The Meaning and the Mining of Legal Texts

Hildebrandt, Mireille

doi:10.1057/9780230371934_8

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…More specifically, in the study indicated, a specific method of unsupervised latent trait scaling was used to discern latent traits of legal traditions in government budgetary legislation in 13 countries by means of examining the texts of this legislation. Big Data research has been evolving within legal research proper (see, for instance, Hildebrandt, 2012; Surden, 2014), but the study that this article has examined indicates re-orientation within political science research on government budgeting and legal policy-making rather than legal studies.…”

Section: Conclusion and Discussionmentioning

confidence: 96%

Institutionalizing Big Data methods in social and political research

Ahonen

2015

Big Data & Society

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We expect Big Data methods to contribute to research with results that are not inferior to those attained in other ways but possibly better, or hard or impossible to generate in other ways. Those who apply these methods may also aspire to augment the arsenal of research methods, offer surrogates for existing research designs, and re-orient research. Moreover, we can critically examine the institutional, societal and political effects of the Big Data methods and the conditions for the solid institutionalization of these methods in social and political research. To reach its primary objective, this article elaborates conclusions on how Big Data methods, not only by means of their 'social life' but also by their 'political life', may influence the institutionalization of social and political research. To reach its secondary objective, the article re-examines a study of budgetary legislation in 13 countries carried out by means of Big Data methods to draw conclusions concerning the augmentation of the arsenal of research methods, the surrogation of existing research designs, and the re-orientation of research.

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Section: Conclusion and Discussionmentioning

confidence: 96%

Institutionalizing Big Data methods in social and political research

Ahonen

2015

Big Data & Society

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“…4 Afterrecognizingandanalysinghumanbehaviour,thenextstepisinfluencingthatbehaviourby, forexample,persuasivetechnology.Persuasivetechnologyusesinsightsfrompsychology,behavioural sciencesandhuman-computerinteraction,todesignsystemsthatencourageuserstochangetheir behaviour(Fogg2002).Thistypeoftechnologicalbehaviourinfluencing-alsocallednudging-is becomingmoreandmoresophisticated.ThinkofFacebook'semotionstudy,whichrevealedthat showinguserspositiveornegativeinformationaffectstheirmood.Consequently,userspostmore positiveornegativethings.Thestudycausedquiteacommotionamonguserswhentheyrealisedthat theyhadunwittinglybeenpartofanexperiment(Flick2016).Theinconspicuouspersonalizingof searchbehaviourbysearchenginessuchasGoogleisalsoanexampleofsubtleinfluencing. Hildebrandt(2012;…”

Section: Digitization Of the Biological Worldmentioning

confidence: 99%

The New Digital Wave of Rationalization

Royakkers

Est

2020

International Journal of Technoethics

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The new wave of digitization and the ensuing cybernetic loop lead to the fact that biological, social, and cognitive processes can be understood in terms of information processes and systems, and thus digitally programmed and controlled. Digital control offers society and the individuals in that society a multitude of opportunities, but also brings new social and ethical challenges. Important public values are at stake, closely linked to fundamental and human rights. This paper focuses on the public value of autonomy, and shows that digitization—by analysis and application of data—can have a profound effect on this value in all sorts of aspects in our lives: in our material, biological, and socio-cultural lives. Since the supervision of autonomy is hardly organized, we need to clarify through reflection and joint debate about what kind of control and human qualities we do not want to lose in the digital future.

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“…Transparent exploratory and properly tested confirmatory machine learning can be a means to provide feedback to lawyers, clients, prosecutors, courts. 8 In previous work I made six recommendations for the use of ML in law, five of which were based on the work of Sculley & Pasanek [41] on the use of ML in literary theory [42] (p. 157):…”

Section: Algorithmic Regulation Under the Rule Of Law: From Agnostic To Agonistic Machine Learningmentioning

confidence: 99%

Algorithmic regulation and the rule of law

Hildebrandt¹

2018

Phil. Trans. R. Soc. A.

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In this brief contribution, I distinguish between code-driven and data-driven regulation as novel instantiations of legal regulation. Before moving deeper into data-driven regulation, I explain the difference between law and regulation, and the relevance of such a difference for the rule of law. I discuss artificial legal intelligence (ALI) as a means to enable quantified legal prediction and argumentation mining which are both based on machine learning. This raises the question of whether the implementation of such technologies should count as law or as regulation, and what this means for their further development. Finally, I propose the concept of 'agonistic machine learning' as a means to bring data-driven regulation under the rule of law. This entails obligating developers, lawyers and those subject to the decisions of ALI to re-introduce adversarial interrogation at the level of its computational architecture.This article is part of a discussion meeting issue 'The growing ubiquity of algorithms in society: implications, impacts and innovations'.

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The Meaning and the Mining of Legal Texts

Cited by 5 publications

References 17 publications

Institutionalizing Big Data methods in social and political research

Institutionalizing Big Data methods in social and political research

The New Digital Wave of Rationalization

Algorithmic regulation and the rule of law

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