The inclusive data governance models for algorithms – a dream of the already convinced or a realistic way of action?

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ABSTRACT The article presents the implications of personal data governance models for algorithmic discrimination. It reflects on the significance of engaging with data subjects to prevent or mitigate discrimination by comparing the effectiveness of the top-down and bottom-up approaches to data governance. The paper goes beyond the option to either decline or agree to terms of service while entering online platforms and argues that bottom-up data governance models of data trusts and information fiduciaries can be more inclusive than the top-down data governance.