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Bridging the Liability Gaps: Why AI Challenges the Existing Rules on Liability and How to Design Human-empowering Solutions

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Law and Artificial Intelligence

Part of the book series: Information Technology and Law Series ((ITLS,volume 35))

Abstract

This chapter explores the so-called ‘liability gaps’ that occurs when, in applying existing contractual, extra-contractual, or strict liability rules to harms caused by AI, the inherent characteristics of AI may result in unsatisfying outcomes, in particular for the damaged party. The chapter explains the liability gaps, investigating which features of AI challenge the application of traditional legal solutions and why. Subsequently, this chapter explores the challenges connected to the different possible solutions, including contract law, extra-contractual law, product liability, mandatory insurance, company law, and the idea of granting legal personhood to AI and robots. The analysis is carried out using hypothetical scenarios, to highlight both the abstract and practical implications of AI, based on the roles and interactions of the various parties involved. As a conclusion, this chapter offers an overview of the fundamental principles and guidelines that should be followed to elaborate a comprehensive and effective strategy to bridge the liability gaps. The argument made is that the guiding principle in designing legal solutions to the liability gaps must be the protection of individuals, particularly their dignity, rights and interests.

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Notes

  1. 1.

    Vincent (2019) Apple’s credit card is being investigated for discriminating against women https://www.theverge.com/2019/11/11/20958953/apple-credit-card-gender-discrimination-algorithms-black-box-investigation. Accessed 19 February 2021.

  2. 2.

    Ibid.

  3. 3.

    Ibid.

  4. 4.

    Vigdor (2019) Apple Card Investigated After Gender Discrimination Complaints https://www.nytimes.com/2019/11/10/business/Apple-credit-card-investigation.html. Accessed 19 February 2021. Please note that as of February 2021 no additional information on the investigation or its outcomes appears to have been made available.

  5. 5.

    In this chapter, AI system indicates a product, device, service, or machine deploying a form of AI. AI should be intended in this chapter as any Machine Learning or other data analytics techniques presenting the capability to achieve a certain objective with a significant degree of autonomy, following supervised or unsupervised learning or other forms of software learning capability.

  6. 6.

    The phenomenon is often referred to as responsibility gaps or liability gaps, cfr, among many, Johnson 2015, p. 2, Bertolini 2013, p. 231, European Commission 2019, p. 17.

  7. 7.

    The example is a simplification. In real life, special liability regimes would create a presumption of fault of Alice. Alice would have a mandatory civil responsibility insurance to cover possible damages occurred while driving. Furthermore, additional parties might be involved, such as the manufacturer of the car or of any of its components, that might exempt Alice from any liability or to which she could demand to be indemnified, in case of defects or malfunctioning.

  8. 8.

    Pagallo et al. 2018, p. 19.

  9. 9.

    Witt 2001, p. 694.

  10. 10.

    Witt 2001, p. 745.

  11. 11.

    European Commission 2019, p. 21.

  12. 12.

    Leenes et al. 2017, p. 9.

  13. 13.

    European Commission 2019, p. 21.

  14. 14.

    Scherer 2016, p. 363.

  15. 15.

    In most legal systems only humans that are capable and of age are liable, even if the damage has been caused by a machine, an animal, or an underage or incapable person (with few exceptions). Cfr. Asaro et al. 2011, p. 176, Pagallo 2012, p. 55.

  16. 16.

    Pagallo 2013b, p. 504, Asaro 2011, p. 174.

  17. 17.

    There is no universal definition of pure economic loss, and the rules concerning it vary widely among European countries. As a general definition, pure economic loss entails the suffering of an economic loss not connected to a pre-existing harm. Cfr. Bussani and Palmer 2003.

  18. 18.

    Johnson 2014, p. 2, European Commission 2019, p. 16.

  19. 19.

    von Bar and Drobnig 2009.

  20. 20.

    Fauvarque-Cosson and Mazeaud 2009.

  21. 21.

    Ibid.

  22. 22.

    Marsh 1994, Farnsworth 2006.

  23. 23.

    Pagallo 2013a, p. 135, European Commission 2019, p. 51.

  24. 24.

    Please note that the relationship between Alice and The Bank might be either contractual or pre-contractual, depending on the kind of documents exchanged and the rules existing in a certain jurisdiction. The existence of a contractual or pre-contractual relationship does not automatically imply the existence of contractual liability in this case, because the damage derives from discrimination, which is an action prohibited by the law.

  25. 25.

    Pagallo 2012, p. 55, Pagallo 2013a, p. 115, Karnow 2016, p. 51.

  26. 26.

    European Commission 2019, p. 51.

  27. 27.

    Buyuksagis and van Boom 2013, p. 609.

  28. 28.

    Ibid.

  29. 29.

    Royakkers and van Est 2016, p. 185.

  30. 30.

    Asaro et al. 2011, p. 170, Bertolini 2013.

  31. 31.

    Bertolini 2013, p. 219.

  32. 32.

    European Commission 2018, 2019.

  33. 33.

    UNESCO 2017, p. 19.

  34. 34.

    This idea has been brought forward at the Sixth T.M.C. Asser Annual Lecture, given by Prof. Andrew Murray and entitled ‘Almost Human: Law and Human Agency in the Time of Artificial Intelligence’ that took place online on 26 November 2020. See also Murray 2021.

  35. 35.

    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, of 21 April 2021 [2021/0106(COD)], Annex III.

  36. 36.

    Royakkers and van Est 2016, p. 185.

  37. 37.

    Marchant and Lindor 2012, p. 1326.

  38. 38.

    European Commission 2019, p. 39.

  39. 39.

    Hevelke and Nida-Rümelin 2015, Marchant and Lindor 2012, p. 1339.

  40. 40.

    Weatherill 2013.

  41. 41.

    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 [OJ L 210, 7.8.1985, pp. 29–33], article 7.

  42. 42.

    Weatherill 2013.

  43. 43.

    Bertolini 2013, Asaro et al. 2011.

  44. 44.

    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 [OJ L 210, 7.8.1985, pp. 29–33], article 2.

  45. 45.

    European Commission 2020, p. 10.

  46. 46.

    Jaquemin 2017.

  47. 47.

    European Commission 2020, p. 4.

  48. 48.

    Weatherill 2013; see also the definition of defect provided by article 6 of the Council Directive 85/374/EEC.

  49. 49.

    European Commission 2020a.

  50. 50.

    Turner 2019, p. 112.

  51. 51.

    European Commission 2019, p. 61.

  52. 52.

    Bayern 2015.

  53. 53.

    Scherer 2019.

  54. 54.

    Solum 1992.

  55. 55.

    European Parliament 2017, p. 61.

  56. 56.

    Teubner 2006, van den Hoven van Genderen 2019.

  57. 57.

    Hage 2017, Teubner 2018.

  58. 58.

    Open Letter to the European Commission: Artificial Intelligence and Robotics 2017, https://www.politico.eu/wp-content/uploads/2018/04/RoboticsOpenLetter.pdf. Accessed 19 February 2021.

  59. 59.

    The European Commission, in the context of its AI strategy for Europe, has not embraced the view of the European Parliament concerning a special legal personality for artificial agents. Cfr. European Commission 2018 and European Commission’s High-Level Expert Group on Artificial Intelligence 2019.

  60. 60.

    These values are expressly protected by the main tools constituting and regulating the EU, such as the Treaty on European Union and the Charter of Fundamental Rights.

  61. 61.

    European Commission 2018, p. 2.

  62. 62.

    European Commission 2020b.

  63. 63.

    European Commission 2019, p. 32.

  64. 64.

    Ibid.

  65. 65.

    Ibid., p. 39.

  66. 66.

    European Commission 2020b.

  67. 67.

    De Conca 2020.

  68. 68.

    European Commission 2019, p. 49.

  69. 69.

    The application of contractual and extra-contractual liability in the past has been challenged by complex situations, such as the case of pre-contractual liability, or the duty of care vis-à-vis third parties. Cfr. for instance Michoński 2015.

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Authors and Affiliations

  1. Transnational Legal Studies Department, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Silvia De Conca

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  1. Silvia De Conca
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  1. eLaw - Center for Law and Digital Technologies, Leiden University, Leiden, The Netherlands

    Bart Custers

  2. eLaw - Center for Law and Digital Technologies, Leiden University, Leiden, The Netherlands

    Eduard Fosch-Villaronga

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De Conca, S. (2022). Bridging the Liability Gaps: Why AI Challenges the Existing Rules on Liability and How to Design Human-empowering Solutions. In: Custers, B., Fosch-Villaronga, E. (eds) Law and Artificial Intelligence. Information Technology and Law Series, vol 35. T.M.C. Asser Press, The Hague. https://doi.org/10.1007/978-94-6265-523-2_13

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