L'argomentazione costituzionale di common law
In: Comparazione e cultura giuridica nuova serie, 3
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In: Comparazione e cultura giuridica nuova serie, 3
In: International journal of social imaginaries, Band 1, Heft 2, S. 278-282
ISSN: 2772-7866
In: Bocconi Legal Studies Research Paper No. 4004541
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In: Forthcoming Goldoni, Wilkinson, Cambridge Handbook of the Material Constitution
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In: Bocconi Legal Studies Research Paper No. 3141422
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Working paper
In: Bocconi Legal Studies Research Paper No. 2989742
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Working paper
In: The Italian Law Journal (2017)
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In: La cittadinanza europea: itinerari, strumenti, scenari ; rivista di studi e documentazione sull'integrazione europea, Heft 1, S. 129-156
ISSN: 2039-9383
In: Ius Comparatum - Global Studies in Comparative Law; Damages for Violations of Human Rights, S. 217-240
In: Immigration and Right to Nationality (Jus Gentium Europaeum, ES, 2015)
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Working paper
In: Cambridge Journal of International and Comparative Law, 3, 2014
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In: Routledge research in constitutional law
In: European journal of risk regulation: EJRR ; at the intersection of global law, science and policy, Band 13, Heft 3, S. 421-442
ISSN: 2190-8249
AbstractUnder what conditions can artificial intelligence contribute to political processes without undermining their legitimacy? Thanks to the ever-growing availability of data and the increasing power of decision-making algorithms, the future of political institutions is unlikely to be anything similar to what we have known throughout the last century, possibly with parliaments deprived of their traditional authority and public decision-making processes largely unaccountable. This paper discusses and challenges these concerns by suggesting a theoretical framework under which algorithmic decision-making is compatible with democracy and, most relevantly, can offer a viable solution to counter the rise of populist rhetoric in the governance arena. Such a framework is based on three pillars: (1) understanding the civic issues that are subjected to automated decision-making; (2) controlling the issues that are assigned to AI; and (3) evaluating and challenging the outputs of algorithmic decision-making.
In: Edinburgh School of Law Research Paper No. 2022/01
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