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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"Ist Künstliche Intelligenz der neue Gott des digitalen Zeitalters? In diesem tiefgründigen Essay entfaltet Claudia Paganini eine philosophisch brisante These: Erstmals erschafft der Mensch einen Gott, statt ihn nur zu denken. Die KI übernimmt zunehmend, was einst der Religion vorbehalten war: Si
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nnstiftung, Orientierung, allzeit verfügbare Antworten. Wir beten nicht mehr, wir klicken. Mit analytischer Schärfe und theologischem Weitblick untersucht Paganini die spirituellen Konsequenzen dieser Entwicklung und zeigt: Im anbrechenden dritten Jahrtausend könnten nicht nur Menschen durch KI ersetzt werden, sondern auch kein geringerer als Gott selbst. Eine provokante Überlegung an der Schnittstelle von Religion und Technik." (Verlagsbeschreibung)
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"[...] this paper presents approximately 30 worldwide examples of successful AI use to promote various aspects of democracy. At the same time, the corresponding challenges that need to be addressed are highlighted. From the examination of international examples, the following theses can be derived:
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AI systems can promote all aspects of democracy in a similar way; the use of AI systems for democracy requires the functioning of democratic structures; focus not only on generative AI: significant advantages can also come from processing and identifying AI systems; AI systems that promote democracy must be particularly comprehensible and transparent; AI systems facilitate participation but do not enable it; AI systems can make large amounts of data usable—for both citizens and the state; AI must be considered in the context of existing digitalization processes; not everything that AI systems can do is desired in a democracy." (Executive summary)
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"This report examines political communication and media trust in the age of generative artificial intelligence systems (AI). Firstly, it provides a brief explainer of generative AI tools and techniques, looking separately at systems that generate text and those that generate or manipulate images, vi
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deos and audio. By reference to real-world examples, the paper then surveys the ways in which generative AI systems have recently been used by political actors, distinguishing between three different use-cases: political campaigning, entertainment and disinformation campaigns. Building on this empirical analysis, the paper distils important insights for policymakers, which highlight the need to: refrain from falsely labelling content as AI-generated to avoid overstating the technical capabilities and persuasive power of those spreading disinformation; acknowledge the multimodality of threats posed by generative AI, in particular voice-generation; delimit fair-use cases of generative AI for political campaigning, given these technologies are already widely used for legitimate political communication purposes; raise awareness of how seemingly non-political uses of generative AI can be exploited for politics, in particular the creation of non-consensual intimate content. This is followed by an evaluation of emerging technical and policy solutions, namely the detection and labelling of deepfakes as well as the development of systems to certify content authenticity and provenance. The section concludes with a discussion of the emerging legal landscape, including the European Union’s AI Act." (Executive summary)
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"This little booklet is brimming with AI knowledge and sample prompts that can help with brainstorming ideas, conducting research and preparing for interviews. How does artificial intelligence work? How did it come about, and what impact does it have on the environment? What are the legal parameters
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for using AI tools responsibly? And what should media professionals keep in mind when creating company-specific AI guidelines? Constructive AI Compass answers these questions and many more, providing orientation and inspiration for everyday work." (Back cover)
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"When used effectively and responsibly, artificial intelligence (AI) holds the potential to accelerate progress on sustainable development and close digital divides, but it also poses risks that could further impede progress toward these goals. With the right enabling environment and ecosystem of ac
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tors, AI can enhance efficiency and accelerate development outcomes in sectors such as health, education, agriculture, energy, manufacturing, and delivering public services. The United States aims to ensure that the benefits of AI are shared equitably across the globe." (Executive summary)
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"Large language models (LLMs) and dialogue agents represent a significant shift in artificial intelligence (AI) research, particularly with the recent release of the GPT family of models. ChatGPT’s generative capabilities and versatility across technical and creative domains led to its widespread
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adoption, marking a departure from more limited deployments of previous AI systems. While society grapples with the emerging cultural impacts of this new societal-scale technology, critiques of ChatGPT’s impact within machine learning research communities have coalesced around its performance or other conventional safety evaluations relating to bias, toxicity, and “hallucination.” We argue that these critiques draw heavily on a particular conceptualization of the “human-centered” framework, which tends to cast atomized individuals as the key recipients of technology’s benefits and detriments. In this article, we direct attention to another dimension of LLMs and dialogue agents’ impact: their effects on social groups, institutions, and accompanying norms and practices. By analyzing ChatGPT’s social impact through a social-centered framework, we challenge individualistic approaches in AI development and contribute to ongoing debates around the ethical and responsible deployment of AI systems. We hope this effort will call attention to more comprehensive and longitudinal evaluation tools (e.g., including more ethnographic analyses and participatory approaches) and compel technologists to complement human-centered thinking with social-centered approaches." (Abstract)
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"The progress of artificial intelligence, particularly with generative AI models, has provoked intense reactions, regardless of whether they are based on the logic and functioning of the technology. Unlike predictive AI, generative AI produces original content by synthesizing texts, images, voices,
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videos, and code from large databases and may significantly impact the creative economy. This study introduces the basic concepts of AI and generative AI (including a taxonomy of generative models) and outlines the distinction between image or video and text production techniques. The central argument of this study claims that the cultural fuss is not accidental, defending the hypothesis that the advent of generative AI places humanity amidst the crossing of its fourth narcissistic wound."(Abstract)
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"International standards provide the guidelines and benchmarks needed to measure and improve the environmental impact of AI. Codifying established best practices, standards help mitigate risks such as high energy consumption and lifecycle emissions. They also provide measurement methodologies to ass
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ess GHG emissions and energy consumption, and thereby identify the actions needed to improve. Achieving this vision of sustainable AI that offers powerful tools for climate action will demand close collaboration among a diverse array of stakeholders from government, industry, academia and civil society. The International Telecommunication Union (ITU) stimulates this collaboration as the United Nations specialized agency for information and communication technologies. This report explores the environmental implications of AI and presents a summary of relevant standards available and under development. It highlights the importance of a coordinated, international approach to standardization and the need for continued engagement and cooperation across all sectors." (Foreword)
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