An FDA for Algorithms

By A. Tutt. 2016

166 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Law, Political Science and International Relations

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Citations in the corpus

The ethics of algorithms: Mapping the debate (2016, neutral): “The forthcoming EU General Data Protection Regulation (GDPR) in particular is indicative of the challenges to be faced globally in regulating algorithms.”
Algorithmic Decision-Making Based on Machine Learning from Big Data: Can Transparency Restore Accountability? (2017, background): “Zarsky (2013: 1532) suggests that branches of government, or bodies external to it (such as expert panels, NGOs) would do, while Tutt floats the idea of an algorithmic safety agency, a kind of FDA for algorithms (Tutt 2017).”
Artificial Intelligence Regulation: A Meta-Framework for Formulation and Governance (2020, methodology): “When mitigating risks, regulatory agencies could bar the introduction of certain algorithms into the market until their safety and efficacy have been proven by means of tests [17] founded on ethics [24].”
Towards Transparency by Design for Artificial Intelligence (2020, background): ““Transpar-ency disclosures may prove more impactful if tailored towards trained third parties or regulators representing public interest as opposed to data subjects themselves” (Mittelstadt et al. 2016, p. 7, with reference to Tutt 2017 and Zarsky 2013).”
Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data (2017, background): “Various proposals have been made for the involvement of external parties in the evaluation and auditing of algorithmic systems (Mantelero, 2016; Pasquale, 2010; Sandvig et al., 2014; Tutt, 2016).”
Auditing large language models: a three-layered approach (2023, background): “Therefore, some researchers have called for more government involvement, including an ‘FDA for algorithms’ [272].”
Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach (2017, background): “110 House of Commons Science and Technology Committee (2016b, p. 36). development of novel regulatory frameworks 111 and principles, which can address the unique legal and ethical issues raised by AI and robotics.”
Trustworthy Artificial Intelligence: A Review (2022, background): “F, A [22, 171, 226] F, E [14, 179] E, A [75, 108, 186, 206] F, E, A, P, Ac [92] F, E, A, Ac [134] F, Ac [26] A, P, Ac [163, 214] E, A [55, 132] A, Ac [25, 29, 105, 113, 157, 159, 168, 197] F, A, Ac [111, 174] Ac [204]”