Knowledge and attitudes of Spanish citizens towards big data and artificial intelligence
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Abstract
The communication of data science, and specifically of big data and artificial intelligence, is one of the greatest challenges of today's society, because technology is constantly changing and citizens need to understand it to make the best decisions. Traditionally, scientific communication has focused on the study of social attitudes and perceptions towards the most controversial issues, as in the Spanish environment, with the Survey of Social Perception of Science and Technology, prepared by the FECYT every two years. This work reports the results of the first national report focused on public knowledge, understanding and attitudes towards big data and artificial intelligence. A national survey was carried out in January 2020 on a sample of 684 Spanish citizens. It is observed that knowledge about big data and artificial intelligence is moderate, with a lower degree of knowledge and interest among older people and that Artificial Intelligence is better known and arouses greater interest and more favorable attitudes than big data. The way in which the public is informed does not vary with respect to traditional surveys, so the information can reach them through these channels.
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Anderson, Janna, Rainie, Lee, & Luchsinger, Alex (2018). Artificial Intelligence and the Future of Humans. https://www.pewinternet.org/2018/12/10/concerns-about-human-agency-evolution-and-survival/
Ballesteros-Ballesteros, Vladimir, & Gallego-Torres, Adriana Patricia (2022). De la alfabetización científica a la comprensión pública de la ciencia. Trilogía Ciencia Tecnología Sociedad, 14(26), 2145–4426. https://doi.org/10.22430/21457778.1855
Balluerka, Nekane, Gómez, Juana, Hidalgo, María Dolores, Gorostiaga, Arantxa, Espada, Jose Pedro, Padilla García, Jose Luis, & Santed, Miguel Ángel (2020). Las consecuencias psicológicas de la Covid-19 y el confinamiento. https://www.ub.edu/web/ub/ca/menu_eines/noticies/docs/Consecuencias_psicologicas_COVID-19.pdf
Cotino Hueso, Lorenzo (2019). Riesgos e impactos del big data, la inteligencia artificial y la robótica. Enfoques, modelos y principios de la respuesta del derecho. Revista General de Derecho Administrativo, 50. https://fra.europa.eu/en/publication/2018/big-data-discrimination
ESADE (2018). Adopción e impacto del Big Data y Advanced Analytics en España. http://itemsweb.esade.edu/wi/Prensa/InformeESADE_AdopcionImpactoBigDataAdvancedAnalytics.pdf
European Commission (2014). Special Eurobarometer 419: Public perceptions of science, research and innovation (Issue October). European Commission. https://doi.org/10.2777/95599
European Commission (2017a). Special Eurobarometer 460: Attitudes towards the impact of digitisation and automation on daily life. https://doi.org/10.2759/835661
European Commission (2017b). Special Eurobarometer 464a: Europeans’ attitudes towards cyber security Fieldwork (European Commision (ed.); Issue June). https://doi.org/10.2838/009088
European Commission (2020). On Artificial Intelligence - A European approach to excellence and trust. https://doi.org/10.1017/CBO9781107415324.004
Felt, Ulrike (editor) (2007). Optimising public understanding of science and technology.
Fundación Española para la Ciencia y la Tecnología (FECYT). (2018). Percepción Social de la Ciencia y la Tecnología en España. https://www.fecyt.es/sites/default/files/users/user378/percepcion_social_de_la_ciencia_y_la_tecnologia_2018_completo.pdf
Fundación Española para la Ciencia y la Tecnología (FECYT). (2021). Percepción social de la ciencia y la tecnología en España 2020. https://icono.fecyt.es/sites/default/files/filepublicaciones/21/percepcion_social_de_la_ciencia_y_la_tecnologia_2020_informe_completo_0.pdf
Godin, Benoit, & Gingras, Yves (2000). What is scientific and technological culture and how is it measured? A multidimensional model. Public Understanding of Science, 9(1), 43–58. https://doi.org/10.1088/0963-6625/9/1/303
Knight, David (2006). Public understanding of science: A history of communicating scientific ideas. In Public Understanding of Science: A History of Communicating Scientific Ideas. https://doi.org/10.4324/9780203966426
Luz Clara, Bibiana Beatriz & Malbernat, Lucia Rosario (2021). Riesgos, dilemas éticos y buenas prácticas en inteligencia artificial. XXIII Workshop de Investigadores En Ciencias de La Computación (WICC 2021, Chilecito, La Rioja), 155–159. http://sedici.unlp.edu.ar/bitstream/handle/10915/119977/Ponencia.pdf-PDFA.pdf?sequence=1&isAllowed=y
Lytras, Miltiades & Visvizi, Anna (2019). Big data and their social impact: Preliminary study. Sustainability (Switzerland), 11(18). https://doi.org/10.3390/su11185067
Mangione, Antonio (2021). La noticia sobre ciencia: sesgo hacia la comunicación de los resultados sobre los procesos de la investigación científica. SciComm Report, 1(1), 1–13. https://doi.org/10.32457/SCR.V1I1.660
Miller, Jon. D. (2004). Public Understanding of, and Attitudes toward, Scientific Research: What We Know and What We Need to Know. Public Understanding of Science, 13(3), 273–294. https://doi.org/10.1177/0963662504044908
Miller, Jon. D., & Laspra Pérez, Belén. (2018). Los factores que influyen en la cultura científica. In Percepción Social de la Ciencia y la Tecnología 2018 (pp. 37–57). https://www.fecyt.es/sites/default/files/users/user378/cap02_percepcion_social_de_la_ciencia_y_la_tecnologia_2018.pdf
Miller, Steve (2001). Public understanding of science at the crossroads. Public Understanding of Science, 10(1), 115–120. https://doi.org/10.3109/A036859
Moreno Castro, Carolina (2010). La construcción periodística de la ciencia a través de los medios de comunicación social: hacia una taxonomía de la difusión del conocimiento científico. Artefactos, 3(3), 109–130. https://gredos.usal.es/bitstream/handle/10366/120836/La_construccion_periodistica_de_la_cienc.pdf?sequence=1
Paniagua, Esther (2019). Inteligencia Artificial. In Future Trends Forum (Vol. 52, Issue 55). https://www.fundacionbankinter.org/wp-content/uploads/2021/09/Publicacion-PDF-ES-FTF_IA.pdf
Pardiñas Remeseiro, Sofía (2020). Inteligencia Artificial: un estudio de su impacto en la sociedad [Universidade da Coruña]. https://ruc.udc.es/dspace/handle/2183/28479
Rohlman, Andrew. (2019). What Is Data Science? - rondo24.github.io. Personal Page. https://rondo24.github.io/what_is_data_science
Sáez, Daniel & Costa-Soria, Cristóbal (2019). Whitepaper: Análisis de la estrategia Big Data e Inteligencia Artificial en España. http://www.plataformaagua.org/images/Interplataformas/BigData_IA/Interplataformas19_WP_BD_IA.pdf
Salaverría-Aliaga, Ramón (2021). Entender y combatir la desinformación sobre ciencia y salud (Informe GTM1). https://dadun.unav.edu/handle/10171/60223
Summ, Annika & Volpers, Anna María (2016). What’s science? Where’s science? Science journalism in German print media. Public Understanding of Science, 25(7), 775–790. https://doi.org/10.1177/0963662515583419
Tomás, David; Cachero, Cristina; Pujol, Francisco A; Navarro Colorado, Borja; Caruana Ortuño, María Inmaculada; González Rico, Sergio & Sempere Maciá, Natalia (2021). Identificación de sesgos y desinformación sobre la Inteligencia Artificial en el alumnado de Educación Superior. http://rua.ua.es/dspace/handle/10045/121042
Vodafone Institute for Society and Communications. (2016). Big Data: a european survey on the opportunities and risks of Data Analytics (Issue January).
Woodie, Alex (2016). Inside the Panama Papers: How Cloud Analytics Made It All Possible. https://www.datanami.com/2016/04/07/inside-panama-papers-cloud-analytics-made-possible/
