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Following the large-scale 2015–2016 migration crisis that shook Europe, deploying big data and social media harvesting methods became gradually popular in mass forced migration monitoring. These methods have focused on producing 'real-time' inferences and predictions on individual and social behavioral, preferential, and cognitive patterns of human mobility. Although the volume of such data has improved rapidly due to social media and remote sensing technologies, they have also produced biased, flawed, or otherwise invasive results that made migrants' lives more difficult in transit. This review article explores the recent debate on the use of social media data to train machine learning classifiers and modify thresholds to help algorithmic systems monitor and predict violence and forced migration. Ultimately, it identifies and dissects five prevalent explanations in the literature on limitations for the use of such data for A.I. forecasting, namely 'policy-engineering mismatch', 'accessibility/comprehensibility', 'legal/legislative legitimacy', 'poor data cleaning', and 'difficulty of troubleshooting'. From this review, the article suggests anonymization, distributed responsibility, and 'right to reasonable inferences' debates as potential solutions and next research steps to remedy these problems. [ABSTRACT FROM AUTHOR]

In this theoretical paper, we explore Big Data ethics in the broader context of general data ethics, stakeholder groups, demand for governance and regulation, social norms, and human values. We follow and expand on the digital divide, governance, and regulatory theories, and we apply them to many levels and contexts, such as state and society, organization, enterprise governance of IT (EGIT), and data projects, among others. We introduce the new role and responsibility of data experts as an important stakeholder group in the balance of power of Big Data ethics because they simultaneously hold a position in groups of data-rich organizations and data-poor users. We argue that the balancing role of data experts consists of motivation and competence, a sense of responsibility for data ethics, and the possibility and means to influence Big Data issues. Finally, we conclude our research by model mapping the role of data experts in Big Data ethics and proposing them as a balancing power. [ABSTRACT FROM AUTHOR]