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10. AI and Politics

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Abstract

Digital technology has pervaded society by penetrating markets, institutions, transactions and social relations, cultural, political, and educational environments. Digital technology exerts an extraordinary transformative force on structures, relations, and processes but presently digital technology has been incorporated and understood as a mere instrument replacing other traditional media and means. AI systems are integrated with escalating frequency into core institutional elements of democracy. Political parties and leaders are now using platforms such as Twitter to point their political affiliations, advance a positive image of their political parties, and express their rejection of the opposition’s viewpoint. Moreover, accountability concerning the consequences of political decisions must be clear and so it has to become clear when AI makes decisions. Good policy is the goal for politics and AI as long as automatically is taking political decisions then AI has got political power. AI will advance participation in the whole political process of various forms and so one manner to instigate this is to stimulate cocreation and “democratizing algorithm.”

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Frederick Schauer, Thinking Like A Lawyer: A New Introduction To Legal Reasoning 103–19 (2009) (discussing the extent of common law’s independence from statute). John Rawls, A Theory Of Justice 224 (1971) (stipulating that any departure from majority rule constitutes a restriction of citizens’ political liberty, possibly justified by other considerations).
 
112
Martin Gilens and Benjamin I. Page, Testing Theories of American Politics: Elites, Interest Groups, and Average Citizens 12 PERSP. ON POL. 564, 576 (2014) (“In the United States, our findings indicate, the majority does not rule—at least not in the causal sense of actually determining policy outcomes. When a majority of citizens disagrees with economic elites or with organized interests, they generally lose.”).
 
113
Dana Remus and Frank Levy, Can Robots be Lawyers? Computers, Lawyers, and the Practice of Law, ABA LAW PRACTICE DIVISION 59 (July 20, 2016), Frank Pasquale, A Rule of Persons, Not Machines: The Limits of Legal Automation, 87 GEO. WASH. L. REV. 1, 55 (2019).
 
114
Anthony J. Casey & Anthony Niblett, The Death of Rules and Standards, 92 IND. L. REV 1401, 1403 (2017) Brian Sheppard, Warming Up to Inscrutability: How Technology Could Challenge Our Concept of Law, 68 U. TORONTO L.J. 36, 40 (2018).
 
115
Lisa Burton Crawford, The Rule Of Law And The Australian Constitution (2018). Lord Bingham, The Rule of Law, 66 The Cambridge Law Journal 67 (2007); Paul Gowder, The Rule Of Law In The Real World (2016).
 
116
Eugene Volokh, Chief Justice Robots, 68 DUKE L.J. 1135, 1138 (2019).
 
117
Anthony J. Casey & Anthony Niblett, Self-Driving Laws, 66 U. TORONTO L.J. 429, 442 (2016), Anthony J. Casey & Anthony Niblett, The Death of Rules and Standards, 92 IND. L.J. 1401, 1404 (2017).
 
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Georgia v. Public Resource.​org, Inc., No. 18–1150, 590 U.S. __, slip op. at *7–8 (2020).
 
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Andrew C. Michaels, Abstract Innovation, Virtual Ideas, and Artificial Legal Thought, 14 MAR. J. BUS. & TECH. L. 1, 25 (2019). Richard M. Re & Alicia Solow-Niederman, Developing Artificially Intelligent Justice, 22 STAN. TECH. L. REV. 242, 247 (2019).
 
120
Benjamin N. Cardozo, The Growth Of The Law 132–133 (1924) (“Stare decisis is not in the constitution, but I should be half ready to put it there, and to add thereto the requirement of mechanical and literal reproduction, if only it were true that legislation is a sufficient agency of growth. The centuries, if they have proved anything, have proved the need of something more.”).
 
121
Henry J. Friendly, Reactions of a Lawyer – Newly Become Judge, 71 YALE L.J. 218, 220 (1961).
 
122
Charles Sampford, Retrospectivity and The Rule Of Law 103–64 (2006); Neil Duxbury, Ex Post Facto Law, 58 AM. J. JURIS. 135, 158–61 (2013); J. Lyn Entrikin, The Death of Common Law, 42 HARV. J.L. & PUB. POL’Y 351, 424 (2019). Jonathan S. Masur & Adam K. Mortara, Patents, Property, and Prospectivity, 71 STAN. L. REV. 963, 997 (2019) (“There is no reason to deprive patent policymakers of the tool of prospective lawmaking just because those policymakers happen to be judges, rather than legislators or executive officials.”).
 
123
Harper v. Va. Dep’t of Taxation, 509 U.S. 86, 105 (1993) (“Prospective decision making is the handmaid of judicial activism, and the born enemy of stare decisis.”). James B. Beam Distilling Co. v. Georgia, 501 U.S. 529, 549 (1991) (explaining that difficulties posed by retroactivity “are one of the understood checks upon judicial lawmaking; to eliminate them is to render courts substantially more free to ‘make new law,’ and thus to alter in a fundamental way the assigned balance of responsibility and power among the three branches”). Chevron, U.S.A., Inc. v. NRDC, Inc., 467 U.S. 837, 843 (1984) (“if the statute is silent or ambiguous with respect to the specific issue, the question for the court is whether the agency’s answer is based on a permissible construction of the statute.”); United States v. Mead Corp., 533 U.S. 218, 229 (2001) (explaining that when Chevron applies, a reviewing court “is obliged to accept the agency’s position if Congress has not previously spoken to the point at issue and the agency’s interpretation is reasonable.”).
 
124
Franklin Foer, World Without Mind: The Existential Threat Of Big Tech 72 (2017) (“The problem is that when we outsource thinking to machines, we are really outsourcing thinking to the organizations that run the machines.”).
 
125
Youngstown Sheet & Tube Co. v. Sawyer, 343 U.S. 579, 646 (1952) (Jackson, J., concurring) (“ours is a government of laws, not of men, and … we submit ourselves to rulers only if under rules.”).
 
126
Ashley S. Deeks, Secret Reason-Giving, 129 YALE L. J. 612, 627–28 (2020); John Rawls, A Theory of Justice 580 (1971)
 
127
Sapna Kumar, Patent Court Specialization, 104 IOWA L. REV. 101, 118 (2019) (“The term ‘separation of powers’ does not appear in the Constitution, but is instead inferred from the dividing of legislative, executive, and judicial power into separate Articles.”) Buckley v. Valeo, 424 U.S. 1, 124 (1976); Michael C. Dorf & Charles F. Sabel, A Constitution of Democratic Experimentalism, 98 COLUM. L. REV. 267, 439–40 (1998).
 
128
Emily Berman, A Government of Laws and Not of Machines, 98 B.U. L. REV. 1277, 1280 (2018).
 
129
Sendhil Mullainathan & Jann Spiess, Machine Learning: An Applied Econometric Approach, 31 J. ECON. PERSP. 87, 88 (2017) (defining machine learning in terms of its capacity for “out of sample” prediction).
 
130
Jamie Susskind, Future Politics: Living Together In A World Transformed By Tech 168–87 (2018).
 
131
Aziz Z. Huq & Genevieve Lakier, Apparent Fault, 131 HARV. L. REV. 1525, 1547–48 (2018) Aziz Z. Huq, Judicial Independence and the Rationing of Constitutional Remedies, 65 DUKE L.J. 1, 70–74 (2015) (noting that a fault regime for constitutional remedies leads to unequal treatment of constitutional wrongs, unequal vindication of constitutional rights, and unequal treatment of litigants).
 
132
Steven Feldstein, How Artificial Intelligence Is Reshaping Repression, 30 J. DEMOCRACY 40, 42 (2019) (noting how effective AI technology is for repressing dissent).
 
133
Ark. Dep’t of Human Servs. v. Ledgerwood, 530 S.W.3d 336, 344–45 (Ark. 2017).
 
134
Richard F. Lowden, Risk Assessment Algorithms: The Answer to an Inequitable Bail System?, 19 N.C. J.L. & TECH. ONLINE 221, 230–31 (2018), Richard Berk, An Impact Assessment of Machine Learning Risk Forecasts on Parole Board Decisions and Recidivism, 13 J. EXPERIMENTAL CRIMINOLOGY 193, 195 (2017).
 
135
Hous. Fed’n of Teachers, Local 2415 v. Hous. Indep. Sch. Dist., 251 F. Supp. 3d 1168, 1171 (S.D. Tex. 2017) (the teacher evaluation algorithm deprived teachers of due process protections against substantively unfair deprivations of property); State v. Loomis, 881 N.W.2d 749, 760 (Wis. 2016) (COMPAS risk assessment violated the defendant’s right to be sentenced based on accurate information).
 
136
Gundy v. United States, 139 S. Ct. 2116, 2131–32 (2019) (Gorsuch, J., dissenting) (casting doubt on rule-making delegations to federal agencies).
 
137
Seattle Mun. Code § 14.18.010 (Wash. 2017) (regulating “any electronic data collected, captured, recorded, retained, processed, intercepted, or analyzed by surveillance technology acquired by the City or operated at the direction of the City”). Similar measures include Santa Clara County, Code of Ordinances § A40–7(c) (Cal. 2020).
 
138
Zoe Robinson, ‘Constitutional Personhood’ (2016) 84 George Washington Law Review 605, 621.
 
139
European Parliament resolution of 20 October 2020 with recommendations to the Commission on a civil liability regime for artificial intelligence (2020/2014(INL)).
 
140
Gyandeep Chaudhary, “Artificial Intelligence: The Liability Paradox”, Summer Issue ILI Law Review Journal 144 (2020).
 
141
Byrn v New York City Health & Hosp Corp [1972] 286 N E 2d 887. Bumper Development Corp Ltd. v Commissioner of Police of the Metropolis and Others (Union of India & Others) [1991] 4 All ER 638. B Smith, “Legal personality”, 37(3) Yale Law Journal 283–299, 1928.
 
142
Samir Chopra and Laurence F. White, A Legal Theory for Autonomous Artificial Agents (University of Michigan Press, Ann Arbor, 2011). Ryan Abbott, “I Think, Therefore I Invent: Creative Computers and the Future of Patent Law” 57 Boston College Law Review 1079, 1080 (2016).
 
143
Shlomit Yanisky-Ravid, “Generating Rembrandt: Artificial Intelligence, Copyright, And Accountability In The 3a Era—The Human-Like Authors Are Already Here—A New Model”, Michigan State Law Review 659 (2017).
 
144
James A. Reggia, “The Rise of Machine Consciousness: Studying Consciousness with Computational Models”, 44 Neural Networks 112 (2013).
 
145
J. Farrar, Corporate governance—theories, principles and practice (Oxford University Press, Melbourne, 2005) People ex rel Nonhuman Rights Project, Inc. v Lavery [2014] 124 A D 3d 148 Ripken, “Corporations are people too: a multi-dimensional approach to the corporate personhood puzzle” 15 Fordham Journal of Corporate & Financial Law 97 (2010).
 
146
John C. Coffee, Jr., “No Soul to Damn: No Body To Kick: An Unscandalized Inquiry into the Problem of Corporate Punishment”, 79 Michigan Law Review 386 (1981). Gabriel Hallevy, When Robots Kill: Artificial Intelligence under Criminal Law (Northeastern University Press, Boston, 2013). Michaela Georgina Lexer and Luisa Scarcella, “Artificial Intelligence and Labor Markets. A Critical Analysis of Solution Models from a Tax Law and Social Security Law Perspective” 1(1) Rivista Italiana Di Informatica E Diritto 53–73 (2019).
 
147
Salomon v Solomon Co Ltd. [1897] AC 22.
 
148
Council of the European Communities, Council Directive 85/374/EEC of 25 July 1985 on the approximation of the laws, regulations and administrative provisions of the Member States concerning liability for defective products, (July 25, 1985). Lauren Sterrett, “Product Liability: Advancements in European Union Product Liability Law and a Comparison Between the EU and U.S. Regime”, 23 Michigan State International Law Review 885 (2015).
 
149
Niva Elkin-Koren & Michal S. Gal, The Chilling Effect of Governance by-Data on Data Markets, 86 U. CHI. L. REV. 403 (2019) (considering use of data and AI to craft “personalized law”—for instance, a speed limit for each driver).
 
150
Andrew D. Selbst & Solon Barocas, The Intuitive Appeal of Explainable Machines in Fordham Law Review, 87 Fordham L. Rev. 1085, 2018.
 
151
Meaghan Dunigan, The Intelligible Principle: How It Briefly Lived, Why It Died, and Why It Desperately Needs Revival in Today’s Administrative State in St. John’s Law Review, 91 St. John’s L. Rev. 247, 2017.
 
152
Kiel Brennan-Marquez & Stephen E. Henderson, Artificial Intelligence and Role-Reversible Judgment, 109 J. CRIM. L & CRIMINOLOGY 137 (2019) (mounting “defense of human judgment that focuses on the normative integrity of decision-making” and advocating “role-reversibility” as a requirement for introduction of “robo-judges”); Eugene Volokh, Chief Justice Robots, 67 DUKE L.J. 1135 (2019) (arguing that robot judges should generally be used for adjudicatory functions when they write relevant opinions as persuasively as competent human judges).
 
153
Eric Niiler, Can AI Be a Fair Judge in Court? Estonia Thinks So, WIRED (Mar. 25, 2019), https://​perma.​cc/​C7LA-GMD6 (describing Estonia’s plans to use a “robot judge” to reduce case backlogs at low cost); Peng Shen, Adoption of AI in Chinese Courts Paves the Way for Greater Efficiencies and Judicial Consistency, BAKER MACKENZIE (Feb. 28, 2018), https://​perma.​cc/​M7BS-Y84Y (discussing the Chinese judicial system’s integration of AI to “facilitate improved efficiencies” and increase access to litigation services).
 
154
Gregory N. Mandel, Legal Evolution in Response to Technological Change, in THE OXFORD HANDBOOK OF LAW, REGULATION, AND TECHNOLOGY 225 (Brownsword et al. eds., 2017).
 
155
Urs Gasser, Commentary, Recoding Privacy Law: Reflections on the Future Relationship Among Law, Technology, and Privacy, 130 HARV. L. REV. F. 61, 64 (2017).
 
156
Brett Frischmann & Evan Selinger, Re-Engineering Humanity (2018) (arguing that new technological applications change people’s habits and tolerances with respect to values such as privacy); Jack M. Balkin, The Path of Robotics Law, 6 CALIF. L. REV. CIR. 45, 49 (2015).
 
157
Ronald Leenes et al., Regulatory Challenges of Robotics: Some Guidelines for Addressing Legal and Ethical Issues, 9 L.INNOVATION & TECH. 1, 25 (2017).
 
158
Lydia Bennett Moses, Regulating in the Face of Sociotechnical Change, in THE OXFORD HANDBOOK OF LAW, REGULATION, AND TECHNOLOGY 573 (Brownsword et al. eds., 2017) (arguing that socio-technological changes due to rapid technological innovation, not new technology per se, produces legal and regulatory challenges). Planned Parenthood v. Casey, 505 U.S. 833, 856 (1992) (“The ability of women to participate equally in the economic and social life of the Nation has been facilitated by their ability to control their reproductive lives.”
 
159
Samuel L. Bray, The System of Equitable Remedies, 63 UCLAL. REV. 530, 536 (2016) (citing Jack B. Jacobs, The Uneasy Truce Between Law and Equity in Modern Business Enterprise Jurisprudence, 8 DEL. L. REV. 1, 4 (2005)).
 
160
Andrea Roth, Trial by Machine, 104 GEO. L.J. 1245, 1288–90 (2016) (discussing the guidelines’ susceptibility to mechanical application). Heckler v. Campbell, 461 U.S. 458, 458 (1983) (permitting “medicalvocational guidelines” that used a “matrix” to allocate disability benefits).
 
161
Arthur Rizner & Caleb Watney, Artificial Intelligence Can Make Our Jail System More Efficient, Equitable and Just, TEX. REV. L. & POL. 181 (2018) (contending that AI may improve pretrial decision-making, as compared to human judgments).
 
162
Joshua A. Kroll et al., Accountable Algorithms, 165 PENN. L. REV. 633, 656–95 (2017).
 
163
Richard Berk, An Impact Assessment of Machine Learning Risk Forecasts on Parole Board Decisions and Recidivism, 13 J.EXP.CRIM. 193, 193 (2017)(“Risk assessments based on machine learning forecasts can improve parole release decisions, especially when distinctions are made between re-arrests for violent and nonviolent crime.”). Chris Stewart, Hey Watson: Local Judge First to Use IBM’s Artificial Intelligence on Juvenile Cases, MY DAYTON DAILY NEWS (Aug. 3, 2017), https://​perma.​cc/​9TAN-4FM3 (quoting a local judge as celebrating use of AI to enhance efficiency and to “standardize best practices, which are not currently uniform”).
 
164
Andrew D. Selbst & Solon Barocas, The Intuitive Appeal of Explainable Machines, 87 FORDHAM L. REV. 1085 (2018) (discussing inscrutability and nonintuitiveness in algorithmic decision-making systems).
 
165
Peña-Rodriguez v. Colorado, 137 S. Ct. 855 (2017) (providing a limited exception to the “black box” of the criminal jury in cases of alleged racial bias).
 
166
Ric Simmons, Big Data, Machine Judges, and the Legitimacy of the Criminal Justice System, 52 U.C. DAVIS L. REV. 1067, 1067–68 (2018) (reporting on an empirical study that suggests ways of making people more likely to perceive algorithmic justice as legitimate).
 
167
Dorothy E. Roberts, Book Review, Digitizing the Carceral State, 132 HARV. L. REV. 1695, 1708 (2019) (characterizing algorithmic decision-making as “[i]nequality in, inequality out”).
 
168
Elizabeth E. Joh, The Undue Influence of Surveillance Companies on Policing, 91 N.Y.U. L. REV. 101, 102 (2017) (“Through different mechanisms intended to promote their own interests and profits, these [surveillance-technology producing] companies exert control over the police long after their products have been adopted. Private surveillance technology companies wield an undue influence over public police today in ways that aren’t widely acknowledged, but have enormous consequences for civil liberties and police oversight.”).
 
169
Albert R. Hunt, The Supreme Court Could Use a Few Good Politicians, Bloomberg News (July 18, 2018), https://​perma.​cc/​Z3UD-NAA9
 
170
Lawrence B. Solum, Artificially Intelligent Law, 1 BIOLAW J. 53 (2019).
 
171
Lawrence B. Solum, Procedural Justice, 78 S. CALIF. L. REV. 181, 275–81 (2004) (“the participation that is essential for legitimacy”).
 
172
Aziz Z. Huq, Racial Equity in Algorithmic Criminal Justice, 68 DUKE L.J. 1043, 1061 (2019) (discussing “substantial residual discretion” that remains “even when a written protocol is used” and noting that “[a]lgorithmic criminal justice represents a categorical rejection of … ad hoc, situated judgments as an instrument of regulations”).
 
173
Cary Coglianese & David Lehr, Regulating by Robot: Administrative Decision Making in the Machine-Learning Era, 105 GEO.L.J. 1147, 1184–91 (2017); William Boyd, Environmental Law, Big Data, and the Torrent of Singularities, 64 UCLA L. REV. DISCOURSE 544, 546–47 (2016). Ashley Deeks, Predicting Enemies, 104 VA.L.REV. 1529 (2018) (discussing the effects of military use of algorithmic prediction and noting transparency and other concerns).
 
174
Lord Chief Justice sets up advisory group on Artificial Intelligence. Retrieved from https://​www.​judiciary.​uk/​announcements/​lord-chief-justice-sets-up-advisorygroup-on-artificial-intelligence/​
 
175
US State Department, Secretary Michael R. Pompeo’s Remarks to the Press, 17 March 2020, https://​www.​state.​gov/​secretary-michael-r-pompeo-remarks-to-the-press-6/​ (“Turning to the ICC, a so-called court which is revealing itself to be a nakedly political body: As I said the last time I stood before you, we oppose any effort by the ICC to exercise jurisdiction over U.S. personnel. We will not tolerate its inappropriate and unjust attempts to investigate or prosecute Americans. When our personnel are accused of a crime, they face justice in our country”).
 
176
Robert E. Goodin, The State of the Discipline, The Discipline of the State, in The Oxford Handbook of Political Science (Robert E. Goodin ed., 2009) 5 (“politics is the constrained use of social power”). Ran Hirschl, The Judicialization of Politics, in The Oxford Handbook of Political Science, (Robert E. Goodin ed., 2009) at pp. 253, 254–255.
 
177
Ran Hirschl, The Judicialization of Politics, in The Oxford Handbook of Political Science (Robert E. Goodin ed., 2011).
 
178
Gerhard Wagner, ‘Robot Liability’ in Sebastian Lohsse, Rainer Schulze and Dirk Staudenmayer (eds), Liability for Artificial Intelligence and the Internet of Things (Hart 2019) 27–28.
 
179
Béatrice Schütte, Lotta Majewski, Katri Havu, Damages Liability for Harm Caused by Artificial Intelligence – EU Law in Flux, Legal Studies Research Paper Series Paper No 69 University Of Helsinki P1.
 
180
Michael Burmann, Rainer Heß, Kathrin Hühnermann and Jürgen Jahnke, Straßenverkehrsrecht (C.H. Beck 2020) Wissenschaftliche Dienste des Deutschen Bundestages ‘Autonomes und automatisiertes Fahren auf der Straße – rechtlicher Rahmen‘(2018) Ausarbeitung WD 7–3000 -111/18 4.
 
181
Estonian Law of Obligations Act (LOA) Janno Lahe and Taivo Liivak, ‘Strict liability for damage caused by self-driving vehicles: the Estonian perspective’ (2019) 12(2) Baltic Journal of Law & Politics 1, 6.
 
182
Case C-171/11 Fra.bo ECLI:EU:C:2012:453.
 
183
Case C-171/11 Fra.bo ECLI:EU:C:2012:176 (Opinion of Advocate General Trstenjak) [49].
 
185
According to Art 6(1) Consumer Rights Directive 2011/83/EU as amended by Directive 2019/2161/EU, the trader may have to inform the consumer “that the price has been personalized on the basis of an automated decision-making process.”
 
186
Article 5(2) Regulation 2019/1150 on promoting fairness and transparency for business users of online intermediation services (P2B Regulation), OJ L 186, 11 July 2019.
 
187
Government of Canada, ʻDirective on Automated Decision-Makingʼ, https://​www.​tbs-sct.​gc.​ca/​pol/​doc-eng.​aspx?​id=​32592
 
188
Loi no. 2016–1321 du 7 octobre 2016 pour une République numérique, Edwards L, Veale M (2018) Enslaving the algorithm: from a “right to an explanation” to a “right to better decisions”? IEEE Security & Privacy, May/June 46.
 
189
European Commission, ‘On Artificial Intelligence – A European Approach to excellence and trust’ COM (2020) 65 final (White Paper).
 
190
DIRECTIVE (EU) 2019/770 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 May 2019 on certain aspects concerning contracts for the supply of digital content and digital services L 136/1/22.5.2019.
 
191
Proposal for a Regulation of the European Parliament and of the Council on contestable and fair markets in the digital sector (Digital Markets Act) COM/2020/842 final.
 
192
European Commission. (2018, April 25). Communication Artificial Intelligence for Europe [Text]. https://​ec.​europa.​eu/​digital-single-market/​en/​news/​communication-artificialintell​igence-europe
 
193
European Parliament. (2020, October 12). Artificial Intelligence: Guidelines for military and non-military use. https://​www.​europarl.​europa.​eu/​news/​en/​pressroom/​20201209IPR93411​/​artificial-intelligence-guidelines-for-military-and-non-militaryuse
 
195
‘Report on the safety and liability implications of AI, the Internet of Things and Robotics’ COM (2020) 64 final, (Safety and Liability Report).
 
196
European Parliament resolution of 20 October 2020 with recommendations to the Commission on a civil liability regime for artificial intelligence (2020/2014(INL)).
 
197
EP, ‘Draft report with recommendations to the Commission on a civil liability regime for artificial intelligence’ 2020/2014(INL) (Draft Report). Resolution 2020/2012(INL) on a Framework of Ethical Aspects of Artificial Intelligence, Robotics and related Technologies (the “AI Ethical Aspects Resolution”), Resolution 2020/2015(INI) on Intellectual Property Rights for the development of Artificial Intelligence Technologies (the “IPR for AI Resolution”).
 
198
Andrea Bertolini, ‘Artificial Intelligence and Civil Liability’ (European Union 2020) (EP JURI Study).
 
199
Resolution 2020/2015(INI) on Intellectual Property Rights for the development of Artificial Intelligence Technologies (the “IPR for AI Resolution”).
 
200
Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts, COM(2021) 206 final, 21 April 2021, https://​digital-strategy.​ec.​europa.​eu/​en/​library/​proposal-regulationeurope​an-approach-artificial-intelligen
 
201
(COM(2021) 206 final).
 
202
Decision No 768/2008/EC of the European Parliament and of the Council of 9 July 2008 on a common framework for the marketing of products, and repealing Council Decision 93/465/EEC, OJ L 218/82.
 
203
European Commission Proposal for a Regulation of the European Parliament and of the Council laying down harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) 2021/0106 (COD) Articles 16–29, 30–39, 56–59 https://​eur-lex.​europa.​eu/​legal-content/​EN/​TXT/​?​uri=​CELEX:​52021PC0206
 
204
Article 6 and Annex III to the Commission draft legislation concerning the utilization of AI.
 
205
Article 5(1)(a)-(d) proposed regulation.
 
206
Artificial Intelligence Act. (21 April 2021). “Proposal for a regulation of the European Parliament and the Council laying down harmonised rules on Artificial Intelligence (Artificial Intelligence Act) and amending certain Union legislative acts.” EUR-Lex - 52021PC0206 https://​eurlex.​europa.​eu/​legalcontent/​EN/​TXT/​?​uri=​CELLAR:​e0649735-a372-11eb-9585-01aa75ed71a1 Digital Services Act. (15 December 2020). Proposal for a regulation of the European Parliament and the Council on a Single Market For Digital Services (Digital Services Act) and amending Directive 2000/31/EC. EUR-Lex - 52020PC0825 https://​eur-lex.​europa.​eu/​legal-content/​EN/​ALL/​?​uri=​CELEX:​52020PC0825. European Commission. (19 February 2020). White Paper on AI - A European approach to excellence and trust. https://​ec.​europa.​eu/​info/​sites/​default/​fles/​commission-white-paper-artificial-intelligencefeb2​020_​en
 
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Anu Bradford The Brussels Effect: How the European Union Rules the World (OUP, 2020); https://​www.​brusselseffect.​com/​ Graham Greenleaf, The ‘Brussels effect’ of the EU’s ‘AI Act’.
on data privacy outside Europe, UNSW Sydney (2021) 171 Privacy Laws & Business International Report 1, 3–7 https://​ssrn.​com/​abstract=​3898904
 
209
Jasmine Park ‘South Korea: The First Case Where the Personal Information Protection Act was Applied to an AI System’ Future of Privacy Forum, 21 May 2021 https://​fpf.​org/​blog/​south-korea-the-first-case-where-the-personal-informationprote​ction-act-was-applied-to-an-ai-system/​
 
210
Frederik Zuiderveen Borgesius, ‘Price Discrimination, Algorithmic Decision-Making, and European Non-Discrimination Law’ (2020) 31 European Business Law Review 401. McKane Andrus and others, ‘What We Can’t Measure, We Can’t Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness’ in (ACM 2021) Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency 249.
 
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Art 15; Michael Veale and others, ‘Algorithms that Remember: Model Inversion Attacks and Data Protection Law’ (2018) 376 Phil Trans R Soc A 20180083.
 
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Metadata
Title
AI and Politics
Author
Georgios I. Zekos
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-94736-1_10

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