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Legal and Regulatory Issues on Artificial Intelligence, Machine Learning, Data Science, and Big Data

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HCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence (HCII 2022)

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Abstract

Technological innovation creates numerous opportunities for businesses, organizations, and societies. Artificial intelligence, machine learning, data science, and big data provide opportunities for developing self-controlling systems emulating human intelligence. In some instances, these systems surpass the performance of humans. The relationship of innovative technology with the law is an important underpinning factor that is often overlooked. Law may encourage innovation but may also inhibit its development and application by adopting stringent regulatory provisions and liability regimes. This article examines the legal and regulatory issues related to new technologies such as artificial intelligence, machine learning, data science, and big data.

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Notes

  1. 1.

    In common law jurisdictions (including United States, UK and of the former British colonies), the default position under tort law is that a person who has been harmed will need to show a duty of care owed by the defendant (and the defendant has breached his duty, causing damages) [6,7].

References

  1. Wang, W., Siau, K.: Artificial intelligence, machine learning, automation, robotics, future of work, and future of humanity – a review and research agenda. J. Database Manage. 30(1), 61–79 (2019)

    Article  Google Scholar 

  2. Siau, K., et al.: Fintech empowerment: data science, artificial intelligence, and machine learning. Cutter Bus. Technol. J. 31(11/12), 12–18 (2018)

    Google Scholar 

  3. Hyder, Z., Siau, K., Nah, F.: Artificial intelligence, machine learning, and autonomous technologies in mining industry. J. Database Manage. 30(2), 67–79 (2019)

    Article  Google Scholar 

  4. Tsimplis, M.: Regulatory systems supporting innovation: lessons from the development of the 2004 ballast water management convention. Int. J. Marine Coastal Law 36(1), 59–87 (2020)

    Article  Google Scholar 

  5. Tsimplis, M., Dbouk, W.: Regulating the safety of offshore oil and gas operations: performance-based regulation and the development of international regulatory uniformity in offshore oil and gas operations. Managing the risk of offshore oil and gas accidents: the international legal dimension, pp. 18–51. Edward Elgar Publishing (2019)

    Google Scholar 

  6. Jones, M.A.: Clerk & Lindsell on torts. 23rd edition. Common Law Library. London: Thomson Reuters, Trading as Sweet & Maxwell (2020)

    Google Scholar 

  7. Restatement (Third) of Torts: Liability for physical harm § 3 (P.F.D. No. 1, 2005)

    Google Scholar 

  8. Wang, W., Siau, K.: Industry 4.0: ethical and moral predicaments. Cutter Bus. Technol. J. 32(6), 36–45 (2019)

    Google Scholar 

  9. Siau, K., Wang, W.: Building trust in artificial intelligence, machine learning, and robotics. Cutter Bus. Technol. J. 31(2), 47–53 (2018)

    Google Scholar 

  10. Siau, K.: Education in the age of artificial intelligence: how will technology shape learning? Global Anal. 7(3), 22–24 (2018)

    Google Scholar 

  11. Myburgh, P.: Richard cooper memorial lecture admiralty law - what is it good for? Univ. Queensl. Law J. 28(1), 19–38 (2009)

    Google Scholar 

  12. Pramatha Nath Mullick v. Pradyumna Kumar Mullick (1925) L.R. 52 I.A. 245, P.C C. v. S. and Another [1987 C. No. 1969], [1988] Q.B. 135

    Google Scholar 

  13. Chesterman, S.: Artificial intelligence and the problem of autonomy. Notre Dame J. Emerg. Technol. 1, 210–250 (2020)

    Google Scholar 

  14. Nersessian, D., Mancha, R.: From automation to autonomy: legal and ethical responsibility gaps in artificial intelligence innovation. Mich. Tech. L. Rev. 27, 55 (2020)

    Google Scholar 

  15. Lee, Z.Y., Karim, M.E., Ngui, K.: Deep learning artificial intelligence and the law of causation: application, challenges and solutions. Inf. Commun. Technol. Law 30(3), 255–282 (2021)

    Article  Google Scholar 

  16. Solum, L.B.: Legal personhood for artificial intelligences. North Carolina Law Rev. 70, 1231 (1991)

    Google Scholar 

  17. Rothenberg, D.M.: Can Siri 10.0 buy your home: the legal and policy based implications of artificial intelligent robots owning real property. Wash. JL Tech. & Arts 11, 439 (2015)

    Google Scholar 

  18. Brown, R.D.: Property ownership and the legal personhood of artificial intelligence. Inf. Commun. Technol. Law 30(2), 208–234 (2021)

    Article  Google Scholar 

  19. Chesterman, S.: Through a glass, darkly: artificial intelligence and the problem of opacity. Am. J. Compar. Law 69(2), 271–294 (2021)

    Article  Google Scholar 

  20. Alexander, C.R., Arlen, J.: Does conviction matter? The reputational and collateral effects of corporate crime. Research Handbook on Corporate Crime and Financial Misdealing, Edward Elgar Publishing (2018)

    Google Scholar 

  21. Werle, N.: Prosecuting corporate crime when firms are too big to jail: investigation, deterrence, and judicial review. Yale LJ 128, 1366 (2018)

    Google Scholar 

  22. Yeager, P.C.: The elusive deterrence of corporate crime. Criminol. Pub. Pol’y 15, 439 (2016)

    Article  Google Scholar 

  23. Low, K.F., Wan, W.Y., Wu, Y.C.: The future of machines: property and personhood. The Cambridge Handbook of Private Law and Artificial Intelligence, forthcoming. Available at SSRN: https://ssrn.com/abstract=3895535

  24. Janofsky A.: AI could make cyberattacks more dangerous, harder to detect. The Wall Street J. (November 13, 2018)

    Google Scholar 

  25. Vaithianathasamy, S.: AI vs. AI: fraudsters turn defensive technology into an attack tool. Comput. Fraud Secur. 8, 6–8 (2019). https://www.sciencedirect.com/science/article/pii/S1361372319300831

  26. Gray, J.: Meridian global funds management Asia Ltd v securities commission. J. Finan. Regul. Compl. 4(1), 93–97 (1996)

    Article  Google Scholar 

  27. LoPucki, L.M.: Algorithmic entities. Wash. UL Rev. 95, 887 (2017)

    Google Scholar 

  28. van der Linden, T.: Regulating artificial intelligence: please apply existing regulation. Amsterdam LF 13(3) (2021)

    Google Scholar 

  29. Scherer, M.U.: Regulating artificial intelligence systems: risks, challenges, competencies, and strategies. Harv. JL Tech. 29(2), 353–400 (2016). http://jolt.law.harvard.edu/articles/pdf/v29/29HarvJLTech353.pdf

  30. Shneiderman, B.: Human-centered artificial intelligence: three fresh ideas. AIS Trans. Hum.-Comput. Interact. 12(3), 109–124 (2020)

    Article  Google Scholar 

  31. Shneiderman, B.: Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems. ACM Trans. Interact. Intell. Syst. 10(4), 1–31 (2020)

    Article  Google Scholar 

  32. Crootof, R., Kaminski, M., Price II, N.: Humans in the loop. Vand. L. Rev. (2023). forthcoming

    Google Scholar 

  33. Mahler, T.: Between risk management and proportionality: the risk-based approach in the EU’s Artificial Intelligence Act proposal. Nordic Yearbook of Law and Informatics (2021)

    Google Scholar 

  34. Trengove, M., Emre, K.: Dilemmas in AI regulation: an exposition of the regulatory trade-offs between responsibility and innovation. Available at SSRN 4072436 (2022)

    Google Scholar 

  35. Ebers, M., Hoch, V., Rosenkranz, F., Ruschemeier, H.: Steinrotter, B: The European Commission’s proposal for an artificial intelligence act – a critical assessment by members of the robotics and AI law society (RAILS). Multidisc. Scient. J. 4, 589–603 (2021)

    Article  Google Scholar 

  36. Siau, K., Wang, W.: Artificial intelligence (AI) ethics – ethics of AI and ethical AI. J. Database Manage. 31(2), 74–87 (2020)

    Article  Google Scholar 

  37. Robert, L.P., Bansal, G., Lutge, C.: ICIS 2019 SIGHCI workshop panel report: human-computer interaction challenges and opportunities for fair, trustworthy and ethical artificial intelligence. AIS Trans. Hum.-Comput. Interact. 12(2), 96–108 (2019)

    Google Scholar 

  38. Stephanidis, C., et al.: Seven HCI grand challenges. Int. J. Hum.-Comput. Interact. 35(14), 1229–1269 (2019)

    Article  Google Scholar 

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Authors and Affiliations

  1. City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China

    Wai Yee Wan, Michael Tsimplis, Keng L. Siau, Wei T. Yue, Fiona Fui-Hoon Nah & Gabriel M. Yu

Authors
  1. Wai Yee Wan
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  2. Michael Tsimplis
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  3. Keng L. Siau
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  4. Wei T. Yue
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  5. Fiona Fui-Hoon Nah
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  6. Gabriel M. Yu
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Corresponding author

Correspondence to Fiona Fui-Hoon Nah .

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Editors and Affiliations

  1. U.S. Army Research Laboratory, Adelphi, MD, USA

    Jessie Y. C. Chen

  2. U.S. Army Combat Capabilities Development Command Soldier Center, Orlando, FL, USA

    Gino Fragomeni

  3. Siemens (United States), Princeton, NJ, USA

    Helmut Degen

  4. Institute of Computer Science, Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

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Wan, W.Y., Tsimplis, M., Siau, K.L., Yue, W.T., Nah, F.FH., Yu, G.M. (2022). Legal and Regulatory Issues on Artificial Intelligence, Machine Learning, Data Science, and Big Data. In: Chen, J.Y.C., Fragomeni, G., Degen, H., Ntoa, S. (eds) HCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence. HCII 2022. Lecture Notes in Computer Science, vol 13518. Springer, Cham. https://doi.org/10.1007/978-3-031-21707-4_40

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  • DOI: https://doi.org/10.1007/978-3-031-21707-4_40

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  • Online ISBN: 978-3-031-21707-4

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