Academic writing is getting harder to read—the humanities most of all

Curated on Posted on by Stefaan Verhulst

The Economist: “Academics have long been accused of jargon-filled writing that is impossible to understand. A recent cautionary tale was that of Ally Louks, a researcher who set off a social media storm with an innocuous post on X celebrating the completion of her PhD. If it was Ms Louks’s research topic (“olfactory ethics”—the politics of smell) that caught the attention of online critics, it was her verbose thesis abstract that further provoked their ire. In two weeks, the post received more than 21,000 retweets and 100m views.

Although the abuse directed at Ms Louks reeked of misogyny and anti-intellectualism—which she admirably shook off—the reaction was also a backlash against an academic use of language that is removed from normal life. Inaccessible writing is part of the problem. Research has become harder to read, especially in the humanities and social sciences. Though authors may argue that their work is written for expert audiences, much of the general public suspects that some academics use gobbledygook to disguise the fact that they have nothing useful to say. The trend towards more opaque prose hardly allays this suspicion…(More)”.

Digital Governance: Confronting the Challenges Posed by Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Book edited by Kostina Prifti, Esra Demir, Julia Krämer, Klaus Heine, and Evert Stamhuis: “This book explores the structure and frameworks of digital governance, focusing on various regulatory patterns, with the aim of tackling the disruptive impact of artificial intelligence (AI) technologies. Addressing the various challenges posed by AI technologies, this book explores potential avenues for crafting legal remedies and solutions, spanning liability of AI, platform governance, and the implications for data protection and privacy…(More)”.

Trust but Verify: A Guide to Conducting Due Diligence When Leveraging Non-Traditional Data in the Public Interest

Curated on Posted on by Stefaan Verhulst

New Report by Sara Marcucci, Andrew J. Zahuranec, and Stefaan Verhulst: “In an increasingly data-driven world, organizations across sectors are recognizing the potential of non-traditional data—data generated from sources outside conventional databases, such as social media, satellite imagery, and mobile usage—to provide insights into societal trends and challenges. When harnessed thoughtfully, this data can improve decision-making and bolster public interest projects in areas as varied as disaster response, healthcare, and environmental protection. However, with these new data streams come heightened ethical, legal, and operational risks that organizations need to manage responsibly. That’s where due diligence comes in, helping to ensure that data initiatives are beneficial and ethical.

The report, Trust but Verify: A Guide to Conducting Due Diligence When Leveraging Non-Traditional Data in the Public Interest, co-authored by Sara Marcucci, Andrew J. Zahuranec, and Stefaan Verhulst, offers a comprehensive framework to guide organizations in responsible data partnerships. Whether you’re a public agency or a private enterprise, this report provides a six-step process to ensure due diligence and maintain accountability, integrity, and trust in data initiatives…(More) (Blog)”.

Beyond checking a box: how a social licence can help communities benefit from data reuse and AI

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst and Peter Addo: “In theory, consent offers a mechanism to reduce power imbalances. In reality, existing consent mechanisms are limited and, in many respects, archaic, based on binary distinctions – typically presented in check-the-box forms that most websites use to ask you to register for marketing e-mails – that fail to appreciate the nuance and context-sensitive nature of data reuse. Consent today generally means individual consent, a notion that overlooks the broader needs of communities and groups.

While we understand the need to safeguard information about an individual such as, say, their health status, this information can help address or even prevent societal health crises. Individualised notions of consent fail to consider the potential public good of reusing individual data responsibly. This makes them particularly problematic in societies that have more collective orientations, where prioritising individual choices could disrupt the social fabric.

The notion of a social licence, which has its roots in the 1990s within the extractive industries, refers to the collective acceptance of an activity, such as data reuse, based on its perceived alignment with community values and interests. Social licences go beyond the priorities of individuals and help balance the risks of data misuse and missed use (for example, the risks of violating privacy vs. neglecting to use private data for public good). Social licences permit a broader notion of consent that is dynamic, multifaceted and context-sensitive.

Policymakers, citizens, health providers, think tanks, interest groups and private industry must accept the concept of a social licence before it can be established. The goal for all stakeholders is to establish widespread consensus on community norms and an acceptable balance of social risk and opportunity.

Community engagement can create a consensus-based foundation for preferences and expectations concerning data reuse. Engagement could take place via dedicated “data assemblies” or community deliberations about data reuse for particular purposes under particular conditions. The process would need to involve voices as representative as possible of the different parties involved, and include those that are traditionally marginalised or silenced…(More)”.

Global Trends in Government Innovation 2024

Curated on Posted on by Stefaan Verhulst

OECD Report: “Governments worldwide are transforming public services through innovative approaches that place people at the center of design and delivery. This report analyses nearly 800 case studies from 83 countries and identifies five critical trends in government innovation that are reshaping public services. First, governments are working with users and stakeholders to co-design solutions and anticipate future needs to create flexible, responsive, resilient and sustainable public services. Second, governments are investing in scalable digital infrastructure, experimenting with emergent technologies (such as automation, AI and modular code), and expanding innovative and digital skills to make public services more efficient. Third, governments are making public services more personalised and proactive to better meet people’s needs and expectations and reduce psychological costs and administrative frictions, ensuring they are more accessible, inclusive and empowering, especially for persons and groups in vulnerable and disadvantaged circumstances. Fourth, governments are drawing on traditional and non-traditional data sources to guide public service design and execution. They are also increasingly using experimentation to navigate highly complex and unpredictable environments. Finally, governments are reframing public services as opportunities and channels for citizens to exercise their civic engagement and hold governments accountable for upholding democratic values such as openness and inclusion…(More)”.

Direct democracy in the digital age: opportunities, challenges, and new approaches

Curated on Posted on by Stefaan Verhulst

Article by Pattharapong Rattanasevee, Yared Akarapattananukul & Yodsapon Chirawut: “This article delves into the evolving landscape of direct democracy, particularly in the context of the digital era, where ICT and digital platforms play a pivotal role in shaping democratic engagement. Through a comprehensive analysis of empirical data and theoretical frameworks, it evaluates the advantages and inherent challenges of direct democracy, such as majority tyranny, short-term focus, polarization, and the spread of misinformation. It proposes the concept of Liquid democracy as a promising hybrid model that combines direct and representative elements, allowing for voting rights delegation to trusted entities, thereby potentially mitigating some of the traditional drawbacks of direct democracy. Furthermore, the article underscores the necessity for legal regulations and constitutional safeguards to protect fundamental rights and ensure long-term sustainability within a direct democracy framework. This research contributes to the ongoing discourse on democratic innovation and highlights the need for a balanced approach to integrating digital tools with democratic processes…(More)”.

Announcing SPARROW: A Breakthrough AI Tool to Measure and Protect Earth’s Biodiversity in the Most Remote Places

Curated on Posted on by Stefaan Verhulst

Blog by Juan Lavista Ferres: “The biodiversity of our planet is rapidly declining. We’ve likely reached a tipping point where it is crucial to use every tool at our disposal to help preserve what remains. That’s why I am pleased to announce SPARROW—Solar-Powered Acoustic and Remote Recording Observation Watch, developed by Microsoft’s AI for Good Lab. SPARROW is an AI-powered edge computing solution designed to operate autonomously in the most remote corners of the planet. Solar-powered and equipped with advanced sensors, it collects biodiversity data—from camera traps, acoustic monitors, and other environmental detectors—that are processed using our most advanced PyTorch-based wildlife AI models on low-energy edge GPUs. The resulting critical information is then transmitted via low-Earth orbit satellites directly to the cloud, allowing researchers to access fresh, actionable insights in real time, no matter where they are. 

Think of SPARROW as a network of Earth-bound satellites, quietly observing and reporting on the health of our ecosystems without disrupting them. By leveraging solar energy, these devices can run for a long time, minimizing their footprint and any potential harm to the environment…(More)”.

A linkless internet

Curated on Posted on by Stefaan Verhulst

Essay by Collin Jennings: “..But now Google and other websites are moving away from relying on links in favour of artificial intelligence chatbots. Considered as preserved trails of connected ideas, links make sense as early victims of the AI revolution since large language models (LLMs) such as ChatGPT, Google’s Gemini and others abstract the information represented online and present it in source-less summaries. We are at a moment in the history of the web in which the link itself – the countless connections made by website creators, the endless tapestry of ideas woven together throughout the web – is in danger of going extinct. So it’s pertinent to ask: how did links come to represent information in the first place? And what’s at stake in the movement away from links toward AI chat interfaces?

To answer these questions, we need to go back to the 17th century, when writers and philosophers developed the theory of mind that ultimately inspired early hypertext plans. In this era, prominent philosophers, including Thomas Hobbes and John Locke, debated the extent to which a person controls the succession of ideas that appears in her mind. They posited that the succession of ideas reflects the interaction between the data received from the senses and one’s mental faculties – reason and imagination. Subsequently, David Hume argued that all successive ideas are linked by association. He enumerated three kinds of associative connections among ideas: resemblance, contiguity, and cause and effect. In An Enquiry Concerning Human Understanding (1748), Hume offers examples of each relationship:

A picture naturally leads our thoughts to the original: the mention of one apartment in a building naturally introduces an enquiry or discourse concerning the others: and if we think of a wound, we can scarcely forbear reflecting on the pain which follows it.

The mind follows connections found in the world. Locke and Hume believed that all human knowledge comes from experience, and so they had to explain how the mind receives, processes and stores external data. They often reached for media metaphors to describe the relationship between the mind and the world. Locke compared the mind to a blank tablet, a cabinet and a camera obscura. Hume relied on the language of printing to distinguish between the vivacity of impressions imprinted upon one’s senses and the ideas recalled in the mind…(More)”.

Harnessing AI: How to develop and integrate automated prediction systems for humanitarian anticipatory action

Curated on Posted on by Stefaan Verhulst

CEPR Report: “Despite unprecedented access to data, resources, and wealth, the world faces an escalating wave of humanitarian crises. Armed conflict, climate-induced disasters, and political instability are displacing millions and devastating communities. Nearly one in every five children are living in or fleeing conflict zones (OCHA, 2024). Often the impacts of conflict and climatic hazards – such as droughts and flood – exacerbate each other, leading to even greater suffering. As crises unfold and escalate, the need for timely and effective humanitarian action becomes paramount.

Sophisticated systems for forecasting and monitoring natural and man-made hazards have emerged as critical tools to help inform and prompt action. The full potential for the use of such automated forecasting systems to inform anticipatory action (AA) is immense but is still to be realised. By providing early warnings and predictive insights, these systems could help organisations allocate resources more efficiently, plan interventions more effectively, and ultimately save lives and prevent or reduce humanitarian impact.


This Policy Insight provides an account of the significant technical, ethical, and organisational difficulties involved in such systems, and the current solutions in place…(More)”.

Harvard Is Releasing a Massive Free AI Training Dataset Funded by OpenAI and Microsoft

Curated on Posted on by Stefaan Verhulst

Article by Kate Knibbs: “Harvard University announced Thursday it’s releasing a high-quality dataset of nearly 1 million public-domain books that could be used by anyone to train large language models and other AI tools. The dataset was created by Harvard’s newly formed Institutional Data Initiative with funding from both Microsoft and OpenAI. It contains books scanned as part of the Google Books project that are no longer protected by copyright.

Around five times the size of the notorious Books3 dataset that was used to train AI models like Meta’s Llama, the Institutional Data Initiative’s database spans genres, decades, and languages, with classics from Shakespeare, Charles Dickens, and Dante included alongside obscure Czech math textbooks and Welsh pocket dictionaries. Greg Leppert, executive director of the Institutional Data Initiative, says the project is an attempt to “level the playing field” by giving the general public, including small players in the AI industry and individual researchers, access to the sort of highly-refined and curated content repositories that normally only established tech giants have the resources to assemble. “It’s gone through rigorous review,” he says…(More)”.