News & Highlights - Digital Sustainability Hub

News & Highlights

Fractured Reality: Can Europe Reclaim Its Information Space?

The European Commission’s Joint Research Centre report “Fractured Reality: How Democracy Can Win the Global Struggle Over the Information Space” provides a powerful diagnosis of the challenges facing democratic systems in the digital age. At the core of the analysis lies the fragmentation of shared reality, driven by platform dynamics, disinformation, and the growing influence of artificial intelligence. The report frames the information space as a contested domain, shaped by economic incentives and geopolitical competition. This article examines its key insights and reflects on their implications for digital sustainability and democratic resilience in Europe.

April 10, 2026

News & Highlights

Why Teen Social Media Bans May Miss the Point

As governments debate whether to ban social media for teenagers under sixteen, a new commentary in Nature Health urges caution. Psychologist Sander van der Linden argues that while online harms are real and deserve serious attention, the scientific evidence does not support sweeping prohibitions. Blanket bans, he contends, risk replacing evidence informed policy with moral panic, offering symbolic reassurance rather than effective solutions. Instead of postponing young people’s digital lives, policymakers should focus on education, resilience, and regulatory accountability. The debate, he suggests, is not about denying risks, but about responding to them in ways that are proportionate, rigorous, and sustainable.

March 3, 2026

News & Highlights

Human–AI Interaction and Cognitive Sustainability: Why the 3R Principle Matters

The rapid diffusion of generative artificial intelligence is reshaping everyday cognitive practices, from writing and searching to decision making. While much of the debate has focused on efficiency and productivity, less attention has been paid to the long term implications for the human brain and for cognitive sustainability. A recent comment published in npj Artificial Intelligence by Rossi et al. 2026 brings this issue to the foreground, arguing that the way humans interact with AI systems can actively shape brain plasticity, agency and responsibility. By proposing the so called 3R principle, the authors offer a concise framework to distinguish between passive reliance on AI and forms of interaction that preserve meaning making and long term cognitive health.

January 28, 2026

News & Highlights

Beyond Green IT: MISQ Calls for a Broader Vision of Digital Sustainability

The latest issue of MIS Quarterly dedicates its Editor’s Comments to a crucial question for the future of the digital society. In her editorial “Beyond Green IT: From Digital Sustainability to Responsible Technology”, Editor in Chief Susan Brown argues that sustainability must move beyond a narrow focus on environmental efficiency. The rise of artificial intelligence, new digital infrastructures, and widespread platformisation require a broader and more integrated perspective. Brown highlights how environmental, social, governance, and human dimensions must be considered together if digital technologies are to support long term prosperity, social wellbeing, and equitable access to opportunity.

January 2, 2026

News & Highlights

Simulating Judgment: What LLMs Can’t Truly Decide and Why It Matters for Digital Sustainability

A recent scientific study by Loru et al. (2025) provides a startling insight into how large language models (LLMs) simulate human judgment. Their research highlights that these models, while impressively fluent, do not actually reason like humans; they instead rely on statistical patterns to generate plausible-sounding “judgments.” For the Digital Sustainability Hub, whose mission bridges understanding, awareness, and action, this raises crucial questions: What are the ethical and societal implications of deploying AI systems that can mimic decision-making without true deliberation? And how should we govern the integration of such systems in high-stakes domains like law, healthcare, or public policy?

December 30, 2025

News & Highlights

From Bias Mitigation to Community Centered Vision Systems: A Holistic Turn in Computer Vision

In a field where fairness often defines the scope of ethical discussions about computer vision the recent work by leading researchers shifts the focus beyond bias correction toward a broader vision of responsibility and community-centered practices. The paper by Gebru and Denton argues that ensuring equity in machine vision systems is not enough if the frameworks, processes, and institutions that build them remain unchanged. Their call for a holistic rethinking of computer vision research emphasizes structural reforms including participatory methods, community involvement, meaningful accountability, and awareness of social harms. For practitioners and researchers in digital sustainability, this represents a profound evolution: from mitigating bias to fostering systems aligned with justice, dignity and collective well-being.

December 20, 2025

News & Highlights

Beyond the Black Box: Why Open-Source Models May Shape a More Sustainable AI Future

As the race between open and closed large language models accelerates, open-source approaches are gaining ground in efficiency, transparency, and adaptability. A recent study titled “The Open-Source Advantage in Large Language Models” sheds light on why community-driven ecosystems could reshape the AI landscape. The authors argue that openness is not only a technical advantage but a foundation for digital sustainability, fostering innovation, accountability, and long-term resilience in the AI ecosystem. For researchers, developers, and policymakers alike, the message is clear: sustainable AI is open, collaborative, and verifiable.

December 15, 2025

News & Highlights

When Machines Eat Their Words: How AI Risks Consuming Its Own Knowledge

A recent study explores a critical question for the future of artificial intelligence: what happens when AI systems start learning too much from their own output? The phenomenon, known as model collapse, occurs when generative models trained on synthetic data progressively lose coherence, diversity, and meaning. Using semantic network analysis and probabilistic modeling, the authors reveal how large language models can drift toward redundancy and self-referential noise. Their findings shed light on a growing risk for digital ecosystems that depend on AI, from content platforms to search engines.

December 8, 2025

News & Highlights

The Crossed Wires of Intelligence: When AI and Cognitive Science Borrow Each Other’s Language

A recent paper by Luciano Floridi and Anna C. Nobre, published in “Minds and Machines”, explores how the languages of artificial intelligence and cognitive neuroscience have become increasingly entangled. We now speak of “neural networks” and “machine learning,” but also of “computational brains” and “neural coding.” This linguistic crosswiring, the authors argue, shapes not only how we describe machines and minds, but also how we understand intelligence itself. Their analysis invites us to rethink the epistemic, ethical, and social implications of treating algorithms as minds, and minds as algorithms.

November 28, 2025

News & Highlights

The Conscious AI Illusion: What Science Tells Us About Machine Awareness

A new paper published in “Humanities and Social Sciences Communications”, part of the Nature Portfolio, argues that the idea of conscious artificial intelligence is not only scientifically unsupported but conceptually misguided. According to researchers Andrzej Porębski and Jakub Figura, AI systems do not possess subjective experience or awareness, and claims to the contrary risk distorting public understanding of intelligence itself. Their analysis challenges the popular narrative that human-like consciousness is just one technological breakthrough away, urging policymakers and innovators to focus instead on transparency, accountability, and ethical responsibility in AI design.

November 19, 2025

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