{"id":84389,"date":"2026-05-12T16:30:39","date_gmt":"2026-05-12T14:30:39","guid":{"rendered":"https:\/\/www.kwrwater.nl\/?p=84389"},"modified":"2026-05-13T09:50:46","modified_gmt":"2026-05-13T07:50:46","slug":"bringing-people-together-in-the-age-of-ai","status":"publish","type":"post","link":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/","title":{"rendered":"Bringing people together in the age of AI"},"content":{"rendered":"<div class=\"post_intro\">\n<p>This year\u2019s EGU General Assembly marked the 20th anniversary of the conference in Vienna. Over five days, around 20,000 researchers gathered \u2014 in person and online \u2014 to share work, exchange ideas, and connect as a community. The scale of EGU inevitably brings with it a sense of overload and a fear of missing out.<\/p>\n<\/div>\n<p>Rather than trying to attend every session and produce an all\u2011encompassing overview \u2014 an impossible task \u2014 I am taking a piece of advice shared by experienced EGU bloggers: focus on what you do get to see and write about. I accept that my notes reflect only a fraction of my own experience \u2014 which is itself just a fraction of everything that happened at EGU \u2014 and I will let that be enough.<\/p>\n<div class=\"wp-caption alignnone\" style=\"width: 780px\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/EGU_background-780x470.jpg\" alt=\"\" width=\"780\" height=\"470\" \/><p class=\"wp-caption-text\">Image 1. Welcome to the EGU26<\/p><\/div>\n<p>What follows is therefore a personal reflection, shaped by a recurring theme that surfaced across many of the sessions I attended. As AI accelerates our work, the human role in modelling and decision support is not disappearing but becoming more important. In short, AI is not replacing physical models; it is scaling expert judgement around them.<\/p>\n<p>That broader challenge was articulated particularly clearly in a lecture by Thorsten Wagener. He reflected on how our difficulties today extend beyond modelling itself. It is becoming increasingly hard not only to discover and understand patterns in data produced by complex, large\u2011scale models, but also to find, connect, and synthesize knowledge from an ever\u2011growing body of scientific literature. Many later discussions at EGU \u2014 including the high number of talks on large language models supporting literature review and synthesis \u2014 can be seen as responses to this challenge. Yet Thorsten\u2019s main message was not technological, but human:<\/p>\n<blockquote><p><strong><em>\u201cPerhaps the true measure of a profession lies above all in its ability to bring people together.\u201d<\/em><\/strong><\/p>\n<p>&#8211; Antoine de Saint-Exup\u00e9ry, <em>Terre des Hommes (1939)<\/em><\/p><\/blockquote>\n<h2><span class=\"EOP SCXW239852861 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:2,&quot;335559740&quot;:255}\">The researchers&#8217; evolving role in the age of AI<\/span><\/h2>\n<p>A recurring theme across several keynotes and sessions was clear: building, calibrating, and deploying models is becoming faster, easier, and more accessible.<\/p>\n<p>Our community has long defined its expertise by the ability to construct, calibrate, and refine complex modelling processes. Today, AI is beginning to reduce the time and effort required to produce a model or prediction, effectively commodifying parts of this work. This shift raises an important question: as we enter the age of AI, where should researchers focus, and what is our role in the modelling process?<\/p>\n<p>Alden Sampson\u2019s keynote, <strong><em>The Hydrologic Modeler\u2019s Evolving Role in the Age of AI<\/em>,<\/strong> captured this transition with particular clarity \u2014 a framing that readily extends beyond hydrology to researchers more broadly. While this shift may require letting go of aspects of our work that many of us enjoy, the roles that remain are increasingly impactful, and arguably even more rewarding. Alden highlighted two roles that are becoming central:<\/p>\n<ul>\n<li><strong>The translator, <\/strong>who bridges users and science and supports decision\u2011making: translating human challenges into the technical domain, and translating results back to decision\u2011makers<\/li>\n<li><strong>The architect, <\/strong>who defines the problem, writes specifications, formulates precise success criteria, and guides how AI should be implemented and evaluated<\/li>\n<\/ul>\n<p>Both roles hinge on judgement: contextual understanding, ethical awareness, and responsibility \u2014 qualities that cannot be automated.<\/p>\n<p>Rather than viewing this evolution as a loss, we can treat it as an opportunity to focus on the parts of the modelling process where human insight adds the greatest value. Which raises a question worth sitting with:<strong> which role will you choose?<\/strong><\/p>\n<p>This reframing also helps explain why many EGU contributions focused less on \u201cyet another algorithm\u201d and more on workflows, platforms, and integration. Several tangible examples stood out. Baoying Shan presented an intelligent flood\u2011forecasting agent that combines large language models with structured hydrological workflows, explicitly designed to scale expert judgement rather than replace it. In a similar spirit, the SeaScope project demonstrated how agentic AI can link satellite data, scientific literature, and executable analysis workflows, while keeping users in control through transparent code generation and validation. Other contributions, such as the Living AI Platform for Earth System Science presented by \u00d6zge Kart Tokmak, explored how retrieval\u2011augmented systems can help researchers synthesise large and growing bodies of literature in a traceable and auditable way.<\/p>\n<div class=\"wp-caption alignnone\" style=\"width: 780px\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/making-a-decision-780x470.jpg\" alt=\"\" width=\"780\" height=\"470\" \/><p class=\"wp-caption-text\">Image 2. Making a decision<\/p><\/div>\n<h2>High skill does not always qual deep understanding<\/h2>\n<blockquote><p><strong><em>\u201cAll of physics is either impossible or trivial. It is impossible until you understand it, and then it becomes trivial.\u201d<\/em><\/strong><\/p>\n<p>&#8211; Ernest Rutherford<\/p><\/blockquote>\n<p>As models become more powerful, several speakers raised a critical question: what does it mean to learn or understand a system, rather than merely perform well within it.<\/p>\n<p>Hans Korving\u2019s (Deltares) talk on<strong> <em>High skill, shallow learning<\/em> <\/strong>illustrated this tension clearly. He showed how deep\u2011learning models can achieve excellent predictive performance while failing to capture the underlying physical mechanisms. James Kirchner made a closely related point, advocating for more physically informative evaluation metrics and warning that many common performance measures obscure rather than reveal model behaviour.<\/p>\n<p>This distinction between <strong>predictability<\/strong> and <strong>learnability<\/strong> matters not only for how we design and evaluate models, but also for how we educate researchers. If AI tools increasingly smooth over complexity, then education must focus even more on asking the right questions and diagnosing when models mislead.<\/p>\n<p>At the same time, AI undeniably amplifies what a single person can do. It can synthesise vast amounts of information and help cope with one of the defining challenges of our time: an overwhelming and growing volume of data, models, and scientific publications. But this raises an uncomfortable question: will this amplification help us slow down and reflect \u2014 or will it simply push us to do more, faster? It is a question that connects directly to a theme I reflected on earlier this year at the Waterinfodag:<strong> <em>Slowing down in an age of acceleration <\/em><\/strong>(<a href=\"https:\/\/www.kwrwater.nl\/en\/actueel\/data-ai-en-de-digitale-toekomst-van-de-watersector\/\">Data, AI and the digital future of the water sector &#8211; KWR)<\/a>.<\/p>\n<p>These questions become particularly pressing in education. In<strong> <em>Geoscience Education in the Age of Generative AI: What Do Students Actually Learn?<\/em>, <\/strong>Ola Fredin showed that AI is not a future challenge but a present reality in university classrooms. Students already use generative AI extensively \u2014 to structure arguments, analyse data, understand literature, and reduce writing anxiety. The question is therefore not <em>if<\/em> students will use AI, but <em>how<\/em>. Universities will need to adapt if they want to assess what students actually understand, rather than what their tools can produce.<\/p>\n<p>Several tensions surfaced here as well. Students and researchers expressed uncertainty about ethical expectations, including concerns about the environmental cost of AI use: avoiding AI may feel principled, but can also mean falling behind peers who do use it. Teaching the next generation of researchers will therefore require more than technical guidelines. It will require helping researchers learn how to work with AI \u2014 using it as an assistant and amplifier \u2014 while retaining responsibility for judgement, reflection, and understanding.<\/p>\n<h2><span class=\"EOP SCXW239852861 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:2,&quot;335559740&quot;:255}\">Uncertainty: from something to eliminate to something to work with<\/span><\/h2>\n<p>Across many sessions at EGU, uncertainty was no longer framed as a technical inconvenience to be reduced, but as a fundamental condition we need to learn how to work with. Whether discussing carbon budgets and overshoot, extreme events, groundwater competition, or cascading infrastructure failures, uncertainty repeatedly emerged as structural rather than accidental.<\/p>\n<p>Several climate\u2011focused talks made this point explicit. Assumptions that often underpin policy \u2014 such as linear temperature responses or small zero\u2011emission commitments \u2014 were shown to rely on fragile compensations within Earth system models. As one speaker reminded us: <em>\u201cClimate is an angry beast and we are poking at it with sticks.\u201d<\/em> The message was clear: even our most refined models cannot fully tame uncertainty.<br \/>\nMany contributions therefore turned to <strong>storylines and scenarios<\/strong> as complementary ways of exploring possible futures. Rather than predicting outcomes, storylines trace physically self\u2011consistent unfoldings of past or plausible events, without assigning probabilities, making uncertainty explicit and discussable.<\/p>\n<p>Across applications \u2014 from extreme\u2011event storylines to participatory scenarios for groundwater management, drought adaptation, and climate\u2011risk communication \u2014 storylines were used to explore interdependencies and cascading impacts that are difficult to capture in single models. Speakers repeatedly emphasized that storylines do not replace models, but <strong>contextualize and complement them<\/strong>, connecting quantitative results to human experience, governance choices, and societal values.<\/p>\n<p>What stood out was how often this work was <strong>co\u2011created<\/strong> with stakeholders, artists, and local communities. Through participatory workshops, narrative images, and art\u2013science collaborations, uncertainty was treated not as something to hide, but as something to be shared and discussed.<\/p>\n<p>Taken together, these contributions point to an important shift: in a world of deep uncertainty, the goal is no longer to eliminate ambiguity, but to <strong>make it governable<\/strong> \u2014 requiring not only better models, but also better narratives that support judgement and decision\u2011making.<\/p>\n<h2><span class=\"EOP SCXW239852861 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:2,&quot;335559740&quot;:255}\">Narrative and art as tools for sense-making<\/span><\/h2>\n<p>A recurring theme at EGU this year was the growing role of narrative, visualisation, and artistic practice in scientific work. This is not a recent development: EGU has been investing in the connection between art and science for several years, most visibly through its Artist\u2011in\u2011Residence programme.<\/p>\n<p>Several sessions showed how storylines can be made tangible through visual and participatory methods. Work on \u201cnarrative images\u201d for urban water adaptation in Hamburg, for example, visualised alternative futures as distinct cities in 2050 \u2014 ranging from coping to transformative adaptation. These images created shared entry points into complex socio\u2011ecological dynamics that are difficult to grasp through text or equations alone.<\/p>\n<p>This resonated strongly with our own experiences at KWR through the<strong> Artist\u2011in\u2011Residenc<\/strong>e program with Mariko Hori. As presented by Joost van Summeren, the value of such collaborations lies not only in illustrating or communicating science \u2014 the most common instrumental approach \u2014 but in creating a space where artistic and scientific practices genuinely challenge one another. In this <strong>synergistic<\/strong> approach, artists and scientists engage in an equitable interaction, jointly shaping the questions, narratives, language, and outcomes of the process.<\/p>\n<div class=\"wp-caption alignnone\" style=\"width: 780px\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/Joost_Mariko-780x470.jpg\" alt=\"\" width=\"780\" height=\"470\" \/><p class=\"wp-caption-text\">Image 3. Joost presenting \u201cArt\/Science collaborations for transformative change in the water sector\u201d<\/p><\/div>\n<h2><span class=\"EOP SCXW239852861 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:2,&quot;335559740&quot;:255}\">Digital water and interconnected urban infrastructure<\/span><\/h2>\n<p>These themes also came together in the session I convened at EGU, together with Andrea Cominola, Stefano Alvisi, Janelcy Alferes, and Robert Sitzenfrei, on Digital Water and Interconnected Urban Infrastructure. The session explored how digitalization is transforming urban water systems \u2014 and how increasing interconnections with other infrastructures demand new approaches that explicitly embrace complexity, uncertainty, and integration across scales.<\/p>\n<p>A solicited talk by Riccardo Taormina (TU Delft) framed the discussion around two emerging paradigms in AI: foundational models and intelligent agents. Using examples from urban drainage and wastewater treatment, including recent work with Waternet and Waterschap Amstel, Gooi en Vecht, Riccardo illustrated how AI systems can act as fast, robust surrogates for traditional simulators. Crucially, he also highlighted that these foundational models still rely on physics\u2011based simulators to learn from, effectively becoming foundational surrogates rather than replacements.<\/p>\n<p>Other contributions underscored the importance of keeping digital approaches both explainable and operationally relevant. Ines Mastouri presented an ensemble\u2011learning approach for leakage localisation in water distribution networks that explicitly combines performance with transparency, linking model output to inspection effort through a physically interpretable metric. Stefano Alvisi showed how high\u2011resolution pressure sensors can be used to infer residential water\u2011use patterns \u2014 an approach that is gaining attention as an alternative to smart\u2011meter\u2011based methods. Unlike flow meters, pressure sensors offer technical and economic advantages, while still enabling fine\u2011grained insight into water\u2011use behaviour when combined with appropriate modelling and signal processing. Together, these examples illustrate how digital methods can unlock new insights while remaining grounded in physics and directly usable in practice.<\/p>\n<div class=\"wp-caption alignnone\" style=\"width: 576px\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/Ina-576x470.jpg\" alt=\"\" width=\"576\" height=\"470\" \/><p class=\"wp-caption-text\">Image 4. Ina convening the session on Digital Water and Interconnected Urban Infrastructure. together with Andrea Cominola (TU Berlin), Stefano Alvisi (University of Ferrara), Janelcy Alferes (Vito) and Robert Sitzenfrei (University of Innsbruck)<\/p><\/div>\n<h2><span class=\"EOP SCXW239852861 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:2,&quot;335559740&quot;:255}\">A conference that brings people together<\/span><\/h2>\n<p>Beyond the content, what always gives me a warm feeling at EGU is the atmosphere: informal, open, curious, and constructive. In that sense, EGU26 brought me back to the line that framed this reflection: <em>\u201cPerhaps the true measure of a profession lies above all in its ability to bring people together.\u201d<\/em> As our tools become more powerful and our models more sophisticated, this ability matters more, not less.<\/p>\n<p>All of this is inspiring and reinforces our ambitions within the Hydroinformatics domain at KWR, particularly in the fields of <em>Data Science and AI<\/em> and <em>Integrated Infrastructure Modelling<\/em>. At the same time, the discussions at EGU strongly resonate with our broader digital ambitions to invest in a <em>shared digital knowledge infrastructure<\/em> together with the drinking water utilities \u2013 which serves both as a facilitating platform and as a flywheel: enabling exchange and implementation, while stimulating research, innovation, and adoption across the drinking water sector.<\/p>\n<p>Seen this way, the insights from EGU26 do not stand apart from our daily work. They actively contribute to the direction set out in our KWR Masterplan, where digital transformation is ultimately about strengthening judgement, collaboration, and responsible decision\u2011making in an increasingly complex water system.<\/p>\n<div class=\"wp-caption alignnone\" style=\"width: 780px\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/conveners2-780x470.jpg\" alt=\"\" width=\"780\" height=\"470\" \/><p class=\"wp-caption-text\">Image 5. Conveners of the session on Digital Water and Interconnected Urban Infrastructure. From left to right: Robert Sitzenfrei (University of Innsbruck), Stefano Alvisi (University of Ferrara), Ina Vertommen and with Andrea Cominola (TU Berlin)<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>At EGU26, advances in AI, modelling, uncertainty, and digital platforms highlighted a shift in the role of researchers. As systems become more complex and interdependent \u2014 while models simultaneously become faster, more accessible, and more powerful \u2014 the focus is shifting from building tools to exercising judgement: making sense of uncertainty, connecting knowledge, and supporting responsible decision making. These reflections show why bringing people together around shared understanding remains essential for addressing complex societal challenges.<\/p>\n","protected":false},"author":76,"featured_media":84391,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[631],"tags":[1925],"class_list":["post-84389","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog-en","tag-water-resource-management","gtag-drinking-water","gtag-climate","gtag-distribution-networks","gtag-horizon-scanning","gtag-freshwater","gtag-citizen-participation","gtag-leakage","gtag-hydrology","gtag-water-infrastructure","gtag-water-meters","gtag-water-management-en","gtag-resilience"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Bringing people together in the age of AI - KWR<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bringing people together in the age of AI - KWR\" \/>\n<meta property=\"og:description\" content=\"At EGU26, advances in AI, modelling, uncertainty, and digital platforms highlighted a shift in the role of researchers. As systems become more complex and interdependent \u2014 while models simultaneously become faster, more accessible, and more powerful \u2014 the focus is shifting from building tools to exercising judgement: making sense of uncertainty, connecting knowledge, and supporting responsible decision making. These reflections show why bringing people together around shared understanding remains essential for addressing complex societal challenges.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\" \/>\n<meta property=\"og:site_name\" content=\"KWR\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/KWRwater\/\" \/>\n<meta property=\"article:published_time\" content=\"2026-05-12T14:30:39+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-13T07:50:46+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/conveners2.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1920\" \/>\n\t<meta property=\"og:image:height\" content=\"1440\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Amber Ammerlaan\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@KWR_water\" \/>\n<meta name=\"twitter:site\" content=\"@KWR_water\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Amber Ammerlaan\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"12 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\"},\"author\":{\"name\":\"Amber Ammerlaan\",\"@id\":\"https:\/\/www.kwrwater.nl\/en\/#\/schema\/person\/43ddbf39b03a439807a25c203b25dcfc\"},\"headline\":\"Bringing people together in the age of AI\",\"datePublished\":\"2026-05-12T14:30:39+00:00\",\"dateModified\":\"2026-05-13T07:50:46+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\"},\"wordCount\":2238,\"publisher\":{\"@id\":\"https:\/\/www.kwrwater.nl\/en\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/conveners2.jpg\",\"keywords\":[\"Water resource management\"],\"articleSection\":[\"Blog\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\",\"url\":\"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/\",\"name\":\"Bringing people together in the age of AI - 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As systems become more complex and interdependent \u2014 while models simultaneously become faster, more accessible, and more powerful \u2014 the focus is shifting from building tools to exercising judgement: making sense of uncertainty, connecting knowledge, and supporting responsible decision making. These reflections show why bringing people together around shared understanding remains essential for addressing complex societal challenges.","og_url":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/","og_site_name":"KWR","article_publisher":"https:\/\/www.facebook.com\/KWRwater\/","article_published_time":"2026-05-12T14:30:39+00:00","article_modified_time":"2026-05-13T07:50:46+00:00","og_image":[{"width":1920,"height":1440,"url":"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/conveners2.jpg","type":"image\/jpeg"}],"author":"Amber Ammerlaan","twitter_card":"summary_large_image","twitter_creator":"@KWR_water","twitter_site":"@KWR_water","twitter_misc":{"Written by":"Amber Ammerlaan","Est. reading time":"12 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/#article","isPartOf":{"@id":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/"},"author":{"name":"Amber Ammerlaan","@id":"https:\/\/www.kwrwater.nl\/en\/#\/schema\/person\/43ddbf39b03a439807a25c203b25dcfc"},"headline":"Bringing people together in the age of AI","datePublished":"2026-05-12T14:30:39+00:00","dateModified":"2026-05-13T07:50:46+00:00","mainEntityOfPage":{"@id":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/"},"wordCount":2238,"publisher":{"@id":"https:\/\/www.kwrwater.nl\/en\/#organization"},"image":{"@id":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/#primaryimage"},"thumbnailUrl":"https:\/\/www.kwrwater.nl\/wp-content\/uploads\/2026\/05\/conveners2.jpg","keywords":["Water resource management"],"articleSection":["Blog"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/","url":"https:\/\/www.kwrwater.nl\/en\/actueel\/bringing-people-together-in-the-age-of-ai\/","name":"Bringing people together in the age of AI - 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