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Seeing like an algorithm: the limits of using remote sensing to link vessel movements with worker abuse at sea

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Abstract

The ship tracking and mapping capabilities that geospatial technology provides create an opportunity to observe fishing vessels as they move through established maritime boundaries. This paper connects data availability to ground-truthing research and explores the limits of vessel movement mapping in representing worker abuse at sea through three related themes. First, a conceptual background links the advancements in maritime remote sensing to critical GIS scholarship and provides a background on worker abuse aboard Taiwanese fishing vessels. Second, the paper examines the potential of machine learning algorithms to represent worker abuse at sea, arguing that more extensive ground-truthing research with workers could help address variations in the data and limited data sets. Third, I use remote sensing data to identify and unpack Taiwanese fishing across the three EEZs with the most concentrated Taiwanese fishing activity: starting with Taiwan, followed by the Falkland Islands, and Seychelles. I argue that fishing activity and the digital representation of vessel movements are governed by terrestrial geopolitics and subject to manipulation by ship captains. Finally, the conclusion offers recommendations for how future research can capitalize on the capabilities of AIS, particularly with respect to addressing problems of working conditions and abuse at sea.

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Funding

This study was supported by the Social Sciences and Humanities Research Council (SSHRC) of Canada, grant number 435–2020-1304.

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  1. York University, 4700 Keele St, Toronto, ON, M3J 1P3, Canada

    Terence Adam Rudolph

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Rudolph, T.A. Seeing like an algorithm: the limits of using remote sensing to link vessel movements with worker abuse at sea. Maritime Studies 23, 13 (2024). https://doi.org/10.1007/s40152-024-00351-7

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