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Gori publishes a report on “Legal Protection Debt in ML training datasets”

 2 May 2023

Postdoctoral researcher Gori has conducted research on the practices of ML dataset creation, curation and dissemination. The report emphasises how such practices play a crucial role for determining the level of legal protection enjoyed by the legal subjects located downstream ML-pipelines. The report illustrates how some structural features of ML-pipelines can give rise to the problem of “many hands” and to the accumulation of various forms of “technical debt”. The report argues that, lacking appropriate safeguards, a “Legal Protection Debt” can incrementally build up along the different stages of the pipeline. The report therefore stresses the need that actors involved in ML pipelines adopt a forward-looking approach to legal compliance. This requires overcoming a siloed and modulated understanding of legal liability and paying of keen attention to the potential use cases of datasets.

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