepted and adapted to? The prevalent models propose that perceptions of emerging technologies’ properties such as job relevance, experience with the technology area, demonstrability of results, and voluntariness to use a technology decide whether an actual implementation of the new system will take place in an organization or in an individual´s professional practice.

In a recent study, results of which were presented in detail in the ECIAIR (European Conference on Impact of Artificial Intelligence and Robotics) 2021 conference, we examined the attitudes, expectations, and questions towards Artificial Intelligence (AI) applicability and impact to the purpose and practice of the teachership within a Finnish Higher Education Institution (later referred to as HEI). Data was collected as a survey-based quantitative study within the four different schools of the HEI, its support units and on all hierarchical layers within. A special focus was on the ethical stances of AI in learning and teaching, mirrored against the Comenius’ Oath used as one optional source of ethical guidance for teachers. (Saukkonen, Huhtala, Rantonen and Vaara, 2021).

On AIEd = Artificial Intelligence for Education

Considerations on AI impacts have long roots. As early as 1995 Beck et al. focused on themes of computer-based training, computer-aided instruction, and intelligent tutoring systems. However, the early optimism vanished and the number of scholarly outputs, as well as practical implementations on the field, was modest for a long. As Welham (2008) put it: “A large number of government-funded initiatives to support the use of technology in learning still continue but they seldom include specific emphases on the use of AI.” Lately, however, AI as a field has risen back to being a hyped-about technology across areas of application.

The core question in the last two decades has not anymore been whether AI can deliver to education, but rather on what kind of advancements have been taken and would be needed for more comprehensive AI adoption to the field of education. Woolf et al. (2015) proposed that AI supports educational goals by providing (1) mentors for every learner; (2) learning 21st-century skills; (3) interaction data for learning; (4) universal access to global classrooms; and (5) lifelong and life-wide learning.

Ethical eye on education and teachership

Education has been stated to an ethics-laden area of activity (Martin, 2013). In the same vein, Martin states that there is a need for grounding in normative professional ethical codes to manage the potential implications of technology usage in e.g. political and socio-technical dimensions. Development steps in the areas of software and automated systems impact not only organizations and their processes but will change the quantity and quality of human employment, which urges the ethical considerations to be studied in parallel with the pure efficiency of such systems.

Ursin and Paloniemi (2015) propose that teacher identity is standing on three pillars: (1) teachership as an activity, (2) teachership as a personal disposition, and (3) teachership as a process. Ursin and Paloniemi also claim the professional identity of a teacher is about balancing personal and social values and needs. According to Day (2019), teachers who have a high commitment to their work are likely to act with quality, vocation, calling and moral purpose. This also calls for clear ethical codes that guide education professionals in their work (Day, 2019). In HEIs the research ethics are widely discussed and visible when compared to teaching ethics.

Comenius’ Oath for teachers – a moral-ethical compass to follow?

In, Finland, these ethical commitments are promoted e.g., via the Comenius Oath for teachers. New teachers may voluntarily take the Oath to demonstrate their commitment to the ethical values and practices of their profession, as the new medical doctors have the Hippocratic Oath and engineers the Archimedes Oath.

Comenius´ Oath (adapted from OAJ, 2017)

“As a teacher, I am engaged in educating the next generation, which is one of the most important human tasks.

My aim in this will be to renew and pass on the existing reserve of human knowledge, culture and skills

I undertake to act with justice and fairness in all that I do and to promote the development of my students, so that each individual may grow up as a complete human being in accordance with his or her aptitudes and talents.

 I will also strive to assist others responsible for working with young people in their educational functions.

 I will not reveal information that is communicated to me confidentially, and I will respect the privacy of young people.

I will also protect their physical and psychological inviolability.

 I will endeavour to shield the young people in my care from political and economic exploitation and defend the rights of every individual to develop his or her own religious and political convictions.

 I will make continuous efforts to maintain and develop my professional skills, committing myself to the common goals of my profession and the support of my colleagues in their work.

I will act in the best interests of the community at large and strive to strengthen the esteem in which the teaching profession is held.”

Case study: Acceptance, adoption and concerns on AI implementation

Our results, presented in full in the Proceedings of ECIAIR 2021 (European Conference on Impact of Artificial Intelligence and Robotics) indicate that despite the fact that the HEI´s internal stakeholders perceive to possess mostly just a basic knowledge level in the area of AI, they have an overall positive attitude on AI, both for education generally and for the HEI in focus.

The potential of AI (measured in perceived “magnitude” of impacts as well as in the positive nature of change AI can bring) was associated with the following elements of Comenius’ Oath: the teachers’ and HEI’s orientation towards the future of the learners, renewal of human knowledge pool, and the commitment to individual professional development. The elements of the Oath where the respondents showed more concerns were related to the protection of rights and individualism of the learners. However, even in these cases, the assessed AI impact was neutral, based on the average of the responses. One can naturally ask if the HEI stakeholders have joint vs. divided view, that the study of just average would hide from sight. Therefore, a look at the highest standard deviations is of need. The respondents somewhat disagreed the benefits of AI to help teachers to assist others in the educational functions and to act for the educational community in a way that supports the value of the teaching profession. This finding proposes there is a perceived risk of growing distances between the people involved with educational processes, i.e., loss of sense of educational community as well as a concern of the value base of AI systems vs. the ethics of education.

Based on the results we claim that AI affects processes and professions in education in contradictory manners. On one hand, AI is regarded as a positive and natural evolution to the skill and knowledge pools of the HEI and people in it, and a “vehicle” towards meaningful education for future learners. We also identified concerns about whether systems built on AI will manage to protect the learners and advance their integrity and holistic personal development. These issues also pose a challenge to the teachers’ role and identity. The Comenius’ Oath appears to be a statement that general by its nature that it bends also to the teaching environment of the AI era. We propose that HEIs and other institutions should explicitly assess, discuss and, if needed, update their ethical principles in the new technology-intensive context. An ambiguity of ethical AI implications can lead to unwanted consequences of tech adoption or hinder the development of the HEI.

Potential ways forward in AIEd research

Studies of the fast-developing technology landscape and its implications bear a risk of obsolescence. As this study focused on perceptions of a technology not yet widely in use in the HEI studied, a longitudinal study in the given context would be recommendable. Also, due to potential context specificity, a comparative study with other HEIs a) in the same societal setting, or, b) different national/cultural contexts would add value to the contribution to the field of study. Another strategy worth pursuing would be a deeper study on the ways people construct their meanings and interpret the opportunities and challenges of emerging technologies such as AI. To achieve that, qualitative research with an interpretative epistemological stance would serve the purpose.

Feel free to join any of these future directions of this quest for knowledge.

by Juha Saukkonen, D.Sc. (Econ.), senior lecturer (management), JAMK Univ. of Applied Sciences, International Business


Beck, J., Stern, M., & Haugsjaa, E. (1996). Applications of AI in Education. XRDS: Crossroads, The ACM Magazine for Students, 3(1), 11–15.

Martin, C. 2013. “On the Educational Value of Philosophical Ethics for Teacher Education: The Practice of Ethical Inquiry as Liberal education.” Curriculum Inquiry 43 (2): 189–209. doi:10.1111/CURI.12010.

OAJ (Trade Union of Education in Finland), (2017) Comenius Oath. Available online: (Accessed on 9th February 2021).

Saukkonen, J., Huhtala, M., Rantonen, M. and Vaara, E. (2021) AI for Learning: Views on Impacts to Teachership in the era of Artificial Intelligence. In Proceedings of the 3rd European Conference on the Impact of Artificial Intelligence and Robotics ECIAIR 2021 A Virtual Conference Hosted By Iscte –Instituto Universitário de Lisboa 18 -19 November 2021, 157-165. Academic Conferences International. Reading, UK.

Ursin, J., & Paloniemi, S. (2019). Conceptions of teachership in the professional identity construction of adult educator graduates. Teacher Development, 23(2), 233–248.

Welham, D. (2008). AI in training (1980–2000): Foundation for the future or misplaced optimism? British Journal of Educational Technology, 39(2), 287–296.

Woolf, B. P., Lane, H. C., Chaudhri, V. K., & Kolodner, J. L. (2013). AI grand challenges for education. AI magazine, 34(4), 66–84.