Název: Ethical concerns of search technology : search engine bias
Zdrojový dokument: ProInflow. 2022, roč. 14, č. 1-2, s. [156]-170
Rozsah
[156]-170
-
ISSN1804-2406 (online)
Trvalý odkaz (DOI): https://doi.org/10.5817/ProIn2022-2-9
Trvalý odkaz (handle): https://hdl.handle.net/11222.digilib/digilib.77650
Type: Článek
Jazyk
Licence: CC BY 4.0 International
Upozornění: Tyto citace jsou generovány automaticky. Nemusí být zcela správně podle citačních pravidel.
Abstrakt(y)
Purpose – Search engines are a dominant part of our everyday activities and lives. These tools support decision-making, play a crucial role in constructing knowledge, and have a significant impact on our individual and social behaviour. The paper is aimed at the search engine bias problem as one of the important ethical issues associated with search technology algorithmic design and development.
Design/Methodology/Approach – Conceptual analytical method and critical approach are applied to a problem of search engine bias. Based on analysis, typology of specific problems and solutions are summarized and characterized. ANT (actor-network theory) (Latour, 2005) was used to introduce model consisting of search engine bias problem actors present in a complex bidirectional relations.
Results – The focus of this conceptual article is mainly on search engine bias in connection with manipulation techniques such as SEO (search engine optimization) methods and paid results. Problems of Google as a gatekeeper, personalization, and biased algorithmic design are also further analysed in more detail. As a result of the analysis, possible solutions to the search engine bias problem are categorized and discussed.
Originality/Value – This work provides new insights into search engine bias problem in the context of recent technological development and trends. The current methods, principles, and frameworks as a solution to the ethical issues of search engine technology are summarized.
Design/Methodology/Approach – Conceptual analytical method and critical approach are applied to a problem of search engine bias. Based on analysis, typology of specific problems and solutions are summarized and characterized. ANT (actor-network theory) (Latour, 2005) was used to introduce model consisting of search engine bias problem actors present in a complex bidirectional relations.
Results – The focus of this conceptual article is mainly on search engine bias in connection with manipulation techniques such as SEO (search engine optimization) methods and paid results. Problems of Google as a gatekeeper, personalization, and biased algorithmic design are also further analysed in more detail. As a result of the analysis, possible solutions to the search engine bias problem are categorized and discussed.
Originality/Value – This work provides new insights into search engine bias problem in the context of recent technological development and trends. The current methods, principles, and frameworks as a solution to the ethical issues of search engine technology are summarized.
Note
The article was developed in the framework of the VEGA 1 / 0360 / 21 project Social representations of ethical challenges of the digital information revolution.
Reference
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[2] ANNUAL Report pursuant to Section 13 or 15(d) of the securities exchange act of 1934 (2022). Alphabet, 2022. Available from: https://abc.xyz/investor/static/pdf/20220202_alphabet_10K.pdf.
[3] BOSTROM, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
[4] CADWALLADR, C. (2016). Google, Democracy and the Truth about Internet Search. The Observer, 4 December 2016, The Guardian. Available from: https://www.theguardian.com/technology/2016/dec/04/google-democracy-truth-internet-search-facebook.
[5] DESIGNING Inclusive Products for Everyone - Google. (2022) Available from: https://about.google/belonging/in-products/.
[6] DUCKDUCKGO. (2022). Homepage. Available from: https://duckduckgo.com.
[7] ETHICS Guidelines for Trustworthy AI: Shaping Europe's Digital Future (2018). Available from: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai.
[8] FRIEDMAN, B., P. KAHN, and A. BORNING. (2008). Value-sensitive design and information systems. The Handbook of Information and Computer Ethics, K. E. Himma and H. T. Tavani (eds.), Hoboken, NJ: John Wiley and Sons, pp. 69–101. https://doi.org/10.1002/9780470281819.ch4
[9] FRIEDMAN, B., HENDRY, D. G. (2019). Value Sensitive Design: Shaping Technology with Moral Imagination. MIT Press. ISBN 9780262351706. https://doi.org/10.7551/mitpress/7585.001.0001
[10] HERSHER, R. (2017). What Happened When Dylann Roof asked Google for information about race? NPR, 10 January 2017. Available from: https://www.npr.org/sections/thetwo-way/2017/01/10/508363607/what-happened-when-dylann-roof-asked-google-for-information-about-race.
[11] GALLAGHER, R. (2018). Google Plans to launch a censored search engine in China, leaks reveal. The Intercept. August 1, 2018. Available from: https://theintercept.com/2018/08/01/google-china-search-engine-censorship/.
[12] GOLDMAN, E. (2006). Search Engine Bias and the Demise of Search Engine Utopianism. Yale Journal of Law and Technology. 188 (Spring 2006). Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=893892.
[13] GOODISON, D. (2020) Google Is "A Monopoly Gatekeeper:" DOJ Antitrust Lawsuit. CRN, 20 Oct. 2020. Available from: https://www.crn.com/news/google-is-a-monopoly-gatekeeper-doj-antitrust-lawsuit.
[14] LATOUR, B. (2005). Reassembling the Social: An Introduction to Actor-Network-Theory. Oxford: OUP Oxford, 2005. ISBN 9780199256044. Available from: http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=211608&lang=sk&site=ehost-live&scope=site
[15] LIU, F. (2020). The Love-at-First-Sight Gaze Pattern on Search-Results Pages. Nielsen Norman Group. Available from: https://www.nngroup.com/articles/love-at-first-sight-pattern/.
[16] MURPHY, G. (2016). Search Engine Bias: An Analysis from the Index. Search Engine Watch. Available from: https://www.searchenginewatch.com/2016/02/17/search-engine-bias-an-analysis-from-the-index/.
[17] NEW Approach to China: An Update. (2010). Official Google Blog. Available from: https://googleblog.blogspot.com/2010/03/new-approach-to-china-update.html.
[18] NOBLE, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, 2018. Available from: http://ebookcentral.proquest.com/lib/uniba-ebooks/detail.action?docID=4834260. https://doi.org/10.2307/j.ctt1pwt9w5
[19] PARISER, E. (2011). Beware online "filter bubbles". TED Talk. Available from: https://www.ted.com/talks/eli_pariser_beware_online_,lter_bubbles.
[20] PASTIEROVÁ, M. (2021a). Aktuálne trendy vyhľadávania informácií. Knižnica. No. 2. Vol. 2021. Available from: https://www.snk.sk/images/Edicna_cinnost/Casopis_Kniznica/2021/2021_07_06_01_Mirka_Pastierova.pdf
[21] PASTIEROVÁ, M. (2021b). Problémy vyhľadávania informácií v kontexte súkromia. ITlib: Informačné technológie a knižnice, 2021, pp. 24–30. Available from: https://doi.org/10.52036/1335793X.2021.1-2.24-30.
[22] PASTIEROVÁ, M. (2021c). Trends in digital information search. Knižničná a informačná veda XIX, 2021, pp. 109–119. Available from: https://fphil.uniba.sk/fileadmin/fif/katedry_pracoviska/kkiv/zbornik_KIV/kiv29_pastierova.pdf.
[23] PITKOW, J. et al. (2002). Personalized search. Communications of the ACM. 45, 9 (September 2002), 50–55. Available from: https://doi.org/10.1145/567498.567526.
[24] RAGHAVAN, P. (2022). Google I/O keynote. Available from: https:io.google/2022/program/8e80903f-955f-4a5b-9118-b0ce4acdb0e6/.
[25] SEARCH Engine Market Share Worldwide. (2022). StatCounter Global Stats. Available from: https://gs.statcounter.com/search-engine-market-share.
[26] SCHULTHEIß, S., and D. LEWANDOWSKI. (2021). Google search results—They're all the same, right? Information Matters. Vol.1, Issue 11. Available from: https://r7q.22f.myftpupload.com/2021/11/google-search-results-theyre-all-the-same-right/
[27] SKIN Tone Research @ Google. (2022). Available from: https://skintone.google/get-started.
[28] SOUTHERN, M. G. (2020). Over 25% of People Click the First Google Search Result". Search Engine Journal. 15. July 2020. Available from: https://www.searchenginejournal.com/google-first-page-clicks/374516/.
[29] STARTPAGE. (2022). Homepage. Available from: https://www.startpage.com/.
[30] SUNDIN, O., D. LEWANDOWSKI and J. HAIDER. (2022). Whose relevance? Web search engines as multisided relevance machines. JASIST. Volume 73, Issue 5, May 2022 https://doi.org/10.1002/asi.24570
[31] SWISSCOWS. (2022). Homepage. Available from: https://swisscows.com/.
[32] TAVANI, H. (2012). Search Engines and Ethics. Stanford Encyclopedia of Philosophy. August 2012. Available from: https://meinong.stanford.edu/entries/ethics-search/index.html.