Skip to main content
SpringerLink
Log in

Individuals, Society, and AI: Online Communication

  • Chapter
  • First Online:
AI Ethics

  • 2108 Accesses

Abstract

This chapter examines a current ethical issue in AI, using the example of online content moderation and consolidating previous material. The problem of online harms is in tension with values of freedom of expression. Freedom of expression is a perennial issue. We consider how the use of technology may impact and exacerbate the problems and examine the possibilities of using technology to address them, such as the challenges of using algorithms to detect nuanced meaning. The ethical issues are tightly connected to wider political, social, regulatory, and legal issues. Here, we focus on ethics while also discussing how wider interests from government and industry may skew debates and solutions. The issue of free speech is outlined, drawing on the claims of John Stuart Mill and the ‘harm principle’ as a limit to free speech. We also address issues in the philosophy of language, considering how meaning and intention are related and the critical importance of context, drawing on the work of H. P. Grice. We consider how communication online may impact views of self and others and consider how both the problems of online content and the attempts to find solutions may influence how we understand and address ethical questions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 69.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Department for Digital, Culture, Media and Sport (2021) Draft Online Safety Bill. UK Government, London. https://www.gov.uk/government/publications/draft-online-safety-bill

  2. Department for Digital, Culture, Media and Sport (2020) Safer technology, safer users: the UK as a world leader in safety tech (Updated 2021). DCMS, London

    Google Scholar 

  3. Garnham N (2000) Emancipation, the media, and modernity: arguments about the media and social theory. Oxford University Press, New York

    Book  Google Scholar 

  4. Christakis N, Fowler J (2010) Connected: the amazing power of social networks and how they shape our lives. HarperCollins, London

    Google Scholar 

  5. Gillespie T (2018) Custodians of the Internet: platforms, content moderation, and the hidden decisions that shape social media. Yale University Press, New Haven

    Google Scholar 

  6. Pariser E (2011) The filter bubble. Viking Penguin, London

    Google Scholar 

  7. Dahlgren PM (2021) A critical review of filter bubbles and a comparison with selective exposure. Nord Rev 42(1):15–33

    Article  Google Scholar 

  8. Munn L (2020) Angry by design: toxic communication and technical architectures. Humanit Soc Sci Commun 7(1):1–11

    Article  MathSciNet  Google Scholar 

  9. Steiger M, Bharucha TJ, Venkatagiri S, Riedl MJ, Lease M (2021) The psychological well-being of content moderators: the emotional labor of commercial moderation and avenues for improving support. In: Proceedings of the 2021 CHI conference on human factors in computing systems, pp 1–14

    Google Scholar 

  10. Ruckenstein M, Turunen LLM (2020) Re-humanizing the platform: and the logic of care. New Media Soc 22(6):1026–1042

    Article  Google Scholar 

  11. Borchert RJ, Azevedo T, Badhwar A, Bernal J, Betts M, Bruffaerts R, Burkhart MC, Dewachter I, Gellersen H, Low A, Machado L (2021) Artificial intelligence for diagnosis and prognosis in neuroimaging for dementia; a systematic review. medRxiv. https://doi.org/10.1101/2021.12.12.21267677

  12. Gibney E (2022) Could machine learning fuel a reproducibility crisis in science? Nature 608(7922):250–251

    Article  Google Scholar 

  13. Char DS, Shah NH, Magnus D (2018) Implementing machine learning in health care—addressing ethical challenges. N Engl J Med 378(11):981

    Article  Google Scholar 

  14. Vidgen B, Burden E, Margetts M (2021) Understanding online hate: VSP regulation and the broader context. Alan Turing Institute, London

    Google Scholar 

  15. Javid S, Wright J (2019) Online harms white paper. Department for Digital, Culture, Media & Sport and the Home Office. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/793360/Online_Harms_White_Paper.pdf

  16. Finkelstein JJ (1968) The laws of Ur-Nammu. J Cuneif Stud 22(3–4):66–82

    Article  Google Scholar 

  17. Internet Society UK England Chapter, Understanding the UK Online Safety Bill webinar, 10 Jun 2021. https://isoc-e.org/understanding-the-uk-online-safety-bill/ at 45 minutes ff

  18. Mill JS (1859) On liberty. In: Collected works of John Stuart Mill, vol XVIII. J. W. Parker and Son, London. Online Library of Liberty

    Google Scholar 

  19. Fogg BJ (2002) Persuasive technology: using computers to change what we think and do. Elsevier, Amsterdam, p 2

    Google Scholar 

  20. Kosner A (2020) Stanford’s School of Persuasion: B J Fogg on how to win users and influence behaviour. Forbes, 4 Dec 2012

    Google Scholar 

  21. Waldron J (2012) The harm in hate speech. Harvard University Press, Cambridge

    Book  Google Scholar 

  22. Simpson RM (2013) Dignity, harm, and hate speech. Law Philos 32(6):701–728

    Article  Google Scholar 

  23. Council of Europe, Freedom of expression: hate speech. https://www.coe.int/en/web/freedom-expression/hate-speech

  24. Bradshaw S, Campbell-Smith U, Henle A, Perini A, Shalev S, Bailey H, Howard PN (2020) Country case studies industrialized disinformation: 2020 global inventory of organized social media manipulation. Oxford Internet Institute, Oxford

    Google Scholar 

  25. Briant E (2021) The grim consequences of a misleading study on disinformation. Wired, 18 Feb 2021

    Google Scholar 

  26. Vidgen B, Taylor H, Pantazi M, Anastasiou Z, Inkster B, Margetts H (2021) Understanding vulnerability to online misinformation. Alan Turing Institute, London

    Google Scholar 

  27. Head ML, Holman L, Lanfear R, Kahn AT, Jennions MD (2015) The extent and consequences of p-hacking in science. PLoS Biol 13(3):e1002106

    Article  Google Scholar 

  28. Ioannidis JP (2005) Why most published research findings are false. PLoS Med 2(8):e124

    Article  Google Scholar 

  29. Kearns M, Roth A (2019) The ethical algorithm: the science of socially aware algorithm design. Oxford University Press, Oxford

    Google Scholar 

  30. Vidgen B, Margetts H, Harris A (2019) How much online abuse is there? A systematic review of evidence from the UK. Alan Turing Institute, London

    Google Scholar 

  31. Vidgen B, Harris A, Nguyen D, Tromble R, Hale S, Margetts H (2019) Challenges and frontiers in abusive content detection. Association for Computational Linguistics, Florence

    Book  Google Scholar 

  32. Doyle A (2021) Free speech and why it matters. Constable, London

    Google Scholar 

  33. Alan Turing Institute Podcast (2021) #25 ‘How good is AI at detecting online hate?’, 2 July 2021. https://www.turing.ac.uk/news/turing-podcast

  34. Almagro M, Hannikainen IR, Villanueva N (2022) Whose words hurt? Contextual determinants of offensive speech. Personal Soc Psychol Bull 48(6):937–953

    Article  Google Scholar 

  35. The Queen on the application of Harry Miller and The College of Policing, [2021] EWCA Civ 1926, 21 Dec 2022. https://www.judiciary.uk/wp-content/uploads/2021/12/Miller-v-College-of-Policing-judgment-201221.pdf. Accessed 26 Sept 2022

  36. Grice HP (1975) Logic and conversation. In: Cole P, Morgan JL (eds) Syntax and semantics, 3: speech acts. Academic, New York, pp 41–58

    Google Scholar 

  37. Davis W (2019) Implicature. In: Zalta EN (ed) The Stanford encyclopedia of philosophy, Fall 2019 edn. Stanford University, Stanford. https://plato.stanford.edu/archives/fall2019/entries/implicature/

    Google Scholar 

  38. Gallie WB (1955) Essentially contested concepts. Proc Aristot Soc 56(1):167–198

    Article  Google Scholar 

  39. Kosenko K, Winderman E, Pugh A (2019) The hijacked hashtag: the constitutive features of abortion stigma in the #ShoutYourAbortion twitter campaign. Int J Commun 13:21

    Google Scholar 

  40. Bhat P, Klein O (2020) Covert hate speech: white nationalists and dog whistle communication on twitter. In: Twitter, the public sphere, and the chaos of online deliberation. Palgrave Macmillan, Cham, pp 151–172

    Chapter  Google Scholar 

  41. Botelho A, Vidgen B, Hale SA (2021) Deciphering implicit hate: evaluating automated detection algorithms for multimodal hate. arXiv preprint arXiv: 2106.05903

    Google Scholar 

  42. Coffin C, O’Halloran K (2006) The role of appraisal and corpora in detecting covert evaluation. Funct Lang 13(1):77–110

    Article  Google Scholar 

  43. Tynes BM, Lozada FT, Smith NA, Stewart AM (2018) From racial microaggressions to hate crimes: a model of online racism based on the lived experiences of adolescents of color. In: Microaggression theory: influence and implications. Wiley, New York, pp 194–212

    Chapter  Google Scholar 

  44. Eschmann R (2021) Digital resistance: how online communication facilitates responses to racial microaggressions. Sociol Race Ethn 7(2):264–277

    Article  Google Scholar 

  45. Binns R, Veale M, Van Kleek M, Shadbolt N (2017) Like trainer, like bot? Inheritance of bias in algorithmic content moderation. In: International conference on social informatics. Springer, Cham, pp 405–415

    Chapter  Google Scholar 

  46. Salminen J, Almerekhi H, Kamel AM, Jung SG, Jansen BJ (2019) Online hate ratings vary by extremes: a statistical analysis. In: Proceedings of the 2019 conference on human information interaction and retrieval. Association for Computing Machinery, New York, pp 213–217

    Chapter  Google Scholar 

  47. Yin W, Zubiaga A (2021) Towards generalisable hate speech detection: a review on obstacles and solutions. arXiv preprint arXiv:2102.08886, p 17

    Google Scholar 

  48. O’Neil C (2016) Weapons of math destruction: how big data increases inequality and threatens democracy. Broadway Books, New York

    MATH  Google Scholar 

  49. Noble SU (2018) Algorithms of oppression: how search engines reinforce racism. New York University Press, New York

    Book  Google Scholar 

  50. Pasquale F (2015) The black box Society. Harvard University Press, Cambridge

    Book  Google Scholar 

  51. Freeman K (2016) Algorithmic injustice: how the Wisconsin supreme court failed to protect due process rights in state v. Loomis. N C J Law Technol 18(5):75

    Google Scholar 

  52. Blodgett SL, O’Connor B (2017) Racial disparity in natural language processing: a case study of social media African-American English. arXiv preprint arXiv:1707.00061

    Google Scholar 

  53. Davidson T, Bhattacharya D, Weber I (2019) Racial bias in hate speech and abusive language detection datasets. arXiv preprint arXiv:1905.12516

    Google Scholar 

  54. Sap M, Card D, Gabriel S, Choi Y, Smith NA (2019) The risk of racial bias in hate speech detection. In: Proceedings of the 57th annual meeting of the association for computational linguistics. Association for Computational Linguistics, Florence, pp 1668–1678

    Chapter  Google Scholar 

  55. Blodgett SL, Barocas S, Daumé III H, Wallach H (2020) Language (technology) is power: a critical survey of ‘bias’ in NLP. arXiv preprint arXiv:2005.14050

    Google Scholar 

  56. Röttger P, Vidgen B, Nguyen D, Waseem Z, Margetts H, Pierrehumbert J (2020) HATECHECK: functional tests for hate speech detection models. arXiv preprint arXiv:2012.15606, 2021

    Google Scholar 

  57. Rudas C, Surányi O, Yasseri T, Török J (2017) Understanding and coping with extremism in an online collaborative environment: a data-driven modeling. PLoS One 12(3):e0173561

    Article  Google Scholar 

  58. Hills TT (2019) The dark side of information proliferation. Perspect Psychol Sci 14(3):323–330

    Article  Google Scholar 

  59. Gross N (2013) Why are professors liberal and why do conservatives care? Harvard University Press, Cambridge

    Book  Google Scholar 

  60. van de Werfhorst HG (2020) Are universities left-wing bastions? The political orientation of professors, professionals, and managers in Europe. Br J Sociol 71(1):47–73

    Article  Google Scholar 

  61. Papakyriakopoulos O, Serrano JCM, Hegelich S (2020) Political communication on social media: a tale of hyperactive users and bias in recommender systems. Online Soc Netw Media 15:100058

    Article  Google Scholar 

  62. https://www.gov.uk/government/speeches/oliver-dowdens-oral-statement-on-the-online-harms-white-paper-consultation-response

  63. Heather Burns (2021) In Internet Society UK England Chapter, Understanding the UK online safety bill webinar, June 10th 2021. https://isoc-e.org/understanding-the-uk-online-safety-bill/

  64. Zimbardo P (2007) The Lucifer effect understanding how good people turn evil. Random House, New York

    Google Scholar 

  65. Pierson J, Robinson SC, Boddington P, Chazerand P, Kerr A, Milan S, Verbeek F, Kutterer C, Nerantzi E, Aconstantinesei IC (2021) AI4People-AI in media and technology sector: opportunities, risks, requirements and recommendations. Atomium–European Institute for Science, Media and Democracy (EISMD), Brussels

    Google Scholar 

  66. Helberger N, Pierson J, Poell T (2018) Governing online platforms: from contested to cooperative responsibility. Inf Soc 34(1):1–14

    Article  Google Scholar 

  67. Anderson B, Wood MA (2021) Doxxing: a scoping review and typology. In: Bailey J, Flynn A, Henry N (eds) The Emerald international handbook of technology-facilitated violence and abuse. Emerald Group Publishing, Bingley, pp 205–226

    Chapter  Google Scholar 

  68. Guo E (2021) How YouTube’s rules are used to silence human rights activists, Wired, 24 Jun 2021. https://www.technologyreview.com/2021/06/24/1027048/youtube-xinjiang-censorship-human-rights-atajurt/

  69. Berdichevsky D, Neuenschwander E (1999) Toward an ethics of persuasive technology. Commun ACM 42(5):51–58

    Article  Google Scholar 

  70. Just N, Latzer M (2017) Governance by algorithms: reality construction by algorithmic selection on the Internet. Media Cult Soc 39(2):238–258

    Article  Google Scholar 

  71. Munn L (2019) Alt-right pipeline: individual journeys to extremism online. First Monday

    Google Scholar 

  72. Vidgen B, Harris A, Cowls J, Guest E, Margetts M (2020) An agenda for research into online hate. Alan Turing Institute, London

    Google Scholar 

  73. Nowotny H (2021) In AI we trust: power, illusion and the control of predictive algorithms. Polity Press, Cambridge

    Google Scholar 

  74. Arsht A, Etcovitch D (2018) The human cost of online content moderation. Harvard Journal of Law and Technology

    Google Scholar 

  75. Pasquale F (2020) New laws of robotics: defending human expertise in the age of AI. Belknap Press, Cambridge

    Book  Google Scholar 

  76. Mac Síthigh D, Siems M (2019) The Chinese social credit system: a model for other countries? Mod Law Rev 82(6):1034–1071

    Article  Google Scholar 

Further Reading

    Free Speech and Hate Speech

    Algorithms, Bias, and Online Harms

    • Fogg BJ (2002) Persuasive technology: using computers to change what we think and do. Elsevier, Amsterdam, p 2

      Google Scholar 

    • Kearns M, Roth A (2019) The ethical algorithm: the science of socially aware algorithm design. Oxford University Press, Oxford

      Google Scholar 

    • Kramer AD, Guillory JE, Hancock JT (2014) Experimental evidence of massive-scale emotional contagion through social networks. Proc Natl Acad Sci 111(24):8788–8790

      Article  Google Scholar 

    • Munn L (2020) Angry by design: toxic communication and technical architectures. Humanit Soc Sci Commun 7(1):1–11

      Article  MathSciNet  Google Scholar 

    • Noble SU (2018) Algorithms of oppression: how search engines reinforce racism. New York University Press, New York

      Book  Google Scholar 

    • O’Neil C (2016) Weapons of math destruction: how big data increases inequality and threatens democracy. Broadway Books, New York

      MATH  Google Scholar 

    • Pariser E (2011) The filter bubble. Viking Penguin, London

      Google Scholar 

    • Pasquale F (2015) The black box Society. Harvard University Press, Cambridge

      Book  Google Scholar 

    • Pasquale F (2020) New laws of robotics: defending human expertise in the age of AI. Belknap Press, Cambridge

      Book  Google Scholar 

    • Vidgen B, Burden E, Margetts M (2021) Understanding online hate: VSP regulation and the broader context. Alan Turing Institute, London

      Google Scholar 

    Download references

    Acknowledgements

    This chapter was partially funded by the National Institute for Health Research, Health Services and Delivery Research Programme (project number 13/10/80). The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care.

    Author information

    Authors and Affiliations

    1. Geller Institute of Aging and Memory, University of West London, London, UK

      Paula Boddington

    Authors
    1. Paula Boddington
      View author publications

      You can also search for this author in PubMed Google Scholar

    Rights and permissions

    Reprints and permissions

    Copyright information

    © 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

    About this chapter

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this chapter

    Boddington, P. (2023). Individuals, Society, and AI: Online Communication. In: AI Ethics. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer, Singapore. https://doi.org/10.1007/978-981-19-9382-4_9

    Download citation

    • DOI: https://doi.org/10.1007/978-981-19-9382-4_9

    • Published:

    • Publisher Name: Springer, Singapore

    • Print ISBN: 978-981-19-9381-7

    • Online ISBN: 978-981-19-9382-4

    • eBook Packages: Computer ScienceComputer Science (R0)

    Publish with us

    Policies and ethics

    Search

    Navigation