"AI tools Radar is designed to map and showcase innovative and impactful AI tools from around the world, with a particular focus on applications in the public sector, media, and judiciary. This platform is a global initiative born out of a collaboration between UNESCO and the International Research
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Centre on Artificial Intelligence (IRCAI). Our mission is to drive transparency, efficiency, and ethics in AI deployment, empowering the public sector, the media and the judiciary with the tools needed to navigate an increasingly digital world. Sourced from leading organizations and experts in the field of AI, the AI tools curated are categorized according to the most common day-to-day operations and needs of organizations and professionals in these three sectors. But our ambition doesn’t stop there. AI Tools Radar is set to expand its scope to include AI tools from other sectors, industries, and research domains, creating the most comprehensive repository of AI applications available." (https://radar.ircai.org/en/about)
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"This year’s Human Development Report examines what distinguishes this new era of AI from previous digital transformations and what those differences could mean for human development (chapter 1), including how AI can enhance or subvert human agency (chapter 2). People are already interacting with
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AI in different ways at different stages of life, in effect scoping out possibilities good and bad and underscoring how context and choices can make all the difference (chapter 3). Human agency is the price when people buy into AI hype, which can exacerbate exclusion (chapter 4) and harm sustainability. And, of course, who produces AI and for what matter a lot for everyone (chapter 5). Letting people take the reins makes good sense, because they expect AI to be a growing part of their lives. A global survey for this Report found that, at all levels of the Human Development Index (HDI), AI use is already substantial (for about 20 percent of respondents) and is expected to shoot up fast. About two-thirds of respondents in low, medium and high HDI countries expect to use AI in education, health and work—the
three HDI dimensions—within one year." (Overview, pages 3-4)
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"Addressing a rarely-examined intersection, the magazine features eight articles highlighting the use of technology in Indigenous communities. These include AI’s role in exacerbating violence and inequality, the use of AI in tracking salmon migration, Indigenous representation in video games, and
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the use of Indigenous languages in coding. Focused on fighting for Indigenous Peoples’ rights and sovereignty, Cultural Survival herewith delves into Indigenous leaders as solution builders rather than simply excluded and discriminated against." (https://www.channelfoundation.org)
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"To foster a multifaceted perspective on AI ethics, a pluriversal approach needs to be employed. This two-day workshop “AI Ethics from the Majority World: Reconstructing the Global Debate Through Decolonial Lenses” offers a forum to discuss alternatives to the status quo of AI ethics. Hosted by
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the University of Bonn’s Institute for Sciences and Ethics, the workshop aims to advance a reconstruction of the proliferated perspectives of AI ethics, dominantly shaped by ethical standards from historically hegemonic groups in the Minority World, by examining the plural decolonial schools of thought that challenge the positions that have shaped AI development worldwide." (Introduction)
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"Imagining AI: How the World Sees Intelligent Machines is the first volume showcasing research into how different cultures around the globe envision life with artificial intelligence. AI is now a global phenomenon. Yet Hollywood narratives dominate perceptions of AI in the English-speaking West and
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beyond, and much of the technology itself is shaped by a disproportionately white, male, US-based elite. However, different cultures have been imagining intelligent machines since long before we could build them, in visions that vary greatly across religious, philosophical, literary and cinematic traditions. This book aims to spotlight these alternative visions. Imagining AI draws attention to the range and variety of visions of a future with intelligent machines and their potential significance for the research, regulation and implementation of AI. The book is structured geographically, with each chapter presenting insights into how a specific region or culture imagines intelligent machines. The contributors, leading experts from academia and the arts, explore how the encounters between local narratives, digital technologies, and mainstream Western narratives create new imaginaries and insights in different contexts across the globe. The narratives they analyse range from ancient philosophy to contemporary science fiction, and visual art to policy discourse. The book sheds new light on some of the most important themes in AI ethics, from the differences between Chinese and American visions of AI, to digital neo-colonialism. It is an essential work for anyone wishing to understand how different cultural contexts interplay with the most significant technology of our time." (Publisher description)
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"Künstliche Intelligenz ist auf Smartphones unser ständiger Begleiter, in sozialen Netzwerken verbreitet sie Desinformation, sie wird zur Überwachung und beim Militär eingesetzt. Welche Regeln braucht es, damit uns KI mehr nützt als schadet? Welche billigen Arbeitskräfte liefern die Daten für
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maschinelles Lernen? Und wie verbessert KI in Bangladesch den Flutschutz?"
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"The rise of Generative AI (GenAI) in knowledge workflows raises questions about its impact on critical thinking skills and practices. We survey 319 knowledge workers to investigate 1) when and how they perceive the enaction of critical thinking when using GenAI, and 2) when and why GenAI affects th
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eir effort to do so. Participants shared 936 first-hand examples of using GenAI in work tasks. Quantitatively, when considering both task- and user-specific factors, a user’s task-specific self-confidence and confidence in GenAI are predictive of whether critical thinking is enacted and the effort of doing so in GenAI-assisted tasks. Specifically, higher confidence in GenAI is associated with less critical thinking, while higher self-confidence is associated with more critical thinking. Qualitatively, GenAI shifts the nature of critical thinking toward information verification, response integration, and task stewardship. Our insights reveal new design challenges and opportunities for developing GenAI tools for knowledge work." (Abstract)
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"Ist Künstliche Intelligenz nur eine weitere Entwicklung der Digitalisierung des Alltags, eine effiziente Software in einer „Cloud“? Die KI-Forscherin Kate Crawford entlarvt diese verharmlosende Vorstellung und beleuchtet die konkreten Auswirkungen der Technologie auf die physische Welt. Ihre R
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echerche bietet Einblicke in den Bergbau, wo für die KI reale Ressourcen wie Gestein, Lithium-Sole und Erdöl abgebaut werden, und in Logistik-Zentren, wo menschliche Arbeitskraft für Unternehmensgewinne ausgebeutet werde. Künstliche Intelligenz gehe, so Crawford, mit Umweltzerstörung und Raubbau an der Natur sowie sozialer Ungerechtigkeit einher, etwa der Ausbeutung von Clickworkern. Zudem basiere Künstliche Intelligenz auf einer Klassifizierung von Daten, die keineswegs einer objektiven Logik folge, sondern Hierarchien perpetuiere und Ungleichheiten verstärke. Angesichts dieser Verzerrungen könne KI nicht als neutrale Technologie angesehen werden, deren Probleme wiederum durch weitere technische Innovationen gelöst werden können. Vielmehr seien politische Regulierung, demokratische Kontrolle und die Einbeziehung der von Vorurteilen, Diskriminierung und Ausbeutung Betroffenen erforderlich. Die bereits existierenden Gefahren der Technologien für Privatsphäre, Menschenrechte, Natur und Arbeitswelt seien weitaus bedrohlicher als die von manchen befürchtete Entwicklung einer künstlichen Superintelligenz." (Back cover)
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"Artificial intelligence (AI) is reshaping the way we address complex societal challenges, offering new possibilities in areas such as healthcare, climate resilience, education, and digital inclusion. The Innovate for Impact project was launched in 2024 to identify, support, and showcase practical A
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I solutions that bring tangible benefits to people and communities. A key part of the initiative involves the sharing of use cases, impactful AI applications and global lessons and expertise from around the world. In 2025, building on the success of its first edition, the project expanded its scope through an open call for AI use cases and AI Scholars. We received 234 use case submissions from 32 countries, out of which 160 were selected for inclusion in this interim report. These use cases span eleven key domains and reflect both the diversity of global innovation, regional solutions with lessons learnt and the practical ways in which AI is being applied to solve real-world problems." (Foreword)
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"As global stakeholders from governments, international organizations, the private sector, academia, and civil society, we convene in Hamburg to shape a human-centric, human-rights-based, inclusive, open, sustainable, and responsible AI future. We commit to advancing AI for the SDGs, aligning with o
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ngoing international efforts. A responsible AI future must be built on equal and meaningful participation, with actions to ensure that all stakeholders, especially those from emerging markets, developing economies, and vulnerable groups, have fair and equitable access to, as well as ownership of, computing, data, investment, and resources for capacity and talent development. AI’s benefits must not remain concentrated among a privileged few. We are committed to bridging digital divides and empowering all nations and communities to co-create and leverage AI solutions and evaluations that serve people and the planet. To achieve this, we call for leveraging AI responsibly, inclusively, and sustainably, aligned with the five pillars of the 2030 Agenda for Sustainable Development: people, planet, prosperity, peace, and partnerships." (A Joint Vision)
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"Im ersten Teil geben wir einen Überblick über den Einsatz von generativer KI in der politischen Kampagnenkommunikation. Insbesondere die generativen KI-Tools ChatGPT und Midjourney werden zunehmend in politischen Kampagnen eingesetzt, um menschenähnliche Texte beziehungsweise fotorealistische Bi
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lder zu erstellen [...] Der zweite Teil liefert ein umfassendes Bild von den Einstellungen der deutschen Bevölkerung zum Einsatz von generativer KI in politischen Kampagnen. Dafür haben wir eine repräsentative Online-Befragung von knapp 2.000 Teilnehmenden durchgeführt und Menschen zu ihrem KI-Wissen und ihren Einschätzungen zur KI-Nutzung in der Politik befragt [...] Im dritten Teil der Studie untersuchen wir, inwieweit KI-generierte Botschaften in politischen Kampagnen von Bürger*innen erkannt und wahrgenommen werden, aber auch wie sie ihre Einstellungen hinsichtlich des politischen Einsatzes von generativer KI beeinflussen. Dafür haben wir ein Online-Experiment mit ebenfalls rund 2.000 neuen Teilnehmenden durchgeführt." (Einleitung, Seiten 7-8)
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[.] Auf Basis von über 2.000 Artikeln aus neun reichweitenstarken Print- und Onlinemedien untersuchen die Autor*innen, welche Themen in der Berichterstattung über KI gesetzt, wie Bezüge zu Fragen sozialer Gerechtigkeit hergestellt werden, welche narrativen Muster sich zeigen und welche Akteur*inn
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en zu Wort kommen [.] Die Ergebnisse der Untersuchung zeigen, dass in den untersuchten Medien eine breite Beschäftigung mit unterschiedlichen Themen rund um Künstliche Intelligenz und insbesondere generative KI stattfindet. Auch Gerechtigkeitsfragen werden in allen untersuchten Medien behandelt. Im Schnitt widmet sich rund jeder vierte Beitrag auch den sozialen Folgen von Künstlicher Intelligenz. Hierbei sticht die taz mit einem Anteil von fast 45 Prozent besonders hervor.
Zugleich zeigt sich jedoch, dass die Berichterstattung über KI stark von wirtschaftlichen Perspektiven geprägt ist. So stehen häufig Produkteinführungen, Personalien, Unternehmensentscheidungen oder Marktentwicklungen im Zentrum der medialen Aufmerksamkeit. Besonders auffällig ist die Präsenz von KI-Unternehmen und ihrer meist männlichen Vertreter. Wissenschaftliche, politische und zivilgesellschaftliche Akteur*innen kommen dagegen deutlich seltener in der Berichterstattung vor, obwohl gerade von dieser Seite zahlreiche wertvolle Analysen und Vorschläge zum Umgang mit KI beigesteuert werden. Eine weitere Erkenntnis der Untersuchung: Obwohl regelmäßig über soziale Folgen von KI geschrieben wird, findet die Berichterstattung mehrheitlich eher oberflächlich und stichwortartig statt. Lösungsvorschläge zur Beseitigung sozialer Ungleichheiten, die durch KI hervorgerufen werden, oder auch notwendige politische Regulierungen werden kaum genauer diskutiert. Außerdem ist immer wieder eine technikdeterministische Haltung zu beobachten: Neue KI-Entwicklungen werden als unausweichlich dargestellt, während die wirtschaftlich motivierten Entscheidungen der Verantwortlichen selten hinterfragt werden." (Vorwort, Seiten 1-2)
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"If 2023 was the year of generative artificial intelligence, 2024 was marked by the rapid expansion and adoption of AI, driving waves of innovation across nearly every conceivable domain. The United Nations system has kept an encouraging pace, redoubling efforts to harness the power and potential of
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AI responsibly. That progress is visible not only in the soaring number of UN AI initiatives — now totalling 729 projects, from 406 last year — but also in the depth of engagement across the system, with 53 UN entities contributing to this year’s Activities Report, six of them for the first time. This gathering momentum reflects our shared conviction that AI is no longer a distant aspiration; it is a present-day imperative within and beyond the United Nations. The projects highlighted here tackle urgent challenges, from accelerating climate action to improving health outcomes to expanding educational access, bolstering governance, and creating decent work. Nearly half of these efforts are built on partnerships with governments, academia, industry, and civil-society organizations, underscoring the multistakeholder spirit at the heart of the UN’s inclusive digital transformation agenda. Across our work, AI is already driving efficiencies, revealing deeper insights, and informing faster responses — from chatbots that streamline public-service delivery to data tools that strengthen emergency responses to applications that keep meetings and consultations running smoothly. These innovations are extending the reach and impact of our work in practical, promising ways. Yet the UN remains keenly aware of the risks and responsibilities that accompany AI. Ethics, human rights, and inclusion anchor every initiative, guiding us toward a shared digital future where AI helps us advance opportunity and prosperity for all. This report — prepared by the International Telecommunication Union (ITU) in partnership with 52 other UN entities — embodies the system’s resolve to lead by example. Read on to discover how AI is already driving progress, delivering results, and reshaping the way the UN serves people and planet in the digital age." (Foreword)
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This report synthesizes key findings from a diverse range of sources, including academic literature, corporate sustainability initiatives, and emerging environmental tracking tools. Collectively, these documents provide a thorough overview of current methodologies for evaluating the environmental im
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pacts of artificial intelligence (AI) systems. While several advances in methodology and tooling are evident, the review highlights substantial inconsistencies in how different lifecycle stages of AI are measured, analysed, and reported.
[.] One of the most pressing issues uncovered is the widespread reliance on indirect estimates when assessing energy consumption during the training phase of AI models. These estimates often lack real-time, empirical measurement. Furthermore, equally important lifecycle stages — such as inference (the operational use of models), Scope 3 emissions (from supply chains and hardware manufacturing), and infrastructure-level impacts (such as water consumption and cooling) — remain significantly underexplored. This reliance on proxies introduces substantial data gaps, impedes accountability, and restricts consumers’ ability to make informed, sustainable choices about AI.
To address these issues, the report uses a lifecycle-based approach, dividing the AI system's environmental impact into three stages: 1. Training, 2. Inference, 3. Supply Chain. For each stage, we examine measurement methodologies, identify current limitations, and offer recommendations for key stakeholder groups: developers (producers), users (consumers), and policy-makers. The overarching aim is to ensure that sustainability becomes a foundational element — embedded from the earliest stages of AI design to its deployment and continued use — rather than an afterthought." (Executive summary, pages v-vi)
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