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Let the Robot Speak! AI-Generated Speech and Freedom of Expression

Part of the YSEC Yearbook of Socio-Economic Constitutions book series (YSEC,volume 2021)

Abstract

Up until very recently, AI-generated, or more precisely, machine learning (ML)-generated content was still in the realm of sci-fi. A recent series of important inventions gave AI the power of creation: Variational Autoencoders (VAEs) in 2013, Generative Adversarial Networks (GANs) in 2014, and Generative Pre-trained Transformers (GPT) in 2017. Synthetic products based on generative ML are useful in diverse fields of application. For example, generative ML can be used for the synthetic resuscitation of a dead actor, or a deceased loved one. Can ML be a source of speech that is protected by the right to freedom of expression in Article 10 ECHR? In contrast to a tool, such as a pen or a typewriter, ML can be such a decisive element in the generative process, that speech is no longer (indisputably) attributable to a human speaker. Is speech generated by a machine protected by the right to freedom of expression in Article 10 ECHR? I first discuss if ML-generated utterances fall within the protective scope of freedom of expression (Article 10(1) ECHR). After concluding that this is the case, I look at specific complexities raised by ML-generated content in terms of limitations to freedom of expression (Article 10(2) ECHR). The first set of potential limitations that I explore are those following from copyright, data protection, privacy and confidentiality law. Some types of ML-generated content could potentially circumvent these limitations. Second, I study how new types of content generated by ML can create normative grey areas where the boundaries of constitutionally protected and unprotected speech are not always easy to draw. In this context, I discuss two types of ML-generated content: virtual child pornography and fake news/disinformation. Third, I argue that the nuances of Article 10 ECHR are not easily captured in an automated filter and I discuss the potential implications of the arms race between automated filters and ML-generated content.

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Fig. 1

Notes

  1. 1.

    Kittler (1986), Hayles (1999).

  2. 2.

    Derrida (1982).

  3. 3.

    Heidegger (2001), p. 188: “Language speaks.

  4. 4.

    McLuhan (1994).

  5. 5.

    https://www.youtube.com/watch?v=uHQnb3HS4hc.

  6. 6.

    Žižek et al. (2006).

  7. 7.

    De Vries (2020).

  8. 8.

    Giles (2018).

  9. 9.

    Kingma and Welling (2013).

  10. 10.

    Goodfellow (2014).

  11. 11.

    GPT-3 (2020); Heaven (2021).

  12. 12.

    Heaven (2021).

  13. 13.

    Hao (2019).

  14. 14.

    GPT-3 (2020).

  15. 15.

    Gervais (2019); European Commission (2020a); Craig and Kerr (2019).

  16. 16.

    I will use the notions “freedom of expression” and “free speech” interchangeably, although it should be noted that the former is rooted in Art. 10 the European Convention of Human Rights and the latter in the First Amendment of the US Constitution.

  17. 17.

    Sunday Times v. the United Kingdom (No. 1), 26.04.1979, no. 6538/74. See also: Wilcox (2016).

  18. 18.

    Heller and van Hoboken (2019).

  19. 19.

    Ibid.

  20. 20.

    Benjamin (2021); Lamo and Calo (2019); Massaro and Norton (2015); Massaro et al. (2016).

  21. 21.

    Benjamin (2021); Lamo and Calo (2019); Massaro and Norton (2015); Massaro et al. (2016); Norton (2017); Kaminski (2017); Witt (2016); Wu (2012); Benjamin (2012).

  22. 22.

    European Court of Human Rights, The Observer and Guardian v. United Kingdom (26 November 1991), Application No. 13585/88, para. 60.

  23. 23.

    European Court of Human Rights, E.S. v. Austria (25 October 2018), Application No. 38450/12, para. 42.2. See also: Handyside v. the United Kingdom (7 December 1976, Series A No. 24), and Fressoz and Roire v. France ([GC], No. 29183/95, §45, ECHR 1999-I).

  24. 24.

    Kaminski (2017), p. 610.

  25. 25.

    European Court of Human Rights, Társaság a Szabadságjogokért v Hungary, App no 37374/05 (ECtHR 14 April 2009), para. 26.

  26. 26.

    Lamo and Calo (2019).

  27. 27.

    Ye (2018).

  28. 28.

    Kaloskampis (2019), Bellovin (2019).

  29. 29.

    Goodfellow (2018).

  30. 30.

    Axberger (2019), p. 16.

  31. 31.

    Stupp (2019).

  32. 32.

    Ajder (2019).

  33. 33.

    Ajder (2019).

  34. 34.

    Chesney and Citron (2019); Roth (2021).

  35. 35.

    Mai (2020).

  36. 36.

    Guerrasio (2019).

  37. 37.

    Harbinja (2017); Buitelaar (2017).

  38. 38.

    European Court of Justice (ECJ), Costeja, Case C-131/12, 13 May 2014.

  39. 39.

    Kulk and Borgesius (2018).

  40. 40.

    Handyside v. the United Kingdom judgment of 7 December 1976, A 24.

  41. 41.

    US Supreme Court, Ashcroft v Free Speech Coalition (122S.Ct. 1,389 (2002)).

  42. 42.

    Idem, p. 235.

  43. 43.

    Mclean (2017), p. 222.

  44. 44.

    Supreme Court of Sweden, NJA 2012s. 400 (Mangamålet).

  45. 45.

    Westrin (2013).

  46. 46.

    Cole (2019).

  47. 47.

    Roettgers (2019).

  48. 48.

    Communication from the Commission to the European Parliament, the Council, The European Economic and Social Committee of the Regions. Tackling online disinformation: a European Approach. COM (2018) 236 final Brussels, 26/4/2018.

  49. 49.

    European Commission (2020b).

  50. 50.

    COM(2018) 236 final Brussels, 26/4/2018, p. 9.

  51. 51.

    COM(2018) 236 final Brussels, 26/4/2018, p. 13.

  52. 52.

    Helberger et al. (2019); Marsden and Meyer (2019).

  53. 53.

    CJEU, Case C-401/19, Republic of Poland v European Parliament and Council of the European Union, action brought on 24 May 2019.

  54. 54.

    Spoerri (2019).

References

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de Vries, K. (2022). Let the Robot Speak! AI-Generated Speech and Freedom of Expression. In: Hindelang, S., Moberg, A. (eds) YSEC Yearbook of Socio-Economic Constitutions 2021. YSEC Yearbook of Socio-Economic Constitutions, vol 2021. Springer, Cham. https://doi.org/10.1007/16495_2021_38

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