The Rule of Law and Automation of Government Decision‐Making

Zalnieriute, Monika; Moses, Lyria Bennett; Williams, George

doi:10.1111/1468-2230.12412

Cited by 64 publications

(58 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Individual justice involves the case in question being judged on its own, with a fresh consideration of the relevant factors and the reasoning involved, no matter how similar it may appear to previous cases. This is just one of several arguments explicating the value of human judgement (with others focusing, amongst other things, on maintaining human liability and responsibility (Bryson et al, 2017;Wagner, 2019), or the need to preserve the rule of law as an argumentative and text-driven system (Hildebrandt, 2018;Zalnieriute et al, 2019)).…”

Section: Discussionmentioning

confidence: 99%

“…Even if algorithms could effectively learn from observing human judgements, we may still want to keep human decision makers around to generate fresh ground truth and to avoid moral atrophy (Hildebrandt, 2013). Related arguments emphasise the importance of human judgement as something which can be justified with reasons (Oswald, 2018;Pasquale, 2018), which can be challenged and rebuked (Pasquale and Cashwell, 2018), and which respects the rule of law (Hildebrandt, 2018;Zalnieriute et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The point that rule-based expert systems and machine learning models are not fundamentally different in this respect, and the consequences for the justifiability of automated systems in government decision-making, has also been made by Monika Zalnieriute and co-authors(Zalnieriute et al, 2019) …”

mentioning

confidence: 98%

See 2 more Smart Citations

Human Judgement in Algorithmic Loops; Individual Justice and Automated Decision-Making

Binns

2019

SSRN Journal

View full text Add to dashboard Cite

There are various arguments in favour of tempering algorithmic decision-making with human judgement. One common family of arguments appeal to concepts and criteria derived from legal philosophy about the nature of law and legal reasoning, and argue that algorithmic systems cannot satisfy them (but humans can). This paper argues that among the latter family of arguments, there is often an implicit appeal to the notion that each case needs to be assessed on its own merits, without comparison to or generalisation from previous cases. This notion of 'individual justice' has featured in jurisprudential debates about the granularity of rules and tests, and the (in)justice of discrimination, but has not yet been explicitly imported into debates about justice and algorithmic decision-making. This paper has several aims. The first is to provide an overview of the concept of individual justice and distinguish it from related but distinct arguments about the value of human discretion. Equipped with this account of human judgement as a guarantor of individual justice, the second aim is to consider its place within and beside algorithmic decision-making. It argues that in so far as individual justice is valuable, it can only be meaningfully served through human judgement, because it antithetical to the kind of predetermined reasoning that characterises algorithmic systems. This suggests that-to the extent that individual justice is deemed important-a requirement for human intervention and oversight over algorithmic decisions is necessary. The third aim is to consider how individual justice relates to other dimensions of justice, namely consistency and fairness or non-discrimination. Finally, the article discusses two challenges that are raised by this account. The first challenge concerns how individual justice can be accommodated alongside other dimensions of justice in the socio-technical contexts in Human Judgement in Algorithmic Loops DRAFT 2 which humans-in-the-loop are situated. The second concerns the potential inequities in individual justice that might result from an uneven application of human judgement in algorithmic settings.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Human Judgement in Algorithmic Loops; Individual Justice and Automated Decision-Making

Binns

2019

SSRN Journal

View full text Add to dashboard Cite

show abstract

“…Such algorithms use big data sets, dividing them into two parts and using one as a training set to discern underlying patterns that are then adaptively improved on in interaction with the rest of the data over time. So they are characterised by their ability to replicate complex human decision making and then adaptively “learn” how to do even better, at least when operating within the limits of their sphere of capability (for a nuanced discussion of the policy balance sheet: Zalnieriute et al ). This “besting” of many human systems not only on cost and reliability but also on “quality,” builds pressure for their rapid adoption.…”

Section: Online Changes To the Character And Form Of Matters For Reviewmentioning

confidence: 99%

Automation in social security: Implications for merits review?

Carney

2019

Aust J Social Issues

View full text Add to dashboard Cite

This paper reviews illustrative aspects of the introduction of artificial intelligence into Australian social security's (Centrelink) original decision making and merits review. The review highlights the complexity and nuanced character of evaluating greater reliance on artifical intellignce over human decision‐making systems. It argues that technological change is inevitable, and is not necessarily either an unadulterated boon or bane, but calls for careful planning and a comparative assessment of the benefits and limitations of artificial intelligence versus human systems. In social security, it is concluded that particular attention should be given to avoiding discrimination against citizens who are technology poor or otherwise vulnerable.

show abstract

“…Considering the difficulties concerning the explainability of automated decision-making (Edwards & Veale, 2017), it is questionable whether the provisions of GDPR might be perceived as feasible solutions to the problems which can be observed on the horizon. Automated decision-making, in itself, may decrease the transparency of the evaluation process and, therefore, blur the reasons behind certain decisions (Zalnieriute, Moses & Williams, 2019). The involvement of machine learning and deep learning technologies in the process of automated decision-making strengthens these tendencies.…”

Section: Automated Decision-making Regulation In the Gdpr And Scientimentioning

confidence: 99%

Automated Decision-Making and the Precautionary Principle in EU Law

Mazur

2019

Baltic Journal of European Studies

View full text Add to dashboard Cite

The article is predicated upon the allegation that there is a similarity between the scientific uncertainty linked to the hazard which human interventions pose to the natural environment and the hazard which the development of automated decision-making techniques poses to certain aspects of human lives in the digital environment. On the basis of this allegation, the analysis examines the similarities between the European environmental law, which is crucial for the natural environment, and the European data protection law, which is fundamental for the digital environment. As there are measures already adopted by the data protection law from the environmental law, such as impact assessments and the right to access information, the main hypothesis of this analysis is to consider whether there are further inspirations for the development of European data protection law which could be drawn from environmental law, regarding the scientific uncertainty which is common to these two areas of regulation. The article examines a legal measure, namely, the precautionary principle, as the conjectural response to the challenges linked to the development of the new technologies. The experiences collected in the area of environmental law concerning the precautionary principle are analysed as a source of lessons to be learned concerning the regulatory measures adopted in order to deal with scientific uncertainty, not only in the natural environment, but also in the digital one.

show abstract

The Rule of Law and Automation of Government Decision‐Making

Cited by 64 publications

References 3 publications

Human Judgement in Algorithmic Loops; Individual Justice and Automated Decision-Making

Human Judgement in Algorithmic Loops; Individual Justice and Automated Decision-Making

Automation in social security: Implications for merits review?

Automated Decision-Making and the Precautionary Principle in EU Law

Contact Info

Product

Resources

About