This study aims to uncover the trends in Turkish experts’ views on the ethical concerns surrounding recommendation systems that use machine learning.
Abstract
Purpose
This study aims to uncover the trends in Turkish experts’ views on the ethical concerns surrounding recommendation systems that use machine learning.
Design/methodology/approach
This study used a Q-methodology approach. To apply Q-methodology, a document review was first conducted as a meta study of meta studies. Then, to create a Q-set, semi-structured interviews were conducted with ten experts. Finally, the Q-methodology was conducted with 42 academics.
Findings
Turkish academics have diverse perspectives on the ethics of recommender systems. All groups agree on the importance of safeguarding user data and ensuring its ethical use, including concerns about data confidentiality and security and preventing data from being sold, stolen or monopolized by companies. Individualistic thinkers believe that recommendation systems have a minimal impact on social issues, such as polarization and inequality, and argue that users benefit from these services. Social thinkers emphasize the need to understand how these systems work and hold individuals accountable for their actions. Anxious thinkers are concerned about the potential for human rights violations and unfair competition through biased algorithms and agree that companies should not be the sole focus of regulations.
Originality/value
To the best of the author’s knowledge, no study has investigated Turkish academics’ thoughts on AI ethics. It is also rare for research to be conducted methodologically using the Q-methodology. Although the findings are based on a recommender system, the results can be generalized to all machine learning systems.