{"id":40,"date":"2024-10-22T13:17:00","date_gmt":"2024-10-22T12:17:00","guid":{"rendered":"https:\/\/lifeofdata.org\/site\/algobias-toolkit\/?page_id=40"},"modified":"2025-10-09T12:05:08","modified_gmt":"2025-10-09T11:05:08","slug":"public-opinion","status":"publish","type":"page","link":"https:\/\/lifeofdata.org\/site\/algobias-toolkit\/public-opinion\/","title":{"rendered":"Public opinion and engaging with effected stakeholders"},"content":{"rendered":"\n<p class=\"\">One of the core components of algorithmic bias mitigation is engaging with members of the public who might be affected by your algorithmic technologies. This can be particularly challenging, as research has shown the general public have wide ranging views about algorithmic technologies and how they expect their data to be used (Ditchfield et al., 2021). Some questions to consider when engaging with the public include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li class=\"\">Will the public be given a meaningful way of contributing towards the project? How will their views be taken into account? Can they shape core decisions already made on the project?<\/li>\n\n\n\n<li class=\"\">Will the public be informed of how their views are used? Will they be updated on the progress of the project?<\/li>\n\n\n\n<li class=\"\">What are the barriers to engaging with the public? How can you handle issues such as sensitive information?<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Further resources<\/h3>\n\n\n\n<p class=\"\">Bates, J., Kennedy, H., Medina Perea, I., Oman, S., &amp; Pinney, L. (2024). Socially meaningful transparency in data-based systems: Reflections and proposals from practice. <em>Journal of Documentation, 80<\/em>(1), 54-72. https:\/\/doi.org\/10.1108\/JD-01-2023-0006<\/p>\n\n\n\n<p class=\"\">You can find the reports from the <a href=\"https:\/\/livingwithdata.org\/resources\/\">Living with Data project<\/a>, the <em>Living With Data<\/em> research projects are all concerned about living with data \u2013 that is, how datafication is affecting the lives of ordinary people, the relationships between data and agency, and between data and inequalities, and whether \u2018good\u2019 data uses are possible.<\/p>\n\n\n\n<p class=\"\">Patel, R. (2025)\u00a0<em>A Framework and Self<\/em>\u00a0<em>Assessment Workbook for Including Public Voices in AI<\/em>. Elgon Social Research and ESRC Digital Good Network. Available at: \u00a0<a href=\"https:\/\/elgon.social\/framework-and-workbook\" target=\"_blank\" rel=\"noreferrer noopener\">elgon.social\/framework-and-workbook<\/a><\/p>\n\n\n\n<p class=\"\">Kaun, A., Larsson, A.O. and Masso, A. (2023) \u2018Automating public administration: citizens\u2019 attitudes towards automated decision-making across Estonia, Sweden, and Germany\u2019, <em>Information, Communication &amp; Society<\/em>, 0(0), pp. 1\u201319. Available at: https:\/\/doi.org\/10.1080\/1369118X.2023.2205493.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>One of the core components of algorithmic bias mitigation is engaging with members of the public who might be affected by your algorithmic technologies. This can be particularly challenging, as [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"nf_dc_page":"","footnotes":""},"class_list":["post-40","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Public opinion and engaging with effected stakeholders - AlgoBias ToolKit<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lifeofdata.org\/site\/algobias-toolkit\/public-opinion\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Public opinion and engaging with effected stakeholders - AlgoBias ToolKit\" \/>\n<meta property=\"og:description\" content=\"One of the core components of algorithmic bias mitigation is engaging with members of the public who might be affected by your algorithmic technologies. 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