AI ethics and learning: EdTech companies’ challenges and solutions

Abstract

The aim of this study is to identify the ethical challenges, solutions and needs of educational technology (EdTech) companies. Qualitative data was collected in interviews with seven experts from four companies, and the data was analysed using inductive content analysis. The four main areas of challenges were ambiguous regulations, inequalities in human learning, ethical dilemmas in machine learning (ML) and lack of ability to assess consequences in society. According to the studied companies, AI regulations are difficult to understand and implement. There is also much to be done in terms of reliability, transparency, and safety. Consequently, companies suggested that AI-based products should be more preventive, safe, explicable, and equally accessible. Sufficient information, multi-professional support also within company, global collaboration, sharing best practices, and general discussion were emphasised. The results show that EdTech companies are aware of their ethical challenges, and their responsibility as disseminators of information. However, translating information into practice is challenging because it is often very fragmented and difficult to understand. Companies hoped that everyone: themselves, consumers, educational institutions, researchers, funders, and decision-makers would do more together to overcome the ethical challenges of AI.

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