5.5 How Do Ethical Issues around AI Effect Vocational Education and Training?
Artificial intelligence is having an increasingly rapid impact on education in general and, in particular, on vocational education and training and the activities and practices of teachers and trainers in this field. First of all, AI and automation are leading to changes in the world of work. This requires new initial and continuing vocational training programs to deal with these changes and prepare the future workforce. In addition, AI is increasingly being used in education in a range of different approaches including learning analytics and the development of personal learning pathways, for formative assessment, for the development of learning materials, and for administration. However, there are growing concerns over the ethical issues around AI in general and in the use of AI in education. Technological Innovation does not always equate to social progress, and education has long raised concerns over equity. The turn to online teaching and learning in the COVID-19 pandemic has raised the issue of access, not only to computers but to spaces for learning at home. The increasing use of AI-based assessment systems has led to online proctoring applications which have been widely criticized for bias and for excluding learners with disabilities for example. The wider issues of bias in AI also impact education, for instance through the use of AI-based programs for teacher recruitment. Widespread concerns have been expressed over surveillance of students monitoring their attention in the classroom and online, especially in China and the USA.
Learning Analytics opens another area of discussion, including the purpose of LA, what rights learners have to their data, the interpretation of LA data and how institutions should intervene based on predictive analysis. An important issue here is equality. According to UNESCO, only 12 percent of AI developers are women. Less than 2% of employees in technical roles at Facebook and Google are black. Little wonder then that in many applications, AI is seen as biased towards white men.
We talked with Dr.-Ing. Fereshta Yazdani about what AI can and can not do and data bias.
Reflexion
All the aspects discussed in the previous learning units, such as transparency, fairness and human supervision, also play a central role in AI applications in education. And yet there are further special features. Namely, ethical educational questions must also be asked specifically. e.g. What is the purpose of learning? What pedagogical means should be chosen? How should the relationship between technology and teachers be shaped?
Activity
What ethical issues do you think need to be discussed in the educational context?
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The equitable use of data.