The Impact Of Generative Ai In A Global Election Year Brookings
The Brookings Institution, Washington District of Columbia Melanie W. Sisson, Colin Kahl, Sun Chenghao, Xiao Qian Martin Neil Baily, Sophia Hart, Melanie W. Sisson This article, written by Valerie Wirtschafter and published in 2024 on January 30th, discusses the potential threat of AI on democratic elections.
AI would amplify the potential harm to the democratic process. Specifically, AI can construct realistic “deep fakes” that can spread misinformation to voters using the internet. This paper offers examples of how this has occurred in the past, drawing on elections from Slovakia and Argentina. In addition, Wirtschafter offers recommendations on how to protect information during the election year in the US – development, distribution, and detection as her main points. Development refers to the policy that monitors and or restricts the development of certain types of AI that interfere with elections – AI-generated images of politicians running for office, for example. If the technology is not built, it can not proliferate.
Secondly, distribution refers to addressing and limiting how harmful generated content is spread. This area focuses on closing loopholes in manipulated media processes and increasing collaboration to better identify when harmful generated content is being spread to the public. Lastly, detection is the most vast area for information protection, it covers widespread education on misinformation, increased research on AI detection technology, and greater access to social media data. Overall, Wirtschafter’s article offers a condensed overview of the potential threat of AI on democratic processes and elections and discusses potential solutions to mitigate said risks. Massachusetts Institute of Technology77 Massachusetts Avenue, Cambridge, MA, USA © 2022 Massachusetts Institute of Technology.
All rights reserved.Last revised on July 29, 2022. to receive quote please email us at abahaijoub@aol.com Centre for Euro-Mediterranean and African StudiesCentre des Etudes Euro-Méditerranéennes et Africaines The impact of generative AI in a global election year By Valerie Wirtschafter, Brookings, January 30, 2024 The influence of the online ecosystem in shaping democratic discourse is well-documented, with the expanded reach of generative artificial intelligence (AI) representing a novel challenge in a historic election year.
Generative AI enables the creation of realistic images, videos, audio, or text based on user-provided prompts. Given the potential exploitation of this technology, particularly in the context of elections, it has garnered significant attention. Daniel S. Schiff, Kaylyn Jackson Schiff, Natália Bueno Melanie W. Sisson, Colin Kahl, Sun Chenghao, Xiao Qian
Wednesday, February 7, 2024, 2:30 – 3:30 p.m. ESTOnline only: https://www.brookings.edu/events/generative-ai-elections 2024 will be a historic year for elections. Democracies comprising 41% of the world’s population and 42% of its GDP will cast their votes around the globe. Yet recent shifts in the information space threaten to turbocharge the spread of false content at the same time major social media platforms are scaling back investments in content moderation. The widespread proliferation of generative AI systems has drastically reduced barriers to creating and disseminating wholly fabricated content or coordinating cyberattacks against political campaigns and electoral infrastructure.
Many are concerned that a wave of AI-generated content could derail democratic processes globally. However, it remains to be seen whether these fears will be borne out in practice or how this technology will impact the information space over the coming year. On February 7, the Artificial Intelligence and Emerging Technology Initiative at Brookings will host an expert panel moderated by Valerie Wirtschafter to assess the effects of generative AI and other novel online threats to... Viewers can submit questions via email to events@brookings.edu or on Twitter/X using #AIandElections. The Brookings Institution, 1775 Massachusetts Ave NW, Washington, DC 20036 Melanie W.
Sisson, Colin Kahl, Sun Chenghao, Xiao Qian Reports from other organizations on the risks that advancements in AI pose to free and fair elections, including some proposed mitigations. This report gives a high level overview of the impacts AI good have on US democracy. – Norman Eisen, Nicol Turner Lee, Colby Galliher, and Jonathan Katz This report describes the risk of AI-backed voter suppression, and details some potential solutions. This report offers specific ways in which election officials can prepare for the impacts of AI.
Norman Eisen, Renée Rippberger, Jonathan Katz Renée Rippberger, Rachel Beatty Riedl, Jonathan Katz, Paul Friesen, Noam Lupu, Marie Miller, Caroline Macneill, Randi Wright, Alexandra Rumford My latest for The Brookings Institution explores the reach of generative AI online thus far (albeit, with what data I could collect!), where it has already uniquely impacted elections, where it could amplify ongoing... Sign up to attend here: https://lnkd.in/eh9-Snih This is extremely interesting Valerie!👏🏼
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The Brookings Institution, Washington District Of Columbia Melanie W. Sisson,
The Brookings Institution, Washington District of Columbia Melanie W. Sisson, Colin Kahl, Sun Chenghao, Xiao Qian Martin Neil Baily, Sophia Hart, Melanie W. Sisson This article, written by Valerie Wirtschafter and published in 2024 on January 30th, discusses the potential threat of AI on democratic elections.
AI Would Amplify The Potential Harm To The Democratic Process.
AI would amplify the potential harm to the democratic process. Specifically, AI can construct realistic “deep fakes” that can spread misinformation to voters using the internet. This paper offers examples of how this has occurred in the past, drawing on elections from Slovakia and Argentina. In addition, Wirtschafter offers recommendations on how to protect information during the election year in ...
Secondly, Distribution Refers To Addressing And Limiting How Harmful Generated
Secondly, distribution refers to addressing and limiting how harmful generated content is spread. This area focuses on closing loopholes in manipulated media processes and increasing collaboration to better identify when harmful generated content is being spread to the public. Lastly, detection is the most vast area for information protection, it covers widespread education on misinformation, incr...
All Rights Reserved.Last Revised On July 29, 2022. To Receive
All rights reserved.Last revised on July 29, 2022. to receive quote please email us at abahaijoub@aol.com Centre for Euro-Mediterranean and African StudiesCentre des Etudes Euro-Méditerranéennes et Africaines The impact of generative AI in a global election year By Valerie Wirtschafter, Brookings, January 30, 2024 The influence of the online ecosystem in shaping democratic discourse is well-docume...
Generative AI Enables The Creation Of Realistic Images, Videos, Audio,
Generative AI enables the creation of realistic images, videos, audio, or text based on user-provided prompts. Given the potential exploitation of this technology, particularly in the context of elections, it has garnered significant attention. Daniel S. Schiff, Kaylyn Jackson Schiff, Natália Bueno Melanie W. Sisson, Colin Kahl, Sun Chenghao, Xiao Qian