{"id":94235,"date":"2026-04-10T18:35:48","date_gmt":"2026-04-10T16:35:48","guid":{"rendered":"https:\/\/schaltzeit.com\/?p=94235"},"modified":"2026-04-10T19:17:18","modified_gmt":"2026-04-10T17:17:18","slug":"denken-wir-ki-zu-eng","status":"publish","type":"post","link":"https:\/\/schaltzeit.com\/en\/denken-wir-ki-zu-eng\/","title":{"rendered":"Are we thinking too narrowly when it comes to AI?"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"94235\" class=\"elementor elementor-94235\" data-elementor-settings=\"{&quot;element_pack_global_tooltip_width&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_widescreen&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_laptop&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_tablet_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_mobile_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_padding&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_widescreen&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_laptop&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_tablet_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_mobile_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_widescreen&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_laptop&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_tablet_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_mobile_extra&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true}}\" data-elementor-post-type=\"post\">\n\t\t\t\t<div class=\"elementor-element elementor-element-295be4e e-con-full e-flex e-con e-parent\" data-id=\"295be4e\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5479294 elementor-widget elementor-widget-text-editor\" data-id=\"5479294\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\tWhat happens when AI stops operating through language and starts modelling the world directly? On World Models, the limitations of language models, and the question of what we actually want AI to achieve.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4a92cdf elementor-widget elementor-widget-text-editor\" data-id=\"4a92cdf\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Where are developements of AI actually heading right now?<\/h3><p>Yann LeCun \u2014 Turing Award laureate and longtime Chief AI Scientist at Meta \u2014 launched a new startup in Paris in March 2026: AMI Labs (Advanced Machine Intelligence Labs). Seed funding of around \u20ac890 million, from investors including Nvidia, Samsung, Toyota, and Jeff Bezos. The largest round of its kind in Europe.<br \/>What caught our attention wasn't the amount. It was a single sentence on the startup's website:<\/p><p><em>\u201cReal intelligence does not start in language. It starts in the world.\u201d<\/em><\/p><p>The sentence isn\u2019t revolutionary \u2014 but it opens a window. Because it raises a question we keep coming back to at Schaltzeit: Where is the development of AI actually taking us and our work? What can and should AI do for us? Have we been too focused on large language models since the breakthrough of LLMs during the last years?<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-398d7bb e-flex e-con-boxed e-con e-parent\" data-id=\"398d7bb\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[],&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-10bac72 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"10bac72\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-info-circle\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">In a nutshell: LLMs and World Models<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\n\t\t\t<img fetchpriority=\"high\" decoding=\"async\" class=\"e-image-base e-da6f21c-0c0376d\" data-interaction-id=\"da6f21c\" data-e-type=\"widget\" data-id=\"da6f21c\" id=\"94237\" src=\"https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN.jpg\" width=\"1920\" height=\"1080\" srcset=\"https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN.jpg 1920w, https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN-300x169.jpg 300w, https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN-1024x576.jpg 1024w, https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN-768x432.jpg 768w, https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN-1536x864.jpg 1536w, https:\/\/schaltzeit.com\/wp-content\/uploads\/2026\/04\/Grafik_World_Models_Text_EN-18x10.jpg 18w\" alt=\"Grafik World Models\" title=\"\">\n\t\t\t\t\t<div class=\"elementor-element elementor-element-e998c09 elementor-widget elementor-widget-text-editor\" data-id=\"e998c09\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><strong>LLMs (Large Language Models)<\/strong> like ChatGPT, Claude, or Gemini learn from vast amounts of text. They recognise statistical patterns in language and use them to generate responses that simulate human communication. Their \u2018worldview\u2019 is always mediated by language: what isn\u2019t written down simply doesn\u2019t exist for them.<\/p>\n\n<p><strong>World Models<\/strong> take a fundamentally different approach: they build an internal model of the physical world and simulate cause and effect within it \u2014 much like toddlers who learn through touch, movement, and observation before they can even speak. This approach is seen as especially promising for AI robotics and physical interaction.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a07fe27 e-con-full e-flex e-con e-parent\" data-id=\"a07fe27\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2524789 elementor-widget elementor-widget-text-editor\" data-id=\"2524789\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Where language models fall short<\/h3><p>Anyone working with ChatGPT, Claude, or Gemini today quickly sees how well these systems can analyse texts, build arguments, and write creatively. Impressive. And at the same time, that very impressiveness conceals a structural problem: language always encodes what already exists. What people have already thought, experienced, and written down feeds into the training data. What hasn\u2019t yet been put into words \u2013 new connections, unnamed phenomena, embodied or intuitive knowledge \u2013 simply remains invisible to language models.<\/p><p>For those of us working in foresight, this isn\u2019t an abstract problem. The foresight researcher and philosopher of science Armin Grunwald has described it precisely: the future doesn\u2019t exist as an empirically researchable fact \u2013 it\u2019s only ever accessible through language, through scenarios, narratives, images, metaphors. We negotiate the future in our language. And in doing so, we carry all the blind spots of language into our anticipation of futures.<\/p><p>Wittgenstein\u2019s proposition \u2018The limits of my language are the limits of my world\u2019 applies to language models too. Perhaps especially to them.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c149fee elementor-widget elementor-widget-text-editor\" data-id=\"c149fee\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>World Models: an alternative paradigm gains momentum<\/h3><p>LeCun\u2019s answer to this limitation: World Models. The idea is that AI shouldn\u2019t learn about the world through text patterns, but build an internal model of the physical world. Like a toddler learning about gravity by falling. Not by reading a Wikipedia article on gravity.<\/p><p>And LeCun isn\u2019t alone. World Labs (also funded at around one billion US dollars), Meta with its JEPA architecture, and Google with Genie 3 are all working on similar approaches in parallel. What we\u2019re witnessing here is no fringe project but maybe rather a paradigm shift taking shape in AI research.<\/p><p>What would that change in practice? An AI that no longer views the world through human language could recognise patterns for which we don\u2019t yet have words. It could model connections that don\u2019t yet fit into our linguistic categories. That makes it exciting \u2014 and at the same time harder to get a handle on.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e95a38 elementor-widget elementor-widget-text-editor\" data-id=\"3e95a38\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>The black box grows \u2013 what does that mean for us?<\/h3><p>With LLMs, we at least have a linguistic surface to work with. We can observe which language a model uses, which metaphors it favours, which futures it frames as \u2018normal\u2019 or \u2018inevitable\u2019. Hermeneutic methods, the systematic interpretation and questioning of texts, still have traction here for us as human foresight experts.<\/p><p>World Models remove that lever, at least in part. Once the processing logic is no longer organised linguistically, we lose the surface where we can reflect on and critically evaluate interpretive patterns.<\/p><p class=\"translation-block\">We know this problem from our own practice. For example <a href=\"https:\/\/schaltzeit.com\/en\/black-box-workshopkonzept-framework-zur-diskussion-von-anforderungen-an-ki-und-intuition-in-entscheidungsfindungsprozessen\/\">our BLACK BOX workshop concept, developed for the Kapitel 21 AI conference<\/a> back then, made this tension tangible: both human intuition and AI decision logic are opaque in their processing. Input and output are visible, but what happens in between is not. With World Models, that black box extends. And the questions we raised in the workshop become more urgent.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fa9d3cb elementor-widget elementor-widget-text-editor\" data-id=\"fa9d3cb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Three starting points that remain<\/h3><p>Does that mean reflection is no longer possible? We don\u2019t think so. We see three starting points:<\/p><p><strong>The framing stays linguistic.<\/strong> What we ask a World Model, how we define the problem, what goals we set \u2013 all of that remains shaped by human language. And that\u2019s exactly where we can still intervene: in the questions we ask, and the assumptions embedded in them.<\/p><p><strong>From process analysis to impact assessment.<\/strong> Perhaps we have to accept that we can no longer ask: \u2018How did the model arrive at this result?\u2019 But we can ask: \u2018What kind of world does this result lead us towards?\u2019 shifting the focus from understanding the process to evaluating the consequences an inherent conditions.<\/p><p><strong>Collective negotiation gains importance.<\/strong> When no one fully understands what\u2019s happening inside the model, the question of whether a result is acceptable becomes even more of a social question. Teams, organisations, democratic publics \u2013 all of them will be increasingly called upon to collectively decide what to do with AI-generated results.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f35fd58 elementor-widget elementor-widget-text-editor\" data-id=\"f35fd58\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Understanding the world without experiencing it \u2013 is that possible?<\/h3><p>World Models promise an understanding of the world beyond language. But they remain bodiless. They model the physical world mathematically \u2013 yet have no access to what shapes human learning so fundamentally: lived experience. A toddler learns about gravity through falling and pain. Not through an equation.<br \/>Behind this lies a question bigger than the technology: can something that grasps the world without a body and without social embeddedness actually understand what we intend to do with it? What is desirable, what is just, what is worthy of human dignity \u2013 that doesn\u2019t emerge from equations. It emerges from shared experience, from conversations, from conflicts, from living together.<\/p><p>And perhaps that\u2019s precisely the point not to lose sight of, amid all the excitement about World Models: language isn\u2019t just a limitation. It\u2019s also a tool of empowerment. We negotiate justice, dignity, and visions for the future in language. Political and social movements are always also struggles over language \u2013 over concepts, metaphors, narratives. This capacity to reflect on ourselves through language is a democratic asset.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34e587a elementor-widget elementor-widget-text-editor\" data-id=\"34e587a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>What this means for foresight \u2013 four thoughts<\/h3><ol><li><strong>Linguistic reflection remains indispensable.<\/strong> Precisely because AI may increasingly operate beyond language, we need people who can interpret results, contextualise them, and relate them to values. Hermeneutic competence becomes even more important.<\/li><li><strong>Participatory processes need to become more robust.<\/strong> The less we can trace how an AI system arrives at its results, the more we need social mechanisms of accountability \u2013 in teams, in organisations, in public debate.<\/li><li><strong>The question \u2018which AI, for what?\u2019 becomes more pressing.<\/strong> \u2018Should we use AI?\u2019 is already an outdated question. What kind of AI, for what goal, under what conditions, that\u2019s what we ask ourselves in many projects. World Models broaden the spectrum and may make the decision more demanding.<\/li><li><strong>The question of the future remains a human one.<\/strong> AI World Models may model the world more precisely than language can. But which world we want to build \u2013 that\u2019s still a normative question. And normativity doesn\u2019t emerge from mathematical models. It emerges between people.<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5158f5b elementor-widget elementor-widget-text-editor\" data-id=\"5158f5b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>A productive paradigm shift<\/h3><p>LeCun has reopened an old question: is intelligence possible without language? For those of us in foresight, it leads to one of our own: Is foresight conceivable without language?<\/p><p>Our provisional answer: probably not. But the question is worth asking. World Models might open up new possibilities for recognising connections that can\u2019t yet be put into words. Thereby they will challenge us to organise reflection of ist results differently. And they remind us that working with AI is ultimately not about the technology \u2013 but about the questions we bring to it.<\/p><p><em>What do you think: how do World Models change our understanding of foresight? What questions does this raise for your work? We\u2019d love to hear your thoughts!<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c02bf1 elementor-widget elementor-widget-text-editor\" data-id=\"2c02bf1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>AI in Foresight at Schaltzeit<\/h3><p>AI wasn\u2019t a topic that first appeared on our agenda with the ChatGPT hype in 2022. Back in 2020, we designed and piloted a foresight process for Germany\u2019s Federal Ministry of Labour and Social Affairs that incorporated AI methods. At the time, that was still pioneering work. What has become clearer since then: there is a wide spectrum between a simple GPT application and a structured AI workflow system \u2013 and which approach makes sense always depends on the goals and specific questions at hand.<\/p><p>The debate around World Models fits right into this. It makes visible what we experience in our daily work: AI is not a monolithic block. It is a field that changes rapidly, one where the right question matters more than the latest technology.<\/p><p><em>Interested in talking about this? We welcome the exchange \u2013 on ongoing projects, methodological questions, or the use of AI in your foresight context.<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e4f29d0 elementor-widget elementor-widget-spacer\" data-id=\"e4f29d0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5b3f66e elementor-widget elementor-widget-text-editor\" data-id=\"5b3f66e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Further links and reading<\/h3><ul><li><em>AMI Labs:<\/em> <a href=\"https:\/\/amilabs.xyz\" rel=\"nofollow noopener\" target=\"_blank\">amilabs.xyz<\/a><\/li><li><em>Heise Online:<\/em> \u201eWorld model instead of LLM: Yann LeCun\u2019s startup receives 890 million euros\u201c (M\u00e4rz 2026)<\/li><li><em>World Labs:<\/em> <a href=\"https:\/\/worldlabs.ai\/blog\/funding-2026\" rel=\"nofollow noopener\" target=\"_blank\">worldlabs.ai\/blog\/funding-2026<\/a><\/li><li><em>Grunwald, A.:<\/em> <em>Wovon ist die Zukunftsforschung eine Wissenschaft?<\/em><\/li><li><em>Soetebeer, M. (2022):<\/em> <a href=\"https:\/\/schaltzeit.com\/en\/black-box-workshopkonzept-framework-zur-diskussion-von-anforderungen-an-ki-und-intuition-in-entscheidungsfindungsprozessen\/\"><em>BLACK BOX Workshopkonzept<\/em>, Schaltzeit Blog<\/a><\/li><li><em>Weh, L. &amp; Soetebeer, M. (2021):<\/em> <em>KI-Ethik und Neuroethik f\u00f6rdern relationalen KI-Diskurs.<\/em> In: <em>Arbeitswelt und KI 2030<\/em>, Springer Gabler<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>What happens when AI stops operating through language and starts modelling the world directly? 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