Is This How Reddit Ends?

Curated on Posted on by Stefaan Verhulst

Article by Matteo Wong: “The internet is growing more hostile to humans. Google results are stuffed with search-optimized spam, unhelpful advertisements, and AI slop. Amazon has become littered with undifferentiated junk. The state of social media, meanwhile—fractured, disorienting, and prone to boosting all manner of misinformation—can be succinctly described as a cesspool.

It’s with some irony, then, that Reddit has become a reservoir of humanity. The platform has itself been called a cesspool, rife with hateful rhetoric and falsehoods. But it is also known for quirky discussions and impassioned debates on any topic among its users. Does charging your brother rent, telling your mom she’s an unwanted guest, or giving your wife a performance review make you an asshole? (Redditors voted no, yes, and “everyone sucks,” respectively.) The site is where fans hash out the best rap album ever and plumbers weigh in on how to unclog a drain. As Google has begun to offer more and more vacuous SEO sites and ads in response to queries, many people have started adding reddit to their searches to find thoughtful, human-written answers: find mosquito in bedroom reddit; fix musty sponge reddit.

But now even Reddit is becoming more artificial. The platform has quietly started beta-testing Reddit Answers, what it calls an “AI-powered conversational interface.” In function and design, the feature—which is so far available only for some users in the U.S.—is basically an AI chatbot. On a new search screen accessible from the homepage, Reddit Answers takes anyone’s queries, trawls the site for relevant discussions and debates, and composes them into a response. In other words, a site that sells itself as a home for “authentic human connection” is now giving humans the option to interact with an algorithm instead…(More)”.

Flipping data on its head: Differing conceptualisations of data and the implications for actioning Indigenous data sovereignty principles

Curated on Posted on by Stefaan Verhulst

Paper by Stephanie Cunningham-Reimann et al: “Indigenous data sovereignty is of global concern. The power of data through its multitude of uses can cause harm to Indigenous Peoples, communities, organisations and Nations in Canada and globally. Indigenous research principles play a vital role in guiding researchers, scholars and policy makers in their careers and roles. We define data, data sovereignty principles, ways of practicing Indigenous research principles, and recommendations for applying and actioning Indigenous data sovereignty through culturally safe self-reflection, interpersonal and reciprocal relationships built upon respect, reciprocity, relevance, responsibility and accountability. Research should be co-developed, co-led, and co-disseminated in partnership with Indigenous Peoples, communities, organisations and/or nations to build capacity, support self-determination, and reduce harms produced through the analysis and dissemination of research findings. OCAP® (Ownership, Control, Access & Possession), OCAS (Ownership, Control, Access & Stewardship), Inuit Qaujimajatuqangit principles in conjunction the 4Rs (respect, relevance, reciprocity & responsibility) and cultural competency including self-examination of the 3Ps (power, privilege, and positionality) of researchers, scholars and policy makers can be challenging, but will amplify the voices and understandings of Indigenous research by implementing Indigenous data sovereignty in Canada…(More)”

AI Commons: nourishing alternatives to Big Tech monoculture

Curated on Posted on by Stefaan Verhulst

Report by Joana Varon, Sasha Costanza-Chock, Mariana Tamari, Berhan Taye, and Vanessa Koetz: “‘Artificial Intelligence’ (AI) has become a buzzword all around the globe, with tech companies, research institutions, and governments all vying to define and shape its future. How can we escape the current context of AI development where certain power forces are pushing for models that, ultimately, automate inequalities and threaten socio-enviromental diversities? What if we could redefine AI? What if we could shift its production from a capitalist model to a more disruptive, inclusive, and decentralized one? Can we imagine and foster an AI Commons ecosystem that challenges the current dominant neoliberal logic of an AI arms race? An ecosystem encompassing researchers, developers, and activists who are thinking about AI from decolonial, transfeminist, antiracist, indigenous, decentralized, post-capitalist and/or socio-environmental justice perspectives?

This fieldscan research, commissioned by One Project and conducted by Coding Rights, aims to understand the (possibly) emerging “AI Common” ecosystem. Focused on key entities (organizations, cooperatives and collectives, networks, companies, projects, and others) from Africa, the Americas, and Europe advancing alternative possible AI futures, the authors identify 234 entities that are advancing the AI Commons ecosystem. The report finds powerful communities of practice, groups, and organizations producing nuanced criticism of the Big Tech-driven AI development ecosystem and, most importantly, imagining, developing, and, at times, deploying an alternative AI technology that’s informed and guided by the principles of decoloniality, feminism, antiracist, and post-capitalist AI systems…(More)”.

Thousands of U.S. Government Web Pages Have Been Taken Down Since Friday

Curated on Posted on by Stefaan Verhulst

Article by Ethan Singer: “More than 8,000 web pages across more than a dozen U.S. government websites have been taken down since Friday afternoon, a New York Times analysis has found, as federal agencies rush to heed President Trump’s orders targeting diversity initiatives and “gender ideology.”

The purges have removed information about vaccines, veterans’ care, hate crimes and scientific research, among many other topics. Doctors, researchers and other professionals often rely on such government data and advisories. Some government agencies appear to have removed entire sections of their websites, while others are missing only a handful of pages.

Among the pages that have been taken down:

(The links are to archived versions.)

Developing a theory of robust democracy

Curated on Posted on by Stefaan Verhulst

Paper by Eva Sørensen and Mark E. Warren: “While many democratic theorists recognise the necessity of reforming liberal democracies to keep pace with social change, they rarely consider what enables such reform. In this conceptual article, we suggest that liberal democracies are politically robust when they are able to continuously adapt and innovate how they operate when doing so is necessary to continue to serve key democratic functions. These functions include securing the empowered inclusion of those affected, collective agenda setting and will formation, and the making of joint decisions. Three current challenges highlight the urgency of adapting and innovating liberal democracies to become more politically robust: an increasingly assertive political culture, the digitalisation of political communication and increasing global interdependencies. A democratic theory of political robustness emphasises the need to strengthen the capacity of liberal democracies to adapt and innovate in response to changes, just as it helps to frame the necessary adaptations and innovations in times such as the present…(More)”

The Impact of Artificial Intelligence on Societies

Curated on Posted on by Stefaan Verhulst

Book edited by Christian Montag and Raian Ali: “This book presents a recent framework proposed to understand how attitudes towards artificial intelligence are formed. It describes how the interplay between different variables, such as the modality of AI interaction, the user personality and culture, the type of AI applications (e.g. in the realm of education, medicine, transportation, among others), and the transparency and explainability of AI systems contributes to understand how user’s acceptance or a negative attitude towards AI develops. Gathering chapters from leading researchers with different backgrounds, this book offers a timely snapshot on factors that will be influencing the impact of artificial intelligence on societies…(More)”.

Establish data collaboratives to foster meaningful public involvement

Curated on Posted on by Stefaan Verhulst

Article by Gwen Ottinger: “…Data Collaboratives would move public participation and community engagement upstream in the policy process by creating opportunities for community members to contribute their lived experience to the assessment of data and the framing of policy problems. This would in turn foster two-way communication and trusting relationships between government and the public. Data Collaboratives would also help ensure that data and their uses in federal government are equitable, by inviting a broader range of perspectives on how data analysis can promote equity and where relevant data are missing. Finally, Data Collaboratives would be one vehicle for enabling individuals to participate in science, technology, engineering, math, and medicine activities throughout their lives, increasing the quality of American science and the competitiveness of American industry…(More)”.

Local Government: Artificial intelligence use cases

Curated on Posted on by Stefaan Verhulst

Repository by the (UK) Local Government Association: “Building on the findings of our recent AI survey, which highlighted the need for practical examples, this bank showcases the diverse ways local authorities are leveraging AI. 

Within this collection, you’ll discover a spectrum of AI adoption, ranging from utilising AI assistants to streamline back-office tasks to pioneering the implementation of bespoke Large Language Models (LLMs). These real-world use cases exemplify the innovative spirit driving advancements in local government service delivery. 

Whether your council is at the outset of its AI exploration or seeking to expand its existing capabilities, this bank offers a wealth of valuable insights and best practices to support your organisation’s AI journey…(More)”.

The Nature and Dynamics of Collaboration

Curated on Posted on by Stefaan Verhulst

Book edited by Paul F. M. J. Verschure: “Human existence depends critically on how well diverse social, cultural and political groups can collaborate. Yet the phenomenon of collaboration itself is ill-defined and badly understood, and there is no straightforward formula for its successful realization. In The Nature and Dynamics of Collaboration, edited by Paul F. M. J. Verschure, experts from wide-ranging disciplines examine how human collaboration arises, breaks down, and potentially recovers. They explore the different contexts, boundary conditions, and drivers of collaboration to expand understanding of the underlying dynamic, multiscale processes in an effort to increase chances for ethical, sustainable, and productive collaboration in the future. This volume is accompanied by twenty-four podcasts, which provide insights from real-world examples…(More)”.

Developing a public-interest training commons of books

Curated on Posted on by Stefaan Verhulst

Article by Authors Alliance: “…is pleased to announce a new project, supported by the Mellon Foundation, to develop an actionable plan for a public-interest book training commons for artificial intelligence. Northeastern University Library will be supporting this project and helping to coordinate its progress.

Access to books will play an essential role in how artificial intelligence develops. AI’s Large Language Models (LLMs) have a voracious appetite for text, and there are good reasons to think that these data sets should include books and lots of them. Over the last 500 years, human authors have written over 129 million books. These volumes, preserved for future generations in some of our most treasured research libraries, are perhaps the best and most sophisticated reflection of all human thinking. Their high editorial quality, breadth, and diversity of content, as well as the unique way they employ long-form narratives to communicate sophisticated and nuanced arguments and ideas make them ideal training data sources for AI.

These collections and the text embedded in them should be made available under ethical and fair rules as the raw material that will enable the computationally intense analysis needed to inform new AI models, algorithms, and applications imagined by a wide range of organizations and individuals for the benefit of humanity…(More)”