Algoritmi za preporuke kao izvor moći u savremenom društvu

  • Ljubiša M. Bojić Univerzitet u Beogradu, Institut za filozofiju i društvenu teoriju, Laboratorija za digitalno društvo, Beograd (Srbija)
DOI: https://doi.org/10.5937/socpreg56-36721
Ključne reči: tehno-feudalizam, velike tehnološke kompanije, algoritmi za preporuke sadržaja zasnovani na veštačkoj inteligenciji, mas mediji, cenzura

Sažetak


Tehnološke kompanije i algoritmi zasnovani na veštačkoj inteligenciji vrše veliku moć u globalno povezanom svetu današnjice, koji se bazira na podacima i na našim digitalnim otiscima. U ovom radu analizira se transfer moći od društava ka tehnološkim kompanijama i algoritmima s ciljem da se ispita da li se algoritmi za preporuke mogu smatrati javnim dobrom. Korišćene metode su analiza sadržaja i pregled literature. Pronađeno je da ovako visok stepen kontrole nad stavovima, individualnim odlukama i raspoloženju onlajn korisnika nikada nije viđen u prošlosti. Pomenuta kontrola zasnovana je na uticajima tehnoloških kompanija i algoritama. Ograničenje ovog istraživanja jeste nedostatak kvantitativne analize. Fokus budućih istraživanja treba da bude definisanje algoritama za preporuke kao javnog dobra i analiza kako različiti sadržaji, uključujući virtuelnu realnost, utiču na psihologiju građana.

Reference

Ali, K. F., Whitebridge, S., Jamal, M. H., Alsafy, M. & Atkin, S. L. (2020). Perceptions, knowledge, and behaviors related to COVID-19 among social media users: Crosssectional study. Journal of Medical Internet Research, 22(9), e19913. https://dx.doi.org/10.2196%2F19913
/>Azucar, D., Marengo, D. & Settanni, M. (2018). Predicting the Big 5 personality traits from digital footprints on social media: A meta-analysis. Personality and Individual Differences, 124, 150–159. https://doi.org/10.1037/a0030383
/>Baumeister, R. F., Bratslavsky, E., Finkenauer, C. & Vohs, K. D. (2001). Bad Is Stronger than Good. Review of General Psychology, 5(4), 323–70. https://doi.org/10.1037/1089-2680.5.4.323
/>BBC (2021, February 18). Social networks: Australia enacts the law forcing Google and Facebook to pay for publishing news. BBC News. Retrieved from: https://www.bbc.com/serbian/lat/svet-56105726 [In Serbian]
Bojić, Lj. (2021). How Media Directly Impact Society: A Psychometric Analysis of Leading Twitter News Profiles and their Followers in Serbia. In: R. Surugiu, A. Stefanel, N. Apostol (eds.) 30 de ani de învăţământ jurnalistic şi de comunicare în Estul Europei/30 Years of Higher Education in Journalism and Communication in Eastern Europe (483-504). Bucharest: Tritonic. https://rifdt.instifdt.bg.ac.rs/handle/123456789/2365
/>Bojić, Lj. (2022). Culture Organism or Techno-Feudalism: How Growing Addictions and Artificial Intelligence Shape Contemporary Society. Belgrade: Institute for Philosophy and Social Theory.
Bojić, Lj., Nikolić, N. & Tucaković, L. (2022). Wars of Echo Chambers: Analysis of COVID-19 Echo Chambers in Serbia. Communications, 48(2).
Bojić, Lj., Zarić, M. & Žikić, S. (2021). Worrying impact of artificial intelligence and big data through the prism of recommender systems. Etnoantropološki problemi, 16(3), 935-957. https://doi.org/10.21301/eap.v16i3.13
/>Bojić, Lj., Zejnulahović, D. & Janković, M. (2021). Technofeudalism illustrated by Trump’s Twitter suspension and Australia vs. Google and Facebook dispute. Sociološki pregled, 55(2), 538-561. DOI: 10.5937/socpreg55-32105
Brown, E. (2017, December 1). 9 out of 10 Americans don’t fact-check information they read on social media. ZdNet. Retrieved from: https://www.zdnet.com/article/nineout-of-ten-americans-dont-fact-check-information-they-read-on-social-media/
/>Cadwalladr, C. (2017, January 18). The great British Brexit robbery: How our democracy was hijacked. The Guardian. Retrieved from: https://www.theguardian.com/technology/2017/may/07/the-great-british-brexit-robbery-hijacked-democracy
/>Cinelli, M., Morales, G. D. F., Galeazzi, A., Quattrociocchi, W. & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9). https://doi.org/10.1073/pnas.2023301118
/>Conway-Silva, B. A., Filer, C. R, Kenski, K. & Tsetsi, E. (2018). Reassessing Twitter’s AgendaBuilding Power: An Analysis of Intermedia Agenda-Setting Effects During the 2016 Presidential Primary Season. Social Science Computer Review, 36(4), 469–83. https://doi.org/10.1177/0894439317715430
/>Coviello, L., Fowler, J. H. & Franceschetti, M. (2014). Words on the web: Noninvasive detection of emotional contagion in online social networks. Proceedings of the IEEE, 102(12), 1911–1921. https://doi.org/10.1109/jproc.2014.2366052
/>Dang-Xuan, L. & Stieglitz, S. (2021). Impact and Diffusion of Sentiment in Political Communication – An Empirical Analysis of Political Weblogs. Proceedings of the International AAAI Conference on Web and Social Media, 6(1), 427-30. https://ojs.aaai.org/index.php/ICWSM/article/view/14326
/>Deeva, I. (2019). Computational Personality Prediction Based on Digital Footprint of a Social Media User. Procedia Computer Science, 156, 185-193. https://doi.org/10.1016/j.procs.2019.08.194
/>Derks, D., Fischer, A. H. & Bosc, A. E. R. (2008). The role of emotion in computer-mediated communication: A review. Computers in Human Behavior, 24(3), 766–785. https://doi.org/10.1016/j.chb.2007.04.004
/>Dhar, V. (2021, December 11). Nationalize’ Facebook and Twitter as public goods. The Hill. Retrieved from: https://thehill.com/opinion/technology/534458-nationalize-facebook-and-twitter-as-public-goods
/>Domke, D., Shah, D. V. & Wackman, D. B. (1998). Media priming effects: accessibility, association, and activation. International Journal of Public Opinion Research, 10(1), 51–74. https://doi.org/10.1093/ijpor/10.1.51
/>Farnadi, G., Sitaraman, G., Sushmita, S., Celli, F., Kosinski, M., Stillwell, D., Davalos, S., Moens, M.-F. & De Cock, M. (2016). Computational personality recognition in social media. User Modeling and User-Adapted Interaction, 26(2), 109-142. https://doi.org/10.1007/s11257-016-9171-0
/>Feezell, J. T. (2018). Agenda Setting through Social Media: The Importance of Incidental News Exposure and Social Filtering in the Digital Era. Political Research Quarterly, 71(2), 482–94. https://doi.org/10.1177/1065912917744895
/>Ferguson, N. (2018, December 11). What Is to Be Done? Safeguarding Democratic Governance in The Age of Network Platforms. Hoover Institution. Retrieved from: https://www.hoover.org/research/what-be-done-safeguarding-democratic-governance-age-network-platforms
/>Ferrara, E. & Yang, Z. (2015). Measuring emotional contagion in social media. PLoS ONE, 10(11), e0142390. https://doi.org/10.1371/journal.pone.0142390
/>Frenda, S. J., Nichols, R. M. & Loftus, E. F. (2011). Current Issues and Advances in Misinformation Research. Current Directions in Psychological Science, 20(1) 20–23. https://doi.org/10.1177/0963721410396620
/>Garimella, K., Morales, G. D. F., Gionis, A. & Mathioudakis, M. (2018). Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. In: Proceedings of the 2018 World Wide Web Conference, Geneva, Switzerland: International World Wide Web Conferences Steering Committee. https://arxiv.org/abs/1801.01665
/>Graham, J. (2022, January 18). Is Facebook listening to me? Why those ads appear after you talk about things. USA Today. Retrieved from: https://www.usatoday.com/story/tech/talkingtech/2019/06/27/does-facebook-listen-to-your-conversations/1478468001/
/>Greving, H., Oeberst, A., Kimmerle, J. & Cress, U. (2018). Emotional Content in Wikipedia Articles on Negative Man-Made and Nature-Made Events. Journal of Language and Social Psychology, 37(3), 267–87. https://doi.org/10.1177/0261927X17717568
/>Haring, M. & Cecire, M. (2013, January 18). Why the Color Revolutions Failed. Foreign Policy. Retrieved from: https://foreignpolicy.com/2013/03/18/why-the-color-revolutions-failed/
/>Harrington, K. M. (2019). Surveillance Is the Business Model of the Internet. What’s Coming Next? MediaVillage. Retrieved from: https://www.mediavillage.com/article/surveillance-is-the-business-model-of-the-internet-whats-coming-next/
/>Hatfield, E., Cacioppo, J. T. & Rapson, R. L. (1993). Emotional Contagion. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139174138
/>Hinds, J. & Joinson, A. (2019). Human and computer personality prediction from digital footprints. Current Directions in Psychological Science, 28(2), 204-211. https://doi.org/10.1177/0963721419827849
/>Holcombe, R. G. (2000). Public Goods Theory and Public Policy. The Journal of Value Inquiry, 34, 273-286. https://doi.org/10.1007/978-94-015-9440-0_8
/>Hsieh, H.-F. & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277−1288. https://doi.org/10.1177/1049732305276687
/>Johnson, J. (2021, December 1). Worldwide digital population as of January 2021. Statista. Retrieved from: https://www.statista.com/statistics/617136/digital-population-worldwide/
/>Kalsnes, B. & Olof Larsson, A. (2017). Understanding news sharing across social media. Journalism Studies, 19(11), 1669–1688. https://doi.org/10.1080/1461670x.2017.1297686
/>Kaplan, A. & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
/>Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J. & Mullainathan, S. (2018). Human Decisions and Machine Predictions. The Quarterly Journal of Economics, 133(1), 237–293. https://doi.org/10.1093/qje/qjx032
/>Lamberti, F., Sanna, A. & Demartini, C. (2009). A Relation-Based Page Rank Algorithm for Semantic Web Search Engines. IEEE Transactions on Knowledge and Data Engineering, 21(1), 123-136. https://doi.org/10.1109/TKDE.2008.113
/>Li, H. O.-Y. L., Bailey, A., Huynh, D. & Chan, J. (2020). YouTube as a source of information on COVID-19: a pandemic of misinformation? BMJ Global Health, 5(5), e002604. https://doi.org/10.1136/bmjgh-2020-002604
/>Liebrecht, C., Hustinx, L. & Mulken, M. (2019). The Relative Power of Negativity: The Influence of Language Intensity on Perceived Strength. Journal of Language and Social Psychology, 38(2), 170–93. https://doi.org/10.1177/0261927X18808562
/>Madison, E. (2014). News Narratives, Classified Secrets, Privacy, and Edward Snowden. Electronic News, 8(1), 72–75. https://doi.org/10.1177/1931243114527869
/>Milano, S., Taddeo, M., & Floridi, L. (2020). Recommender systems and their ethical challenges. AI & Society. https://doi.org/10.1007/s00146-020-00950-y
/>Nickerson, R. S. (1998). Confirmation Bias: A Ubiquitous Phenomenon in Many Guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175
/>NYT (2022, February 3). Meta spent $10 billion on the Metaverse in 2021, dragging down profit. The Indian Express. Retrieved from: https://indianexpress.com/article/technology/tech-news-technology/meta-spent-10-billion-on-the-metaverse-in-2021-dragging-down-profit-7754565/
/>Orlowski, J. (2020). The Social Dilemma. IMDB. https://www.imdb.com/title/tt11464826/
/>Park, S. P. (2015). Applying “negativity bias” to Twitter: Negative news on Twitter, emotions, and political learning. Journal of Information Technology & Politics, 12(4), 342–359. https://doi.org/10.1080/19331681.2015.1100225
/>Paul, K. (2020, December 1). Russian hackers targeting US political campaigns ahead of elections, Microsoft warns. The Guardian. Retrieved from: https://www.theguardian.com/technology/2020/sep/10/microsoft-russia-us-election-2020-hackers
/>Pavlović, M. & Bojić, Lj. (2020). Political marketing and strategies of digital illusions – examples from Venezuela and Brazil. Sociološki pregled, 54(4), 1391-1414. DOI:10.5937/socpreg54-27846
Perrigo, B. (2021). Inside Frances Haugen’s Decision to Take on Facebook. Time. Retrieved from: https://time.com/6121931/frances-haugen-facebook-whistleblower-profile/
/>Pew (2019, December 1). Americans Are Wary of the Role Social Media Sites Play in Delivering the News. Pew Research Center. Retrieved from: https://www.journalism.org/wp-content/uploads/sites/8/2019/09/PJ_2019.09.25_Social-Media-and-News_FINAL.pdf
/>Philippe M. (2014). Politics 2.0: New forms of digital political marketing and political communication. Trípodos, 34, 13-22. http://www.tripodos.com/index.php/Facultat_Comunicacio_Blanquerna/article/view/163
/>Redding, R. (2019, December 1). A Brief History of Google Ad Strategy (and why you should care). DP Marketing Services. Retrieved from: https://www.dpmarketing.services/abrief-history-of-google-ad-strategy-and-why-you-should-care
/>Rieger, M. O. & Wang, M. (2020, December 1). Trust in Government Actions during the COVID-19 Crisis. Universitat Trier. Retrieved from: https://www.uni-trier.de/fileadmin/fb4/prof/BWL/FIN/Files/Trust_in_Government_Actions_during_the_COVID-19_Crisis.pdf
/>Risso, L. (2018). Harvesting your soul? Cambridge Analytica and Brexit. In: Brexit Means Brexit? The Selected Proceedings of the Symposium (75-90). Mainz, Germany: Akademie der Wissenschaften und der Literatur. https://www.adwmainz.de/fileadmin/user_upload/Brexit-Symposium_Online-Version.pdf
/>Rozin, P. & Royzman, E. B. (2001). Negativity Bias, Negativity Dominance, and Contagion. Personality and Social Psychology Review, 5(4), 296–320. https://doi.org/10.1207/S15327957PSPR0504_2
/>Schmidt, A. L., Zollo, F., Scala, A., Betsch, C., and Quattrociocchi, W. (2018). Polarization of the vaccination debate on Facebook. Vaccine, 36(25), 3606–3612. https://doi.org/10.1016/j.vaccine.2018.05.040
/>Sear, R. F., Velásquez, N., Leahy, R., Restrepo, N. J., El Oud, S., Gabriel, N., Lupu, Y. & Johnson, N. F. (2020). Quantifying COVID-19 content in the online health opinion war using machine learning. IEEE Access, 8, 91886-91893. https://doi.org/10.1109/ACCESS.2020.2993967
/>Settanni, M., Azucar, D. & Marengo, D. (2018). Predicting individual characteristics from digital traces on social media: A meta-analysis. Cyberpsychology, Behavior and Social Networking, 21(4), 217-228. https://doi.org/10.1089/cyber.2017.0384
/>Spohr, D. (2017). Fake news and ideological polarization: Filter bubbles and selective exposure on social media. Business Information Review, 34(3), 150–160. https://doi.org/10.1177/0266382117722446
/>Stieglitz, S., & Dang-Xuan, L. (2013). Emotions and information diffusion in social media —Sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217–248. https://doi.org/10.2753/mis0742-1222290408
/>Trougakos, J. P., Chawla, N., & McCarthy, J. M. (2020). Working in a pandemic: Exploring the impact of COVID-19 health anxiety on work, family, and health outcomes. Journal of Applied Psychology, 105(11), 1234–1245. https://doi.org/10.1037/apl0000739
/>UNESCO (2021). WPFD 2021 – Concept Note - Word Press Freedom Day 2021: Information as a public good - 30 years of the Windhoek Declaration. UNESCO. Retrieved from: https://en.unesco.org/sites/default/files/wpfd_2021_concept_note_en.pdf
/>Varoufakis, Y. (2021, September 7). Techno-Feudalism is taking over. DiEM25. https://diem25.org/techno-feudalism-taking-over/
/>Witteman, H. O. & Zikmund-Fisher, B. J. (2012). The defining characteristics of Web 2.0 and their potential influence in the online vaccination debate. Vaccine, 30(25), 3734-3740. https://doi.org/10.1016/j.vaccine.2011.12.039
/>Youyou, W., Kosinski, M. & Stillwell, D. (2015). Computer-based personality judgments are more accurate than those made by humans. Proceedings of the National Academy of Sciences, 112(4), 1036-1040. https://doi.org/10.1073/pnas.1418680112
/>Zollo, F. (2019). Dealing with digital misinformation: A polarised context of narratives and tribes. EFSA Journal, 17(S1) e170720. http://dx.doi.org/10.2903/j.efsa.2019.e170720
/>Zuckerman, E. (2009, December 1). “Twitter.org? and building models for social media.” Ethan Zuckerman Blog. Retrieved from: https://ethanzuckerman.com/2009/09/28/twitter-org-and-building-models-for-social-media/

Objavljeno
2022/11/02
Broj časopisa
Vol. 56 Br. 3 (2022)
Rubrika
Pregledni naučni rad