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DESCRIPTION:Pour la première conférence du cycle Intelligence Artificielle 
 et Droit\, nous accueuillons Christopher Markou\, Faculté de droit\, Unive
 rsité de Cambridge\, et auteur de livre Lex Ex Machina: From Rule of Law t
 o Legal Singularity.\n\nLa conférence se tiendra sur Zoom: mcgill.zoom.us/
 j/81640916943\n\nRésumé\n\n[En anglais seulement] The question ‘is law com
 putable?’ immediately recalls the classic jurisprudential question: ‘what 
 is law?’ – a question posed by both legal pragmatists and idealists. For t
 ough-minded pragmatists\, the question ‘what is law’ might entail little m
 ore than a prediction of whether those in authority will or will not stop 
 a planned action or penalise a completed one. This pragmatic approach appe
 als to business—including the burgeoning LegalTech industry—because effici
 ency (read: throughput) is the name of the game. After all\, commercial cl
 ients don’t concern themselves with esoteric legal values\, and non-lawyer
  clients may not even recognise them. Rather\, the question is really whet
 her some law enforcement body or judge will stop\, penalise\, or reward th
 e action. If the law is reframed as the task of predicting behaviours and 
 proactively intervening\, the skills needed to practice law may become sim
 ilarly circumscribed\, more formulaic\, and more readily computable.\n\nBu
 t what does computable law really portend about the future of legal regime
 s premised on due process\, equality of arms\, and fairness?\n	\n	Thought le
 aders in the field of computational legal studies or those straddling the 
 line between legal academics and entrepreneurship are quick to tout the ab
 ilities of their models to best human experts at some narrow game of foret
 elling the future by doing yesterday’s homework. Most often this involves 
 predicting whether the U.S. Supreme Court or European Court of Human Right
 s\, for instance\, will affirm an appealed judgment based on some set of v
 ariables about the relevant jurists. For reductionist projects in computat
 ional law (particularly those that seek to replace cases before them rathe
 r than complement legal practitioners)\, traces of the legal process are e
 quivalent to the process itself. If a machine produces a judgement that is
  in some way persuasive\, we should accept it\, goes one refrain.\n\nBut d
 o we not teach our students that in law the process of exercising legal ju
 dgement is inseparable from the resulting judgement? Isn’t the process the
  exercise?\n	\n	For enthusiastic LegalTech developers\, the answer is “no”. 
 The words in a complaint and an opinion\, for instance\, are taken to be t
 he essence of the proceeding\, and variables gleaned from decisionmakers’ 
 past actions and affiliations determine their subsequent ones. In this beh
 aviouristic rendering\, litigants present pages of words to the decisionma
 ker\, and some set of pages better matches the decisionmaker’s preferences
 \, and then the decisionmaker tries to write a justification of the decisi
 on sufficient not to be overruled by higher levels of appeal. From the per
 spective of the client\, predictions that are 30 per cent more accurate th
 an a coin flip\, or 20 per cent more accurate than casually consulted expe
 rts\, are not just useful\; they are seen as the future. But there is more
  to law and legal process than can be computationally imputed\, and limits
  to public trust and acceptance of so-called ‘Robot Judges’ and automating
  ever more aspects of legal process and judgement. The human and repetitio
 nal toll\, however\, of automating human discretional authority ‘out of th
 e loop’ has become acutely clear from the Australian ‘RoboDebt’ fiasco\, t
 he UK's use of a proprietary algorithm to award marks for classes curtaile
 d by COVID\, and Canada’s use of biometrics to assess refugee claims.\n	\n	T
 his talk will first examine the history of computers and AI in legal conte
 xts\, focusing specifically on the hype around Legal Expert Systems (LES) 
 in the 1980s-1990s to the current generation of LegalTech applications. Dr
 awing on first-hand accounts from lawyers\, developers and researchers the
  talk will survey the technical\, practical\, and theoretical seeds of fai
 lure and what can be learned from it. The talk will then turn to an examin
 ation of how concurrent developments in neuroscience\, physics\, biology a
 nd data science are actualising a machinic ontology of the world whereby e
 verything\, including law\, is computable. The talk will conclude with rec
 ommendations for research priorities in computational legal studies and su
 ggestions for where to draw ‘red lines’ for automating legal process or ju
 dgement.\n\nLe conférencier\n\n[En anglais seulement] Dr Christopher Marko
 u is Leverhulme Fellow and Lecturer in the Faculty of Law\, University of 
 Cambridge\, Associate at the Cambridge Centre for Business Research (CBR)\
 , Director of the AI\, Law & Society LLM at King’s College London\, and Fe
 llow of the Royal Society of the Arts. He writes widely on emerging techno
 logies policy and governance\, with work featured in outlets such as Scien
 tific American\, Newsweek\, and Wired\, among others. Christopher has been
  a keynote speaker at the Cheltenham Science Festival\, Cambridge Festival
  of Ideas\, Ted Talks\, and World Congress on Information Technology. He i
 s co-editor (with Professor Simon Deakin\, Cambridge) of the forthcoming v
 olume 'Is Law Computable? Critical Perspectives on Law + Artificial Intell
 igence' (Hart 2020) and author of the forthcoming monograph Lex Ex Machina
 : From Rule of Law to Legal Singularity. Twitter: @cpmarkou\n\nLe cycle In
 telligence artificielle et droit\n\nCe cycle de conférences est une collab
 oration du Laboratoire de Cyberjustice de Montréal\; le Collectif étudiant
  pour la technologie et le droit\; le groupe de recherche Justice privée e
 t état de droit\; et le projet d'Autonomisation des Acteurs Judiciaires pa
 r la Cyberjustice et l’Intelligence Artificielle (AJC).\n\nCette activité 
 est admissible pour 1 heure de formation continue obligatoire tel que décl
 aré par les membres du Barreau du Québec.\n
DTSTART:20201030T170000Z
DTEND:20201030T180000Z
LOCATION:Zoom: https://mcgill.zoom.us/j/81640916943
SUMMARY:Characteristica Universalis Lex: Artificial Intelligence and the Gh
 osts of LegalTech Past
URL:/law/fr/channels/event/characteristica-universalis
 -lex-artificial-intelligence-and-ghosts-legaltech-past-325258
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