{"query_echo":{"q":"","filters":{"geography":["Taiwan"]},"warnings":[]},"total":{"value":212,"relation":"eq"},"page":3,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Taiwan&page=3","next":"https://climateinsightsdirectory.org/api/v1/search?geography=Taiwan&page=4","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":"cmw-000778","url":"https://climateinsightsdirectory.org/document/cmw-000778","title":"Corporate Climate Responsibility","publisher":{"name":"Carbon Market Watch","organization":"carbon-market-watch"},"document_type":"guide","language":"en","date_published":"2025-06","source_url":"https://carbonmarketwatch.org/wp-content/uploads/2025/06/NewClimate_CCRM2025_Methodology.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Corporate Climate Responsibility Monitor (v5.0) establishes a framework to distinguish genuine corporate climate leadership from greenwashing. It assesses companies across four pillars: comprehensive GHG emissions disclosure (Scopes 1, 2, and 3), the alignment of emission reduction targets with 1.5°C pathways, the implementation of sector-specific transitions, and the scaling of durable carbon dioxide removals (CDR). The guidance emphasizes that net-zero claims are misleading without deep absolute reductions and argues against the use of standalone Renewable Energy Certificates (RECs) and traditional offsetting in favor of 'climate contributions' and millennial-scale durable CDR.","ai_generated":true,"unit":"cmw-000778#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"High-integrity emissions disclosure requires annual reporting of full greenhouse gas emissions, broken down by specific sources, with historical data for at least the last five years and the target base year.","ai_generated":true,"unit":"cmw-000778#insight-1","date_modified":"2026-10-23"},{"text":"Credible short-term emission reduction targets must be set in maximum five-year intervals and align with 1.5°C-compatible benchmarks to ensure immediate action and accountability.","ai_generated":true,"unit":"cmw-000778#insight-2","date_modified":"2026-10-23"},{"text":"Net-zero targets are considered misleading if they do not commit to deep absolute emission reductions—at least 90% below 2019 levels for most sectors (or 72% for agriculture)—independent of offsetting and carbon dioxide removals.","ai_generated":true,"unit":"cmw-000778#insight-3","date_modified":"2026-10-23"},{"text":"The guidance identifies 'climate contributions' (Beyond Value Chain Mitigation) as a superior alternative to offsetting, where companies provide financial support for climate action without claiming to neutralise their own emissions.","ai_generated":true,"unit":"cmw-000778#insight-4","date_modified":"2026-10-23"},{"text":"The document recommends an internal carbon fee of at least USD 100 per tCO2e for climate contributions, tending toward the social cost of carbon to create effective incentives for internal reductions.","ai_generated":true,"unit":"cmw-000778#insight-5","date_modified":"2026-10-23"},{"text":"Traditional offsetting is deemed fundamentally flawed due to risks of distracting from immediate reductions, double counting, and the lack of 'high-hanging fruit' projects that are truly additional in the Paris Agreement era.","ai_generated":true,"unit":"cmw-000778#insight-6","date_modified":"2026-10-23"},{"text":"Only 'durable CDR'—defined as storage exceeding 1,000 years—is considered suitable for neutralising fossil fuel emissions, while land-based sequestration is viewed as non-durable and insufficient for this purpose.","ai_generated":true,"unit":"cmw-000778#insight-7","date_modified":"2026-10-23"},{"text":"Standalone Renewable Energy Certificates (RECs) are classified as having a low likelihood of contributing to additional renewable capacity and are not considered a suitable approach for reducing electricity-related emissions.","ai_generated":true,"unit":"cmw-000778#insight-8","date_modified":"2026-10-23"},{"text":"Hourly matching (24/7 matching) of electricity consumption with renewable generation is promoted as the high-integrity standard for Scope 2 reporting to drive real-time displacement of fossil fuels.","ai_generated":true,"unit":"cmw-000778#insight-9","date_modified":"2026-10-23"},{"text":"The use of bioenergy is cautioned against unless it is a temporary solution in sectors with limited electrification options and is proven to have no negative sustainability implications for food security, biodiversity, or water resources.","ai_generated":true,"unit":"cmw-000778#insight-10","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","Scope 2","Scope 3","carbon neutrality","carbon dioxide removal","carbon offset","power purchase agreement","bioenergy","carbon accounting","greenwashing"],"geography_discussed":["Germany","United States","Canada","European Union","South Korea","Taiwan","Vietnam","People's Republic of China","Indonesia","Bangladesh"],"frame_perspective":[],"analysis_type":["methodology","guidance","assessment criteria"]},{"id":"prio-001675","url":"https://climateinsightsdirectory.org/document/prio-001675","title":"Unlocking Nigeria’s future demographic dividend through its youth","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"policy brief","language":"en","date_published":"2025-06","source_url":"https://cdn.cloud.prio.org/files/2c058512-f78e-4286-994a-ecd91a0fbcb8/PRIO Policy Brief 6 - 2025.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"Nigeria possesses a significant 'youth bulge', with approximately 70% of its population under 30 and a median age of 18.1 years. While this presents an opportunity for a 'demographic dividend'—accelerated economic growth driven by a large working-age population—the document warns that failure to invest in human capital and economic reform could lead to a 'demographic disaster'. Key obstacles include high youth unemployment (estimated at 53.4% for ages 15–24 in 2020), a mono-economy dependent on crude oil, and an education system that fails to align curricula with market needs. The brief argues that unlocking this potential requires a multi-pronged approach focusing on human capital, economic opportunity, gender equality, and effective governance.","ai_generated":true,"unit":"prio-001675#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Nigeria has a distinct 'youth bulge', with an estimated population exceeding 230 million in 2025, of which approximately 70% are under the age of 30 and the median age is 18.1 years.","ai_generated":true,"unit":"prio-001675#insight-1","date_modified":"2026-10-23"},{"text":"The country faces a severe youth unemployment crisis caused by a mismatch between the formal economy's capacity and labour market demands. In 2020, unemployment was estimated at 53.4% for youth aged 15–24 and 37.2% for those aged 25–34.","ai_generated":true,"unit":"prio-001675#insight-2","date_modified":"2026-10-23"},{"text":"Nigeria's economy is characterized as a 'mono-economy' with a heavy reliance on crude oil exports since the 1970s, which, combined with public debt, has increased social inequality and poverty.","ai_generated":true,"unit":"prio-001675#insight-3","date_modified":"2026-10-23"},{"text":"The education system suffers from low completion rates and a lack of alignment with market needs. In 2020, secondary education completion was 42% for boys and 36% for girls.","ai_generated":true,"unit":"prio-001675#insight-4","date_modified":"2026-10-23"},{"text":"Gender inequality, particularly in northern regions, acts as a barrier to development through limited female empowerment, higher fertility rates, and systemic obstacles to education and labour market participation.","ai_generated":true,"unit":"prio-001675#insight-5","date_modified":"2026-10-23"},{"text":"While Nigeria has a National Population Policy (2006/2008) and National Youth Policies (NYPs), implementation gaps and a lack of tangible improvements in socioeconomic conditions have undermined their effectiveness and can erode trust in government.","ai_generated":true,"unit":"prio-001675#insight-6","date_modified":"2026-10-23"},{"text":"Rapid urbanization is occurring, with an estimated 55% of Nigerians living in urban areas in 2025, projected to rise to 66.9% by 2050, placing pressure on public services like housing, water, and healthcare.","ai_generated":true,"unit":"prio-001675#insight-7","date_modified":"2026-10-23"}],"climate_tags":["gender equality","urbanization","economic diversity"],"geography_discussed":["sub-Saharan Africa","South Korea","Singapore","Taiwan"],"frame_perspective":[],"analysis_type":["policy analysis","demographic assessment","socioeconomic analysis"]},{"id":"ember-000070","url":"https://climateinsightsdirectory.org/document/ember-000070","title":"Global Electricity Source Trends","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2025-04-08","source_url":"https://ember-energy.org/chapter/global-electricity-source-trends-2/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"In 2024, global electricity generation reached new record highs for solar, wind, hydro, gas, and coal. Solar was the fastest-growing source, increasing by 474 TWh to reach a 6.9% share of the global mix, with China contributing 53% of this growth. Wind generation also hit a record of 2,494 TWh, though growth slowed due to weather conditions. Hydro rebounded to an all-time high of 4,416 TWh following 2023 droughts, largely driven by China. Nuclear generation grew by 2.5% to 2,768 TWh, but its global market share fell to a 45-year low of 9%. Gas and coal both reached record generation levels in 2024, though their shares of the global electricity mix declined to 22% and 34% respectively, as electricity demand grew faster than their production.","ai_generated":true,"unit":"ember-000070#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Solar power was the fastest-growing electricity source in 2024, increasing by 474 TWh to reach a total of 2,131 TWh, which represents a 29% increase. Its share of the global electricity mix rose to 6.9% from 5.6% in 2023.","ai_generated":true,"unit":"ember-000070#insight-1","date_modified":"2026-10-23"},{"text":"China is the dominant leader in solar expansion, adding 250 TWh in 2024, which accounts for 53% of the global increase. China's total solar generation reached 834 TWh, meaning 39% of the world's solar generation came from China in 2024.","ai_generated":true,"unit":"ember-000070#insight-2","date_modified":"2026-10-23"},{"text":"Global wind generation reached a record high of 2,494 TWh in 2024, an increase of 182 TWh (+7.9%) over 2023. Despite the record, growth slowed for the third consecutive year, partly due to less windy conditions in China.","ai_generated":true,"unit":"ember-000070#insight-3","date_modified":"2026-10-23"},{"text":"Hydro generation rebounded to an all-time high of 4,416 TWh in 2024, increasing by 182 TWh (+4.3%) as weather conditions improved after 2023 droughts. China was responsible for 71% of this global increase, adding 130 TWh.","ai_generated":true,"unit":"ember-000070#insight-4","date_modified":"2026-10-23"},{"text":"Nuclear generation rose by 2.5% (+69 TWh) to a record high of 2,768 TWh in 2024, driven by returning units in France and Japan. However, its share of the global electricity mix fell to 9%, the lowest level in over 45 years.","ai_generated":true,"unit":"ember-000070#insight-5","date_modified":"2026-10-23"},{"text":"Global gas generation reached a record high of 6,788 TWh in 2024, increasing by 1.6% (+103 TWh). Despite the record, its market share fell for the fourth year in a row to 22%, the lowest since 2013.","ai_generated":true,"unit":"ember-000070#insight-6","date_modified":"2026-10-23"},{"text":"Coal generation rose by 1.4% (+149 TWh) to a new record in 2024, with China accounting for 74% of the global increase (+110 TWh). Coal remains the largest single source of electricity, though its global share fell to 34% as demand grew faster than generation.","ai_generated":true,"unit":"ember-000070#insight-7","date_modified":"2026-10-23"}],"climate_tags":["solar energy","wind power","hydropower","nuclear power","natural gas","coal","electricity generation","energy transition","onshore wind farm","offshore wind power"],"geography_discussed":["People's Republic of China","United States","Brazil","India","Germany","Hungary","Chile","Australia","Denmark","Ireland","Portugal","Netherlands","Finland","Sweden","Spain","Morocco","Norway","Canada","France","Japan","South Korea","Taiwan","Slovakia","Ukraine","Egypt","Mexico","Russia","United Kingdom","Iran","Bahrain","Qatar","Vietnam","Bangladesh","Kosovo","Mongolia","South Africa","Kazakhstan","Serbia","Bosnia and Herzegovina","Europe","European Union"],"frame_perspective":[],"analysis_type":["trend analysis","comparative analysis"]},{"id":"iejza-000017","url":"https://climateinsightsdirectory.org/document/iejza-000017","title":"Why are classrooms and children becoming fast food billboards?","publisher":{"name":"Institute for Economic Justice","organization":"institute-for-economic-justice"},"document_type":"statement","language":"en","date_published":"2025-02-27","source_url":"https://iej.org.za/press-room/statements/joint-statement-why-are-classrooms-and-children-becoming-fast-food-billboards/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"Civil society organisations are protesting the handover of McDonald’s-branded ‘Mi Desk’ desks to Cape Town schools, facilitated by the Minister of Basic Education. The groups argue that such donations are not charity but junk food marketing targeting vulnerable children amidst a crisis of malnutrition and obesity. They contend that corporate philanthropy fills gaps created by state austerity and disinvestment, particularly in rural and working-class communities. The statement calls for the immediate recall of branded desks, the finalisation of regulations to restrict the marketing of harmful foods to children, and proper funding of education by the National Treasury to remove the need for corporate partnerships.","ai_generated":true,"unit":"iejza-000017#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The donation of McDonald’s-branded 'Mi Desk' desks to Cape Town schools is viewed as junk food marketing targeting vulnerable children rather than charity, occurring during a period where South Africa faces a \"compounding crisis of malnutrition, obesity, and a non-communicable disease epidemic\".","ai_generated":true,"unit":"iejza-000017#insight-1","date_modified":"2026-10-23"},{"text":"The prevalence of fast and ultra-processed foods in South African markets has contributed to an obesity epidemic, with nearly 25% of children under five being overweight or obese.","ai_generated":true,"unit":"iejza-000017#insight-2","date_modified":"2026-10-23"},{"text":"Corporate donations of branded furniture, including those from the Hollywood Foundation (linked to Hollywood Bets), are described as a consequence of austerity and education budget cuts that allow corporate actors to enter spaces abandoned by the state, specifically targeting black children in rural and working-class areas.","ai_generated":true,"unit":"iejza-000017#insight-3","date_modified":"2026-10-23"},{"text":"The South African government is urged to finalise draft regulations R3337 on the Labelling and Advertising of Foodstuffs and the Audio and Audio Visual Content Services White Paper to protect children from the marketing of health-harming foods.","ai_generated":true,"unit":"iejza-000017#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Cape Town","Canada","Norway","Iran","United Kingdom","Chile","Mexico","Ireland","Argentina","Portugal","South Korea","Taiwan","Brazil","Spain","Sweden"],"frame_perspective":[],"analysis_type":["policy critique","advocacy"]},{"id":"iisd-003536","url":"https://climateinsightsdirectory.org/document/iisd-003536","title":"The State of BCAs 2025","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2025-02","source_url":"https://www.iisd.org/system/files/2025-02/state-of-bcas-2025.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report examines the implementation of the EU and UK Carbon Border Adjustment Mechanisms (CBAMs) and the preliminary findings of Australia's Carbon Leakage Review. It highlights the shift from free allocation of emissions permits to border adjustments to prevent carbon leakage, where emissions reductions in one country are offset by increases elsewhere. The EU CBAM is set for full implementation by 2026, and the UK CBAM by 2027. Australia is considering a BCA as a 'robust underpinning' to its Safeguard Mechanism. The document also analyzes WTO discussions from 2020 to 2024, noting a transition from general concerns about protectionism and WTO compliance toward specific discussions on cooperation and interoperability.","ai_generated":true,"unit":"iisd-003536#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Carbon leakage occurs when climate policies in one country are offset by emissions increases in countries with less ambitious policies; one study found that 13% of emissions reductions from carbon pricing were offset this way, with cement showing a 23% leakage rate and steel 3%.","ai_generated":true,"unit":"iisd-003536#insight-1","date_modified":"2026-10-23"},{"text":"The EU CBAM will enter full implementation by 2026, phasing out free allocations from 2026 to 2034 to ensure full price convergence with the EU ETS by 2034. In 2022, the mechanism would have covered approximately 5% of EU imports, with iron and steel representing 55% of those goods.","ai_generated":true,"unit":"iisd-003536#insight-2","date_modified":"2026-10-23"},{"text":"The United Kingdom intends to implement its CBAM starting January 1, 2027, without a transition phase. Unlike the EU, the UK CBAM will systemically include scope 2 emissions across all covered sectors.","ai_generated":true,"unit":"iisd-003536#insight-3","date_modified":"2026-10-23"},{"text":"Australia's Carbon Leakage Review suggests a BCA could be an appropriate measure to address leakage and serve as a \"robust underpinning\" to the Safeguard Mechanism. Preliminary findings suggest cement as suitable for initial coverage, with potential later inclusion of steel, glass, ammonia fertilizers, and lime.","ai_generated":true,"unit":"iisd-003536#insight-4","date_modified":"2026-10-23"},{"text":"Between 2020 and 2024, the WTO saw 519 official statements or proposals on BCAs. The nature of the debate evolved from general concerns about \"hidden protectionism\" and WTO compliance toward calls for cooperation and \"interoperability between TrCMs\" in 2024.","ai_generated":true,"unit":"iisd-003536#insight-5","date_modified":"2026-10-23"}],"climate_tags":["Carbon Border Adjustment Mechanism","carbon leakage","carbon price","European Union Emission Trading Scheme 1","emission trading","Scope 2","Industrial decarbonization"],"geography_discussed":["People's Republic of China","United States","Canada","Taiwan","Montenegro","Albania","Bosnia and Herzegovina","Mozambique","Germany","Spain","Morocco","Japan","Thailand"],"frame_perspective":[],"analysis_type":["policy assessment","trade impact analysis","multilateral review"]},{"id":"iisd-003537","url":"https://climateinsightsdirectory.org/document/iisd-003537","title":"El Estado de los Mecanismos de Ajuste en Frontera por Carbono 2025","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"es","date_published":"2025-02","source_url":"https://www.iisd.org/system/files/2025-05/state-of-bcas-2025-es.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report provides a detailed analysis of the implementation of Carbon Border Adjustment Mechanisms (CBAMs) in the EU, UK, and Australia. It examines the transition from free allocations to border adjustments in the EU, the UK's planned 2027 launch, and Australia's ongoing carbon leakage review. Additionally, it tracks the evolution of multilateral discussions at the WTO, noting a shift from general concerns about protectionism toward specific technical cooperation and interoperability.","ai_generated":true,"unit":"iisd-003537#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The European Union's Carbon Border Adjustment Mechanism (CBAM) will be fully operational by 2026, with a gradual phase-in of costs and a corresponding phase-out of free allocations under the EU ETS until 2034.","ai_generated":true,"unit":"iisd-003537#insight-1","date_modified":"2026-10-23"},{"text":"The EU CBAM primarily targets iron, steel, aluminum, and electricity; in 2022, iron and steel alone accounted for 55% of the imports covered by the mechanism.","ai_generated":true,"unit":"iisd-003537#insight-2","date_modified":"2026-10-23"},{"text":"The United Kingdom intends to implement its own CBAM starting January 1, 2027, without a transitional phase, and will include Scope 2 emissions for all covered sectors.","ai_generated":true,"unit":"iisd-003537#insight-3","date_modified":"2026-10-23"},{"text":"Australia's independent Carbon Leakage Review suggests that a CBAM could serve as a 'strong backstop' to the Safeguard Mechanism, potentially starting with cement before expanding to steel, glass, and lime.","ai_generated":true,"unit":"iisd-003537#insight-4","date_modified":"2026-10-23"},{"text":"Between 2020 and 2024, the WTO saw 519 official communications regarding CBAMs, with a notable shift in 2024 toward increased interest in cooperation and technical interoperability.","ai_generated":true,"unit":"iisd-003537#insight-5","date_modified":"2026-10-23"},{"text":"Carbon leakage is a documented reality rather than a theoretical risk; one cited OECD study found that 13% of emission reductions from carbon pricing in one country were offset by increases elsewhere.","ai_generated":true,"unit":"iisd-003537#insight-6","date_modified":"2026-10-23"}],"climate_tags":["Carbon Border Adjustment Mechanism","carbon leakage","carbon price","emission trading","Scope 2","Scope 3","Industrial decarbonization","Paris Agreement"],"geography_discussed":["United States","Canada","People's Republic of China","Taiwan"],"frame_perspective":[],"analysis_type":["policy review","trade impact analysis","multilateral diplomatic tracking"]},{"id":"iisd-003538","url":"https://climateinsightsdirectory.org/document/iisd-003538","title":"État des lieux des Ajustements carbone aux frontières, 2025","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"fr","date_published":"2025-02","source_url":"https://www.iisd.org/system/files/2025-05/state-of-bcas-2025-fr.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report provides a comprehensive overview of carbon border adjustment mechanisms (CBAMs) as tools to prevent carbon leakage. It details the operational timelines and design features of the EU and UK mechanisms, analyzes a proposed Australian framework, and tracks legislative efforts in the US, Canada, and Taiwan. Additionally, it examines the evolving nature of CBAM discussions at the WTO, noting a shift from general concern toward specific design cooperation and interoperability.","ai_generated":true,"unit":"iisd-003538#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Carbon leakage is a documented phenomenon where climate policies in one country are partially offset by increased emissions in countries with less ambitious policies; one OECD study found that, on average, 13% of emission reductions from carbon pricing were compensated by increases elsewhere.","ai_generated":true,"unit":"iisd-003538#insight-1","date_modified":"2026-10-23"},{"text":"The European Union's CBAM is in a transitional phase until December 31, 2025, with full implementation expected by 2026. It will gradually replace free quota allocations between 2026 and 2034, with full price convergence between the CBAM and the EU ETS planned for 2034.","ai_generated":true,"unit":"iisd-003538#insight-2","date_modified":"2026-10-23"},{"text":"The UK intends to implement its own CBAM starting January 1, 2027, without a transitional phase. Unlike the EU model, the UK mechanism will systematically include scope 2 emissions across all covered sectors.","ai_generated":true,"unit":"iisd-003538#insight-3","date_modified":"2026-10-23"},{"text":"An independent Carbon Leakage Review in Australia suggested that a CBAM could be an appropriate measure to combat leakage and support the national Safeguard Mechanism. Preliminary findings suggest a phased approach, potentially starting with cement before expanding to steel, glass, ammonia fertilizers, and lime.","ai_generated":true,"unit":"iisd-003538#insight-4","date_modified":"2026-10-23"},{"text":"In the United States, four separate bills introducing carbon-related import taxes were presented before the end of the 118th Congress in 2024, including the Clean Competition Act and the Foreign Pollution Fee Act.","ai_generated":true,"unit":"iisd-003538#insight-5","date_modified":"2026-10-23"},{"text":"Between 2020 and 2024, the WTO saw 519 official statements or proposals regarding CBAMs. The discourse has evolved from general expressions of concern and protectionism fears toward specific discussions on design, interoperability, and cooperation, particularly in 2024.","ai_generated":true,"unit":"iisd-003538#insight-6","date_modified":"2026-10-23"}],"climate_tags":["Carbon Border Adjustment Mechanism","carbon leakage","carbon price","emission trading","Scope 2","Scope 3","Industrial decarbonization"],"geography_discussed":["United States","Canada","Taiwan","People's Republic of China","Turkey","Montenegro","World"],"frame_perspective":[],"analysis_type":["policy review","trade impact analysis"]},{"id":"ipie-000089","url":"https://climateinsightsdirectory.org/document/ipie-000089","title":"선거 캠페인에서의 생성형 AI: 글로벌 패턴 매핑 정책 입안자를 위한 요약","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ko","date_published":"2025-01","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0cb3311bb4c0a3808958_Final%20KO%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 cases of GenAI use in 2024 elections across 50 countries, finding that 80% of these countries experienced GenAI-related incidents. The majority of these cases (90%) involved content creation, such as deepfake audio and video, and 69% were classified as harmful to the electoral process. A significant portion of the content (46%) had untraceable origins, while 20% was attributed to foreign actors, all of whom were found to be acting with harmful intent. The document advocates for increased transparency, disclosure mandates for AI-generated political content, and improved detection mechanisms to protect democratic integrity.","ai_generated":true,"unit":"ipie-000089#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was prevalent in 2024 elections, with 80% of the 50 analyzed countries experiencing GenAI cases. The highest volumes of cases were recorded in India and the United States, with 30 cases each.","ai_generated":true,"unit":"ipie-000089#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is content creation, accounting for 90% of cases. This includes the production of audio messages, images, videos, and social media posts, often combined with targeted distribution to maximize influence.","ai_generated":true,"unit":"ipie-000089#insight-2","date_modified":"2026-10-23"},{"text":"A large proportion of GenAI-generated electoral content has anonymous or untraceable origins. Specifically, 46% of cases had unknown sources, while 25% were produced by political candidates and parties, and 20% by foreign actors.","ai_generated":true,"unit":"ipie-000089#insight-3","date_modified":"2026-10-23"},{"text":"The majority of GenAI applications in elections were harmful, with 69% of cases described as playing a detrimental role. Notably, 100% of GenAI use by foreign actors was conducted for harmful purposes.","ai_generated":true,"unit":"ipie-000089#insight-4","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI has been used constructively in some instances. For example, 38% of use cases by domestic parties and candidates were classified as beneficial, such as using AI chatbots in Japan to engage voters.","ai_generated":true,"unit":"ipie-000089#insight-5","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 data-driven analysis","pattern mapping"]},{"id":"ipie-000092","url":"https://climateinsightsdirectory.org/document/ipie-000092","title":"选举活动中的生成式智能：全球模式图谱 政策制定者摘要","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"vi","date_published":"2025-01","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0cd40eb47fa7e1641fac_Final%20ZH%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 events, with 69% of these events having a harmful impact. The majority of GenAI use focused on content production, and nearly half of the events had unknown sources.","ai_generated":true,"unit":"ipie-000092#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"GenAI was prevalent in 2024 elections, appearing in 80% of the countries that held competitive national elections. India and the United States recorded the highest number of events, with 30 each.","ai_generated":true,"unit":"ipie-000092#insight-1","date_modified":"2026-10-23"},{"text":"A significant portion of GenAI activity lacks clear attribution: 46% of events had unknown sources, while political candidates and parties were responsible for 25% and foreign actors for 20%. Among cases with unknown sources, 79% were suspected of political manipulation.","ai_generated":true,"unit":"ipie-000092#insight-2","date_modified":"2026-10-23"},{"text":"Most GenAI applications in elections were harmful, with 69% of events categorized as having a negative impact. Notably, 100% of GenAI use attributed to foreign actors served harmful purposes, whereas 38% of use by national parties and candidates was categorized as beneficial.","ai_generated":true,"unit":"ipie-000092#insight-3","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["India","United States","Taiwan","Solomon Islands"],"frame_perspective":[],"analysis_type":["data-driven analysis","policy summary"]},{"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-000017","url":"https://climateinsightsdirectory.org/document/ipie-000017","title":"Information Integrity about Climate Science: A Systematic Review","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"report","language":"en","date_published":"2025","source_url":"https://www.ipie.info/research/sr2025-1","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report identifies a crisis of information integrity about climate science, characterized by a shift from outright denial to more nuanced skepticism and 'response skepticism' regarding climate solutions. It documents how powerful economic interests, particularly the fossil fuel industry, and political actors use strategies like greenwashing, delay, and obstruction to undermine scientific consensus. The review highlights the role of social media algorithms, bots, and 'source media' (such as corporate reports) in amplifying misleading narratives. It concludes that while individual-level interventions like inoculation and education are valuable, systemic governance through public regulation, standardized corporate reporting, and litigation is essential to restore information integrity.","ai_generated":true,"unit":"ipie-000017#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The report defines information integrity through four criteria: accuracy (alignment with climate science), consistency (stability of information across time and place), reliability (explication of origins and relevance), and transparency (the ability for citizens to trace information trajectories).","ai_generated":true,"unit":"ipie-000017#insight-1","date_modified":"2026-10-23"},{"text":"Fossil fuel companies, including TotalEnergies, ExxonMobil, Chevron, BP, Shell, and ConocoPhillips, have historically used a 'dual deception' strategy: denying the reality of climate change while simultaneously using greenwashing to appear environmentally sustainable.","ai_generated":true,"unit":"ipie-000017#insight-2","date_modified":"2026-10-23"},{"text":"There is a documented shift in misleading communication from outright denial of climate change toward 'skepticism,' specifically 'response skepticism' which questions the feasibility and effectiveness of proposed policies and solutions.","ai_generated":true,"unit":"ipie-000017#insight-3","date_modified":"2026-10-23"},{"text":"The 'climate change countermovement' is an organized 'denial machine' involving coordinated efforts across the fossil fuel, plastic, and agrichemical industries to obstruct climate action.","ai_generated":true,"unit":"ipie-000017#insight-4","date_modified":"2026-10-23"},{"text":"Social media platforms facilitate the spread of misinformation through algorithms and the use of bots; one study found that nearly 25% of tweets regarding the U.S. withdrawal from the Paris Agreement originated from bot accounts that promoted denialist discourses.","ai_generated":true,"unit":"ipie-000017#insight-5","date_modified":"2026-10-23"},{"text":"Source media, such as corporate sustainability reports and government documents, are critical but underestimated channels for misleading information, often used for greenwashing or to justify delays in climate action outside of public scrutiny.","ai_generated":true,"unit":"ipie-000017#insight-6","date_modified":"2026-10-23"},{"text":"Youth and students are identified as particularly vulnerable to misleading climate information due to their high reliance on social media and limited information literacy, sometimes facing 'petro-pedagogy' where industry narratives penetrate education systems.","ai_generated":true,"unit":"ipie-000017#insight-7","date_modified":"2026-10-23"},{"text":"Inoculation—preemptively exposing people to the techniques used to mislead—is found to be an effective strategy for building resilience against misinformation, though its efficacy can be limited by strong pre-existing ideological worldviews.","ai_generated":true,"unit":"ipie-000017#insight-8","date_modified":"2026-10-23"},{"text":"The report identifies a severe 'elephant in the room' regarding research gaps: there is a critical dearth of studies on information integrity about climate science in the Global South and a lack of globally comparative perspectives.","ai_generated":true,"unit":"ipie-000017#insight-9","date_modified":"2026-10-23"},{"text":"Effective solutions to the crisis of information integrity require a combination of public regulation, mandatory standardized corporate reporting (such as the EU taxonomy), and the use of litigation against repeat offenders of greenwashing.","ai_generated":true,"unit":"ipie-000017#insight-10","date_modified":"2026-10-23"}],"climate_tags":["obsidian","climate change disinformation","greenwashing","climate justice","fossil fuel industry","climate change litigation","environmental education","environmental, social and corporate governance"],"geography_discussed":["United States","European Union","Russia","People's Republic of China","Australia","Canada","Germany","Spain","Switzerland","France","Poland","Austria","Malaysia","United Kingdom","Norway","Taiwan"],"frame_perspective":[],"analysis_type":["systematic review","gap analysis","network analysis"]},{"id":"ipie-000025","url":"https://climateinsightsdirectory.org/document/ipie-000025","title":"The Role of Generative AI Use in 2024 Elections Worldwide","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"research paper","language":"en","date_published":"2025","source_url":"https://www.ipie.info/research/tp2025-2","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The IPIE analyzed GenAI usage across 50 countries with competitive national elections in 2024. Findings show that GenAI was reported in 80% of these countries, primarily for content creation (90% of cases). While 69% of instances served malicious ends, 16% were benevolent. The study highlights a significant challenge in actor identification, with 46% of cases remaining unclear, and notes that foreign actors were involved in 20% of reported incidents, all for nefarious purposes.","ai_generated":true,"unit":"ipie-000025#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"GenAI was utilized in national elections in 80% of the 50 competitive countries tracked in the IPIE database. The countries with the highest number of recorded instances were India and the USA, with 30 occurrences each.","ai_generated":true,"unit":"ipie-000025#insight-1","date_modified":"2026-10-23"},{"text":"Content creation—including audio, images, videos, and text—was the dominant application of GenAI, accounting for 90% of all recorded usage in 2024 elections worldwide.","ai_generated":true,"unit":"ipie-000025#insight-2","date_modified":"2026-10-23"},{"text":"The majority of GenAI applications in elections were malicious, with 69% serving apparently nefarious ends, while 16% were used for benevolent purposes.","ai_generated":true,"unit":"ipie-000025#insight-3","date_modified":"2026-10-23"},{"text":"Identifying the actors behind GenAI usage is difficult; in 46% of the recorded incidents, the identity of the actor remained unclear.","ai_generated":true,"unit":"ipie-000025#insight-4","date_modified":"2026-10-23"},{"text":"Foreign actors were involved in 20% of reported incidents, and all such instances of foreign interference were conducted for nefarious purposes.","ai_generated":true,"unit":"ipie-000025#insight-5","date_modified":"2026-10-23"},{"text":"Hypertargeting—the use of GenAI to direct specific content to particular demographics to tilt political preferences—was the least common application, appearing in only 4% of recorded instances.","ai_generated":true,"unit":"ipie-000025#insight-6","date_modified":"2026-10-23"},{"text":"Political parties and candidates were responsible for 25% of the recorded GenAI usage, with 38% of their applications deemed benevolent.","ai_generated":true,"unit":"ipie-000025#insight-7","date_modified":"2026-10-23"},{"text":"The 'liar's dividend' is a significant risk, where the prevalence of deepfakes allows politicians to dismiss authentic content as being AI-generated.","ai_generated":true,"unit":"ipie-000025#insight-8","date_modified":"2026-10-23"},{"text":"In Romania, a sophisticated and coordinated GenAI campaign was perceived to have significantly influenced the national election, contributing to the annulment of the presidential results.","ai_generated":true,"unit":"ipie-000025#insight-9","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["India","United States","Romania","Indonesia","Bangladesh","Taiwan","Namibia","Ghana","Lithuania","Mexico","Tunisia"],"frame_perspective":[],"analysis_type":["descriptive analysis","cross-case comparison","content analysis"]},{"id":"ipie-000028","url":"https://climateinsightsdirectory.org/document/ipie-000028","title":"Artificial Intelligence and Peacebuilding: Opportunities and Challenges","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"research paper","language":"en","date_published":"2025","source_url":"https://www.ipie.info/research/tp2025-3","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report examines the dual-use nature of AI in peacebuilding, highlighting its potential to enhance conflict forecasting, real-time mapping, and inclusive dialogue while warning against risks such as algorithmic bias, surveillance, and the erosion of human facilitation skills. It emphasizes that AI's effectiveness depends on a healthy information environment and a rights-based approach to design and governance.","ai_generated":true,"unit":"ipie-000028#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"AI tools are being used for conflict prediction and early warning, with systems like ACLED's Conflict Alert System (CAST) reportedly achieving accuracy rates of up to 95% for forecasts up to six months in advance.","ai_generated":true,"unit":"ipie-000028#insight-1","date_modified":"2026-10-23"},{"text":"AI-enhanced mapping and satellite imagery are significantly accelerating humanitarian response; for example, the DISHA system has shown potential to reduce damage assessment time by a factor of six.","ai_generated":true,"unit":"ipie-000028#insight-2","date_modified":"2026-10-23"},{"text":"AI-powered platforms like Remesh and Polis are scaling citizen engagement in conflict zones, such as in Libya, Yemen, and Syria, by facilitating large-scale dialogues and identifying areas of consensus.","ai_generated":true,"unit":"ipie-000028#insight-3","date_modified":"2026-10-23"},{"text":"There is a critical risk of 'dual-use' where AI tools intended for peacebuilding are repurposed for military targeting and surveillance, as seen with the Israeli military's use of the Gospel and Lavender systems in Gaza.","ai_generated":true,"unit":"ipie-000028#insight-4","date_modified":"2026-10-23"},{"text":"The report identifies a significant 'implementation gap' where an abundance of AI-generated data does not automatically translate into policy action due to complex political and economic realities.","ai_generated":true,"unit":"ipie-000028#insight-5","date_modified":"2026-10-23"},{"text":"AI's role in mediation is currently most effective in a support capacity—such as automating administration or scenario planning—rather than as a substitute for human mediators in high-stakes conflicts.","ai_generated":true,"unit":"ipie-000028#insight-6","date_modified":"2026-10-23"},{"text":"The sustainability of AI peacebuilding initiatives is threatened by precarious funding and low user engagement, exemplified by the DEEP platform where only 20% of registered users show active annual participation.","ai_generated":true,"unit":"ipie-000028#insight-7","date_modified":"2026-10-23"},{"text":"A healthy information environment—characterized by digital literacy, diversity of voices, and accountability—is a prerequisite for AI to support peacebuilding rather than exacerbate conflict.","ai_generated":true,"unit":"ipie-000028#insight-8","date_modified":"2026-10-23"},{"text":"Current Large Language Models (LLMs) continue to suffer from hallucinations, with error rates between 0.8% and 5% even in ideal conditions, which poses dangers in critical humanitarian operations.","ai_generated":true,"unit":"ipie-000028#insight-9","date_modified":"2026-10-23"}],"climate_tags":["human rights","digital divide"],"geography_discussed":["Libya","Yemen","Syria","Gaza Strip","Ukraine","Sudan","Kenya","Taiwan","People's Republic of China","United States"],"frame_perspective":[],"analysis_type":["literature review","case study analysis","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-000084","url":"https://climateinsightsdirectory.org/document/ipie-000084","title":"IA generativa en campañas electorales: identificación de patrones globales","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"es","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0c9286759bdd611e2a47_Final%20ES%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 incidents of generative AI use across 50 countries that held competitive national elections in 2024. It finds that GenAI was present in 80% of these countries, primarily used for creating synthetic content such as deepfake audio and video. A significant majority (69%) of these incidents were categorized as harmful to the electoral process, with 20% attributed to foreign actors, all of whom demonstrated harmful intent. The document emphasizes the challenge of anonymity, as 46% of incidents had unidentifiable authors, and recommends mandatory disclosure norms and improved detection methods to protect democratic integrity.","ai_generated":true,"unit":"ipie-000084#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI (GenAI) was utilized in the campaign phases of 80% of the countries that held competitive national elections in 2024. India and the United States were particularly prominent, with 30 documented incidents each.","ai_generated":true,"unit":"ipie-000084#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is the production of synthetic content, accounting for 90% of recorded incidents. This includes the creation of audio messages, images, videos, and social media posts designed to be realistic and misleading.","ai_generated":true,"unit":"ipie-000084#insight-2","date_modified":"2026-10-23"},{"text":"Attributing the source of GenAI content is difficult, as 46% of incidents have no identifiable author. Among those that could be traced, candidates and political parties were responsible for 25%, foreign operators for 20%, and other groups for 9%.","ai_generated":true,"unit":"ipie-000084#insight-3","date_modified":"2026-10-23"},{"text":"A majority of GenAI applications in electoral contexts are detrimental, with 69% of incidents categorized as harmful. All documented uses by foreign actors were found to have harmful intentions, such as interfering in processes or manipulating voter perception.","ai_generated":true,"unit":"ipie-000084#insight-4","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI has been used constructively by 38% of national political parties and candidates. Examples include the use of chatbots in Japan to interact with voters and the use of GenAI for civic outreach and accessibility (16% of incidents).","ai_generated":true,"unit":"ipie-000084#insight-5","date_modified":"2026-10-23"},{"text":"Specific instances of GenAI-driven electoral interference include the invalidation of presidential election results in Romania due to coordinated manipulation, a deepfake video of a candidate withdrawing in Bangladesh, and a fake audio clip of US President Joe Biden supporting local parties in Namibia.","ai_generated":true,"unit":"ipie-000084#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":["empirical analysis","global trend analysis","policy review"]},{"id":"ipie-000085","url":"https://climateinsightsdirectory.org/document/ipie-000085","title":"Генеративный ИИ в избирательных кампаниях: составление карты глобальных закономерностей","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ru","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0c994389c3a190966c3b_Final%20RU%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 incidents of GenAI use in 2024 elections across 50 countries, finding that 80% of these countries experienced GenAI-related incidents. The vast majority of use (90%) focused on content creation, and 69% of incidents were classified as harmful. A significant portion of GenAI content (46%) remains unattributed, while 20% is linked to foreign actors, all of whom were found to have harmful intentions. The document advocates for mandatory disclosure and transparency standards to protect electoral processes.","ai_generated":true,"unit":"ipie-000085#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was present in the vast majority of competitive national elections in 2024, with 80% of the 50 studied countries recording incidents. The highest volume of incidents occurred in India and the United States, with 30 incidents each.","ai_generated":true,"unit":"ipie-000085#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is the production of synthetic content, accounting for 90% of recorded incidents. This includes the creation of audio messages, images, videos, and social media posts, often used to fabricate statements or impersonate figures.","ai_generated":true,"unit":"ipie-000085#insight-2","date_modified":"2026-10-23"},{"text":"Attribution of GenAI content is frequently impossible, with 46% of incidents having an unknown source. Among known sources, political candidates and parties were responsible for 25%, while foreign actors accounted for 20%.","ai_generated":true,"unit":"ipie-000085#insight-3","date_modified":"2026-10-23"},{"text":"Most GenAI applications in the studied elections were harmful, with 69% of incidents classified as having a negative role. Notably, 100% of GenAI use attributed to foreign actors was intended to be harmful.","ai_generated":true,"unit":"ipie-000085#insight-4","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI has been used constructively by some political parties (38% of their cases were 'useful'), such as using chatbots in Japan to engage voters or creating content in local dialects to reach underserved populations.","ai_generated":true,"unit":"ipie-000085#insight-5","date_modified":"2026-10-23"},{"text":"The report highlights specific high-impact cases, such as in Romania, where coordinated GenAI and information campaigns contributed to the annulment of presidential election results.","ai_generated":true,"unit":"ipie-000085#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":["incident analysis","global trend mapping","policy recommendation"]},{"id":"ipie-000086","url":"https://climateinsightsdirectory.org/document/ipie-000086","title":"الذكاء الاصطناعي التوليدي في الانتخابات: رؤى للأنماط العالمية لصانعي السياسات 2025","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ar","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0ca048177b5b2af84666_Final%20AR%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 incidents of generative AI (GenAI) use during 2024 national elections across 50 countries. It finds that 80% of these countries experienced GenAI-related incidents, with 90% of cases involving the creation of synthetic content such as audio, images, and video. Approximately 69% of these incidents were classified as harmful, often involving impersonation or disinformation. While 38% of uses were deemed useful—such as for civic outreach or simplifying communications—nearly half of all incidents (46%) came from unknown sources, complicating accountability and transparency.","ai_generated":true,"unit":"ipie-000086#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was present in the vast majority of analyzed national elections in 2024, with 80% of the 50 countries that held competitive elections recording related incidents. The highest volume of incidents occurred in India and the United States, with 30 recorded cases each.","ai_generated":true,"unit":"ipie-000086#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of generative AI in elections is content creation, accounting for 90% of recorded incidents. This includes the production of synthetic audio, images, videos, and social media posts designed to be realistic and misleading.","ai_generated":true,"unit":"ipie-000086#insight-2","date_modified":"2026-10-23"},{"text":"A significant portion of generative AI use in elections is anonymous or unattributable. In 46% of cases, the source was unknown; 25% were produced by political candidates and parties, 20% by foreign actors, and 9% by other sources such as lobby groups or individuals.","ai_generated":true,"unit":"ipie-000086#insight-3","date_modified":"2026-10-23"},{"text":"Most generative AI applications in the studied elections had a negative impact, with 69% of incidents described as playing a harmful role. Harmful uses included adversarial impersonation, automated disinformation, and the use of bots to amplify low-quality content. Notably, 100% of the GenAI use attributed to foreign actors was reported as serving harmful purposes.","ai_generated":true,"unit":"ipie-000086#insight-4","date_modified":"2026-10-23"},{"text":"Generative AI also had constructive applications in 38% of reported cases, including civic awareness (16%) and improving accessibility for marginalized or illiterate populations. For example, candidates in Japan used GenAI chatbots to interact with voters.","ai_generated":true,"unit":"ipie-000086#insight-5","date_modified":"2026-10-23"},{"text":"The report highlights specific instances where GenAI severely impacted electoral integrity, such as in Romania, where coordinated efforts to distort national elections led to the annulment of presidential election results.","ai_generated":true,"unit":"ipie-000086#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["India","United States","Romania","Taiwan","Japan"],"frame_perspective":[],"analysis_type":["data analysis","global assessment","policy recommendation"]},{"id":"ipie-000087","url":"https://climateinsightsdirectory.org/document/ipie-000087","title":"Generative KI in Wahlkampagnen: Kartierung globaler Muster","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"de","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0ca6fcede156eee4ac8e_Final%20DE%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 215 incidents of GenAI use in 2024 elections, finding that 80% of countries with competitive elections experienced such incidents. The majority of these cases involved content creation (90%) and were deemed harmful to the electoral process (69%). A significant portion of the sources remain unknown (46%), while political candidates (25%) and foreign actors (20%) are the primary identified sources. The document recommends transparency standards and disclosure requirements to protect electoral integrity.","ai_generated":true,"unit":"ipie-000087#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was utilized in 80% of the countries that held competitive national elections in 2024. The highest number of recorded incidents occurred in India and the United States, with 30 cases each.","ai_generated":true,"unit":"ipie-000087#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is content creation, accounting for 90% of reported incidents. This includes the production of audio messages, images, videos, and social media posts.","ai_generated":true,"unit":"ipie-000087#insight-2","date_modified":"2026-10-23"},{"text":"Attributing the source of GenAI content is difficult, as the origin was unknown in 46% of cases. Among identified sources, political candidates and parties accounted for 25%, and foreign actors accounted for 20%.","ai_generated":true,"unit":"ipie-000087#insight-3","date_modified":"2026-10-23"},{"text":"The majority of GenAI applications in elections are detrimental, with 69% of recorded incidents classified as harmful. Notably, 100% of the GenAI use attributed to foreign actors served harmful purposes.","ai_generated":true,"unit":"ipie-000087#insight-4","date_modified":"2026-10-23"},{"text":"While largely harmful, GenAI has been used constructively by some political actors. In Japan, candidates used GenAI-powered chatbots to engage with voters, and 38% of reported uses by national political parties and candidates were classified as useful.","ai_generated":true,"unit":"ipie-000087#insight-5","date_modified":"2026-10-23"},{"text":"Specific examples of harmful GenAI use include a deepfake video in Bangladesh falsely announcing a candidate's withdrawal, a manipulated video in Taiwan targeting a presidential candidate, and cloned audio of US President Joe Biden in Namibia to support local parties.","ai_generated":true,"unit":"ipie-000087#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":["data-driven analysis","mapping of global patterns"]},{"id":"ipie-000090","url":"https://climateinsightsdirectory.org/document/ipie-000090","title":"IA generativa em campanhas eleitorais: mapeamento de padrões globais","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"policy brief","language":"pt","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0cbc67ee8b8ecfd81f08_Final%20PTB%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed"],"summary":{"text":"The report finds that GenAI was present in 80% of competitive national elections in 2024, primarily used for creating synthetic content like deepfakes. While some beneficial uses for civic outreach were noted, 69% of incidents were categorized as harmful. A significant portion of GenAI content (46%) remains unattributable to a known source, complicating electoral governance and transparency.","ai_generated":true,"unit":"ipie-000090#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Generative AI was present in the vast majority of competitive national elections in 2024, with 80% of the 50 analyzed countries experiencing GenAI use during campaign periods. The highest volume of incidents occurred in India and the United States, with 30 incidents recorded in each.","ai_generated":true,"unit":"ipie-000090#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in elections is content creation, accounting for 90% of recorded incidents. This includes the production of synthetic audio, images, videos, and social media posts, often used to impersonate public figures or manipulate narratives.","ai_generated":true,"unit":"ipie-000090#insight-2","date_modified":"2026-10-23"},{"text":"Attributing the source of GenAI content is a major challenge, as 46% of incidents have no known source. Among identified sources, candidates and political parties accounted for 25%, while foreign actors were responsible for 20%.","ai_generated":true,"unit":"ipie-000090#insight-3","date_modified":"2026-10-23"},{"text":"Most GenAI applications in elections are detrimental, with 69% of incidents categorized as harmful. Notably, 100% of GenAI use attributed to foreign agents served harmful purposes, such as interfering in electoral processes.","ai_generated":true,"unit":"ipie-000090#insight-4","date_modified":"2026-10-23"},{"text":"There are limited but documented beneficial uses of GenAI, particularly by national candidates and parties, where 38% of their uses were categorized as beneficial. Examples include using chatbots in Japan to engage voters and using GenAI for civic outreach and accessibility (16% of incidents).","ai_generated":true,"unit":"ipie-000090#insight-5","date_modified":"2026-10-23"},{"text":"The report highlights specific high-impact cases, such as in Romania, where coordinated GenAI use contributed to the annulment of presidential election results, and in Bangladesh, where a synthetic video falsely announced a candidate's withdrawal.","ai_generated":true,"unit":"ipie-000090#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":[]},{"id":"ipie-000091","url":"https://climateinsightsdirectory.org/document/ipie-000091","title":"Uzalishaji wa AI katika Kampeni za Uchaguzi: Kuchora Miundo ya Ulimwenguni","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"sw","date_published":"2025","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/690a0cc4817fd01ff7f2b539_Final%20SW%20Elections%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document analyzes the role of Generative AI in 2024 national elections across 50 countries. It finds that 80% of these countries experienced GenAI incidents, with 90% of those cases involving content creation such as audio, images, and video. A significant portion of these incidents (69%) were classified as harmful to electoral integrity, and nearly half (46%) originated from unknown sources. The report highlights specific examples of misuse in countries like Romania, Bangladesh, and Taiwan, while noting some beneficial uses in Japan. It concludes by recommending mandatory disclosure standards and increased transparency to protect democratic processes.","ai_generated":true,"unit":"ipie-000091#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 recording GenAI incidents. The highest volume of incidents occurred in India and the United States, with 30 cases recorded in each.","ai_generated":true,"unit":"ipie-000091#insight-1","date_modified":"2026-10-23"},{"text":"The primary application of GenAI in these contexts is content generation, accounting for 90% of recorded incidents. This includes the creation of synthetic audio, images, videos, and social media posts used for both authentic and misleading communication.","ai_generated":true,"unit":"ipie-000091#insight-2","date_modified":"2026-10-23"},{"text":"A large proportion of GenAI content sources are anonymous, with 46% of cases having no identifiable source. Among identified sources, political candidates and parties accounted for 25%, while foreign actors accounted for 20%.","ai_generated":true,"unit":"ipie-000091#insight-3","date_modified":"2026-10-23"},{"text":"Most GenAI applications in elections were deemed harmful, with 69% of incidents described as playing a negative role in the electoral process. Notably, 100% of reported GenAI use by foreign actors was classified as having harmful objectives.","ai_generated":true,"unit":"ipie-000091#insight-4","date_modified":"2026-10-23"},{"text":"GenAI has been used to disrupt specific national elections, such as in Romania, where coordinated AI efforts contributed to the annulment of presidential election results. Other examples include deepfake videos in Bangladesh and Taiwan, and fake audio of US President Joe Biden in Namibia.","ai_generated":true,"unit":"ipie-000091#insight-5","date_modified":"2026-10-23"},{"text":"While predominantly harmful, GenAI also had constructive applications; 38% of reported use by national political parties and candidates was classified as beneficial. For example, candidates in Japan used GenAI chatbots to engage voters and answer basic questions.","ai_generated":true,"unit":"ipie-000091#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["India","United States","Romania","Bangladesh","Taiwan","Namibia","Solomon Islands","Japan","Switzerland"],"frame_perspective":[],"analysis_type":["data-driven analysis","global assessment","policy recommendation"]}]}