{"query_echo":{"q":"","filters":{"organization":["International Panel on the Information Environment"]},"warnings":[]},"total":{"value":105,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?organization=international-panel-on-the-information-environment&page=1","next":"https://climateinsightsdirectory.org/api/v1/search?organization=international-panel-on-the-information-environment&page=2","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-000105","url":"https://climateinsightsdirectory.org/document/ipie-000105","title":"应对生成式人工智能虚假信息 科学证据荟萃分析结果","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"zh","date_published":"2026-02","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a3b8d3107d35aa999ef186b_SFP%20CHINESE%20FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The report finds that text-based GenAI misinformation currently poses a higher persuasive risk than visual misinformation. It identifies preemptive debunking as the most consistent intervention for reducing perceived credibility, while content labeling is effective only when standardized. The analysis highlights a critical evidence gap, as existing research is heavily concentrated in English-speaking and high-income countries.","ai_generated":true,"unit":"ipie-000105#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Content labeling (adding visual or text tags to indicate AI generation) can reduce the perceived credibility of misinformation, but its effectiveness is inconsistent and highly dependent on design, wording, and implementation. The report notes that the impact of labels varies significantly across different companies and scenarios.","ai_generated":true,"unit":"ipie-000105#insight-1","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["meta-analysis","systematic review","randomized controlled trials"]},{"id":"ipie-000010","url":"https://climateinsightsdirectory.org/document/ipie-000010","title":"Confronting Misinformation Produced with Generative AI: A Meta-Analysis of Experimental Scientific Evidence","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"report","language":"en","date_published":"2026","source_url":"https://www.ipie.info/research/sr2026-2-confronting-generative-ai-misinformation-meta-analysis","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that textual GenAI misinformation is increasingly perceived as credible over time, while visual GenAI misinformation, such as deepfakes, shows a decline in perceived credibility. Preventive corrective information and content labeling are identified as effective countermeasures, though their impact varies by context.","ai_generated":true,"unit":"ipie-000010#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Textual generative AI misinformation shows a statistically significant upward trend in perceived realism and credibility between 2019 and 2024, with a modest increase in effect size over time (β = 0.08).","ai_generated":true,"unit":"ipie-000010#insight-1","date_modified":"2026-10-23"},{"text":"Visual generative AI misinformation, including deepfakes, has experienced a statistically significant decline in perceived credibility since approximately 2021 (β = -0.22).","ai_generated":true,"unit":"ipie-000010#insight-2","date_modified":"2026-10-23"},{"text":"Preventive corrective information—such as educational forewarnings about AI hallucinations or deepfake techniques—is associated with a consistent reduction in the perceived credibility of GenAI misinformation (g = -0.30 for post-2020 studies).","ai_generated":true,"unit":"ipie-000010#insight-3","date_modified":"2026-10-23"},{"text":"Content labeling (e.g., tags like \"AI-Generated\") provides a small but statistically significant reduction in the perceived credibility of GenAI misinformation (g = -0.24), though its effectiveness is highly context-dependent.","ai_generated":true,"unit":"ipie-000010#insight-4","date_modified":"2026-10-23"},{"text":"The meta-analysis is based on 60 effect estimates extracted from 24 peer-reviewed publications, focusing exclusively on randomized controlled trials (RCTs).","ai_generated":true,"unit":"ipie-000010#insight-5","date_modified":"2026-10-23"},{"text":"The report identifies a significant geographic gap in research, as the analyzed evidence is heavily concentrated on participants from the USA and the European Union.","ai_generated":true,"unit":"ipie-000010#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation","climate change"],"geography_discussed":["United States","European Union","South Korea","Austria","Germany","Netherlands","United Kingdom"],"frame_perspective":[],"analysis_type":["meta-analysis","randomized controlled trials"]},{"id":"ipie-000019","url":"https://climateinsightsdirectory.org/document/ipie-000019","title":"Resilience and Vulnerability to Misinformation and Disinformation in Political Information Environments: A Comparative Review of Ten Indexes","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"research paper","language":"en","date_published":"2026","source_url":"https://www.ipie.info/research/tp2026-1-misinformation-disinformation-resilience-index-review","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report evaluates ten distinct indexes designed to diagnose the resilience or vulnerability of political information environments to mis- and disinformation. It develops a typology of these tools—categorizing them as advertising-oriented, policy-driven, academically oriented, or public outreach—and analyzes their conceptual foundations, data collection methods, and scoring architectures. The review finds that most indexes rely on proxy indicators (such as institutional trust or media freedom) rather than direct measurement of false content. Comparative case studies reveal that while some indexes converge on structural constants in advanced democracies, others diverge sharply due to different operational definitions of 'resilience,' such as distinguishing between reactive mobilization and long-term structural capacity. The document concludes that current measurement is fragmented and recommends a more unified architecture that integrates structural, behavioral, and platform-specific dynamics.","ai_generated":true,"unit":"ipie-000019#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Indexes of mis- and disinformation rarely measure the actual volume of false content; instead, they operationalize risk through proxy indicators that capture the structural, perceptual, or psychological conditions that make a society susceptible or resilient.","ai_generated":true,"unit":"ipie-000019#insight-1","date_modified":"2026-10-23"},{"text":"The reviewed indexes can be classified into four distinct groups based on their funding, target audience, and purpose: Advertising- and Funding-Oriented (e.g., GDI), Policy-Driven/Security-Oriented (e.g., GVI, GPI), Academically Oriented (e.g., ROD, EV), and Public Outreach (e.g., MLI, MVI).","ai_generated":true,"unit":"ipie-000019#insight-2","date_modified":"2026-10-23"},{"text":"Vulnerability is conceptualized as the susceptibility of a political information environment to harmful information, driven by political and societal weaknesses, media-system fragility, and external pressures like foreign malign influence.","ai_generated":true,"unit":"ipie-000019#insight-3","date_modified":"2026-10-23"},{"text":"Resilience is defined as the capacity of an information environment to absorb, adapt to, and recover from manipulative forces, depending on societal trust, institutional/legal strength, and the health of the media ecosystem.","ai_generated":true,"unit":"ipie-000019#insight-4","date_modified":"2026-10-23"},{"text":"There is a significant geographic bias in current indexing, with strong representation of Europe and North America but persistent gaps in the Global South, Central and South America, and East and Southeast Asia due to data scarcity and institutional priorities.","ai_generated":true,"unit":"ipie-000019#insight-5","date_modified":"2026-10-23"},{"text":"Comparative analysis shows that indexes using the same label, such as 'resilience,' can produce contradictory results because they measure different things; for example, the DRI captures reactive mobilization while the FIMI index captures long-term structural capacity.","ai_generated":true,"unit":"ipie-000019#insight-6","date_modified":"2026-10-23"},{"text":"Most existing indexes fail to integrate the role of large online platforms, ignoring the impact of algorithms, recommendation ecosystems, and platform-specific governance on the amplification of disinformation.","ai_generated":true,"unit":"ipie-000019#insight-7","date_modified":"2026-10-23"},{"text":"Methodological transparency is inconsistent across the ten indexes, with frequent gaps in documentation regarding indicator weighting, aggregation choices, and the handling of missing data.","ai_generated":true,"unit":"ipie-000019#insight-8","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["Europe","North America","West Africa","Western Balkans","Finland","United States","Greece"],"frame_perspective":[],"analysis_type":["comparative review","meta-analysis","typology development"]},{"id":"ipie-000103","url":"https://climateinsightsdirectory.org/document/ipie-000103","title":"Confronting Misinformation Produced with Generative AI","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"research paper","language":"en","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643e793799ecf3065c893f9d/6a15599a2cfb42fe2e6843d8_Online%20Appendix%20Final.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document serves as a technical appendix to a meta-analysis on generative AI misinformation. It details the risk of bias assessment for various randomized controlled trials using the Cochrane RoB 2 protocol, finding that most studies scored 'low' to 'moderate' for bias. It also describes tests for publication selection bias—including Egger's test and the Duval and Tweedie trim-and-fill method—across samples focusing on visual misinformation, corrective information, and content labeling, concluding that while some small-study effects may exist, they do not fully explain the observed effects. Additionally, it provides supplementary figures on the perception of GenAI misinformation and the efficacy of corrective information.","ai_generated":true,"unit":"ipie-000103#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The risk of bias assessment using the Cochrane RoB 2 protocol indicated that most publications in the sample performed well, with scores ranging from \"low\" to \"moderate\" across most domains. A small number of publications showed a moderate risk of bias, primarily due to the randomization process, and one publication was removed entirely due to numerous concerns regarding random assignment.","ai_generated":true,"unit":"ipie-000103#insight-1","date_modified":"2026-10-23"},{"text":"Analysis of publication selection bias for the post-2021 sample on visual misinformation perception showed no strong statistical evidence of funnel plot asymmetry via Egger's test (p = 0.17). However, the Duval and Tweedie trim-and-fill method suggested a mild asymmetry potentially consistent with small-study bias, though a 3-parameter selection model (3PSM) found no reliable evidence of publication bias.","ai_generated":true,"unit":"ipie-000103#insight-2","date_modified":"2026-10-23"},{"text":"For post-2020 preventive correction information experiments, Egger's test and heterogeneity tests were not significant, and the 3PSM test did not detect publication bias (p = 0.85). Despite this, visual analysis of the funnel plot suggested that smaller studies reporting stronger negative effects might be disproportionately represented.","ai_generated":true,"unit":"ipie-000103#insight-3","date_modified":"2026-10-23"},{"text":"In the full sample of content labeling studies, Egger's test indicated no significant evidence of small-study effects. While trim-and-fill analysis adjusted the overall effect size to g = -0.25 (p < 0.001), the 3PSM test confirmed the effect remained significant with a bias-adjusted effect size of -0.24, indicating that publication bias does not fully account for the observed effect.","ai_generated":true,"unit":"ipie-000103#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["meta-analysis","risk of bias analysis","publication bias assessment"]},{"id":"ipie-000104","url":"https://climateinsightsdirectory.org/document/ipie-000104","title":"Responding to Generative AI Misinformation","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"en","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a155addc27920c702732ffa_GenAI%20and%20Misinfo%20SFP%20Final.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that text-based generative AI misinformation currently poses a greater persuasive risk than visual misinformation. It identifies preventive corrective information as the most consistently effective intervention to reduce the perceived credibility of such content, while noting that content labeling is promising but highly dependent on consistent design and implementation. The authors highlight a critical evidence gap, as current research is heavily concentrated in English-language and high-income countries.","ai_generated":true,"unit":"ipie-000104#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Text-based generative AI misinformation is currently a more significant persuasive threat than visual misinformation. While deepfakes remain risky, evidence suggests that false GenAI-generated text is often viewed as more accurate or believable than true information, whereas visual misinformation is often perceived as less credible than true information in studies conducted after 2021.","ai_generated":true,"unit":"ipie-000104#insight-1","date_modified":"2026-10-23"},{"text":"There is a substantial global knowledge gap because the existing evidence base is primarily limited to English-language and high-income countries, including the USA, United Kingdom, South Korea, the Netherlands, Germany, and Austria. This limitation hinders the development of safeguards for different languages, cultures, and political systems.","ai_generated":true,"unit":"ipie-000104#insight-2","date_modified":"2026-10-23"},{"text":"Preventive corrective information—such as educational warnings or prompts provided before a user encounters misleading content—is the most consistently effective intervention. In studies from after 2020, these measures showed a small to moderate effect in reducing the perceived accuracy and credibility of GenAI misinformation.","ai_generated":true,"unit":"ipie-000104#insight-3","date_modified":"2026-10-23"},{"text":"Content labeling can decrease the perceived credibility of misleading GenAI information, but its effectiveness is inconsistent and depends heavily on the design, wording, and source of the labels. Most evidence for labeling is based on participants in the USA, making its cross-cultural applicability uncertain.","ai_generated":true,"unit":"ipie-000104#insight-4","date_modified":"2026-10-23"},{"text":"The scientific evidence base often lags behind the rapid pace of technological advancement, with many experiments testing older systems like GPT-2 or FaceSwap, meaning current policies may be based on evidence from weaker systems than those currently available to the public.","ai_generated":true,"unit":"ipie-000104#insight-5","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["Austria","Germany","Netherlands","South Korea","United Kingdom","United States"],"frame_perspective":[],"analysis_type":["meta-analysis","randomized controlled trials"]},{"id":"ipie-000106","url":"https://climateinsightsdirectory.org/document/ipie-000106","title":"Répondre à la désinformation générée par l’IA générative","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"fr","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a3b8d43c6f80f520fa37a13_SFP%20FRENCH%20FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed"],"summary":{"text":"The document analyzes the impact of generative AI misinformation, finding that textual misinformation currently poses a higher persuasion risk than visual misinformation. It highlights a significant global data gap, as research is heavily concentrated in high-income, English-speaking countries. Among countermeasures, preventive corrective information is identified as the most consistent intervention for reducing perceived credibility, while content labeling is effective only when applied consistently and with rigorous design.","ai_generated":true,"unit":"ipie-000106#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Text-based misinformation generated by AI is currently more persuasive and poses a greater risk than visual misinformation. While deepfakes remain a risk, recent data indicates that AI-generated fake texts are often perceived as more accurate and credible than truthful information, whereas AI-generated visual misinformation is often seen as less credible than truth.","ai_generated":true,"unit":"ipie-000106#insight-1","date_modified":"2026-10-23"},{"text":"There is a critical lack of global data on generative AI misinformation, with existing research predominantly focused on high-income, English-speaking nations. This creates a knowledge gap regarding how such misinformation operates in different linguistic, cultural, and political environments.","ai_generated":true,"unit":"ipie-000106#insight-2","date_modified":"2026-10-23"},{"text":"Preventive corrective information—such as educational warnings or prompts provided before exposure—is the most consistently effective intervention for reducing the perceived accuracy, credibility, and acceptance of AI-generated misinformation.","ai_generated":true,"unit":"ipie-000106#insight-3","date_modified":"2026-10-23"},{"text":"Content labeling can reduce the perceived credibility of misleading AI information, but its effectiveness is inconsistent and highly dependent on the design, wording, and presentation of the labels.","ai_generated":true,"unit":"ipie-000106#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Austria","Germany","Netherlands","South Korea","United Kingdom","United States"],"frame_perspective":[],"analysis_type":[]},{"id":"ipie-000107","url":"https://climateinsightsdirectory.org/document/ipie-000107","title":"Respuesta a la desinformación generada por inteligencia artificial generativa Resultados de un metaanálisis de la evidencia científica","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"es","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a3b8d4bd9700c3d09dad036_SFP%20SPANISH%20FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that generative AI-produced textual misinformation currently poses a higher persuasion risk than visual misinformation. It identifies preventive corrective information as the most consistently effective intervention for reducing the perceived credibility of such content, while content labeling shows promising but inconsistent results depending on design. The analysis highlights a significant global evidence gap, as most research is concentrated in high-income, English-speaking countries.","ai_generated":true,"unit":"ipie-000107#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Textual misinformation generated by generative AI is currently perceived as more accurate, credible, or plausible than true information, posing a more immediate persuasive risk than visual misinformation such as deepfakes.","ai_generated":true,"unit":"ipie-000107#insight-1","date_modified":"2026-10-23"},{"text":"Preventive corrective information—such as educational warnings or reminders provided before exposure—consistently reduces the perceived accuracy, credibility, or acceptance of generative AI misinformation with a small to moderate effect size.","ai_generated":true,"unit":"ipie-000107#insight-2","date_modified":"2026-10-23"},{"text":"Content labeling can reduce the perceived credibility of misleading generative AI information, but its effectiveness varies significantly based on design, wording, presentation, and the source of the label.","ai_generated":true,"unit":"ipie-000107#insight-3","date_modified":"2026-10-23"},{"text":"There is a substantial global knowledge gap because the current evidence base is heavily concentrated on high-income, English-speaking countries, leaving many regions, languages, and political systems under-researched.","ai_generated":true,"unit":"ipie-000107#insight-4","date_modified":"2026-10-23"},{"text":"The meta-analysis was based on 60 effect estimates from randomized controlled trials extracted from 24 peer-reviewed publications involving 33,801 people, published between 2018 and 2025.","ai_generated":true,"unit":"ipie-000107#insight-5","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["Austria","Germany","Netherlands","South Korea","United Kingdom","United States"],"frame_perspective":[],"analysis_type":["meta-analysis","experimental evidence","randomized controlled trials"]},{"id":"ipie-000108","url":"https://climateinsightsdirectory.org/document/ipie-000108","title":"Реагирование на дезинформацию, создаваемую генеративным ИИ","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ru","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a3b8d51f8e4588d0472af23_SFP%20RUSSIAN%20FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 60 effect estimates from 24 peer-reviewed studies (33,801 participants) published between 2018 and 2025 to evaluate generative AI (GenAI) misinformation. It finds that GenAI-generated text currently poses a higher risk of persuasive impact than visual misinformation. The most consistently effective countermeasure is the preemptive provision of corrective information, while content labeling shows variable effectiveness depending on design and application. The authors highlight a significant global knowledge gap, as research is heavily concentrated in English-speaking, high-income countries.","ai_generated":true,"unit":"ipie-000108#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Text-based misinformation created by GenAI is currently perceived as more accurate, credible, or plausible than authentic information, posing a higher risk of persuasive impact than visual misinformation like deepfakes.","ai_generated":true,"unit":"ipie-000108#insight-1","date_modified":"2026-10-23"},{"text":"The current scientific evidence base is geographically limited, focusing primarily on English-language publications and high-income countries, including Austria, Germany, the Netherlands, South Korea, the UK, and the USA, leaving a significant knowledge gap for other regions and languages.","ai_generated":true,"unit":"ipie-000108#insight-2","date_modified":"2026-10-23"},{"text":"Preemptive corrective information—such as educational warnings or psychological 'inoculation' provided before exposure to content—is the most consistently effective intervention for reducing the perceived accuracy and credibility of GenAI misinformation.","ai_generated":true,"unit":"ipie-000108#insight-3","date_modified":"2026-10-23"},{"text":"Content labeling can reduce the perceived credibility of GenAI misinformation, but its effectiveness is inconsistent and highly dependent on the label's design, wording, presentation, and the source of the label.","ai_generated":true,"unit":"ipie-000108#insight-4","date_modified":"2026-10-23"},{"text":"Scientific research often lags behind the rapid pace of technological development, with many experiments testing outdated systems like GPT-2 or early tools like FaceSwap rather than current state-of-the-art models.","ai_generated":true,"unit":"ipie-000108#insight-5","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["Austria","Germany","Netherlands","South Korea","United Kingdom","United States","Switzerland"],"frame_perspective":[],"analysis_type":["meta-analysis","systematic review"]},{"id":"ipie-000109","url":"https://climateinsightsdirectory.org/document/ipie-000109","title":"التصدي للمعلومات المضللة المنشأة بواسطة الذكاء الاصطناعي التوليدي: نتائج تحليل تجميعي للأدلة العلمية","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"ar","date_published":"2026","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6a3b8d5ddd2fbb0a215c5d7a_SFP%20AR%20FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that text-based generative AI misinformation poses a higher persuasive risk than visual misinformation. It identifies a significant knowledge gap due to research focusing primarily on high-income, English-speaking countries. Among countermeasures, preemptive corrective information is the most consistent and effective intervention, while content labeling shows promising but inconsistent results depending on design and application.","ai_generated":true,"unit":"ipie-000109#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Text-based misinformation generated by generative AI is currently more persuasive and poses a greater risk than visual misinformation. While deepfakes are often perceived as less credible than real content, AI-generated text is frequently seen as more accurate and credible than true information.","ai_generated":true,"unit":"ipie-000109#insight-1","date_modified":"2026-10-23"},{"text":"There is a substantial global knowledge gap because existing research is heavily concentrated in high-income, English-speaking nations such as the US, UK, Germany, Austria, the Netherlands, and South Korea. Less than five percent of screened publications were in languages other than English.","ai_generated":true,"unit":"ipie-000109#insight-2","date_modified":"2026-10-23"},{"text":"Preemptive corrective information—such as brief educational warnings or reminders—is the most consistently effective intervention for reducing the perceived accuracy and credibility of AI-generated misinformation. This effect is most pronounced when individuals are asked to evaluate the content's credibility rather than simply detect the misinformation.","ai_generated":true,"unit":"ipie-000109#insight-3","date_modified":"2026-10-23"},{"text":"Content labeling (using visual or text tags to indicate AI generation) can reduce the perceived credibility of misinformation, but its effectiveness is inconsistent and highly dependent on the specific design, wording, and application of the labels.","ai_generated":true,"unit":"ipie-000109#insight-4","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["Austria","Germany","Netherlands","South Korea","United Kingdom","United States","Switzerland"],"frame_perspective":[],"analysis_type":["meta-analysis","randomized controlled trials"]},{"id":"ipie-000082","url":"https://climateinsightsdirectory.org/document/ipie-000082","title":"人工智能在和平建设中的应用：前景与隐患","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"zh","date_published":"2025-03","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/6909ee86db55b570b239340f_Final%20ZH%20AIPB%20SFP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document examines how AI can support peacebuilding through early warning systems, digital dialogue, and humanitarian mapping, while warning against risks such as digital surveillance, misinformation, and algorithmic bias. It argues that AI must be treated as a supplementary tool governed by human rights and 'do no harm' principles, emphasizing the need for localized models and cross-sector collaboration to prevent the technology from exacerbating instability in fragile regions.","ai_generated":true,"unit":"ipie-000082#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"In humanitarian response, AI tools such as DISHA integrate drone and satellite imagery with crowdsourced reports to create real-time maps of disaster damage and displacement, reducing damage analysis time to one-sixth of previous durations. There is a significant risk, however, that geospatial data could be misused for civilian targeting or suppression of dissent without strict privacy and ethical safeguards.","ai_generated":true,"unit":"ipie-000082#insight-1","date_modified":"2026-10-23"},{"text":"Responsible AI governance in conflict zones is critical because weak regulatory systems can lead to AI being used for surveillance, predictive policing, and algorithmic discrimination. Effective governance must be based on human rights, community consultation, and transparency, with a preference for small-scale, context-specific models over generic ones.","ai_generated":true,"unit":"ipie-000082#insight-2","date_modified":"2026-10-23"}],"climate_tags":["early warning system","human rights","digital divide"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["policy analysis","literature review"]},{"id":"ipie-000071","url":"https://climateinsightsdirectory.org/document/ipie-000071","title":"事实、虚假信息与 候科学 关于提升气候议题信息完整性的建议","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"executive summary","language":"zh","date_published":"2025-02","source_url":"https://cdn.prod.website-files.com/643ecb10be528d2c1da863cb/68ffea8ac6e8e8a98a5d627c_ZH_SFP2025.2%20-%20Facts%20Fakes%20and%20Climate%20Science.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document identifies a strategic shift from outright climate denial to 'strategic doubt,' where influential economic and political actors—including fossil fuel companies and right-wing populist movements—deliberately spread misleading information to obstruct climate action. It highlights that policymakers are primary targets of these campaigns, which are disseminated through traditional media, social media, and non-public corporate channels. The report notes a significant research gap in the Global South and proposes four policy interventions: mandatory standardized carbon reporting, litigation against greenwashing, the creation of cross-sectoral voluntary alliances, and the enhancement of scientific and media literacy for the public and officials.","ai_generated":true,"unit":"ipie-000071#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Climate disinformation has evolved from total denial of the fact of climate change to 'strategic doubt,' which acknowledges climate change as a fact but questions its human causes, the feasibility of solutions, and their cost-effectiveness to delay action.","ai_generated":true,"unit":"ipie-000071#insight-1","date_modified":"2026-10-23"},{"text":"Policymakers, including elected officials and civil servants, are central targets in the communication chain of disinformation, receiving unreliable data through corporate sustainability reports, greenwashing PR, and partisan briefings.","ai_generated":true,"unit":"ipie-000071#insight-2","date_modified":"2026-10-23"},{"text":"Disinformation erodes public trust in climate science and the institutions responsible for translating evidence into policy, creating a vicious cycle where elite-driven skepticism fuels public opposition to climate policies.","ai_generated":true,"unit":"ipie-000071#insight-3","date_modified":"2026-10-23"},{"text":"There is a severe lack of research on climate information integrity in the Global South, while research remains heavily concentrated in the Global North.","ai_generated":true,"unit":"ipie-000071#insight-4","date_modified":"2026-10-23"}],"climate_tags":["obsidian","climate change disinformation","climate policy","greenwashing","fossil fuel industry","climate finance"],"geography_discussed":["Global North","Global South"],"frame_perspective":[],"analysis_type":["systematic review","policy recommendation"]},{"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-000001","url":"https://climateinsightsdirectory.org/document/ipie-000001","title":"Expert Survey on the Global Information Environment 2025: Safeguarding Epistemic Security","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/sfp2025-4","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2025 Expert Survey on the Global Information Environment, involving 438 researchers across 76 countries, examines the state of 'epistemic security'—the reliability of information supply chains. The report finds that while social media can increase political participation, it also drives polarization and distrust in institutions. A significant 66% of surveyed experts reported experiencing harassment, intervention, or chilling effects in their scientific work, with funding constraints and data access remaining primary barriers. Regarding AI, there is strong expert consensus (60%) that AI-generated content should be clearly labeled, and 83% believe such labeling would improve the information environment. The document advocates for treating the information environment as critical infrastructure, recommending independent algorithmic auditing and stronger protections for researchers and journalists.","ai_generated":true,"unit":"ipie-000001#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Social media platforms have a contradictory impact on the information environment, simultaneously increasing political participation and informing users on cultural, economic, and political issues, while also increasing political polarization, populist sentiment, and mental health issues, and decreasing trust in institutions.","ai_generated":true,"unit":"ipie-000001#insight-1","date_modified":"2026-10-23"},{"text":"Researchers studying the information environment face significant professional risks and barriers; 66% of the surveyed community reported harassment, intervention, or chilling effects, and 73% reported some form of harassment, intervention, chilling effect, or self-censorship.","ai_generated":true,"unit":"ipie-000001#insight-2","date_modified":"2026-10-23"},{"text":"The most prevalent obstacles for experts in this field are financial and data-related, with 62% citing funding constraints and 49% citing insufficient data access.","ai_generated":true,"unit":"ipie-000001#insight-3","date_modified":"2026-10-23"},{"text":"There is a strong expert consensus on the need for transparency regarding synthetic content, with 60% stating AI-generated content should be clearly labeled and 83% believing that such labeling would improve the information environment.","ai_generated":true,"unit":"ipie-000001#insight-4","date_modified":"2026-10-23"},{"text":"Experts advocate for systemic safeguards in the AI era, including regular independent audits of algorithms to mitigate bias and promote a diversity of perspectives.","ai_generated":true,"unit":"ipie-000001#insight-5","date_modified":"2026-10-23"},{"text":"A healthy information environment is fundamentally characterized by the availability of accurate information and the presence of diverse voices.","ai_generated":true,"unit":"ipie-000001#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["United States","Western Europe","Brazil","People's Republic of China","Kenya","India","Mexico"],"frame_perspective":[],"analysis_type":["expert survey","policy recommendations"]},{"id":"ipie-000004","url":"https://climateinsightsdirectory.org/document/ipie-000004","title":"AI for Peacebuilding: Promises and Pitfalls","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/sfp2025-3","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document examines the dual-use nature of AI in peacebuilding, highlighting its ability to forecast violence and scale civic inclusion while warning against risks like digital surveillance, algorithmic bias, and the erosion of human-led diplomacy. It argues for a hybrid approach that combines AI tools with local expertise and strict ethical governance to ensure technology supports stability rather than deepening conflict.","ai_generated":true,"unit":"ipie-000004#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"AI can improve early warning systems by identifying precursors to violence—such as hate speech or troop movements—with short-term accuracy up to 95%, though overreliance is risky due to potential errors and biases in data-scarce environments.","ai_generated":true,"unit":"ipie-000004#insight-1","date_modified":"2026-10-23"},{"text":"AI-enabled platforms like Remesh and Talk to the City are scaling civic inclusion in conflict zones, including Libya, Syria, and Yemen, by amplifying marginalized voices and facilitating multilingual consultations.","ai_generated":true,"unit":"ipie-000004#insight-2","date_modified":"2026-10-23"},{"text":"AI-powered mapping, such as the DISHA initiative, accelerates humanitarian response by reducing damage analysis times by a factor of six, but these tools risk being misused for targeting civilians or suppressing dissent.","ai_generated":true,"unit":"ipie-000004#insight-3","date_modified":"2026-10-23"},{"text":"While social media business models often reward polarization, pro-social AI design—such as the Perspective API and Phoenix—can foster constructive online spaces by prioritizing thoughtful narratives over sensationalism.","ai_generated":true,"unit":"ipie-000004#insight-4","date_modified":"2026-10-23"},{"text":"Responsible AI governance is essential in fragile settings where regulatory systems are weak, as without guardrails, AI can facilitate algorithmic discrimination, predictive policing, and surveillance.","ai_generated":true,"unit":"ipie-000004#insight-5","date_modified":"2026-10-23"}],"climate_tags":["early warning system"],"geography_discussed":["Libya","Syria","Yemen"],"frame_perspective":[],"analysis_type":["policy assessment","literature review"]},{"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-000020","url":"https://climateinsightsdirectory.org/document/ipie-000020","title":"Submission to the UK Department for Science, Innovation and Technology Researchers’ Access to Information in the Data (Use and Access) Bill","publisher":{"name":"International Panel on the Information Environment","organization":"international-panel-on-the-information-environment"},"document_type":"statement","language":"en","date_published":"2025","source_url":"https://www.ipie.info/research/tp2025-1","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The International Panel on the Information Environment (IPIE) argues that the UK's Data (Use and Access) Bill must move from discretionary to obligatory language regarding researchers' access to platform data. The IPIE recommends that the Secretary of State be required to set regulations for data access, that platforms bear the costs of this access to ensure equity among researchers, and that enforcement mechanisms be strengthened to prevent platforms from using privacy concerns as a pretext to deny data. These measures are presented as essential for fulfilling the Online Safety Act's goal of making internet services safer for individuals in the United Kingdom.","ai_generated":true,"unit":"ipie-000020#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The IPIE recommends changing the language in Clause 125(2) of the Data (Use and Access) Bill from discretionary to obligatory, replacing the word \"may\" with \"should\" to ensure the Secretary of State is required to set regulations for researchers' access to information.","ai_generated":true,"unit":"ipie-000020#insight-1","date_modified":"2026-10-23"},{"text":"The document argues that the cost of providing data access should be borne by the platforms, websites, and online services themselves to prevent financial barriers from hindering research and to ensure equality for researchers from institutions with less funding.","ai_generated":true,"unit":"ipie-000020#insight-2","date_modified":"2026-10-23"},{"text":"The IPIE expresses concern that open-ended wording in the Bill could allow platforms to disproportionately restrict access by citing privacy concerns, and suggests that the balancing of interests must be conducted holistically.","ai_generated":true,"unit":"ipie-000020#insight-3","date_modified":"2026-10-23"},{"text":"To ensure meaningful implementation, the IPIE recommends that the Bill include specific requirements for platforms to maintain easily accessible APIs and that enforcement provisions be amended to ensure sanctions are proportionate and timely.","ai_generated":true,"unit":"ipie-000020#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["European Union"],"frame_perspective":[],"analysis_type":["policy recommendation"]},{"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-000027","url":"https://climateinsightsdirectory.org/document/ipie-000027","title":"Trends in the Information environment: 2025 Expert Survey Results","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/sr2025-2","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report presents findings from the 2025 IPIE Expert Survey, highlighting a growing pessimism about the future of the information environment. It identifies the availability of accurate information and diverse voices as essential for a healthy environment, while citing lack of platform accountability as a primary threat. The document also examines the mixed impact of social media, the negative perceptions of generative AI, and the increasing barriers faced by researchers, particularly regarding funding and academic freedom.","ai_generated":true,"unit":"ipie-000027#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Experts consistently identify the availability of accurate information and the presence of diverse voices as the most critical components of a healthy information environment. Specifically, 67% of experts view the availability of accurate information as \"absolutely essential\".","ai_generated":true,"unit":"ipie-000027#insight-1","date_modified":"2026-10-23"},{"text":"There is a significant regional divide regarding the primary barriers to media diversity. Experts focusing on developed countries primarily cite the \"dominance of large private media companies\" (32%), whereas those studying developing countries identify \"political control or censorship\" as the top barrier (32%).","ai_generated":true,"unit":"ipie-000027#insight-2","date_modified":"2026-10-23"},{"text":"Lack of platform accountability is viewed as a major threat, with 76% of experts classifying it as a \"big or extreme threat\". Other significant threats include mis/disinformation, polarization, and concentrated media ownership.","ai_generated":true,"unit":"ipie-000027#insight-3","date_modified":"2026-10-23"},{"text":"Generative AI is perceived as having a mostly negative impact on the information environment, with experts expecting these negative effects to increase over the next five years. AI-generated videos are considered more threatening than AI-generated text.","ai_generated":true,"unit":"ipie-000027#insight-4","date_modified":"2026-10-23"},{"text":"Social media is viewed as a double-edged sword: over 75% of experts believe it has increased polarization, populism, and mental health issues, yet more than half believe it has increased political participation.","ai_generated":true,"unit":"ipie-000027#insight-5","date_modified":"2026-10-23"},{"text":"Research barriers have shifted, with funding opportunities (62%) now overtaking data access (49%) as the most frequently mentioned obstacle. US-based experts are particularly likely to report \"government control of funding\" (48%) as a barrier.","ai_generated":true,"unit":"ipie-000027#insight-6","date_modified":"2026-10-23"},{"text":"Researchers face significant personal and professional risks; 23% reported being \"harassed or doxed\", and one-third of experts reported self-censoring on social media due to career concerns.","ai_generated":true,"unit":"ipie-000027#insight-7","date_modified":"2026-10-23"},{"text":"Expert pessimism regarding the future of the information environment has risen steadily from 54% in 2023 to 72% in 2025. In 2025, experts in developed countries (76%) were more pessimistic than those in developing countries (67%).","ai_generated":true,"unit":"ipie-000027#insight-8","date_modified":"2026-10-23"}],"climate_tags":["climate change disinformation"],"geography_discussed":["United States","Brazil","People's Republic of China","Kenya","India","Mexico"],"frame_perspective":[],"analysis_type":["expert survey","comparative analysis","trend analysis"]}]}