Skip to main content

Barriers to the Introduction of Artificial Intelligence to Support Communication Experts in Media and the Public Sector to Combat Fake News and Misinformation

  • Conference paper
  • First Online:
Electronic Participation (ePart 2023)

Abstract

Public trust represents a cornerstone of today’s democracies, their media, and institutions and in the search for consensus among different actors. However, the deliberate and non-deliberate spreading of misinformation and fake news severely damages the cohesion of our societies. This effect is intensified by the ease and speed of information creation and distribution that today’s social media offers. In addition, the current state-of-the-art for artificial intelligence available to everybody at their fingertips to create ultra-realistic fake multimedia news is unprecedented. This situation challenges professionals within the communication sphere, i.e., media professionals and public servants, to counter this flood of misinformation. While these professionals can also use artificial intelligence to combat fake news, introducing this technology into the working environment and work processes often meets a wide variety of resistance. Hence, this paper investigates what barriers but also chances these communication experts identify from their professional point of view. For this purpose, we have conducted a quantitative study with more than 100 participants, including journalists, press officers, experts from different ministries, and scientists. We analyzed the results with a particular focus on the types of fake news and in which capacity they were encountered, the experts’ general attitude towards artificial intelligence, as well as the perceived most pressing barriers concerning its use. The results are then discussed, and propositions are made concerning actions for the most pressing issues with a broad societal impact.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Hossová, M.: Fake news and disinformation: phenomenons of post-factual society. Media Literacy Acad. Res. 1, 27–35 (2018)

    Google Scholar 

  2. Bybee, C.: Can democracy survive in the post-factual age?: A return to the Lippmann-Dewey debate about the politics of news. Journal. Commun. Monographs 1, 28–66 (1999)

    Article  Google Scholar 

  3. Khaldarova, I., Pantti, M.: Fake news: the narrative battle over the Ukrainian conflict. Journal. Pract. 10, 891–901 (2016). https://doi.org/10.1080/17512786.2016.1163237

    Article  Google Scholar 

  4. Seboeck, W., Biron, B., Lampoltshammer, T.J., Scheichenbauer, H., Tschohl, C., Seidl, L.: Disinformation and fake news. In: Masys, A.J. (ed.) Handbook of Security Science, pp. 1–22. Springer, Cham (2020). https://doi.org/10.1007/978-3-319-51761-2_3-1

  5. Fraas, C., Klemm, M., Gesellschaft für Angewandte Linguistik (eds.) Mediendiskurse: Bestandsaufnahme und Perspektiven. P. Lang, Frankfurt am Main ; New York (2005)

    Google Scholar 

  6. Kriesi, H., Lavenex, S., Esser, F., Matthes, J., Bühlmann, M., Bochsler, D.: Democracy in the Age of Globalization and Mediatization. Palgrave Macmillan UK, London (2013). https://doi.org/10.1057/9781137299871

  7. Bennett, W.L., Livingston, S.: The disinformation order: disruptive communication and the decline of democratic institutions. Eur. J. Commun. 33, 122–139 (2018). https://doi.org/10.1177/0267323118760317

    Article  Google Scholar 

  8. Carayannis, E.G., Barth, T.D., Campbell, D.F.: The Quintuple Helix innovation model: global warming as a challenge and driver for innovation. J. Innov. Entrepreneurship. 1, 1–12 (2012)

    Article  Google Scholar 

  9. Van Meter, H.J.: Revising the DIKW pyramid and the real relationship between data, information, knowledge, and wisdom. Law Technol. Hum. 2, 69–80 (2020)

    Article  Google Scholar 

  10. Guo, L.: China’s “fake news” problem: exploring the spread of online rumors in the government-controlled news media. Digit. Journal. 8, 992–1010 (2020)

    Google Scholar 

  11. Ninkov, I.: Separating truth from fiction: legal aspects of “fake news.” Biztonságtudományi Szemle. 2, 51–64 (2020)

    Google Scholar 

  12. Wood, T.J., Porter, E.: The elusive backfire effect: mass attitude’ steadfast factual adherence. Polit. Behav. 41, 135–163 (2019)

    Article  Google Scholar 

  13. Huijstee, D., Vermeulen, I., Kerkhof, P., Droog, E.: Continued influence of misinformation in times of COVID‐19. Int. J. Psychol. ijop.12805 (2021). https://doi.org/10.1002/ijop.12805

  14. Jacobson, N.G., Thacker, I., Sinatra, G.M.: Here’s hoping it’s not just text structure: the role of emotions in knowledge revision and the backfire effect. Discourse Process. 1–23 (2021). https://doi.org/10.1080/0163853X.2021.1925059

  15. Appel, M. (ed.): Die Psychologie des Postfaktischen: über Fake News, “Lügenpresse” Clickbait & Co. Springer, Heidelberg (2020). https://doi.org/10.1007/978-3-662-58695-2

    Book  Google Scholar 

  16. Hagen, L.: Nachrichtenjournalismus in der Vertrauenskrise. “Lügenpresse” wissenschaftlich betrachtet: Journalismus zwischen Ressourcenkrise und entfesseltem Publikum. ComSoz. 48, 152–163 (2015). https://doi.org/10.5771/0010-3497-2015-2-152

  17. Hajli, N., Saeed, U., Tajvidi, M., Shirazi, F.: Social bots and the spread of disinformation in social media: the challenges of artificial intelligence. Brit. J. Manag. 1467–8551.12554 (2021). https://doi.org/10.1111/1467-8551.12554

  18. Shao, C., Ciampaglia, G.L., Varol, O., Flammini, A., Menczer, F.: The spread of fake news by social bots. 96, 104. arXiv preprint arXiv:1707.07592 (2017)

  19. Wang, P., Angarita, R., Renna, I.: Is this the era of misinformation yet: combining social bots and fake news to deceive the masses. Presented at the Companion Proceedings of the Web Conference 2018 (2018)

    Google Scholar 

  20. Zhang, T.: Deepfake generation and detection, a survey. Multimedia Tools Appl. 81, 6259–6276 (2021). https://doi.org/10.1007/s11042-021-11733-y

    Article  Google Scholar 

  21. Mirsky, Y., Lee, W.: The creation and detection of deepfakes: a survey. ACM Comput. Surv. 54, 1–41 (2022). https://doi.org/10.1145/3425780

    Article  Google Scholar 

  22. Ozbay, F.A., Alatas, B.: Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Stat. Mech. Appl. 540, 123174 (2020)

    Google Scholar 

  23. Faustini, P.H.A., Covoes, T.F.: Fake news detection in multiple platforms and languages. Expert Syst. Appl. 158, 113503 (2020)

    Article  Google Scholar 

  24. Neves, J.C., Tolosana, R., Vera-Rodriguez, R., Lopes, V., Proença, H., Fierrez, J.: Ganprintr: improved fakes and evaluation of the state of the art in face manipulation detection. IEEE J. Sel. Top. Sig. Process. 14, 1038–1048 (2020)

    Article  Google Scholar 

  25. Zhou, X., Jain, A., Phoha, V.V., Zafarani, R.: Fake news early detection: a theory-driven model. Digit. Threats Res. Pract. 1, 1–25 (2020)

    Article  Google Scholar 

  26. Xu, K., Wang, F., Wang, H., Yang, B.: Detecting fake news over online social media via domain reputations and content understanding. Tsinghua Sci. Technol. 25, 20–27 (2019)

    Article  Google Scholar 

  27. de Oliveira, N.R., Medeiros, D.S., Mattos, D.M.: A sensitive stylistic approach to identify fake news on social networking. IEEE Sig. Process. Lett. 27, 1250–1254 (2020)

    Article  Google Scholar 

  28. Elhadad, M.K., Li, K.F., Gebali, F.: Detecting misleading information on COVID-19. IEEE Access 8, 165201–165215 (2020)

    Article  Google Scholar 

  29. Allcott, H., Gentzkow, M.: Social media and fake news in the 2016 election. J. Econ. Perspect. 31, 211–236 (2017). https://doi.org/10.1257/jep.31.2.211

    Article  Google Scholar 

  30. Wardle, C., Derakhshan, H.: Information disorder: toward an interdisciplinary framework for research and policymaking. Council of Europe Strasbourg (2017)

    Google Scholar 

  31. Jung, T., Kim, S., Kim, K.: Deepvision: deepfakes detection using human eye blinking pattern. IEEE Access 8, 83144–83154 (2020)

    Article  Google Scholar 

  32. Müller, N.M., Pizzi, K., Williams, J.: Human perception of audio deepfakes. Presented at the Proceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia (2022)

    Google Scholar 

  33. Ahmed, S.: Who inadvertently shares deepfakes? Analyzing the role of political interest, cognitive ability, and social network size. Telematics Inform. 57, 101508 (2021)

    Article  Google Scholar 

  34. Valenzuela, S., Halpern, D., Katz, J.E., Miranda, J.P.: The paradox of participation versus misinformation: social media, political engagement, and the spread of misinformation. Digit. Journal. 7, 802–823 (2019). https://doi.org/10.1080/21670811.2019.1623701

    Article  Google Scholar 

  35. Weerawardana, M., Fernando, T.: Deepfakes detection methods: a literature survey. In: 2021 10th International Conference on Information and Automation for Sustainability (ICIAfS), pp. 76–81 (2021). https://doi.org/10.1109/ICIAfS52090.2021.9606067

  36. Sundar, S.S., Molina, M.D., Cho, E.: Seeing is believing: is video modality more powerful in spreading fake news via online messaging apps? J. Comput.-Mediat. Commun. 26, 301–319 (2021). https://doi.org/10.1093/jcmc/zmab010

    Article  Google Scholar 

  37. Pennathur, P.R., Bisantz, A.M., Fairbanks, R.J., Perry, S.J., Zwemer, F., Wears, R.L.: Assessing the impact of computerization on work practice: information technology in emergency departments. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 51, pp. 377–381 (2007). https://doi.org/10.1177/154193120705100448

  38. Grabowski, M., Rowen, A., Rancy, J.-P.: Evaluation of wearable immersive augmented reality technology in safety-critical systems. Saf. Sci. 103, 23–32 (2018). https://doi.org/10.1016/j.ssci.2017.11.013

    Article  Google Scholar 

  39. Gillath, O., Ai, T., Branicky, M.S., Keshmiri, S., Davison, R.B., Spaulding, R.: Attachment and trust in artificial intelligence. Comput. Hum. Behav. 115, 106607 (2021). https://doi.org/10.1016/j.chb.2020.106607

    Article  Google Scholar 

  40. Nass, C., Moon, Y.: Machines and mindlessness: social responses to computers. J. Soc. Isssues 56, 81–103 (2000). https://doi.org/10.1111/0022-4537.00153

    Article  Google Scholar 

  41. Seeber, I., et al.: Machines as teammates: a research agenda on AI in team collaboration. Inf. Manag. 57, 103174 (2020). https://doi.org/10.1016/j.im.2019.103174

    Article  Google Scholar 

  42. Okamura, K., Yamada, S.: Adaptive trust calibration for human-AI collaboration. PLoS ONE 15, e0229132 (2020). https://doi.org/10.1371/journal.pone.0229132

    Article  Google Scholar 

  43. Shin, J., Chan-Olmsted, S.: User perceptions and trust of explainable machine learning fake news detectors. Int. J. Commun. 17, 23 (2022)

    Google Scholar 

  44. Brandtzaeg, P.B., Følstad, A.: Trust and distrust in online fact-checking services. Commun. ACM. 60, 65–71 (2017). https://doi.org/10.1145/3122803

    Article  Google Scholar 

  45. Zhou, X., Zafarani, R.: A survey of fake news: fundamental theories, detection methods, and opportunities. ACM Comput. Surv. 53, 1–40 (2021). https://doi.org/10.1145/3395046

    Article  Google Scholar 

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

    Google Scholar 

  47. Mohseni, S., Zarei, N., Ragan, E.D.: A Multidisciplinary survey and framework for design and evaluation of explainable AI systems. ACM Trans. Interact. Intell. Syst. 11, 1–45 (2021). https://doi.org/10.1145/3387166

    Article  Google Scholar 

  48. Matthews, G., Lin, J., Panganiban, A.R., Long, M.D.: Individual differences in trust in autonomous robots: implications for transparency. IEEE Trans. Human-Mach. Syst. 50, 234–244 (2020). https://doi.org/10.1109/THMS.2019.2947592

    Article  Google Scholar 

  49. Araujo, T., Helberger, N., Kruikemeier, S., de Vreese, C.H.: In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI Soc. 35(3), 611–623 (2020). https://doi.org/10.1007/s00146-019-00931-w

    Article  Google Scholar 

  50. Hofkirchner, W., Kreowski, H.-J.: Digital humanism: how to shape digitalisation in the age of global challenges? In: IS4SI 2021, p. 4. MDPI (2022). https://doi.org/10.3390/proceedings2022081004

  51. Schmölz, A.: Die Conditio Humana im digitalen Zeitalter: Zur Grundlegung des Digitalen Humanismus und des Wiener Manifests. MedienPädagogik. 208–234 (2020). https://doi.org/10.21240/mpaed/00/2020.11.13.X

  52. Floridi, L., Cowls, J.: A unified framework of five principles for AI in society. Harvard Data Sci. Rev. (2019). https://doi.org/10.1162/99608f92.8cd550d1

    Article  Google Scholar 

  53. Hickok, M.: Lessons learned from AI ethics principles for future actions. AI Ethics 1(1), 41–47 (2020). https://doi.org/10.1007/s43681-020-00008-1

    Article  Google Scholar 

  54. Becker, S.J., Nemat, A.T., Lucas, S., Heinitz, R.M., Klevesath, M., Charton, J.E.: A code of digital ethics: laying the foundation for digital ethics in a science and technology company. AI Soc. (2022). https://doi.org/10.1007/s00146-021-01376-w

    Article  Google Scholar 

Download references

Acknowledgments

The work described in this paper was funded in the context of the defalsif-AI project (FFG project number 879670, funded by the Austrian security research program KIRAS of the Federal Ministry of Agriculture, Regions, and Tourism BMLRT).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas J. Lampoltshammer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Seböck, W., Biron, B., Lampoltshammer, T.J. (2023). Barriers to the Introduction of Artificial Intelligence to Support Communication Experts in Media and the Public Sector to Combat Fake News and Misinformation. In: Edelmann, N., Danneels, L., Novak, AS., Panagiotopoulos, P., Susha, I. (eds) Electronic Participation. ePart 2023. Lecture Notes in Computer Science, vol 14153. Springer, Cham. https://doi.org/10.1007/978-3-031-41617-0_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-41617-0_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41616-3

  • Online ISBN: 978-3-031-41617-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics