{"id":16,"date":"2021-10-14T16:11:38","date_gmt":"2021-10-14T20:11:38","guid":{"rendered":"https:\/\/sites.nd.edu\/data-feminism\/?page_id=16"},"modified":"2021-12-01T23:04:17","modified_gmt":"2021-12-02T04:04:17","slug":"challenge-power","status":"publish","type":"page","link":"https:\/\/sites.nd.edu\/data-feminism\/challenge-power\/","title":{"rendered":"Challenge Power"},"content":{"rendered":"\n<h2 class=\"has-pale-pink-color has-text-color wp-block-heading\">&#8220;Challenging power requires mobilizing data science to push back against existing and unequal power structures and to work toward more just and equitable futures.&#8221;<\/h2>\n\n\n\n<h2 class=\"has-vivid-purple-color has-text-color wp-block-heading\">Key Terms<\/h2>\n\n\n\n<ol class=\"wp-block-list\"><li><strong><span style=\"text-decoration: underline\">Auditing Algorithms<\/span><\/strong> : An analysis method used to show how the harms and benefits of automated systems are differentially distributed.<\/li><li><strong><span style=\"text-decoration: underline\">Deficit Narratives<\/span><\/strong> : Narratives that reduce a group or culture to its problems, rather than portraying it with the strengths, creativity, and agency that people from those cultures possess. Proof and data  can unwittingly contribute to deficit narratives, whether sexist or racist or ableist or otherwise oppressive.<\/li><li><strong><span style=\"text-decoration: underline\">Imagined Objectivity<\/span><\/strong> : The phenomenon that occurs when people imagine (wrongly) that datasets and algorithms are less partial and less discriminatory than people and thus more &#8220;objective.&#8221;<\/li><li><strong><span style=\"text-decoration: underline\">Data Ethics<\/span><\/strong> : A growing interdisciplinary effort &#8212; both critical and computational &#8212; to ensure that the ethical issues brought about by our increasing reliance on data-driven systems are identified and addressed.<\/li><li><strong><span style=\"text-decoration: underline\">Equity<\/span><\/strong> : A world where everyone is treated equitably, not equally, means taking into account present power differentials and distributing (or redistributing) resources accordingly. <\/li><li><strong><span style=\"text-decoration: underline\">New Racism<\/span><\/strong> : The belief that racism is due to individual bad actors, rather than structures or systems.<\/li><li><strong><span style=\"text-decoration: underline\">Co-liberation<\/span><\/strong> : It requires a commitment to and a belief in mutual benefit, from members of both dominant groups and minoritized groups. <\/li><li><strong><span style=\"text-decoration: underline\">Reflexivity<\/span><\/strong> : The ability to reflect on and take responsibility for one&#8217;s own position within the multiple, intersecting dimensions of the matrix of domination.<\/li><\/ol>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"https:\/\/sites.nd.edu\/data-feminism\/examine-power\/\">Previous Principle<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"https:\/\/sites.nd.edu\/data-feminism\/elevate-emotion-and-embodiment\/\">Next Principle<\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;Challenging power requires mobilizing data science to push back against existing and unequal power structures and to work toward more just and equitable futures.&#8221; Key Terms Auditing Algorithms : An analysis method used to show how the harms and benefits of automated systems are differentially distributed. Deficit Narratives : Narratives that reduce a group or &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/sites.nd.edu\/data-feminism\/challenge-power\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Challenge Power&#8221;<\/span><\/a><\/p>\n","protected":false},"author":4082,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-16","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/pages\/16","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/users\/4082"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/comments?post=16"}],"version-history":[{"count":6,"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/pages\/16\/revisions"}],"predecessor-version":[{"id":101,"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/pages\/16\/revisions\/101"}],"wp:attachment":[{"href":"https:\/\/sites.nd.edu\/data-feminism\/wp-json\/wp\/v2\/media?parent=16"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}