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Challenging AI for Sustainability: what ought it mean?
This paper argues that the terms ‘Sustainable artificial intelligence (AI)’ in general and ‘Sustainability of AI’ in particular are overused to the...
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Assessing the current landscape of AI and sustainability literature: identifying key trends, addressing gaps and challenges
The United Nations’ 17 Sustainable Development Goals stress the importance of global and local efforts to address inequalities and implement...
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Resilient and Sustainable AI. Positioning paper on the relation of AI, resilience and sustainability
In the contemporary debate, surrounding the future of work and life, Artificial Intelligence (AI), resilience, and sustainability have emerged as...
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Sustainable AI: AI for sustainability and the sustainability of AI
While there is a growing effort towards AI for Sustainability (e.g. towards the sustainable development goals) it is time to move beyond that and to...
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Design culture for Sustainable urban artificial intelligence: Bruno Latour and the search for a different AI urbanism
The aim of this paper is to investigate the relationship between AI urbanism and sustainability by drawing upon some key concepts of Bruno Latour’s...
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AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act
The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a...
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Green and sustainable AI research: an integrated thematic and topic modeling analysis
This investigation delves into Green AI and Sustainable AI literature through a dual-analytical approach, combining thematic analysis with BERTopic...
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AI for crisis decisions
Increasingly, our cities are confronted with crises. Fuelled by climate change and a loss of biodiversity, increasing inequalities and fragmentation,...
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Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI
As Artificial Intelligence (AI) rapidly advances and integrates into various domains, cybersecurity emerges as a critical field grappling with both...
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Taking AI risks seriously: a new assessment model for the AI Act
The EU Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories...
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Applying the ethics of AI: a systematic review of tools for develo** and assessing AI-based systems
Artificial Intelligence (AI)-based systems and their increasingly common use have made it a ubiquitous technology; Machine Learning algorithms are...
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Beware of sustainable AI! Uses and abuses of a worthy goal
The ethical debate about technologies called artificial intelligence (AI) has recently turned towards the question whether and in which sense using...
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Measuring adherence to AI ethics: a methodology for assessing adherence to ethical principles in the use case of AI-enabled credit scoring application
This article discusses the critical need to find solutions for ethically assessing artificial intelligence systems, underlining the importance of...
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Trustworthy AI: AI made in Germany and Europe?
As the capabilities of artificial intelligence (AI) continue to expand, concerns are also growing about the ethical and social consequences of...
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ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review
ChatGPT is another large language model (LLM) vastly available for the consumers on their devices but due to its performance and ability to converse...
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The ethics of AI business practices: a review of 47 AI ethics guidelines
Many AI ethics guidelines have recently been published that center the fairness, accountability, sustainability, and transparency of algorithmic...
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Lorenz Zonoids for Trustworthy AI
Machine learning models are boosting Artificial Intelligence (AI) applications in many domains, such as finance, health care and automotive. This is...
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A semi-automated software model to support AI ethics compliance assessment of an AI system guided by ethical principles of AI
Compliance with principles and guidelines for ethical AI has a significant impact on companies engaged in the development of artificial intelligence...
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CloudAIBus: a testbed for AI based cloud computing environments
Smart resource allocation is essential for optimising cloud computing efficiency and utilisation, but it is also very challenging as traditional...
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The case for a broader approach to AI assurance: addressing “hidden” harms in the development of artificial intelligence
Artificial intelligence (AI) assurance is an umbrella term describing many approaches—such as impact assessment, audit, and certification...