{"query_echo":{"q":"","filters":{"analysis_type":["randomized controlled trials"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'randomized controlled trials' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":5,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=randomized+controlled+trials","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-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-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. 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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-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. 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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"]}]}