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DTSTART;TZID=America/New_York:20260910T100000
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SUMMARY:The Label Paradox: Can AI Transparency Create More Distrust? | AI\, Media\, and Democracy Lab
DESCRIPTION:Our hopes are pinned on AI labels. AI labels are expected to help users navigate an increasingly synthetic information environment by distinguishing fact from fiction\, human from machine. Beginning in August 2025\, the EU AI Act requires professional users of GenAI\, including journalists\, advertisers\, political actors\, governments\, and public institutions\, to disclose AI-generated content. The EU AI Office has already proposed concrete approaches for what such labels should look like. \nWith these labels becoming governance mechanisms of trust online\, some crucial questions remain largely unanswered – what if labels do not work as intended? What if they produce unintended consequences\, or even undermine the very conditions of trust they are designed to protect? \nWhile public support for AI transparency is high\, and mandatory AI labels are an important step towards more transparency on AI for users\, we still know surprisingly little about how labels shape user perceptions\, platform behavior\, and information ecosystems. Does a “Generated with AI” label erode trust in content that is actually accurate and reliable? Does the absence of a label become a proxy for authenticity\, regardless of whether content is actually trustworthy? How do users interpret or strategically mobilize labels in politically polarized environments? And could mandatory labeling create a two-tier information ecosystem in which labeled content is dismissed while unlabeled content receives unearned credibility? \nThese questions become even more pressing in contexts such as journalism\, elections\, activism\, war reporting\, and platform moderation\, where trust and authenticity are already highly contested. Our online panel brings together experts in AI regulation\, media studies\, cognitive psychology\, computational linguistics\, and platform governance to explore the promises\, limits\, and unintended consequences of AI labeling. Together\, we will zoom out and investigate AI labels and their implications as part of the broader information ecosystem. Which problems exactly can AI labels solve\, which not\, and when do they backfire. \nClick here to learn more and register to attend. Note: This webinar is taking place in Central European Summer Time (UTC+2). Event details below are listed in ET (GMT-5). 
URL:https://mediawell.ssrc.org/event/the-label-paradox-can-ai-transparency-create-more-distrust-ai-media-and-democracy-lab/
LOCATION:Virtual
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260910T110000
DTEND;TZID=America/New_York:20260910T123000
DTSTAMP:20261022T234014
CREATED:20260901T161419Z
LAST-MODIFIED:20260901T161419Z
UID:517722-1789038000-1789043400@mediawell.ssrc.org
SUMMARY:LLMs are the Third Wave of Automated Content Moderation | Penn MEDIATED
DESCRIPTION:Content moderation is critical to protecting users against harmful and illegal online content\, although it may also restrict free expression. Over the past two decades\, platforms have increasingly turned to automation to perform content moderation at scale. First through hashing algorithms and later through predictive machine learning methods\, many large platforms have automated over 90% of content moderation actions. Today\, online platforms are increasingly exploring using large language models (LLMs)\, as a new component of the content moderation technology stack. With online platforms conducting mass layoffs of trust and safety teams\, while also increasing investments in their AI development\, this convening will explore how LLMs fit in the content moderation landscape and what that means for platforms\, policymakers\, and users. \nThis convening brings together researchers\, technologists\, and practitioners to examine what this third wave of automated content moderation means in practice. We will explore how LLMs are being deployed by platforms today\, how they compare to prior automated systems\, and what the emerging research in this space tells us. We will hear from experts who are building their own custom systems using LLMs for content moderation and researchers who study their implications for information integrity. The conversation will also examine the policy environment shaping adoption: regulatory frameworks in the EU\, Brazil and India\, are setting new expectations for the speed and transparency of content moderation decisions\, incentivizing further automation by online platforms. We will share a pre-read working paper on this topic in advance of this event. [Register at this link]
URL:https://mediawell.ssrc.org/event/llms-are-the-third-wave-of-automated-content-moderation-penn-mediated/
LOCATION:Virtual
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260915T140000
DTEND;TZID=America/New_York:20260915T150000
DTSTAMP:20261022T234014
CREATED:20260908T151621Z
LAST-MODIFIED:20260908T151621Z
UID:517806-1789480800-1789484400@mediawell.ssrc.org
SUMMARY:Global Guardrails for Agentic AI: Can the UN\, or Anybody Else\, Provide Them? | Carnegie Endowment for International Peace
DESCRIPTION:Dramatic advances in agentic AI models are rapidly outpacing governance responses\, raising profound safety concerns and even questions about the future of civilization. As these capabilities explode\, the world needs guardrails to minimize AI risks while allowing humanity to reap its rewards. But who\, precisely\, is best placed to shape the contours of such a regime? \nThe United Nations aims to lead the AI governance agenda\, but its aspirations collide headlong with two realities. First\, the United States and China\, the two main AI players\, are locked in a fierce rivalry to dominate this frontier technology. Second\, most AI capabilities rest in the hands of private companies locked in zero-sum competition of their own. Given these dynamics\, what can the UN realistically hope to accomplish in this arena? \nAs the world convenes in New York for the opening of the 81STsession of the UN General Assembly\, please join Carnegie’s Stewart Patrick in conversation with Lucia Velasco\, co-director of the Oxford AI Diplomacy Lab\, and Scott Singer\, co-director of Carnegie’s China AI Initiative. Our speakers will identify priorities for the governance of agentic AI and suggest potential pathways for establishing needed guardrails. The discussion will consider the relative roles of the UN\, major and middle powers\, subnational actors\, and tech companies themselves in any future governance arrangements.
URL:https://mediawell.ssrc.org/event/global-guardrails-for-agentic-ai-can-the-un-or-anybody-else-provide-them-carnegie-endowment-for-international-peace/
LOCATION:Virtual
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260916T140000
DTEND;TZID=America/New_York:20260916T150000
DTSTAMP:20261022T234014
CREATED:20260903T185237Z
LAST-MODIFIED:20260903T185237Z
UID:517742-1789567200-1789570800@mediawell.ssrc.org
SUMMARY:Governing AI: Policy\, Power\, and Accountability in the Age of Artificial Intelligence | Center for Transformative Media
DESCRIPTION:Artificial intelligence is no longer an emerging technology — it is already embedded in hiring\, healthcare\, public infrastructure\, and democratic processes\, yet the institutions meant to govern it remain incomplete and unevenly distributed across global contexts.\n\nThis webinar treats AI governance as a political and cultural question rather than a technical one: who sets the rules\, whose values are encoded in them\, and what accountability is possible when systems operate across borders and communities.\n\nDrawing on applied ethics\, media and communication studies\, and labor-centered approaches to AI policy\, the conversation traces how regulation is shaped from above\, through legislation\, industry self-governance\, and international bodies\, and contested from below\, through worker organizing\, civil society advocacy\, and grassroots demands for digital sovereignty. Moderated by John Wihbey\, the session brings researchers into dialogue with each other and the audience around the tensions\, possibilities\, and stakes of governing AI as a medium of social and political life.
URL:https://mediawell.ssrc.org/event/governing-ai-policy-power-and-accountability-in-the-age-of-artificial-intelligence-center-for-transformative-media/
LOCATION:Virtual
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20260916T170000
DTEND;TZID=Europe/Helsinki:20260916T180000
DTSTAMP:20261022T234014
CREATED:20260902T122844Z
LAST-MODIFIED:20260902T123335Z
UID:517731-1789578000-1789581600@mediawell.ssrc.org
SUMMARY:IPIE Global Expert Survey 2026 - Launch Webinar
DESCRIPTION:“For the fourth year running\, we asked experts who study the information environment what they’re seeing in their respective countries. The answer is sobering: three in four experts now expect it to worsen over the next year\, the highest level we’ve recorded since the survey began. \nJoin us on 16 September at 18:00 CEST for a virtual briefing on the findings of the IPIE‘s Global Expert Survey 2026\, drawn from 470 experts across 71 countries. \nWhat you will hear: \n\nWhy unaccountable platforms\, not generative AI\, remain experts’ biggest concern\nAn increasing concern over generative AI\, especially AI generated video\nWhat AI summaries in search engines mean for news traffic and the diversity of viewpoints people see\nWhy funding and data access are making the information environment harder to study.”\n\nClick here to register to attend. Note: Event details are listed in CEST (UTC+2). 
URL:https://mediawell.ssrc.org/event/ipie-global-expert-survey-2026/
LOCATION:Virtual
CATEGORIES:Webinar
ORGANIZER;CN="International Panel on the Information Environment (IPIE)":MAILTO:Contact@IPIE.info
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BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20260917T143000
DTEND;TZID=Europe/Helsinki:20260917T153000
DTSTAMP:20261022T234014
CREATED:20260903T152439Z
LAST-MODIFIED:20260903T152439Z
UID:517736-1789655400-1789659000@mediawell.ssrc.org
SUMMARY:Reject then launder: Catching AI Models validating extremist narratives in crisis | EU Disinfo Lab
DESCRIPTION:What happens when you ask AI chatbots about a crisis or terror attack? While models are programmed to block violent content\, real-world audits reveal a concerning phenomenon: “Reject then launder.” \nChatbots initially condemn the violence to pass safety filters\, only to immediately validate and whitewash the underlying extremist ideology in their response. Crucially\, this is not a real-time data gap where models simply lack confirmed facts during a breaking story. Through real-world case studies\, including an audit of nine frontier LLMs on the 2011 Norway terror attack and social feed dynamics from the Bondi Beach shooting\, this session proves the core issue is not a shortage of information\, but a fundamental flaw in how LLMs process and reason through ideology. \nIn this webinar\, speakers from Factiverse and SimPPL will dive into these real case study findings. Beyond LLM vulnerabilities\, the session will explore how unverified viral posts and faulty AI outputs rapidly become the “accepted record” during high-stakes crises\, providing practical\, cost-effective frameworks for researchers\, fact-checkers\, and policymakers to audit these environments. \nNote: Event details are listed in CEST (UTC+2).
URL:https://mediawell.ssrc.org/event/reject-then-launder-catching-ai-models-validating-extremist-narratives-in-crisis-eu-disinfo-lab/
LOCATION:Virtual
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260923T160000
DTEND;TZID=America/New_York:20260923T173000
DTSTAMP:20261022T234014
CREATED:20260806T190633Z
LAST-MODIFIED:20260806T190704Z
UID:517573-1790179200-1790184600@mediawell.ssrc.org
SUMMARY:Co-Opting AI: Archives
DESCRIPTION:Co-Opting AI: Archives will examine how archives and archiving—as infrastructure\, epistemology\, and social practice—relate to contemporary AI systems. \nThe session will be recorded for those who cannot attend live – make sure to register to receive notification when the video is available to view.
URL:https://mediawell.ssrc.org/event/co-opting-ai-archives/
LOCATION:Virtual
CATEGORIES:Webinar
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