2021 | OriginalPaper | Chapter
Hint
Swipe to navigate through the chapters of this book
Published in:
Economics and Law of Artificial Intelligence
Artificial intelligence has become a new engine for economic growth and as the central driving force of the new round of industrial reforms, artificial intelligence will further discharge the energy accumulated from prior technological revolutions and industrial alterations by generating new powerful engines to modernize economic activities such as production, distribution, exchange, and consumption. The decentralized nature of blockchain generates, the new concept of a token economy in which the community’s revenue is allocated to the actual content producers and service users who generate value. In addition, Blockchain is a key technology that enables new protocols for the establishment of a token economy in the future, leading to a new economic paradigm. Digital technologies are now turning the world upside down and so an ongoing series of technological developments have transformed economic and social life. The integration of AI agents into society has led to a different manner in which persons interact with each other, along with a new kind of direct interaction presented with AI agents, which are increasingly posed in society.
Please log in to get access to this content
To get access to this content you need the following product:
Advertisement
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
Řehák, D., Šenovský, P., Hromada, M., Pidhaniuk, L., Dvořák, Z., Loveček, T., Ristvej, J., Leitner, B., Sventeková, E., Mariš, L., 2018. Metodika hodnocení resilience prvku kritické infrastruktury. Ostrava: VŠB-Technická univerzita Ostrava, Fakulta bezpečnostního inženýrství. ISBN 978-80-248-4164-9.
Obrová, V., Smolíková, L., 2013. The role of risk management in successful project management. International Business Information Management Association Conference, IBIMA 2013; Vienna.
Klučka, J., Havko, J., Haviernikova, K., 2016. Risk Management in Cluster’s Cooperation in Slovak Republic. Conference: 3rd International Multidisciplinary Scientific Conference on Social Sciences and Arts, SGEM 2016 Location: Albena, Bulgaria.
P. Dunphy, F.A. Petitcolas, A first look at identity management schemes on the blockchain, IEEE Secur. Priv. 16 (4) (2018) 20–29.
R. Beck, M. Avital, M. Rossi, J.B. Thatcher, Blockchain Technology in Business and Information Systems Research, Springer, 2017.
G. He, W. Su, S. Gao et al., TD-Root: A trustworthy decentralized DNS root management architecture based on permissioned blockchain, Future Generation Computer Systems (2019), doi:
https://doi.org/10.1016/j.future.2019.09.037.
Durst, S., Bruns, G., & Henschel, T. (2016), The management of knowledge risks: What do we really know? International Journal of Knowledge and Systems Science, 7, 19–29. https://10.4018/IJKSS.2016070102.
Bratianu, C. (2018). A holistic approach to knowledge risk. Management Dynamics in the Knowledge Economy, 6, 593–607.
https://doi.org/10.25019/MDKE/6.4.06.
Susanne Dursta, Christoph Hinteregger, Malgorzata Zieba, The linkage between knowledge risk management and organizational performance, 2019 Journal of Business Research 1-10.
Valeria Naciti, Corporate governance and board of directors: The effect of a board composition on firm sustainability performance, 2019 Journal of Cleaner Production 117727.
Charilaos Mertzanisa, Mohamed A.K. Basuonyb, Ehab K.A. Mohamed, Social institutions, corporate governance and firm-performance in the MENA region 2019 Research in International Business and Finance 75.
Shiyang Huang, Ying Jiang, Zhigang Qiuc, Zhiqiang Ye, An equilibrium model of risk management spillover, 2020 Journal of Banking and Finance 105604 p15 (The risk management spillover effect arises because relative performance concerns have different effects on different managers. Specifically, relative performance concerns do not change the behaviors of RM managers but have a significant impact on those of normal managers. As a result, relative performance concerns amplify the effects of risk management suggesting that a small fraction of RM managers can have a significant market impact.) Sumon Bhaumik, Nigel Driffield, Ajai Gaur, Tomasz Mickiewicz, Paul Vaalere, Corporate governance and MNE strategies in emerging economies, Journal of World Business 54 (2019) 234–243.
Corinne H.Y. Tan, ‘Technological “Nudges” and Copyright on Social Media Sites’ (2015) 2015(1) Intellectual Property Quarterly 62; David Tan, ‘Fair Use and Transformative Play in the Digital Age’ in Megan Richardson and Sam Ricketson (eds), Research Handbook on Intellectual Property in Media and Entertainment (Edward Elgar 2017).
‘Intellectual Property’ (Facebook) <
transparency.facebook.com/intellectual-property> accessed 26 July 2019. See further Daniel Seng, ‘The State of the Discordant Union: An Empirical Analysis of DCMA Takedown Notices’ (2014) 18 Virginia Journal of Law & Technology 369; Jennifer Daskal, ‘Google Inc. v. Equustek Solutions Inc.’ (2018) 112 American Journal of International Law 727.
Anat Lior, The AI Accident Network: Artificial Intelligence Liability Meets Network Theory
https://ssrn.com/abstract=3561948.
Hous. Fed’n of Teachers, Local 2415 v. Hous. Indep. Sch. Dist., 251 F. Supp. 3d 1168 (S.D. Tex. 2017). Danielle Keats Citron & Frank Pasquale, The Scored Society: Due Process for Automated Predictions, 89 WASH. L. REV. 1, 8–10 (2017) (describing the use of algorithms in credit scoring). Andrew D. Selbst, Disparate Impact in Big Data Policing, 52 GA. L. REV. 109, 113–15 (2017) (describing predictive policing). Meredith Whittaker Et Al., AI Now Inst., AI Now Report 2018, at 18–22 (2018),
https://ainowinstitute.org/AI_Now_2018_Report.pdf.
Andrew Guthrie Ferguson, Big Data and Predictive Reasonable Suspicion, 163 U. PA. L. REV. 327, 389–95 (2015) (discussing some of the ways law enforcement can use large data sets to eliminate biases in policing); Ric Simmons, Big Data, Machine Judges, and the Legitimacy of the Criminal Justice System, 52 U.C. DAVIS L. REV. 1067, 1096–97 (2018) (noting that one of the “primary benefits of using predictive algorithms” is “their complete disregard of irrelevant subjective factors” like race, religion, what a person wears, how they conduct themselves in court, and so forth).
Frank Pasquale, The Black Box Society: The Secret Algorithms That Control Money And Information 1–17 (2015) (describing the ways in which data analyses about consumers are hidden from view and from legal process). Emily Berman, A Government of Laws and Not of Machines, 98 B.U. L. REV. 1277, 1279 (2018).
Rebecca Wexler, Life, Liberty, and Trade Secrets: Intellectual Property in the Criminal Justice System, 70 Stan. L. Rev. 1343 (2017) (describing how trade secrecy impacts the criminal justice system noting that policies for algorithmic transparency should consider the potential for gaming). Andrew D. Selbst & Solon Barocas, The Intuitive Appeal of Explainable Machines, 87 Fordham L. Rev. 1085, 1092–94 (2018) (arguing that understanding machine learning algorithms takes “specialized knowledge” and even with that knowledge, the basis of a decision is often still inscrutable). Harry Surden, Machine Learning and the Law, 89 Wash. L. Rev. 87, 89 (2014) (explaining how machine learning can make algorithms capable of adapting “to enhance their performance on some task through experience”).
Mayer-Schönberger/Cukier, Big Data: A Revolution that will Transform How We Live, Work and Think, 2013, p. 14, 15, 18, and p. 163: “Big Data does not tell us anything about causality”. Skopek, Big Data’s Epistemology and Its Implications for Precision Medicine and Privacy, in: Cohen/Fernandez Lynch/Vayena/Gasser (eds.), Big Data, Health Law, and Bioethics, 2018, pp. 30 et seq.
Ari Ezra Waldman, Power, Process, and Automated Decision-Making, 88 Fordham L. Rev. 613 (2019). Available at:
https://ir.lawnet.fordham.edu/flr/vol88/iss2/9; Jedediah Purdy, Neoliberal Constitutionalism: Lochnerism for a New Economy, 77 Law & Contemp. Probs. 195, 198–203 (2014) (describing neoliberal interpretations of constitutional provisions); Amanda Shanor, The New Lochner, 2016 Wis. L. Rev. 133, 145 (chronicling a corporate social movement to interpret the First Amendment in line with neoliberal, libertarian ideas).
Chris Jay Hoofnagle et al., The European Union General Data Protection Regulation: What It Is and What It Means, 28 Info. & Comm. Tech. L. 65, 67 (2019) (“[T]he GDPR can be seen as a data governance framework. The GDPR encourages companies to think carefully about data and have a plan for the collection, use, and destruction of the data. The GDPR compliance process may cause some businesses to increase the use of data in their activities, especially if the companies are not dataintensive, but the GDPR causes them to realize the utility of data.”); Margot E. Kaminski, Binary Governance: Lessons from the GDPR’s Approach to Algorithmic Accountability, 92 S. Cal. L. Rev. 1529, 1552–53 (2019).
Article 29 Data Protection Working Party (28 November 2017) EU – U.S. Privacy Shield – First annual Joint Review, Brussels,
https://ec.europa.eu/newsroom/just/document.cfm?doc_id=48782.
Article 29 Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679,
https://www.autoriteitpersoonsgegevens.nl/sites/default/files/atoms/files/guidelines_on_profiling_w p251rev01_enpdf.pdf.
Mikella Hurley and Julius Adebayo, “Credit Scoring in the Era of Big Data,” Yale Journal of Law & Technology 18, no. 1 (2016): 148–216.
Wachter/Mittelstadt/Floridi, Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation, (2017) 7(2) International Data Privacy Law 76, at p, 92.
http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-%2F%2FEP%2F%2FTEXT%2BREPORT%2BA7-2013-0402%2B0%2BDOC%2BXML%2BV0%2F%2FEN&language=EN.
F. Decarolis and G. Rovigatti. From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising. working paper, 2018. E. Calvano, G. Calzolari, V. Denicolo, and S. Pastorello. Artificial Intelligence, Algorithmic Pricing and Collusion. SSRN Electronic Journal, 2019b. www.ssrn.3304991.
Greenberg, A., “An AI That Reads Privacy Policies So That You Don’t Have To,” Wired (9 Feb. 2018),
https://www.wired.com/story/polisis-ai-reads-privacy-policies-so-you-dont-have-to/.
S Barocas and AD Selbst, ‘Big data’s disparate impact’ (2016) 104 Calif Law Rev 671. Equivant, COMPAS Classification, 2018,
http://www.equivant.com/solutions/inmateclassification.
M. Ali and others, ‘Discrimination through optimization: How Facebook’s ad delivery can lead to skewed outcomes’ (2019)
https://arxiv.org/abs/1904.02095.
Direct discrimination is defined as follows in Article 2(2)(a) of the Racial Equality Directive 2000/43/EC: ‘Direct discrimination shall be taken to occur where one person is treated less favourably than another is, has been or would be treated in a comparable situation on grounds of racial or ethnic origin.’ the Employment Equality Directive (2000/78/EC), the Gender Goods and Services Directive (2004/113/EC), and the Recast Gender Equality Directive (2006/54/EC) use similar definitions.
Tobler C, Indirect discrimination: a case study into the development of the legal concept of indirect discrimination under EC law, vol 10 (Intersentia 2005).
ECtHR, Biao v. Denmark (Grand Chamber), No. 38590/10, 24 May 2016, par. 89.
G. González Fuster, The Emergence of Personal Data Protection as a Fundamental Right of the EU (Springer 2014), p. 164–166. Article 5, 7, and 10 COE Data Protection Convention 2018. Article 1(2) and recital 71, 75, and 85 GDPR, and article 1 of the Convention for the protection of individuals with regard to the processing of personal data, Amending protocol to the Convention for the Protection of Individuals with Regard to the Processing of Personal Data, adopted by the Committee of Ministers at its 128th Session in Elsinore on 18 May 2018,
https://rm.coe.int/convention-108-conventionfor-the-protection-of-individuals-with-regar/16808b36f1; S. Wachter and B. Mittelstadt, ‘A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI’,
https://ssrn.com/abstract=3248829.
P. Hacker, ‘Teaching fairness to artificial intelligence: Existing and novel strategies against algorithmic discrimination under EU law’ (2018) 55 Common Market Law Review, Issue 4, pp. 1143–1185.
Gutachten der Datenethikkommission, 2019,
https://www.bmjv.de/SharedDocs/Downloads/DE/Themen/Fokusthemen/Gutachten_DEK_DE.pdf?__blob=publicationFile&v=5.
A. Rieke, M. Bogen and D.G. Robinson, ‘Public Scrutiny of Automated Decisions: Early Lessons and Emerging Methods, Upturn and Omidyar Network’ (2018)
http://www.omidyar.com/sites/default/files/file_archive/Public%20Scrutiny%20of%2Automated%20Decisions.pdf; B. Bodo et al., ‘Tackling the algorithmic control crisis-the technical, legal, and ethical challenges of research into algorithmic agents’ (2017) 19 Yale JL & Tech. 133.
Zuiderveen Borgesius, Frederik J. “Strengthening legal protection against discrimination by algorithms and artificial intelligence.” The International Journal of Human Rights (2020): 1–22.
https://doi.org/10.1080/13642987.2020.1743976.
Emre Kazim, Adriano Koshiyama, Lack of Vision A Comment on the EU’s White Paper on Artificial Intelligence,
https://ssrn.com/abstract=3558279 p29.
42 USC § 3601 et seq. 4 42 USC § 3605(a). These laws do not exhaust the legal framework governing discrimination in credit pricing.
Talia B. Gillis & Jann L. Spiess, Big Data and Discrimination, 2019 The University of Chicago Law Review 459 p17.
Deepak Amirtha Raj, ‘Spotlight on the Remarkable Potential of AI in KYC’ (13 June 2017) <
https://medium.com/all-technology-feeds/spotlight-on-the-remarkable-potential-of-ai-in-kyc7441bf7eec38>.
Chartis Research, Demystifying AI for Risk and Compliance (2018) 2 <
https://www.ibm.com/blogs/insightson-business/banking/demystifying-ai-risk-compliance/>. Global Financial Innovation Network (GFIN), Consultation document (August 2018) 4
https://www.fca.org.uk/publication/consultation/gfin-consultation-document.pdf.
Jen Clarke, ‘Spotlight on “LawTech”: How Machine Learning is Disrupting the Legal Sector’, IBM Blogs (online), 11 December 2017, <
https://www.ibm.com/blogs/internet-of-things/iot-spotlight-on-lawtech/>. Paul Lippe, Daniel Martin Katz and Dan Jackson, ‘Legal by Design: A New Paradigm for Handling Complexity in Banking Regulation and Elsewhere in Law’ (2015) 93 Oregon Law Review 833, 849–850. Rage-AI, <
http://www.rageframeworks.com>; eBrevia, <
https://ebrevia.com/diligenceaccelerator>; Seal, <
https://www.seal-software.com/role-head-ma>; Kira, <
https://kirasystems.com>.
In ASIC v Healey (2011) 278 ALR 618 (the “Centro case”) the Federal Court found the directors of the Centro Group personally liable for errors in the financial statements of the Group for the financial year ended 30 June 2007. The court found that the directors failed to discharge their duties with the degree of care and diligence that a reasonable person would in the circumstances; and failed to take all reasonable steps to comply with, or to secure compliance with, the financial reporting provisions in the Corporations Act 2001.
Sean Martin, AI Warning: Robots will be Smarter than Humans by 2045, Google Boss Says’, 17 October 2017, Express (online),
https://www.express.co.uk/news/science/867565/google-artificial-intelligence-ray-kurzweil-AI-singularity.
Sarah Danckert and Clancy Yeates, ‘CBA Accused of Board Minutes Criminal Breach’ The Sydney Morning Herald (21 November 2018).
Maziar Peihani, ‘Financial Regulation and Disruptive Technologies: The Case of Cloud Computing in Singapore’ (2017) Singapore Journal of Legal Studies 77 Ellie Chapple and Elisabeth Sinnewe, ‘So What’s a Secretary to Do? Banking Royal Commission Raises Questions About What’s in Minutes’ The Conversation (29 November 2018) (online)
http://theconversation.com/so-whats-a-secretary-to-do-banking-royal-commission-raises-questions-aboutwhats-in-minutes-107509: ‘Company secretaries are already acutely aware that every set of minutes of every board meeting might one day end up as evidence.’ Australian Securities and Investments Commission v Hellicar (2012) 286 ALR 501 (the resolution adopting a misleading ASX announcement in the minutes of a board meeting was held to have been a ‘contemporaneous record of proceedings at the meeting).
Attila Gulyás, István Kiss, István Berta, Artificial intelligence in electrostatic risk management Journal of Electrostatics 71 (2013) 387–391.
Mark Fenwick and Erik P. M. Vermeulen ‘The Digital Future of Corporate Governance’ International Corporate Governance Network Yearbook 2018, p. 11; Mark Fenwick and Erik P. M. Vermeulen, ‘Technology & Corporate Governance’ 48(1) The Texas Journal of Business Law, 1 (2019); Mark Fenwick and Erik P. M. Vermeulen, ‘The Unmediated and Technology-Driven Corporate Governance of Today’s Winning Companies’ New York University Journal of Law and Business (2020). Mark Fenwick & Erik P. M. Vermeulen, ‘Technology & Corporate Governance’ (2018)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3263222.
Kevin Kelly Alec Ross, Understanding the 12 Technological Forces that Will Shape Our Future (Penguin 2017).
Mark Fenwick Erik P.M. Vermeulen, The End of the Corporation, Working Paper N° 482/2019 November 2019, ECGI Working Paper Series in Law P 3.
Ajay Agrawal, Joshua Gans, and Avi Goldfarb. Exploring the impact of artificial intelligence: Prediction versus judgment. Information Economics and Policy, 46:1–6, 2019.
Dylan Hadfield-Menell and Gillian K. Hadfield. Incomplete contracting and ai alignment. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019.
Jessica Fjeld, Nele Achten, Hannah Hilligoss, Adam Christopher Nagy, Madhulika Srikumar Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI Research Publication No. 2020-1 January 15, 2020
https://ssrn.com/abstract=3518482.
R. Feracone, ‘Good Governance, Do Boards Need Cyber Security Experts?’, Forbes 9 July 2019,
www.forbes.com/sites/robinferracone/2019/07/09/goodgovernance-do-boards-need-cyber-security-experts/#e9ded6618592.
Safiya Umoja Noble, Algorithms Of Oppression: How Search Engines Reinforce Racism (2018); Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, And Punish The Poor (2017).
Winter, The Human Experience of Being-in-the-Board: A Phenomenological Approach, SSRN, 2018,
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3319392; E. van de Loo & J. Winter, ‘Corporate Culture is an Alarmingly Low Priority for Boards’, Insead Knowledge, 10 November 2017,
https://knowledge.insead.edu/leadership-organisations/corporate-culture-is-analarmingly-low-priority-for-boards-76.
Ursula Von der Leyen, ‘A Union that strives for more: My agenda for Europe’ (July 2019) <ec.europa.eu/commission/sites/beta-political/files/political-guidelines-nextcommission_en.pdf >
Niklas Bussmann, Paolo Giudici, Dimitri Marinelli, Jochen Papenbrock, Explainable AI in credit risk management,
https://ssrn.com/abstract=3506274 p 12.
J. Miller, ‘Mark Zuckerberg asks governments to regulate tech firms’, Techspot 31 March 2019,
www.techspot.com/news/79440-mark-zuckerberg-asks-governments-regulate-tech-firms.html.
Prof. Lokke Moerel, Reflections on the impact of the digital revolution on corporate governance of listed companies, at:
https://ssrn.com/abstract=3519872 P45.
Barry Libert, Megan Beck and Mark Bonchek, ‘AI in the Boardroom: The Next Realm of Corporate Governance’ (October 2017) MIT Sloan Management Review <
https://sloanreview.mit.edu/article/ai-in-theboardroom-the-next-realm-of-corporate-governance/>. David Lancefield and Carlo Gagliardi, ‘Reimaging the Boardroom for an Age of Virtual Reality and AI’ Harvard Business Review (April 2015) <
https://hbr.org/2015/04/reimagining-the-boardroom-for-an-age-of-virtual-reality-and-ai>.
https://www.austrac.gov.au/lists-enforcement-actions-taken
https://www.apra.gov.au/news-and-publications/apra-launcheswestpac-investigation-and-increases-capital-requirement-add-ons.
Australian Prudential Regulation Authority, Prudential Inquiry into the Commonwealth Bank of Australia – Final Report (20 April 2018),
https://www.apra.gov.au/sites/default/files/CBA-Prudential-Inquiry_FinalReport_30042018.pdf.
Martin Petrin, ‘Corporate management in the Age of AI’UCL Working Paper Series (No. 3/2019), at
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3346722##; H James Wilson and Paul R Daugherty, ‘Collaborative Intelligence: Humans and AI are Joining Forces’, Harvard Business Review (online), July-August 2018, <
https://hbr.org/2018/07/collaborativeintelligence-humans-and-ai-are-joining-forces?referral=03758&cm_vc=rr_item_page.top_right>; Anita Williams Woolley, Ishani Aggarwal and Thomas W Malone, ‘Collective Intelligence and Group Performance’ (2015) 25 Current Directions in Psychological Science 420; Timothy C Bates and Shivani Gupta, ‘Smart Groups of Smart People: Evidence of IQ as the Origin of Collective Intelligence in the Performance of Human Groups’ (2017) 60 Intelligence 46.
Kraus, Sascha and Palmer, Carolin and Kailier, Norbert and Lukas kallinger, Friedrich and Spitzer, Jonathan, Digital entrepreneurship: A research agenda on new business models (September 20, 2018). Available at:
https://www.emerald.com/insight/content/doi/10.1108/IJEBR-06-2018-0425/full/html.
Laila Al-Blooshi, Haitham Nobanee, Applications of Artificial Intelligence in Financial Management Decisions: A Mini-Review,
https://ssrn.com/abstract=3540140 p 13–14.
State v. Loomis, 881 N.W.2d 749, 755 (Wis., 2016). Herbert Wechsler, Toward Neutral Principles of Constitutional Law, 73 Harv. L. Rev. 1, 19–20 (1959) (arguing that the ‘virtue or demerit of a judgment turns … entirely on the reasons that support it’) Mathilde Cohen, When Judges Have Reasons Not to Give Reasons: A Comparative Law Approach, 72 Wash. & Lee L. Rev. 483 (2015).
Lin, Tom, Artificial Intelligence, Finance, and the Law (November 04, 2019).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3480607.
Deloitte EMEA Centre for Regulatory Strategy, AI and Risk Management – Innovating with Confidence (April 2018) 1–2 <
https://www2.deloitte.com/au/en/pages/financial-services/articles/ai-riskmanagement.html>; Jeanne Boillet, EY, “Why AI is both a risk and a way to manage risk” (1 April 2018) <
https://www.ey.com/en_gl/assurance/why-ai-is-both-a-risk-and-a-way-to-manage-risk>; McKinsey & Company, “The future of risk management in the digital era” (October 2017) <
https://www.mckinsey.com/business-functions/risk/our-insights/the-future-of-risk-management-in-thedigital-era>.
Pascal Bizarro and Margaret Dorian, ‘Artificial Intelligence: The Future of Auditing’ (October 2017) Internal Auditing 21.
The Institute of Internal Auditors Global, Global Perspectives and Insights – The IIA’s Artificial Intelligence Auditing Framework (September 2017) 2,
https://na.theiia.org/periodicals/Pages/Global-Perspectives-andInsights.aspx; Paul Holland, Shamus Rae and Paul Taylor, ‘Why AI must be included in audits’ (June 2018)
https://assets.kpmg.com/content/dam/kpmg/uk/pdf/2018/06/why-ai-must-be-included-in-audits.PDF.
He Li, Jun Dai, Tatiana Gershberg and Miklos Vasarhelyi, ‘Understanding Usage and Value of Audit Analytics for Internal Auditors: An Organisational Approach’ (2018) 28 International Journal of Accounting Information Systems 59; Nurmazilah Mazhan and Andy Lymer, ‘Examining the Adoption of Computerassisted Audit Tools and Techniques’ (2014) 29 Managerial Auditing Journal 327.
Syed Moudud-UI-Huq, ‘The Role of Artificial Intelligence in the Development of Account Systems: A Review” (2014) 13 Journal of Accounting Research & Audit Practices 7. Bill Brennan, Mike Baccala, Mike Flynn and 10Rule, ‘Artificial Intelligence Comes to Financial Statement Audits’, CFO Magazine (February 2017) <
http://ww2.cfo.com/auditing/2017/02/artificial-intelligenceaudits/>.
Michael P Cangemi and Patrick Taylor, ‘Harnessing Artificial Intelligence to Deliver Real-Time Intelligence and Business Process Improvements’ EDPACS (online), 27 April 2018, 3 <
https://www.tandfonline.com/doi/abs/10.1080/07366981.2018.1444007>.
Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry (Interim Report, September 2018). Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry (Final Report, February 2019).
Steven L. Schwarcz, Systemic Risk, 97 Geo. L.J. 193, 200 (2008) (explaining disintermediation’s role in “enabling companies to access the ultimate source of funds, the capital markets, without going through banks or other financial intermediaries”). Tom C. W. Lin, Infinite Financial Disintermediation, 50 Wake Forest L. Rev. 643 (2015) (discussing disintermediation in the financial industry). Sarah Kellogg, The Uncertain Future: Turbulence and Change in the Legal Profession, 30 Wash. Law. 18, 21 (2016) (explaining that 67% of law firms surveyed in 2016 stated they were “currently losing business to corporate law departments that are insourcing legal work”).
Jane Croft, The Relentless Advance of the Super-Intelligent Attorney, FIN. TIMES (Dec. 5, 2016),
https://www.ft.com/content/af3e2a64-a069-11e6-891e-abe238dee8e2.
The New Reality: Turning Risk Into Opportunity Through The Dupont Legal Model 2 (Silvio J. Decarli & Andrew L. Schaeffer eds., 5th ed. 2009).
Sterling Miller, Artificial Intelligence And Its Impact on Legal Technology: To Boldly Go Where No Legal Department Has Gone Before, Thomson Reuters (“As CEOs and CFOs become more accustomed to using AI, they will expect the other members of the CSuite—including the general counsel and legal department—to follow suit. In-house lawyers that embrace AI, will become more valuable to the next generation of CEOs and CFOs.”).
Sarah Murray, Algorithms Tame Ambiguities in Use of Legal Data, FIN. TIMES (Nov. 15, 2018),
https://www.ft.com/content/50b0eba4-d063-11e8-9a3c-5d5eac8f1ab4 (“[T]he next step is to enable machines to make qualitative analyses of legal documents.”).
What Is Project Management?, PROJECT MGMT. INST.,
https://www.pmi.org/about/learn-about-pmi/what-is-project-management.
Jeffrey K. Liker, The Toyota Way: 14 Management Principles From The World’s Greatest Manufacturer (2004).
In re Citigroup, Inc. S’holder Derivative Litig., 964 A.2d 106, 127–28 (Del. Ch. 2009) (shareholder suit alleging directors breached fiduciary duties pursuing excessively risky strategies); Stephen M. Bainbridge, Caremark and Enterprise Risk Management, 34 J. CORP. L. 967, 969 (2009); Kristin N. Johnson, Addressing Gaps in the Dodd-Frank Act: Directors’ Risk Management Oversight Obligations, 45 U. MICH. J.L. REFORM 55, 59 (2011) (“In the absence of rigorous ERM obligations under state corporate law and in the wake of the recent financial crisis, Congress has taken steps to impose federal regulation on risk management oversight. In July of 2010, Congress adopted the [Dodd-Frank Act].”).
Carolyn Kay Brancato Et Al., The Conference Bd., The Role Of U.S. Corporate Boards In Enterprise Risk Management 10 (2006),
https://www.conference-board.org/pdfdownload.cfm?masterProductID=3840.
Alm Intelligence & Morrison & Foerster LLP, General Counsel Up-Atnight Report 5 (2018),
https://media2.mofo.com/documents/170622-gc-up-at-nightreport.pdf (“Now, GCs must not only think globally to maintain a culture of compliance regardless of geography, but also act locally in establishing policies and procedures to ensure corporate action meets the prevailing local regulatory standards.”).
June Eichbaum, Globalization and General Counsel, MINORITY CORP. COUNS. ASS’N,
https://www.mcca.com/mcca-article/globalization-and-general-counsel/ (explaining that “hands-on experience with regulators in the European Union and in Asia” is a ‘must-have[]’ for general counsel”). Jennifer G. Hill, Legal Personhood and Liability for Flawed Corporate Cultures (European Corp. Governance Inst. Working Paper Series in Law, Working Paper No. 413/2018, 2018).
Lisa M. Fairfax, From Apathy to Activism: The Emergence, Impact, and Future of Shareholder Activism as the New Corporate Governance Norm, 99 B.U. L. REV. 1301, 1314 (2019). Matteo Tonello & Matteo Gatti, Board-Shareholder Engagement Practices, Harv. L. Sch. F. On Corp. Governance (Dec. 30, 2019),
https://corpgov.law.harvard.edu/2019/12/30/board-shareholder-engagement-practices/ (“Sixty percent or more of the largest companies involve their general counsel in board exchanges with investors.”).
Matteo Tonello & Matteo Gatti, Board-Shareholder Engagement Practices: Findings From A Survey Of Secregistered Companies 42–43 (2019),
https://www.conference-board.org/pdfdownload.cfm?masterProductID=20347.
Veena Ramani, Environmental, Social, and Governance (“ESG”) Issues Pose Risks to Companies. Can Chief Legal Officers Help Drive Solutions?, ASS’N CORP. COUNS. (Nov. 6 2019),
https://www.acc.com/resource-library/environmental-social-and-governance-esgissues-pose-risks-companies-can-chief-0 (“In 2018, investors filed nearly 400 shareholder resolutions on sustainability issues, many of them related to climate change.”).
Safavi, K. and F. Dare, 2018. Virtual health care could save the U.S. billions each year. Harvard Business Review, April 3, 2018.
https://hbr.org/2018/04/virtual-health-care-could-save-theu-s-billions-each-year.
Pacis, D.M.M., E.D.C. Subido Jr. and N.T. Bugtai, 2018. Trends in telemedicine utilizing artificial intelligence. AIP Conf. Proc., Vol. 1933, No. 1.
OECD (2019). Artificial intelligence in society. Paris: OECD. Emre Pakdemirli. Artificial intelligence in radiology: Friend or foe? Where are we now and where are we heading? Acta Radiologica Open, 8, 2, 1–5, 2019.
Denise Myshko & Robin Robinson, Artificial Intelligence: Molecule to Market, Pharmavoice (Jan. 2019),
https://www.pharmavoice.com/article/2019-01-pharma-ai/.
Bank for International Settlements (2020). Policy responses to fintech: a cross-country overview. FSI Insights on Policy Implementation, No. 23. January Kearns, M., Roth, A. 2019. The Ethical Algorithm: The Science of Socially Aware Algorithm Design (Oxford University Press, Oxford).
Balyuk, T. & Davydenko, S. A. (2019). Reintermediation in fintech: Evidence from online lending. Available at SSRN 3189236.
Vallee, B. & Zeng, Y. (2019). Marketplace lending: a new banking paradigm? The Review of Financial Studies, 32(5), 1939–1982.
Xiaoyang Li, Haitian Lu, Iftekhar Hasan The Dark Side of Unregulated Artificial Intelligence: Evidence from Online Marketplace Lending, at:
https://ssrn.com/abstract=3575260.
Kristina Irion, and Josephine Williams (2019). ‘Prospective Policy Study on Artificial Intelligence and EU Trade Policy’. Amsterdam: The Institute for information Law, 2019. Amsterdam, January 2020 The Institute for Information Law (IViR).
Peter Cappelli, Prasanna Tambe, & Valery Yakubovich, Artificial Intelligence in Human Resources Management: Challenges and a Path Forward (Nov. 1, 2018),
https://ssrn.com/abstract=3263878. Report by the High-Level Expert Group on Artificial Intelligence, A definition of AI: Main capabilities and scientific disciplines, at 1, COM (2019) (Apr. 8, 2019).
Mirela Ivanova et al., The App as a Boss? Control and Autonomy in Application-Based Management, 2 Interdisziplinärer Arbeitsforschung (2018). Christian Ernst, Algorithmische Entscheidungsfindung und personenbezogene Daten, 72 Juristenzeitung (2017). “[a]n algorithm can be understood as an unambiguous, executable sequence of clearly defined instructions of finite length to solve a problem.”
Marta Otto, “Workforce Analytics” V Fundamental Rights Protection in the EU in the Age of Big Data, 40 Comp Lab. L. & Pol’y J. 389 (2019).
Alexandra Mateescu & Aiha Nguyen, Workplace Monitoring & Surveillance, Data & Society (2019),
https://goo.gl/Cv4EAi. Sarah Kessler, Gigged: The End Of The Job And The Future Of Work (2018). Derek Zimmer, The Internet of Things is Surveillance, Private Internet Access, Nov. 21, 2018,
https://www.privateinternetaccess.com/blog/2018/11/the-internet-of-things-is-surveillance/.
Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60.
Phoebe Moore, The Mirror for (Artificial) Intelligence: In Whose Reflection?, 41 COMP. LAB. L. & POL’Y J PG# (2019) Valerio De Stefano, ‘Negotiating the Algorithm’: Automation, Artificial Intelligence and Labour Protection, 41 Comp. Lab. L. & Pol’y J PG# (2019).
Brishen Rogers, Beyond Automation: The Law & Political Economy of Workplace Technological Change 24 (Roosevelt Institute Working Paper, 2019),
https://ssrn.com/abstract=3327608.
Evgeny Morozov, Capitalism’s New Clothes, The Baffler (Feb. 4, 2019),
https://thebaffler.com/latest/capitalisms-new-clothes-morozov; Ekkehard Ernst et al., The economics of artificial intelligence: Implications for the future of work, 5 ILO Future Of Work Research Paper Series 1 (ILO, 2018).
Code Du Travail [C. TRAV.], art. L. 1222-4. 92. Code Du Travail [C. TRAV.], art. L. 2321-38. Cour de Cassation, Chambre Sociale [Labor Division of the supreme court] October 2, 2001, No. 99-42.942 (Fr.).
Marie Morin and Francis Kessler, Labor impact of technological devices in France, 2 IUSLABOR 19–34 (2018). Christophe Vigneau, Information Technology and Workers’ Privacy: The French Law, 23 Comp. Lab. L. & Pol’y J. 351 (2002). Bernard Bossu & Alexandre Barège, Preuve et surveillance des salariés: regard français, 54 Les Cahiers De Droit 277, 279 (2013).
Udo Di Fabio, GG, Article 2, margin 14, in GRUNDGESETZ-KOMMENTAR (Theodor Maunz & Gunter Dürig eds. 2018, 84th supplement August 2018). Ingrid Schmidt, GG, Article 2, margin 43, in ERFURTER KOMMENTAR ZUM ARBEITSRECHT (2019).
Pietro Lambertucci, La disciplina dei «controlli a distanza», GIUR. IT., 737 (2016); Alessandra Ingrao, Il controllo disciplinare e la privacy del lavoratore dopo il Jobs Act, 1 RIV. IT. DIR. LAV. 46 (2017).
OECD, Recommendation of the Council on Artificial Intelligence, OECD/LEGAL/0449 (May 12, 2019),
https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449.
Danielle Keats Citron & Frank Pasquale, The scored society: Due process for automated predictions, 89 WASH. L. REV. 1 (2014). Graham Sewell, Nice work? Rethinking managerial control in an era of knowledge work, 12 ORG. 685 (2005). Catherine Tucker, Privacy, Algorithms, and Artificial Intelligence, in The Economics Of Artificial Intelligence: An Agenda (Ajay Agrawal, Joshua Gans & Avi Goldfarb eds., 2017).
Lilian Mitrou, Data Protection, Artificial Intelligence and Cognitive Services: Is the General Data Protection Regulation (GDPR) ‘Artificial Intelligence-Proof’? (June 3, 2019),
https://ssrn.com/abstract=3386914.
Lee A. Bygrave, Automated Profiling: Minding the Machine: Article 15 of the EC Data Protection Directive and Automated Profiling, 17 Computer L. & Sec. Rev. 17 (2001).
Robert, L. P., Pierce, C., Marquis, E., Kim, S., Alahmad, R. 2020. “Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda,” Human-Computer Interaction,
https://doi.org/10.1080/07370024.2020.1735391.
Rasha Alahmad, Lionel Robert, Artificial Intelligence (AI) and IT identity: Antecedents Identifying with AI Applications Completed Research,
https://ssrn.com/abstract=3601724.
Rai, A., Constantinides, P., and Sarker, S. 2019. “Editor’s Comments: Next-Generation Digital Platforms: Toward Human–AI Hybrids,” MIS Quarterly, (43:1), pp. iii–ix.
Savić, D. 2019. “Are we ready for the future? Impact of Artificial Intelligence on Grey Literature Management,” Conference on Grey Literature and Repositories, (15), pp. 7–15.
Brian O’Keefe and Marty Jones “How Uber plays the tax shell game”,
Fortune.com, Oct. 22, 2015.
Uber BV v Aslam [2018] EWCA Civ 2748.
Case C-434/15 Asociación Profesional Élite Taxi v Uber Systems Spain SL ECLI:EU:C:2017:981.
Enikő Horvath and Severin Klinkmüller, “The concept of ‘investment’ in the digital economy: The case of social media companies,” Journal of World Investment and Trade, vol. 20 (2019), pp. 590–609.
Daniel Schneider and Kristen Harknett, “Schedule Instability and Unpredictability and Worker and Family Health and Wellbeing,” Washington Center for Equitable Growth Working Paper (Sept. 2016),
http://cdn.equitablegrowth.org/wp-content/uploads/2016/09/12135618/091216-WPSchedule-instability-and-unpredictability.pdf.
William Magnuson, Regulating Fintech, 71 Vand. L. Rev. 1167, 1169 (2018).
Sonia K. Katyal, Private Accountability in the Age of Artificial Intelligence, 66 UCLA L. REV. 54, 59 (2019).
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, And Punish The Poor (2018).
Algorithmic Just. League,
https://www.ajlunited.org.
IBM, X-FORCE Threat Intelligence Index 4 (2019),
https://www.securindex.com/downloads/8b9f94c46a70c60b229b04609c07acff.pdf.
Shane Harris, @War: The Rise Of The Military-Internet Complex 103–22 (2014).
Mark Bowden, Worm: The First Digital World War 48 (2011).
IBM GLOB. TECH. SERVS., IBM Security Services 2014 Cyber Security Intelligence Index 3 (2014),
http://media.scmagazine.com/documents/82/ibm_cyber_security_intelligenc_20450.pdf.
U.S. DEP’T OF DEF., The Department Of Defense Cyber Strategy 9 (2015),
https://archive.defense.gov/home/features/2015/0415_cyber-strategy/final_2015_dod_cyber_strategy_for_web.pdf (“Criminal actors pose a considerable threat in cyberspace, particularly to financial institutions, and ideological groups often use hackers.”).
Sealed Indictment, United States v. Murgio, 15 Cr. 769 (S.D.N.Y. Nov. 5, 2015), ECF No. 14; Sealed Indictment, United States v. Shalon, 15 Cr. 333 (S.D.N.Y. June 2, 2015), ECF No. 3.
Brad Smith & Carole Ann Browne, Tools And Weapons: The Promise And The Peril Of The Digital Age 69–76 (2019).
Chris Brummer & Yesha Yadav, Fintech and the Innovation Trilemma, 107 GEO. L.J. 235 (2019).
Nathaniel Popper, The Stock Market Bell Rings, Computers Fail, Wall Street Cringes, N.Y. TIMES (July 8, 2015), https://
www.nytimes.com/2015/07/09/business/dealbook/new-york-stock-exchange-suspendstrading.html.
Anthony Saunders & Marcia Cornett, Financial Institutions Management: A Risk Management Approach 97–103 (9th Ed. 2017).
Odia Kagan, Finnish DPA Orders Company to Modify Automated Creditworthiness Assessment, Improve Disclosures, Fox Rothschild (Apr. 27, 2019),
https://dataprivacy.foxrothschild.com/2019/04/articles/european-union/finnish-dpa-orderscompany-to-modify-automated-creditworthiness-assessment-improve-disclosures/ (reporting that the Finnish Data Protection Authority ordered a firm to “provide individuals with information on the logic behind the decision-making process, its relevance to the credit decision and its consequences for the borrower” pursuant to the General Data Protection Regulation’s provisions guaranteeing a right to an explanation).
Adam Levitin, Pandora’s Digital Box: The Promise and Perils of Digital Wallets, 166 U. PA. L. REV. 305, 335 (2018). Brian T. Melzer, The Real Costs of Credit Access: Evidence from the Payday Lending Market, 126 Q.J. ECON. 517, 522 (2011) (indicating that loans give families flexibility “in managing consumption over time” yet may create “substantial debt service burdens”). Christine L. Dobridge, For Better and for Worse?: Effects of Access to High Cost Consumer Credit (Fed. Reserve Bd., Working Paper No. 2016-056, 2016),
https://www.federalreserve.gov/econresdata/feds/2016/files/2016056pap.pdf (“[P]ayday credit access improves well-being for households in distress by helping them smooth consumption. In periods of temporary financial distress—after extreme weather events like hurricanes and blizzards—I find that payday loan access mitigates declines in spending on food, mortgage payments, and home repairs. In an average period, however, I find that access to payday credit reduces well-being.”).
Mark DeCambre, U.S. Consumer Debt Is Now Above Levels Hit During the 2008 Financial Crisis, MARKETWATCH (June 25, 2019),
Simina Mistreanu, “Life Inside China’s Social Credit Laboratory,” Foreign Policy, April 3, 2018,
https://foreignpolicy.com/2018/04/03/life-inside-chinas-social-credit-laboratory/.
1.
go back to reference Waldman, A. E. (2019). Power, process, and automated decision-making. Fordham Law Review, 88, 613. Waldman, A. E. (2019). Power, process, and automated decision-making.
Fordham Law Review, 88, 613.
2.
go back to reference Rogers, B. (2019). Beyond automation: The law & political economy of workplace technological change 24 (Roosevelt Institute Working Paper). Rogers, B. (2019).
Beyond automation: The law & political economy of workplace technological change 24 (Roosevelt Institute Working Paper).
3.
go back to reference Brummer, C., & Yadav, Y. (2019). Fintech and the innovation trilemma. Georgetown Law Journal, 107, 235. Brummer, C., & Yadav, Y. (2019). Fintech and the innovation trilemma.
Georgetown Law Journal, 107, 235.
4.
go back to reference Schneider, D., & Harknett, K. (2016, September). Schedule instability and unpredictability and worker and family health and wellbeing. Washington Center for Equitable Growth Working Paper. Schneider, D., & Harknett, K. (2016, September).
Schedule instability and unpredictability and worker and family health and wellbeing. Washington Center for Equitable Growth Working Paper.
5.
go back to reference Equivant (2018). COMPAS classification. Equivant (2018).
COMPAS classification.
6.
go back to reference Decarolis, F., & Rovigatti, G. (2018). From mad men to maths men: Concentration and buyer power in online advertising. Working paper. Decarolis, F., & Rovigatti, G. (2018).
From mad men to maths men: Concentration and buyer power in online advertising. Working paper.
7.
go back to reference Croft, J. (2016, December 5). The relentless advance of the super-intelligent attorney. Financial Times. Croft, J. (2016, December 5). The relentless advance of the super-intelligent attorney.
Financial Times.
8.
go back to reference Liker, J. K. (2004). The toyota way: 14 management principles from the world’s greatest manufacturer. Liker, J. K. (2004).
The toyota way: 14 management principles from the world’s greatest manufacturer.
9.
go back to reference Fjeld, J., Achten, N., Hilligoss, H., Nagy, A. C., & Srikumar, M. Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. Research Publication No. 2020. Fjeld, J., Achten, N., Hilligoss, H., Nagy, A. C., & Srikumar, M.
Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. Research Publication No. 2020.
10.
go back to reference Ross, K. K. A. (2017). Understanding the 12 technological forces that will shape our future. Penguin. Ross, K. K. A. (2017).
Understanding the 12 technological forces that will shape our future. Penguin.
11.
go back to reference Kraus, S., Palmer, C., Kailier, N., Lukas Kallinger, F., & Spitzer, J. (2018, September 20). Digital entrepreneurship: A research agenda on new business models. Kraus, S., Palmer, C., Kailier, N., Lukas Kallinger, F., & Spitzer, J. (2018, September 20).
Digital entrepreneurship: A research agenda on new business models.
12.
go back to reference Fairfax, L. M. (2019). From apathy to activism: The emergence, impact, and future of shareholder activism as the new corporate governance norm. Boston University Law Review, 99, 1301–1314. Fairfax, L. M. (2019). From apathy to activism: The emergence, impact, and future of shareholder activism as the new corporate governance norm.
Boston University Law Review, 99, 1301–1314.
13.
go back to reference Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. CrossRef Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms.
Futures, 90, 46–60.
CrossRef
14.
go back to reference Obrová, V., & Smolíková, L. (2013). The role of risk management in successful project management. International Business Information Management Association Conference, IBIMA 2013. Obrová, V., & Smolíková, L. (2013).
The role of risk management in successful project management. International Business Information Management Association Conference, IBIMA 2013.
15.
go back to reference OECD. (2019). Artificial intelligence in society. Paris: OECD. CrossRef OECD. (2019).
Artificial intelligence in society. Paris: OECD.
CrossRef
16.
go back to reference OECD. (2019, May 12). Recommendation of the council on artificial intelligence. OECD/LEGAL/0449. OECD. (2019, May 12).
Recommendation of the council on artificial intelligence. OECD/LEGAL/0449.
17.
go back to reference Beck, R., Avital, M., Rossi, M., & Thatcher, J. B. (2017). Blockchain technology in business and information systems research. Springer. Beck, R., Avital, M., Rossi, M., & Thatcher, J. B. (2017).
Blockchain technology in business and information systems research. Springer.
18.
go back to reference Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. Noble, S. U. (2018).
Algorithms of oppression: How search engines reinforce racism.
19.
go back to reference Danckert, S., & Yeates, C. (2018, November 21). CBA accused of board minutes criminal breach. The Sydney Morning Herald. Danckert, S., & Yeates, C. (2018, November 21). CBA accused of board minutes criminal breach.
The Sydney Morning Herald.
20.
go back to reference Murray, S. (2018, November 15). Algorithms tame ambiguities in use of legal data. Financial Times. Murray, S. (2018, November 15). Algorithms tame ambiguities in use of legal data.
Financial Times.
21.
go back to reference Mistreanu, S. (2018, April 3). Life inside China’s social credit laboratory. Foreign Policy. Mistreanu, S. (2018, April 3). Life inside China’s social credit laboratory.
Foreign Policy.
22.
go back to reference Gillis, T. B., & Spiess, J. L. (2019). Big data and discrimination. The University of Chicago Law Review, 459. Gillis, T. B., & Spiess, J. L. (2019). Big data and discrimination.
The University of Chicago Law Review, 459.
- Title
- AI Risk Management
- DOI
- https://doi.org/10.1007/978-3-030-64254-9_6
- Author:
-
Georgios I. Zekos
- Publisher
- Springer International Publishing
- Sequence number
- 6
- Chapter number
- Chapter 6