{"id":9056,"date":"2024-10-08T20:28:59","date_gmt":"2024-10-08T19:28:59","guid":{"rendered":"https:\/\/icertpublication.com\/?page_id=9056"},"modified":"2024-10-11T09:24:21","modified_gmt":"2024-10-11T08:24:21","slug":"misuse-of-artificial-intelligence-in-elections","status":"publish","type":"page","link":"https:\/\/icertpublication.com\/index.php\/shodh-sari-2\/sodh-sari-vol-3-issue-4\/misuse-of-artificial-intelligence-in-elections\/","title":{"rendered":"Misuse Of Artificial Intelligence in Elections"},"content":{"rendered":"\t\t
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Misuse Of Artificial Intelligence in Elections<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Jayant<\/span><\/p>

Research Scholar, Baba Mastnath University, Rohtak<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Abstract\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Artificial Intelligence (AI) has emerged as a double-edged sword in the realm of electoral processes, promising efficiency and accuracy while simultaneously casting a shadow on the integrity and fairness of democratic practices. This abstract delves into the intricate web of challenges posed by the misuse of AI in elections, shedding light on its potential for manipulation, polarization, and disenfranchisement. The proliferation of AI-driven algorithms in voter targeting and micro-targeted advertising has transformed the landscape of political campaigning, enabling unprecedented levels of personalized messaging. Social media platforms, fueled by AI algorithms, have become breeding grounds for echo chambers and filter bubbles, exacerbating societal polarization and undermining the foundation of informed democratic discourse. Moreover, the deployment of AI-powered predictive analytics for voter suppression tactics has further eroded the principles of free and fair elections. By leveraging sophisticated data analytics techniques, political actors can systematically identify and disenfranchise specific demographics, thereby subverting the fundamental right to vote. This nefarious application of AI not only undermines the legitimacy of electoral outcomes but also perpetuates systemic inequalities and undermines the democratic fabric of society. Furthermore, the opacity and lack of accountability surrounding AI algorithms used in electoral processes raise profound questions regarding transparency and oversight. The black-box nature of AI systems hampers meaningful scrutiny, making it challenging to detect and address instances of algorithmic bias, discrimination, and manipulation. Without robust regulatory frameworks and mechanisms for algorithmic accountability, the unchecked proliferation of AI in elections poses a significant threat to the principles of democratic governance and electoral integrity. Additionally, the advent of AI-generated deepfakes has introduced a new dimension of vulnerability to electoral integrity, enabling the fabrication of realistic yet entirely falsified audio and video content. In an era where perception often shapes reality, the dissemination of AI-generated deepfakes has the potential to <\/span>undermine public trust in electoral processes, sow discord, and destabilize democratic institutions<\/span>.<\/span><\/p>\n

Keywords<\/span>–<\/span>Artificial Intelligence, Elections, Voter Suppression, Algorithmic Bias, Democratic Process<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Impact Statement\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The article “Misuse of AI in Elections” explores the profound implications of deploying artificial intelligence technologies in the electoral process, highlighting the potential threats to democratic integrity and public trust. The misuse of AI can manifest in various forms, including the dissemination of misinformation, voter manipulation, surveillance, and undermining the credibility of election outcomes. These risks underscore the urgent need for comprehensive regulatory frameworks and ethical guidelines to safeguard democratic processes from the adverse effects of AI. By examining case studies and current practices, the article illustrates how AI-driven technologies, such as deepfake videos, automated bots, and predictive analytics, can be weaponized to influence voter behaviour and election results. It delves into the mechanics of these technologies, explaining their capabilities and the specific ways they can disrupt elections. The article also highlights the global nature of this challenge, with examples from different regions to underscore the widespread risk. The impact of this article lies in its ability to inform policymakers, technologists, and the general public about the critical vulnerabilities that AI introduces into the electoral process. It serves as a call to action for the development of robust defences against AI misuse, including the creation of international standards and cooperation among nations to address these challenges collectively. Furthermore, the article aims to foster a dialogue on the ethical use of AI, advocating for transparency, accountability, and the protection of democratic values. Ultimately, the article “Misuse of AI in Elections” contributes to the broader understanding of how emerging technologies can shape political landscapes. It emphasizes the dual-edged nature of AI\u2014its potential to enhance electoral processes through efficiency and accuracy, contrasted with its capacity to undermine democracy if left unchecked. By shedding light on these critical issues, the article seeks to inspire proactive measures to ensure that AI serves as a tool for strengthening, rather than compromising, democratic institutions.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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About The Author<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Jayant is a research scholar from BMU ROHTAK with keen interest inthe feilds of law, Science and technology with this article he attempts to make complex topics accessible and engaging for a wide audience.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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References<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\u00a0<\/p>

  1. Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. In Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency (pp. 149\u2013159).<\/span><\/p><\/li>

  2. Brundage, M., Avin, S., Clark, J. et al. (2018). The malicious use of artificial intelligence: Forecasting, prevention, and mitigation.<\/span><\/p><\/li>

  3. Chessen, M. (2017). Artificial intelligence and the future of politics. Future of Life Institute.<\/span><\/p><\/li>

  4. Feldstein, S. (2019). The global expansion of AI surveillance. Carnegie Endowment for International Peace.<\/span><\/p><\/li>

  5. Howard, P. N., Ganesh, B., & Kollanyi, B. (2018). The junk news aggregator: Examining the supply of English-language news and information about elections and politics. Computational Propaganda Research Project, Oxford Internet Institute.<\/span><\/p><\/li>

  6. Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., Schudson, M., Sloman, S. A., Sunstein, C. R., Thorson, E. A., Watts, D. J., & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094\u20131096. <\/span>https:\/\/doi.org\/10.1126\/science.aao2998<\/span><\/a><\/p><\/li>

  7. Mar\u00e9chal, N. (2017). Bots, elections, and the future of digital politics. Internet Policy Review, 6(4).<\/span><\/p><\/li>

  8. Woolley, S. C., & Howard, P. N. (2017). \u2018Computational Propaganda Worldwide: Executive Summary.\u2019 Working Paper 2017.11. Oxford Internet Institute.<\/span><\/p><\/li>

  9. Kumar, P. (2024). The Role of Ethics and Moral Values in Teaching: A Comprehensive Examination. <\/span>Shodh Sari-An International Multidisciplinary Journal<\/span>, <\/span>03<\/span>(01), 99\u2013112. https:\/\/doi.org\/10.59231\/sari7659<\/span><\/p><\/li>

  10. Avurakoghene, O. P., & Oredein, A. O. (2023). Educational leadership and artificial intelligence for sustainable development. <\/span>Shodh Sari-An International Multidisciplinary Journal<\/span>, <\/span>02<\/span>(03), 211\u2013223. https:\/\/doi.org\/10.59231\/sari7600<\/span><\/p><\/li>

  11. Kumar, S. (2023). Artificial Intelligence Learning and Creativity. <\/span>Eduphoria<\/span>, <\/span>01<\/span>(01), 13\u201314. https:\/\/doi.org\/10.59231\/eduphoria\/230402<\/span><\/p><\/li>

  12. Kumar, S., & Simran. (2024). Equity in K-12 STEAM education. <\/span>Eduphoria<\/span>, <\/span>02<\/span>(03), 49\u201355. https:\/\/doi.org\/10.59231\/eduphoria\/230412<\/span><\/p><\/li>

  13. Kumar, S. (2024). Patience Catalyst for Personal Transformation. <\/span>Eduphoria, 02<\/span>(02), 77\u2013 80. <\/span>https:\/\/doi.org\/10.59231\/eduphoria\/230408<\/span><\/a><\/p><\/li>

  14. Kumar, S. (2024). Mental Detox: positive self talks. <\/span>Eduphoria, 02<\/span>(01), 05\u201307. <\/span>https:\/\/doi.org\/10.59231\/eduphoria\/23040<\/span><\/a><\/p><\/li>

  15. Kumar, S. (2024). The Relationship Between Cognitive Behavior therapy (CBT) and Depression Treatment Outcomes: A Review of literature. <\/span>Eduphoria<\/span>, <\/span>02<\/span>(03), 20\u201326. https:\/\/doi.org\/10.59231\/EDUPHORIA\/230410<\/span><\/p><\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Misuse Of Artificial Intelligence in Elections Jayant Research Scholar, Baba Mastnath University, Rohtak Abstract Artificial Intelligence (AI) has emerged as a double-edged sword in the realm of electoral processes, promising efficiency and accuracy while simultaneously casting a shadow on the integrity and fairness of democratic practices. This abstract delves into the intricate web of challenges […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":8763,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-9056","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/9056","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/comments?post=9056"}],"version-history":[{"count":7,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/9056\/revisions"}],"predecessor-version":[{"id":9189,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/9056\/revisions\/9189"}],"up":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/8763"}],"wp:attachment":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/media?parent=9056"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}