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Ethical and Privacy Issues When Using AI Tools

The use of AI in education leads to various ethical challenges. Ethics in AI examines the moral implications and responsibilities of developing, deploying, and using artificial intelligence systems.1 This page provides an overview of the main ethical challenges of the use of AI in education and also shows recommendations for action on how to address these challenges. 

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Risk of bias 

Artificial intelligence can be trained with data that is biased, which can lead to biased, erroneous, and or unfair results. It is necessary for educational intuitions and educators to take steps to identify these problems in the system. There also needs to be a person responsible for the continuous monitoring of the results presented by the AI. 

How to react? Students as well as educators should be made aware of the risk of bias and discrimination of AI systems and sensitised to the topic of critically questioning AI-generated content. For this purpose, training and further education can be offered, for example. Especially educational institutions and teachers should take steps to identify problems such as discrimination in assessment systems. It can be helpful to assign extra persons who are responsible for monitoring AI-generated results.

Lack of transparency

AI systems can be complex and difficult to understand, which can make it difficult for teachers and students to understand how decisions are being made. Furthermore, with some tools the decision is inherently opaque, as with deep learning or Convolutional Neural Network. Consequently, it’s harder to trust the data and opinions presented by artificial intelligence.

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How to react? If possible, it is helpful, to know how the data was collected, from where and how the conclusion on a certain issue was made.

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Privacy and Data concerns

AI collects a large amount of data from teachers and lecturers, which can lead to privacy concerns. Users of AI tools must actively consent to this data collection, but this consent is more or less forced when educational institutions require the use of AI tools. In this case, educators as well as students and parents have no choice but to agree.

How to react? It is important to comply with the General Data Protection Regulation (GDPR) and make sure to use appropriate security measures to protect and lectures student data und privacy.

Over-dependence on technology

If artificial intelligence systems are used inappropriately, there can be a risk that teachers and students become over-dependent on these technological tools, which can hinder teaching and learning, losing important skills and knowledge. 

How to react? Students as well as teachers should keep in mind that AI tools should only support their own work and cannot completely replace their own creativity and skills. Doing your own research, for example, is a key skill. AI-generated content can be used as a starting point, but should be supplemented by the own research.

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Job Losses

The use of AI potentially threatens the jobs of teachers and others working in education. Therefore, there could be job losses as the tools save costs in the long run.

How to react? Instead of cutting jobs, tasks should be realigned. AI can help to make certain tasks more efficient, allowing teachers more time for other activities, such as individual support or creative lesson design. Retraining and professional development programmes can also enable them to take on new tasks that AI cannot replace, such as providing individual attention and support to learners. AI can also create new areas of work, such as the creation of digital learning content.

Sources

Akgun, S. & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical  

challenges in K-12 settings, AI Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681- 021-00096-7 

 

Borenstein, J. & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics  

education, AI Ethics, 1(2), 61-65. https://doi.org/10.1007/s43681-020-00002-7 

 

Iyer, R., Li, Y., Li, H., Lewis, M., Sundar, R. & Sycara, K.  (Februar, 2018).  

Transparency and Explanation in Deep Reinforcement Learning Neural Networks [Conference paper]. AIES '18: Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, New York, USA. https://doi.org/10.1145/3278721.327877  

 

European Union (2022). Use of artificial intelligence (AI) and data in teaching and learning. https://www.internetsegura.pt/sites/default/files/2022-11/ethical-guidelines-on- the-use-of-artificial-intelligence-nc0722649enn.pdf 

 

UNESCO (2022). Recommendation on the Ethics of Artificial Intelligence. https://apee.pt/wp-content/uploads/2023/03/381137eng.pdf 

University of Adelaide (o.D.) How to work with Artificial Intelligence - the University of Adelaide. https://www.adelaide.edu.au/student/academic-  
skills/ua/media/234/artificial-intelligence-student-slides-v0.1.pdf 

 

Zawacki-Richter, O., Marín, V., Bond, M. & Gouverneur, F. (2019). Systematic  

review of research on artificial intelligence applications in higher education - where are the educators, International Journal of Educational Technology in Higher Education, 16(39), 1-27. http://dx.doi.org/10.1186/s41239-019-0171-0 

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