{"query_echo":{"q":"","filters":{"analysis_type":["incident mapping"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'incident mapping' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":3,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=incident+mapping","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"ipie-000012","url":"https://climateinsightsdirectory.org/document/ipie-000012","title":"Generative AI in Electoral Campaigns: Mapping Global Patterns","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"en","date_published":"2025","source_url":"https://www.ipie.info/research/sfp2025-1","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 recorded GenAI incidents across 50 countries during 2024 elections, finding that 80% of these countries experienced such incidents. GenAI was primarily used for synthetic content production, with 69% of cases deemed harmful to electoral integrity. Attribution is a significant challenge, as 46% of sources remained unknown, while political candidates and foreign actors accounted for 25% and 20% of incidents, respectively.","ai_generated":true,"unit":"ipie-000012#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was prevalent in 2024 elections, with 80% of countries holding competitive national elections experiencing GenAI incidents. The highest number of recorded incidents occurred in India and the USA, with 30 incidents each.","ai_generated":true,"unit":"ipie-000012#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is content production, accounting for 90% of recorded incidents. This includes the creation of audio messages, images, videos, and text used to impersonate figures or spread falsehoods, such as a synthetic video in Bangladesh falsely showing candidate Abdullah Nahid Nigar withdrawing from a race.","ai_generated":true,"unit":"ipie-000012#insight-2","date_modified":"2026-10-23"},{"text":"Attribution of GenAI content is difficult, as the source was unknown in 46% of cases. Among identifiable sources, political candidates and parties were responsible for 25% of incidents, and foreign actors for 20%.","ai_generated":true,"unit":"ipie-000012#insight-3","date_modified":"2026-10-23"},{"text":"The majority of GenAI applications in elections were harmful, with 69% of recorded incidents playing a detrimental role. Notably, 100% of GenAI use attributed to foreign actors served harmful purposes, such as coordinated Russian and Chinese AI-generated voice content in the Solomon Islands election.","ai_generated":true,"unit":"ipie-000012#insight-4","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI has been used constructively by some political actors. Approximately 38% of uses by national political parties and candidates were categorized as beneficial, including the use of GenAI-powered chatbots in Japan to engage voters.","ai_generated":true,"unit":"ipie-000012#insight-5","date_modified":"2026-10-23"},{"text":"GenAI use has had severe institutional impacts in some regions; in Romania, coordinated GenAI deployment contributed to the annulment of presidential election results.","ai_generated":true,"unit":"ipie-000012#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["India","United States","Romania","Bangladesh","Taiwan","Namibia","Ireland","Solomon Islands","Japan"],"frame_perspective":[],"analysis_type":["global assessment","incident mapping","policy recommendation"]},{"id":"ipie-000083","url":"https://climateinsightsdirectory.org/document/ipie-000083","title":"L'IA générative dans les campagnes électorales : cartographie des tendances mondiales","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"fr","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0c8b6525d26d8c8c7906_Final%20FR%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The report finds that 80% of countries with competitive national elections in 2024 experienced GenAI-related incidents, with 69% of these incidents having a harmful impact. The majority of GenAI use focused on content creation (90%), and nearly half of the incidents (46%) had unknown sources. While some positive uses for civic engagement were noted, the document emphasizes the risks of disinformation and foreign interference, calling for mandatory disclosure standards and improved detection mechanisms.","ai_generated":true,"unit":"ipie-000083#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was prevalent in the majority of competitive national elections in 2024, with 80% of the 50 analyzed countries experiencing GenAI-related incidents. India and the United States recorded the highest number of incidents, with 30 each.","ai_generated":true,"unit":"ipie-000083#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is the production of synthetic content, including audio, images, videos, and social media posts, which accounted for 90% of recorded incidents. These tools are often integrated into broader influence operations using personalized messaging and targeted distribution.","ai_generated":true,"unit":"ipie-000083#insight-2","date_modified":"2026-10-23"},{"text":"Attributing GenAI content to a specific source is difficult, as 46% of incidents had unknown origins. Among identifiable sources, candidates and political parties were responsible for 25%, foreign actors for 20%, and other groups (such as lobbyists or individuals) for 9%.","ai_generated":true,"unit":"ipie-000083#insight-3","date_modified":"2026-10-23"},{"text":"Most GenAI applications in elections were harmful, with 69% of incidents categorized as having a detrimental role. Notably, 100% of incidents attributed to foreign actors were found to be harmful, such as the coordinated use of AI-generated voice content by Russian and Chinese actors during the Solomon Islands elections.","ai_generated":true,"unit":"ipie-000083#insight-4","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI has been used constructively for civic engagement and accessibility. For example, 38% of uses by national political parties and candidates were beneficial, including the use of AI chatbots in Japan to answer voter questions and encourage turnout.","ai_generated":true,"unit":"ipie-000083#insight-5","date_modified":"2026-10-23"},{"text":"The report highlights specific cases where GenAI significantly impacted electoral outcomes or perceptions, such as in Romania, where coordinated AI manipulation contributed to the annulment of presidential election results, and in Bangladesh, where a deepfake video falsely announced a candidate's withdrawal.","ai_generated":true,"unit":"ipie-000083#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["India","United States","Romania","Bangladesh","Taiwan","Namibia","Ireland","Solomon Islands","Japan"],"frame_perspective":[],"analysis_type":["trend analysis","incident mapping","policy assessment"]},{"id":"ipie-000088","url":"https://climateinsightsdirectory.org/document/ipie-000088","title":"選挙キャンペーンにおける 成AI： 国際的パターンのマッピング 政策立案者向けサマリー 2025.1","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ja","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0cad92d810a0f2eb7909_Final%20JP%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that 80% of countries with competitive national elections in 2024 experienced GenAI-related incidents, with 69% of these being harmful. Most incidents involved content creation, such as deepfakes, and nearly half had unknown sources. While some candidates used GenAI for positive voter outreach, the majority of use—especially by foreign actors—was deceptive or malicious.","ai_generated":true,"unit":"ipie-000088#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI (GenAI) was present in the vast majority of competitive national elections in 2024, with 80% of the 50 countries studied experiencing GenAI-related incidents. The highest number of recorded incidents occurred in India and the United States, with 30 cases each.","ai_generated":true,"unit":"ipie-000088#insight-1","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["India","United States","Bangladesh","Namibia"],"frame_perspective":[],"analysis_type":["empirical analysis","incident mapping","policy review"]}]}