{"id":80063,"date":"2026-04-16T01:07:38","date_gmt":"2026-04-16T05:07:38","guid":{"rendered":"https:\/\/world.edu\/?p=80063"},"modified":"2026-04-16T01:07:38","modified_gmt":"2026-04-16T05:07:38","slug":"in-the-face-of-rampant-ai-is-data-poisoning-a-new-form-of-civil-disobedience","status":"publish","type":"post","link":"https:\/\/world.edu\/in-the-face-of-rampant-ai-is-data-poisoning-a-new-form-of-civil-disobedience\/","title":{"rendered":"In the face of rampant AI, is \u2018data poisoning\u2019 a new form of civil disobedience?"},"content":{"rendered":"

\"\"<\/p>\n

The explosion of generative artificial intelligence (AI) tools has provoked both hopes and anxieties about the potential benefits and harms of this technology. In advanced economies, people are\u00a0almost equally worried and optimistic<\/a>\u00a0about it.<\/p>\n

This is perhaps unsurprising. AI consumes vast amounts of natural resources yet promises to\u00a0save the planet<\/a>. It may\u00a0improve human efficiency and productivity<\/a>, while putting millions\u00a0out of work<\/a>.<\/p>\n

For many white-collar workers, AI use now\u00a0seems non-optional<\/a>. The messaging is clear \u2013\u00a0get on board or be left behind<\/a>.<\/p>\n

Amid this uncertainty and rapid technological uptake, concerned citizens have made efforts to resist AI. One form of AI resistance, aimed at sabotaging the functionality of AI large language models, is data poisoning. But how accessible is it to the everyday person? And what is at stake in its use?<\/p>\n

What is AI resistance?<\/strong><\/h4>\n

Acts of AI resistance range from\u00a0social sanctions<\/a>\u00a0and\u00a0boycotts<\/a>, to\u00a0strikes<\/a>,\u00a0protests<\/a>,\u00a0public outcry<\/a>\u00a0and\u00a0lawsuits<\/a>.\u00a0Driving these acts<\/a>\u00a0are perceived threats to jobs, ethics, safety, democracy and sovereignty, and the environment.<\/p>\n

AI is also described as an existential\u00a0risk to creative industries<\/a>, including\u00a0music<\/a>,\u00a0fiction<\/a>\u00a0and\u00a0film<\/a>. In the United Kingdom, generative AI has been\u00a0characterised<\/a>\u00a0as an \u201cindustrial scale theft\u201d that threatens a \u00a3124.6 billion (A$237bn) creative sector and more than 2.4 million jobs.<\/p>\n

People have long used civil disobedience to address social injustices. Famously,\u00a0Rosa Parks\u2019<\/a>\u00a0refusal to sit at the back of a bus in Alabama led to a\u00a013-month bus boycott<\/a>\u00a0by tens of thousands of Black residents. It only ended when racial segregation on public transport was deemed unconstitutional in the United States.<\/p>\n

Acts of sabotage<\/a>\u00a0have also long been central to collective action against injustice. In fights for labour rights, workers have employed\u00a0diverse tactics<\/a>\u00a0to reduce efficiency and productivity. This has ranged from hotel workers putting salt in sugar bowls to farm workers breaking machinery.<\/p>\n

Data poisoning can be viewed as a modern version of these historic actions.<\/p>\n

How does data poisoning work?<\/strong><\/h4>\n

Data poisoning<\/a>\u00a0means deliberately inserting misleading, biased, or nonsensical content into the data AI models learn from, to make their outputs worse. Only\u00a0250 poisoned documents<\/a>\u00a0in a dataset could compromise outputs across AI models of any size.<\/p>\n

There are various ways to poison data. Some require highly technical skills, others are accessible to anyone with an internet connection \u2013 if their text or images are used as training data.<\/p>\n

Researchers have developed several data poisoning tools that exploit the vulnerabilities of AI models.\u00a0Glaze and Nightshade<\/a>\u00a0enable artists to make poisoned visual images that can\u2019t be used as training data. The tool\u00a0CoProtector<\/a>\u00a0defends against the exploitation of open source code repositories like Github. Monash University and the Australian Federal Police have created\u00a0Silverer<\/a>, enabling social media users to doctor personal images to prevent them from being used in deepfakes.<\/p>\n

But you don\u2019t need a tool or advanced skills to affect AI. Simply\u00a0creating websites<\/a>\u00a0with factitious information, making\u00a0jokes in Reddit<\/a>,\u00a0feeding models<\/a>\u00a0their own outputs, or\u00a0editing Wikipedia<\/a>\u00a0can poison data.<\/p>\n

Data poisoning is commonly presented as a\u00a0dangerous<\/a>\u00a0act perpetrated by \u201ccyber criminals<\/a>\u201d or \u201cmalicious actors<\/a>\u201d. But what if it\u2019s used to protect human rights?<\/p>\n

Is data poisoning legal? Is it ethical?<\/strong><\/h4>\n

Legal obligations<\/a>\u00a0related to data poisoning are often directed to AI developers and organisations. The\u00a0EU Artificial Intelligence Act<\/a>\u00a0requires that appropriate measures are adopted to prevent and detect data poisoning.<\/p>\n

The legal status of AI data poisoning by individual users is\u00a0less clear<\/a>. Criminal penalties may apply under\u00a0US<\/a>\u00a0or\u00a0UK<\/a>\u00a0computer fraud and misuse laws. Interference with an AI model would also likely breach the terms of service of AI companies.<\/p>\n

If AI data poisoning is unlawful, questions could still be asked about its\u00a0ethical status<\/a>. Philosophers have long recognised that\u00a0civil disobedience<\/a>\u00a0can be justifiable in circumstances where legally sanctioned practices produce serious injustice.<\/p>\n

If AI companies are operating with state approval in ways that impact citizens\u2019 rights to\u00a0privacy<\/a>,\u00a0copyright<\/a>,\u00a0safe and secure work<\/a>, quality\u00a0education<\/a>,\u00a0social<\/a>\u00a0and\u00a0sexual safety<\/a>, data poisoning may constitute ethical civil disobedience.<\/p>\n

For philosopher\u00a0John Rawls<\/a>, \u201c[civil disobedience] is one of the stabilising devices of a constitutional system, although by definition an illegal one\u201d.<\/p>\n

If the intention is to prevent\u00a0mass unemployment<\/a>, preserve the\u00a0integrity of elections<\/a>, and protect against social harms (suicide<\/a>,\u00a0child abuse<\/a>, increased\u00a0human isolation<\/a>, loss of\u00a0human creativity<\/a>\u00a0and\u00a0environmental degradation<\/a>), data poisoning could align with the principles of justice that underpin democratic social institutions.<\/p>\n

A significant problem with data poisoning is that even if models become compromised \u2013 and outputs grow inconsistent, misleading, or nonsensical \u2013 users\u00a0overly trust AI systems<\/a>. Data poisoning then could contribute to harms it seeks to resist, amplifying the inaccuracy of systems humans are increasingly relying on, irrespective of their quality and effects.<\/p>\n

Data poisoning is not simply an immoral cyber crime. It can be an ethically complex strategy to address social injustices. AI development needs to be of collective benefit and aligned with public values and interests. If AI company employees\u00a0are asking<\/a>\u00a0\u201cAre we the baddies?<\/a>\u201d, history may prove that in some cases data poisoners are on the side of good.<\/p>\n

Author Bios:<\/strong> Claire Tanner is a Senior Lecturer in Sociology and Gender Studies, Mor Vered is a Senior Lecturer, Data Science & AI and Sam Cadman is a Research Fellow, Criminology all at Monash University<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

The explosion of generative artificial intelligence (AI) tools has provoked both hopes and anxieties about the potential benefits and harms of this technology. In advanced economies, people are\u00a0almost equally worried and optimistic\u00a0about it. This is perhaps unsurprising. AI consumes vast amounts of natural resources yet promises to\u00a0save the planet. It may\u00a0improve human efficiency and productivity, […]\n… learn more→<\/a><\/p>","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[434804],"tags":[435675],"coauthors":[11733],"class_list":["post-80063","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","tag-data-poisoning"],"acf":[],"yoast_head":"\nIn the face of rampant AI, is \u2018data poisoning\u2019 a new form of civil disobedience? - World leading higher education information and services<\/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:\/\/world.edu\/in-the-face-of-rampant-ai-is-data-poisoning-a-new-form-of-civil-disobedience\/\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_US\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"In the face of rampant AI, is \u2018data poisoning\u2019 a new form of civil disobedience? - World leading higher education information and services\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"The explosion of generative artificial intelligence (AI) tools has provoked both hopes and anxieties about the potential benefits and harms of this technology. 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