Unveiling public perception of AI ethics: an exploration on Wikipedia data

Mengyi Wei1, Yu Feng1, Chuan Chen1, Peng Luo1, Chenyu Zuo2, Liqiu Meng1
1Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany
2Center for Sustainable Future Mobility (CSFM), ETH Zurich, Zürich, Switzerland

Tóm tắt

Artificial Intelligence (AI) technologies have exposed more and more ethical issues while providing services to people. It is challenging for people to realize the occurrence of AI ethical issues in most cases. The lower the public awareness, the more difficult it is to address AI ethical issues. Many previous studies have explored public reactions and opinions on AI ethical issues through questionnaires and social media platforms like Twitter. However, these approaches primarily focus on categorizing popular topics and sentiments, overlooking the public’s potential lack of knowledge underlying these issues. Few studies revealed the holistic knowledge structure of AI ethical topics and the relations among the subtopics. As the world’s largest online encyclopedia, Wikipedia encourages people to jointly contribute and share their knowledge by adding new topics and following a well-accepted hierarchical structure. Through public viewing and editing, Wikipedia serves as a proxy for knowledge transmission. This study aims to analyze how the public comprehend the body of knowledge of AI ethics. We adopted the community detection approach to identify the hierarchical community of the AI ethical topics, and further extracted the AI ethics-related entities, which are proper nouns, organizations, and persons. The findings reveal that the primary topics at the top-level community, most pertinent to AI ethics, predominantly revolve around knowledge-based and ethical issues. Examples include transitions from Information Theory to Internet Copyright Infringement. In summary, this study contributes to three points, (1) to present the holistic knowledge structure of AI ethics, (2) to evaluate and improve the existing body of knowledge of AI ethics, (3) to enhance public perception of AI ethics to mitigate the risks associated with AI technologies.

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Tài liệu tham khảo

Araujo T, Helberger N, Kruikemeier S, de Vreese CH (2020) In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI Soc 35:611–623. https://doi.org/10.1007/s00146-019-00931-w Bohlin L, Edler D, Lancichinetti A, Rosvall M (2014) Community detection and visualization of networks with the map equation framework. In: Ding Y, Rousseau R, Wolfram D (eds) Measuring scholarly impact. Springer, Cham, pp 3–34 Buscaldi D, Rosso P (2006) Mining knowledge from Wikipedia for the question answering task Cucerzan S (2007) Large-scale named entity disambiguation based on Wikipedia data Das S, Lavoie A, Magdon-Ismail M (2011) Pushing your point of view: behavioral measures of manipulation in Wikipedia Di Lauro F, Johinke R (2017) Employing Wikipedia for good not evil: innovative approaches to collaborative writing assessment. Assess Eval High Educ 42:478–491. https://doi.org/10.1080/02602938.2015.1127322 Dowler E, Bauer M, Green J, Gasperoni G (2006). Assessing public perception: issues and methods Fast E, Horvitz E (2016) Long-term trends in the public perception of artificial intelligence Ferguson MJ, Bargh JA (2004) How social perception can automatically influence behavior. Trends Cogn Sci 8:33–39. https://doi.org/10.1016/j.tics.2003.11.004 Fichman P, Hara N (2014) Global Wikipedia: international and cross-cultural issues in online collaboration. Rowman & Littlefield, Totowa Fortunato S (2010) Community detection in graphs. Phys Rep 486:75–174. https://doi.org/10.1016/j.physrep.2009.11.002 Fu Y, Zhuang Z, Zhang L (2022) AI ethics on blockchain: topic analysis on Twitter data for blockchain security Gillespie N, Lockey S, Curtis C et al. (2023) Trust in artificial intelligence: a global study. University of Queensland, Brisbane Greenstein S, Zhu F (2012) Is Wikipedia biased? Am Econ Rev 102:343–348. https://doi.org/10.1257/aer.102.3.343 Grünwald P, Myung J, Pitt M (2005) Advances in minimum description length Halatchliyski I, Moskaliuk J, Kimmerle J, Cress U (2014) Explaining authors’ contribution to pivotal artifacts during mass collaboration in the Wikipedia’s knowledge base. Int J Comput-Support Collab Learn 9:97–115. https://doi.org/10.1007/s11412-013-9182-3 Ikkatai Y, Hartwig T, Takanashi N, Yokoyama HM (2022) Octagon measurement: public attitudes toward AI ethics. Int J Hum-Comput Interact 38:1589–1606. https://doi.org/10.1080/10447318.2021.2009669 Jobin A, Ienca M, Vayena E (2019) The global landscape of AI ethics guidelines. Nat Mach Intell 1:389–399. https://doi.org/10.1038/s42256-019-0088-2 Kelley PG, Yang Y, Heldreth C et al. (2021) Exciting, useful, worrying, futuristic: public perception of artificial intelligence in 8 countries. In: Proceedings of the 2021 AAAI/ACM conference on AI, ethics, and society. Assoc. Comput. Mach., New York, pp 627–637 Kieslich K, Keller B, Starke C (2022) Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence. Big Data Soc 9:205395172210929. https://doi.org/10.1177/20539517221092956 Köchling A, Wehner MC (2020) Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Bus Res 13:795–848. https://doi.org/10.1007/s40685-020-00134-w Lizorkin D, Medelyan O, Grineva M (2009) Analysis of Community Structure in Wikipedia (Poster) Majchrzak A (2009) Comment: where is the theory in wikis? MIS Q 33:18–20. https://doi.org/10.2307/20650275 Medelyan O, Milne D, Legg C, Witten IH (2009) Mining meaning from Wikipedia. Int J Hum-Comput Stud 67:716–754. https://doi.org/10.1016/j.ijhcs.2009.05.004 Microsoft (2022) Microsoft responsible AI standard v2 general requirements. Impact assess Moy CL, Locke JR, Coppola BP, McNeil AJ (2010) Improving science education and understanding through editing Wikipedia. J Chem Educ 87:1159–1162. https://doi.org/10.1021/ed100367v Nastase V, Strube M (2008) Decoding Wikipedia Categories for Knowledge Acquisition Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45:167–256. https://doi.org/10.1137/S003614450342480 Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45:167–256. https://doi.org/10.1137/S003614450342480 Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69:026113. https://doi.org/10.1103/PhysRevE.69.026113 Nguyen DPT (2007) Relation extraction from Wikipedia using subtree mining Palla G, Derényi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435:814–818. https://doi.org/10.1038/nature03607 Rosvall M, Axelsson D, Bergstrom CT (2009) The map equation. Eur Phys J Spec Top 178:13–23. https://doi.org/10.1140/epjst/e2010-01179-1 Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci 105:1118–1123. https://doi.org/10.1073/pnas.0706851105 Rosvall M, Bergstrom CT (2011) Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems. PLoS ONE 6:e18209. https://doi.org/10.1371/journal.pone.0018209 Sartori L, Bocca G (2022) Minding the gap(s): public perceptions of AI and socio-technical imaginaries. AI Soc. https://doi.org/10.1007/s00146-022-01422-1 Siau K, Wang W (2020) Artificial Intelligence (AI) ethics: ethics of AI and ethical AI. J Database Manag 31:74–87. https://doi.org/10.4018/JDM.2020040105 Smith BK, Gustafson A (2017) Using Wikipedia to predict election outcomes. Public Opin Q 81:714–735. https://doi.org/10.1093/poq/nfx007 Srivastava A, Geethakumari G (2013) Measuring privacy leaks in online social networks. In: 2013 international conference on advances in computing, communications and informatics (ICACCI). IEEE, Mysore, pp 2095–2100 Stahl BC (2021) Ethical issues of AI. In: Artificial intelligence for a better future. Springer, Cham, pp 35–53 Susser D, Roessler B, Nissenbaum H (2019) Online manipulation: hidden influences in a digital world. Georget Law Technol Rev 4:1–46 Tomašev N, Cornebise J, Hutter F et al. (2020) AI for social good: unlocking the opportunity for positive impact. Nat Commun 11:2468. https://doi.org/10.1038/s41467-020-15871-z van Steen M (2010) Graph theory and complex networks Vieira Bernat M (2023) Topical classification of images in Wikipedia: development of topical classification models followed by a study of the visual content of Wikipedia Wei M, Zhou Z (2022) AI ethics issues in real world: evidence from AI incident database Zickuhr K, Rainie L (2011) Wikipedia. past and present Zipf GK (1949) Human behavior and the principle of least effort: an introduction to human eoclogy