Vol. 8 (2023)
Artículos

Artificial intelligence challenging core State functions: A focus on law-making and rule-making

Nicoletta Rangone
LUMSA University

Publicado 2023-11-14

Palabras clave

  • artificial intelligence,
  • regulation,
  • legislation,
  • impact assessment,
  • simplification,
  • consultation
  • ...Más
    Menos

Los autores mantienen los derechos de autor en la publicación y sólo autorizan a la editorial Marcial Pons los derechos no exclusivos de la publicación y distribución de los artículos

Resumen

The use of AI in the public sector is emerging around the world and its spread affects the core States functions: the administrative, the judiciary, and the legislative. Nevertheless, a comprehensive approach to AI in the life-cycle of rules - from the proposal of a new rule to its implementation, monitoring and review- is currently lacking in the rich panorama of studies from different disciplines. The analysis shows that AI has the power to play a crucial role in the life-cycle of rules, by performing time-consuming tasks, increasing access to knowledge base, and enhancing the ability of institutions to draft effective rules and to declutter the regulatory stock. However, it is not without risks, ranging from discrimination to challenges to democratic representation. In order to play a role in achieving law effectiveness while limiting the risks, a complementarity between human and AI should be reached both at the level of the AI architecture and ex post. Moreover, an incremental and experimental approach is suggested, as well as the elaboration of a general framework, to be tailored by each regulator to the specific features of its tasks, aimed at setting the rationale, the role, and adequate guardrails to AI in the life-cycle of rules. This agile approach would allow the AI revolution to display its benefits while preventing potential harms or side effects.

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Citas

  1. Omar AL-UBAYDLI and Patrick McLAUGHLIN, “RegData: A Numerical Database on IndustrySpecific Regulations for All United States Industries and Federal Regulations, 1997-2012”, in Regulation and Governance, vol. 11, n. 1, 2017, pp. 109-123.
  2. Layman E. ALLEN and Charles S. SAXON, “Computer-Aided Normalizing and Unpacking: Some Interesting Machine-Processable Transformations of Legal Rules”, in Charles WALTER (ed.), Computing Power and Legal Reasoning, St. Paul: West Pub. Co., 1985, pp. 495-572.
  3. Robert BALDWIN, Rules and Government, Clarendon Press, Oxford, 1997.
  4. Robert BALDWIN, Martin CAVE, Martin LODGE, Understanding regulation. Theory, strategy, and practice, Oxford University Press, Oxford, second ed., 2012.
  5. Robert BALDWIN and Julia BLACK, “Really Responsive Risk-Based Regulation”, in Law & Policy, vol. 32, n. 2, 2010, pp. 181-213, p. 205-206.
  6. Steven J. BALLA, Alexander R. BECK, Elisabeth MEEHAN, Arymala PRASAD, “Lost in the flood?: Agency responsiveness to mass comment campaigns in administrative rulemaking”, in Regulation & Governance, 2020.
  7. Omri BEN-SHAHAR and Ariel PORAT, Personalized Law. Different Rules for Different People, Oxford University Press, Oxford, 2021.
  8. Jamie BERRYHILL et al., “Hello, World: Artificial intelligence and its use in the public sector”, in OECD Working Papers on Public Governance, n. 36/2019, OECD Publishing, Paris.
  9. Reuben BINNS, “Human judgment in algorithmic loops: individual justice and automated decision-making”, in Regulation & Governance, vol. 16, 2022, p. 197-211.
  10. Daniel BYLER, Beth FLORES, Jason LEWRIS, “Using advanced analytics to drive regulatory reform”, Deloitte, 2017.
  11. Aylin CALISKAN, Joanna J. BRYSON, Arvind NARAYANAN, “Semantics derived automatically from language corpora contain human-like biases”, in Science, n. 356, 2017, pp. 183-186.
  12. Simon CHERSTERMAN, We, the Robots: Regulating artificial intelligence and the limits of the law, Cambridge University Press, Cambridge, 2021.
  13. Danielle Keats CITRON, “Technological Due Process”, in Washington University Law Review, vol. 85, n. 6, 2008, pp. 1249-1313.
  14. Stefano CIVITARESE MATTEUCCI, “Public Administration Algorithm Decision-Making and the Rule of Law”, in European Public Law, vol. 27, n. 1, 2021, pp. 103-129.
  15. Simon CHESTERMAN, We, the Robots: Regulating artificial intelligence and the limits of the law, Cambridge University Press, Cambridge, 2022.
  16. Cary COGLIANESE, “Why Regulating AI Is Like Regulating Air or Water”, in PYMNTS, August 4, 2023
  17. Cary COGLIANESE and Alicia LAY, “Antitrust by algorithm”, in Stanford Computational Antitrust, vol. 2, 2022, p. 1-22.
  18. Cary COGLIANESE, “E-rulemaking Information Technology and Regulatory Policy”, in Administrative Law Review, vol. 56, n. 2, 2004, pp. 353-402.
  19. Cary COGLIANESE and David LEHR, “Regulating by Robot: Administrative Decision Making in the Machine Learning Era”, in The GeorgeTown Law Journal, vol. 105, 2017, pp. 1147-1223.
  20. Cary COGLIANESE and David LEHR, “Transparency and Algorithmic Governance”, in Administrative Law Review, vol. 71, n. 1, 2019, pp. 1-56.
  21. Cary COGLIANESE, “Moving toward personalised law”, in The University of Chicago Law Review online, 2022.
  22. Cary COGLIANESE and Alicia LAI, “Algorithm v. Algorithm”, in Duke Law Journal, vol. 72, 2022, pp. 1281-1340.
  23. Cary COGLIANESE, Gabriel SCHEFFLER and Daniel WALTERS, “Unrules”, in Stanford Law Review, 2021, pp. 885-967.
  24. Cary COGLIANESE and Erik LAMPMANN, “Contracting for algorithmic accountability”, in Public law and legal theory research paper series, Research paper n. 21-20, 2021.
  25. Germana COLARUSSO and Cinzia MATONTI, “GISA Autovalutazione: un servizio digitale per la compliance volontaria in sicurezza alimentare e sanità pubblica veterinaria”, in Rassegna dell’Osservatorio AIR, n. 3, 2023.
  26. Guido CORSO, Maria DE BENEDETTO, Nicoletta RANGONE, Diritto amministrativo effettivo. Una introduzione, Il Mulino, Bologna, 2022.
  27. Mariano-Florentino CUELLAR, “Cyberdelegation and the Administrative State”, in Nicholas R. PARRILLO (ed.), The Administrative State from the Inside Out. Essays on Themes in the Work of Jerry L. Mashaw, Oxford University Press, Oxford, pp. 134-169.
  28. Nello CRISTIANINI, “Shortcuts to Artificial Intelligence”, in M. Pelillo and T. Scantaburlo, Machine we trust. Perspective on dependable AI, The Mit Press, Cambridge, Massachusetts, London, England, 2021.
  29. Ana DE ALMEIDA BORGESA, Juan José CONEJERO RODRIGUEZ, David FERNANDEZ-DUQUE, David Freeman ENGSTROM, Daniel E. HO, Cathrine M. SHARKEY, Mariano-Florentino CUELLAR, Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies, Report submitted to the Administrative Conference of the United States, 2020.
  30. Gabriele BUCHHOLTZ, “Artificial intelligence and legal tech: challenges to the rule of law”, in Thomas WISCHMEYER, Timo RADEMACHER, Regulating artificial intelligence, Springer International Publishing, 2020.
  31. Alejandro DE LA GARZA, “States’ Automated Systems Are Trapping Citizens in Bureaucratic Nightmares With Their Lives on the Line”, in Times, May 28, 2020.
  32. Berkeley J. DIEVORST, Joseph P. SIMMONS, Cade MASSEY, “Algorithm aversion: People erroneously avoid algorithms after seeing them err”, in Journal of Experimental Psychology: General, vol. 144, n. 1, 2015, pp. 114-126.
  33. Marco D’ALBERTI, Pubblici poteri, mercati, globalizzazione, Il Mulino, Bologna, 2008.
  34. Anoush DARABI, “New Zealand explores machine-readable laws to transform government”, 11 May 2018, https://apolitical.co/solution-articles/en/new-zealand-explores-machine-readable-laws-to-transform-government.
  35. Stijn DEBAENE, Raf VAN KUYCK and Bea VAN BUGGENHOUT, “Legislative Technique as Basis of a Legislative Drafting System”, in Information and Communication Technology Law, vol. 9, issue 2, 2000, pp. 149-159.
  36. Fabiana DI PORTO, Paolo FANTOZZI, Maurizio NALDI, Nicoletta RANGONE, “Identifying stakeholders’ interests in EU consultations through a text mining approach”, forthcoming.
  37. Laurence DIVER, “Computational legalism and the affordance of delay in law”, in Journal of Cross-disciplinary Research in Computational Law, 2020, pp. 2-15.
  38. Bridget C.E DOOLING and Mark FEBRIZIO, “Robotic rulemaking”, in Brookings series on Regulatory Process and Perspectices, April 4, 2023.
  39. Ronald DWORKIN, Law’s Empire, Harvard University Press, Cambridge-Ma, 1986.
  40. Eric EGAN, “Generative AI Offers Federal Agencies Common-Sense Opportunities to Simplify and Improve How They Work”, in Information technology and Innovation Foundation, June 28, 2023.
  41. Birthe ENOUGH and Thomas MUSSWEILER, “Sentencing under Uncertainty: Anchoring Effects in the Courtroom”, in Journal of Applied Social Psychology, 31, 2001, pp. 1535-1551.
  42. Fotios FITSILIS et al., Guidelines on the Introduction and Use of Artificial Intelligence in the Parliamentary Workspace, 2023 , in https://joinup.ec.europa.eu/collection/egovernment/solution/hocrt/document/guidelines-introduction-and-use-artificial-intelligence-parliamentary-workspace
  43. Aram A. GAVOOR, “The Impending Judicial Regulation of Artificial Intelligence in the Administrative State”, in Notre Dame Law Review Reflection, vol. 97, 2022, pp. 197-206, p. 180 ss.
  44. Kate GODDARD, Abdul ROUDSARI, Jeremy C. WYATT, “Automation bias: a systematic review of frequency, effect mediators, and mitigators”, in J. Am. Med. Inform. Assoc., 2012, vol. 19, pp. 121-127.
  45. Mireia GONZALEZ BEDMAR, Joost J. JOOSTEN, “To Drive or Not to Drive: A Logical and Computational Analysis of European Transport Regulations”, in Information and Computation, vol. 280, 2021.
  46. Michael GOTZE, “Political and systematic push for legal pre-accept of AI solutions”, draft for the Symposium Public Administration and the EU Proposal for a Regulation of Artificial Intelligence, September 18-19, 2023.
  47. Elena GRIGLIO and Carlo MARCHETTI, “La “specialità” delle sfide tecnologiche applicate al drafting parlamentare: dal quadro comparato all’esperienza del Senato italiano”, in Osservatorio delle fonti, n. 3, 2022, pp. 361-386.
  48. Michael HERZ, “Malattributed comments in agency rule-making”, in Cardozo Law Review, in vol. 42, 2020, pp. 1-67.
  49. Mireille HILDEBRANDT, “Code-driven Law: Freezing the Future and Scaling the Past”, in Simon DEAKIN and Christopher MARKOU (eds.), Is law computable? Critical perspectives on law and artificial intelligence, Hart Publishing, Oxford, New York, Dublin, 2020, chapter 3.
  50. Mireille HILDEBRANDT, “Law as computation in the era of artificial legal intelligence. Speaking law to the power of statistics”, in University of Toronto Law Journal, vol. 68, n. 1, 2020, pp. 12-35.
  51. Daniel KAHNEMAN and Gary KLEIN, “Conditions for Intuitive Expertise. A Failure to Disagree”, in American Psychologist, 2009, pp. 515-526.
  52. Mark KELMAN, The Heuristics Debate, Oxford University Press, Oxford, 2011.
  53. Heidi R. KING, “Regulation Must Become Agile to Remain Relevant”, in The Regulatory Review, August 2, 2023.
  54. Nihal KRISHAM, “Congress gets 40 ChatGPT Plus licenses to start experimenting with generative AI”, in Fedscoop, April 24, 2023.
  55. Sarah KREPS and Douglas KRINER, “How generative Artificial Intelligence impact democratic engagement”, March 21, 2023, in How generative AI impacts g engagement | Brookings.
  56. David LEHR and Paul OHOM, “Playing with the Data: What Legal Scholars Should Learn About Machine Learning”, in University of California, vol. 51, 2017, pp. 653-717.
  57. Michael A. LIVERMORE, Vladimir EIDELMAN, Brian GROM, “Computationally Assisted Regulatory Participation”, in Notre Dame Law Review, vol. 93, n. 3, 2018, pp. 977-1034.
  58. Michael A. LIVERMORE, “Rules by Rules”, in Ryan WHALEN, Computational Legal Studies: The Promise and Challenge of Data-Driven Legal Research, Edward Elgar, 2020, Cheltenham-UK, Northampton-USA, pp. 238-264.
  59. Charles G. LORD and Cheryl TAYLOR, “Biased Assimilation: Effects of Assumptions and Expectations on the Interpretation of New Evidence”, in Social and Personality Psychology Compass, 2009, n. 3, pp. 827-841.
  60. Matt LYNC, “Lawmaker – the new legislative drafting service of the UK and Scotland”, in The Loophole, n. 2, 2022, pp. 24-39.
  61. Sandra G. MAYSON, “Bias In, Bias Out”, in The Yale Law Journal, 128, 2019, pp. 2219-2300.
  62. Barbara MARCHETTI, “Giustizia amministrativa e transizione digitale. Spunti per riflettere su un futuro non troppo lontano”, in Margherita RAMAJOLI (ed.), Una giustizia artificiale?, Il Mulino, Bologna, 2023, pp. 59-90.
  63. Patrick A. McLAUGHLIN, “RegData Canada: A Data-Driven Approach to Regulatory Reform”, in Mercatus Center, George Mason University, Policy Brief, 2019, pp. 1-5.
  64. Nina A. MENDELSON, “On the Value of Comments from Individual Members of the Public (ACUS Update)”, in Notice and Comment. A Blog from Yale Journal of Regulation, July 14, 2021.
  65. Nina A. MENDELSON, “Public Engagement, Equity, and Executive Order 14094”, Symposium on Modernizing Regulatory Review, June 7, 2023.
  66. Eva MICHEL and Anna WHALEY, “Regulatory technology: replacing law with computer code”, in LSE Legal Studies Working Paper, n. 14, 2018, pp. 1-27.
  67. Johon MORISON and Adam HARKENS, “Re-engineering Justice? Robot Judges, Computerised Courts and (Semi) Automated Legal Decision-Making”, in Legal Studies, vol. 39, n. 4, 2019, pp. 618-635.
  68. Melissa MORTAZAVI, “Rulemaking Ex Machina”, in Columbia Law Review, vol. 117, n. 6, 2017.
  69. Jason MORRIS, “Rules as Code: How Technology May change the Language in which Legislation is Written, and What it Might Mean for Lawyers of Tomorrow”, in Techshow, February 5, 2021, pp. 2-16.
  70. Kathleen L. MOSIER and Linda J. SKITKA, “Automation Bias: Decision Making and Performance in High-Tech Cockpits”, in International Journal of Aviation Psychology, 1997, n. 8, vol. 1, p. 47-63.
  71. Maria MOUSMOUTI, Designing Effective Legislation, Edward Elgar Publishing, Cheltenham-UK, Northampton-USA, 2019.
  72. Cathy O’NEIL, Weapons of math destruction. How Big Data increases inequality and threatens democracy, Penguin, London, 2016.
  73. Monica PALMIRANI, Fabio VITALI, Willy VAN PUYMBROECK, Fernando Nubla DURANGO, Legal drafting in the era of artificial intelligence and digitization, Study commissioned by the EC, Directorate-General for Informatics Solutions for Legislation, Policy & HR, Brussels, 2022.
  74. Juli PONCE SOLE, “Some considerations on the relationship between humans and artificial intelligence: the “human reserve” and human supervision (human in/on the loop)”, draft for the Symposium Public Administration and the EU Proposal for a Regulation of Artificial Intelligence, September 18-19, 2023).
  75. J. PONCE SOLE, “De como la calidad normativa y los sistemas algorítmicos, unidos a las aportaciones conductuales, pueden contribuir a la buena administración: a propósito del estudio El impacto de los trámites administrativos en el acceso a las prestaciones sociales. Una perspectiva conductual – Nudging aplicado a la Mejora de la Regulación y al Uso de Algoritmos y de Inteligencia Artificial”, (wordpress.com) June 3, 2022.
  76. Sofia RANCHIRDAS, “Empathy in the digital administrative State”, in Duke Law Journal, vol. 71, 2022, pp. 1341-1389.
  77. Nicoletta RANGONE, “Improving consultation to ensure the European Union’s democratic legitimacy: From traditional procedural requirements to behavioural insights”, in European Law Journal, vol. 28, n. 4-6, 2022, p. 154-171.
  78. Nicoletta RANGONE, “A Regulatory Reboot Cannot Neglect Artificial Intelligence”, in The Regulatory Review. University of Pennsylvania, December 15, 2022.
  79. Giuseppe Ugo RESCIGNO, “Relazione di sintesi; Atti del Seminario: Fonti, tecniche legislative, fattibilità, implementazione delle leggi e sistemi informativi”, in Quaderni a cura del servizio studi legislativi e promozione culturale dell’Assemblea regionale siciliana, 28, 1990.
  80. Cinara ROCHA and João CARVALHO, “Artificial intelligence in the judiciary: uses and threats”, in CEUR Workshop Proceedings, 2022.
  81. Alberto SANCHEZ-GRAELLS, “Data-driven and digital procurement governance: Revisiting two well-known elephant tales”, in Communications Law - Journal of Computer, Media and Telecommunications Law, vol. 24, n. 4, 2019, p. 157-170.
  82. Andrew D. SELBST, “An institutional view of algorithmic Impact Assessment”, in Harvard Journal of Law & Technology, vol. 35, n. 1, 2021, p. 117-191.
  83. Sidney A. SHAPIRO, “Marginalized Groups and the Multiple Languages of Regulatory Decision-Making”, in The Regulatory Review, 14 March 2022.
  84. Catherine M. SHARKEY and Cade MALLET, “Artificial Intelligence for Retrospective Regulatory Review”, in The Regulatory Review, September 12, 2023.
  85. Cathrine M. SHARKEY, “Algorithmic tools in retrospective review of agency rules”, Report for the Administrative Conference of the United States, May 3, 2023.
  86. Cathrine M. SHARKEY, “AI for retrospective review”, in Belmont Law Review, vol. 8, 2021, pp. 374-408.
  87. Bernd Carsten STAHL, Josephina ANTONIOU, Nikita BHALLA et al., “A systematic review of artificial intelligence impact assessments”, in Artificial Intelligence Review, 2023.
  88. Cass R. SUNSTEIN, “Algorithms, correcting biases”, in Social Research: An Int. Quart., vol. 86, n. 2, 2019, p. 499-511.
  89. Linda J. SKITKA et al., “Automation Bias and Errors: Are Crews Better Than Individuals?”, in The International Journal of Aviation Psychology, 2000, vol. 10, n. 1, pp. 85-97.
  90. Minesh TANNA and William DUNNING, “Bias and discrimination”, in Charles KERRIGAN (ed.), Artificial intelligence. Law and Regulation, Edward Elgar, Cheltenham-UK, Northampton-USA, 2022, p. 422-441.
  91. Laura TAFANI, “A Legislative Drafter’s Perspective”, in ChatGPT series, April 13, 2023, https://betteregulation.lumsa.it/chatgpt-essay-series-legislative-drafters-perspective
  92. Luca TANGI, Colin VAN NOORDT, Marco COMBETTO, Dietmar GATTWINKEL, and Francesco PIGNATELLI, AI Watch. European landscape on the use of Artificial Intelligence by the Public Sector, Publications Office of the European Union, Luxembourg, 2022.
  93. Luisa TORCHIA, “La giustizia amministrativa digitale”, in Margherita RAMAJOLI (ed.), Una giustizia amministrativa digitale?, Il Mulino, Bologna, 2023, pp. 39-58
  94. Amos TVERSKY and Daniel KAHNEMAN, “Judgment under Uncertainty: Heuristics and Biases”, in Science, vol. 185, n. 4157, 1974, pp. 1124-1131.
  95. Alessio VIGNA, “Modello di classificazione in base al rischio. Revisione dei metodi di pianificazione dei controlli ufficiali per la sicurezza alimentare in Lombardia”, in Rassegna dell’Osservatorio AIR, n. 3, 2023.
  96. Wim J.M. VOERMANS, Wolmoed FOKKEMA, Remco VAN WLJK, “Free the Legislative Process of its Paper Chains: IT-inspired Redesign of The Legislative Procedure Cycle”, in The Loophole, January, 2012, pp. 54-73.
  97. Wim VOERMANS, “Computer-assisted legislative drafting in the Netherlands: the LEDA system”, 2019, in https://ial-online.org/wp-content/uploads/2019/07/Voermans-Legimatics.pdf
  98. Matthew WADDINGTON, “Machine-consumable legislation: A legislative drafter’s perspective – Human v artificial intelligence”, in The Loophole, June 2019, pp. 22-52.
  99. Matthew WADDINGTON, “Research Note. Rules as Code”, in Law in Context, vol. 37, n. 1, 2020, p. 179-186.
  100. Helen XANTHAKI, Drafting Legislative. Art and technologies of rules for regulation, Hart Publishing, Oxford, New York, Dublin, 2014.
  101. Helen XANTHAKI, “Legislative drafting: a new sub-discipline of law is born”, in IALS Student Law Review, Vol. 1, Issue 1, 2013, pp. 57-70.
  102. Zichun XU, “Human Judges in the Era of Artificial Intelligence: Challenges and Opportunities”, in Applied Artificial Intelligence, vol. 36, n. 1, 2022.
  103. Karen YEUNG, “Algorithmic regulation: A critical interrogation”, in Regulation & Governance, vol. 12, 2018, pp. 505-523.
  104. Eyal ZAMIR and Doron TEICHMAN, Behavioural law and economics, Oxford University Press, Oxford, 2018.