Machines Learning Justice: The Case for Judgmental Bootstrapping of Legal Decisions

Laqueur, Hannah; Copus, Ryan

doi:10.2139/ssrn.2694326

Cited by 2 publications

(3 citation statements)

References 31 publications

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“…We believe that, properly applied, algorithms can not only make more accurate predictions, but offer increased transparency and fairness over their human counterparts (cf. [23]).…”

Section: Discussionmentioning

confidence: 99%

“…The role of extraneous and ethically inappropriate factors in human decision making is well documented (see, for example, Tversky and Kahneman [1974]; Danziger, Levav, and Avnaim-Pesso [2011]; Abrams, Bertrand, and Mullainathan [2012]), and discriminatory decision making is pervasive in many of the sectors where algorithmic profiling might be introduced (see, for example, Holmes and Horvitz [1994]; Bowen and Bok [1998]). We believe that, properly applied, algorithms can not only make more accurate predictions, but offer increased transparency and fairness over their human counterparts (Laqueur and Copus 2015). 9 Above all else, the GDPR is a vital acknowledgement that, when algorithms are deployed in society, few if any decisions are purely "technical."…”

Section: Discussionmentioning

confidence: 99%

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European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”

2017

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We summarize the potential impact that the European Union's new General Data Protection Regulation will have on the routine use of machine learning algorithms. Slated to take effect as law across the EU in 2018, it will restrict automated individual decision-making (that is, algorithms that make decisions based on userlevel predictors) which "significantly affect" users. The law will also effectively create a "right to explanation," whereby a user can ask for an explanation of an algorithmic decision that was made about them. We argue that while this law will pose large challenges for industry, it highlights opportunities for computer scientists to take the lead in designing algorithms and evaluation frameworks which avoid discrimination and enable explanation.

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“…We believe that, properly applied, algorithms can not only make more accurate predictions, but offer increased transparency and fairness over their human counterparts (cf. [23]).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”

2017

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“…Researchers in Australia and Canada have thus publicized data to encourage judges and courts to audit their decision making to address cognitive and social biases. 31 Other scholars have advocated for using forms of AI to crowd-source problems of evidence in refugee decision making amongst judges 32 or to resolve epistemic doubt in favor of the applicant. 33 The above examples point to ways that digitization may equally reconstitute our understandings of what types of evidence are relevant for RSD as a complex process where human decision making is also itself prone to significant bias and information gaps.…”

Section: Digital Evidence To Address Epistemic Injustice In Rsdmentioning

confidence: 99%

Digital Evidence in Refugee Status Determination

Byrne,

Gammeltoft-Hansen

2023

Preprint

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Digital evidence is now rapidly emerging in refugee status determination (‘RSD’) – the procedure for determining whether a person meets the criteria for protection as a ‘refugee’ under the 1951 Refugee Convention. Its growing popularity among migration authorities may be seen as a response to the relative dearth of “hard” evidence in refugee status determination (RSD) and the repeated critiques of human decision-making in asylum as prone to arbitrariness, subjectivity and bias. RSD transpires under particularly difficult conditions of epistemic uncertainty, where the applicant’s testimony is central, and the risks of misjudgment are profound for both for the applicant who may be sent to harm and the state whom may thereby in violation of international law. However, the efficiency of decision making is not the only way of thinking about the problem. Reimagining evidence practices through digital means may not only help refugees to support their claims but also counter existing epistemic asymmetries whereby the state has also the resources and the refugee has none in RSD.

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Machines Learning Justice: The Case for Judgmental Bootstrapping of Legal Decisions

Cited by 2 publications

References 31 publications

European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”

European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”

Digital Evidence in Refugee Status Determination

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