In a data-driven period, with Machine Learning (ML) systems that thrive, owing to the huge data availability (Big Data), and affect people with assessments, predictions and decisions, our focus rests upon some prerequisites which must be met if ML is ever to operate fairly, i.e. data quality and its standardisation. In reference to the underlying (apparently mere) technical procedures, the paper rests on the relevant legal implications in terms of both fundamental rights and regulatory techniques. In this respect, it is the constitutional recovery of the EU through its recently launched Strategies (on Artificial Intelligence and Standardisation) that comes into play, paving the path towards a steering and monitoring role by the European institutions that supports an improving rights-oriented approach and a re-framing of regulatory techniques.
The European path towards Data Quality and its standardisation in AI: a legal perspective
N. Maccabiani
2022-01-01
Abstract
In a data-driven period, with Machine Learning (ML) systems that thrive, owing to the huge data availability (Big Data), and affect people with assessments, predictions and decisions, our focus rests upon some prerequisites which must be met if ML is ever to operate fairly, i.e. data quality and its standardisation. In reference to the underlying (apparently mere) technical procedures, the paper rests on the relevant legal implications in terms of both fundamental rights and regulatory techniques. In this respect, it is the constitutional recovery of the EU through its recently launched Strategies (on Artificial Intelligence and Standardisation) that comes into play, paving the path towards a steering and monitoring role by the European institutions that supports an improving rights-oriented approach and a re-framing of regulatory techniques.File | Dimensione | Formato | |
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