Book by Ina Sander: “Despite the increasing influence of data technologies on our world, many people still lack a profound understanding of what this ›datafication‹ means for their lives and our societies. Ina Sander argues that this knowledge gap cannot be addressed by digital skills alone, but that more critical and empowering approaches are needed. Through a review of existing literacies, an analysis of established education concepts, and empirical research on online educational resources about datafication, she develops a framework for »critical datafication literacy«. Novel insights on the design strategies, pedagogical methods and challenges of practitioners who foster such education add to her analysis…(More)”.
Article by Andrew R. Chow: “Over the past year, rural farmers in Malawi have been seeking advice about their crops and animals from a generative AI chatbot. These farmers ask questions in Chichewa, their native tongue, and the app, Ulangizi, responds in kind, using conversational language based on information taken from the government’s agricultural manual. “In the past we could wait for days for agriculture extension workers to come and address whatever problems we had on our farms,” Maron Galeta, a Malawian farmer, told Bloomberg. “Just a touch of a button we have all the information we need.”
The nonprofit behind the app, Opportunity International, hopes to bring similar AI-based solutions to other impoverished communities. In February, Opportunity ran an acceleration incubator for humanitarian workers across the world to pitch AI-based ideas and then develop them alongside mentors from institutions like Microsoft and Amazon. On October 30, Opportunity announced the three winners of this program: free-to-use apps that aim to help African farmers with crop and climate strategy, teachers with lesson planning, and school leaders with administration management. The winners will each receive about $150,000 in funding to pilot the apps in their communities, with the goal of reaching millions of people within two years.
Greg Nelson, the CTO of Opportunity, hopes that the program will show the power of AI to level playing fields for those who previously faced barriers to accessing knowledge and expertise. “Since the mobile phone, this is the biggest democratizing change that we have seen in our lifetime,” he says…(More)”.
Open Access Book edited by Giuseppe Ugazio and Milos Maricic: “…acts as a catalyst for the dialogue between two ecosystems with much to gain from collaboration: artificial intelligence (AI) and philanthropy. Bringing together leading academics, AI specialists, and philanthropy professionals, it offers a robust academic foundation for studying both how AI can be used and implemented within philanthropy and how philanthropy can guide the future development of AI in a responsible way.
The contributors to this Handbook explore various facets of the AI‑philanthropy dynamic, critically assess hurdles to increased AI adoption and integration in philanthropy, map the application of AI within the philanthropic sector, evaluate how philanthropy can and should promote an AI that is ethical, inclusive, and responsible, and identify the landscape of risk strategies for their limitations and/or potential mitigation. These theoretical perspectives are complemented by several case studies that offer a pragmatic perspective on diverse, successful, and effective AI‑philanthropy synergies.
As a result, this Handbook stands as a valuable academic reference capable of enriching the interactions of AI and philanthropy, uniting the perspectives of scholars and practitioners, thus building bridges between research and implementation, and setting the foundations for future research endeavors on this topic…(More)”.
JRC Report: “Drawing upon the ambitious policy and legal framework outlined in the Europe Strategy for Data (2020) and the establishment of common European data spaces, this Science for Policy report explores innovative approaches for unlocking relevant data to achieve the objectives of the European Green Deal.
The report focuses on the governance and sharing of Green Deal data, analysing a variety of topics related to the implementation of new regulatory instruments, namely the Data Governance Act and the Data Act, as well as the roles of various actors in the data ecosystem. It provides an overview of the current incentives and disincentives for data sharing and explores the existing landscape of Data Intermediaries and Data Altruism Organizations. Additionally, it offers insights from a private sector perspective and outlines key data governance and sharing practices concerning Citizen-Generated Data (CGD).
The main conclusions build upon the concept of “Systemic Data Justice,” which emphasizes equity, accountability, and fair representation to foster stronger connections between the supply and demand of data for a more effective and sustainable data economy. Five policy recommendations outline a set of main implications and actionable points for the revision of the INSPIRE Directive (2007) within the context of the common European Green Deal data space, and toward a more sustainable and fair data ecosystem. However, the relevance of these recommendations spills over Green Deal data only, as they outline key elements to ensure that any data ecosystem is both just and impact-oriented…(More)”.
Paper by Panos Fitsilis et al: “The significance of open data in higher education stems from the changing tendencies towards open science, and open research in higher education encourages new ways of making scientific inquiry more transparent, collaborative and accessible. This study focuses on the critical role of open data stewards in this transition, essential for managing and disseminating research data effectively in universities, while it also highlights the increasing demand for structured training and professional policies for data stewards in academic settings. Building upon this context, the paper investigates the essential skills and competences required for effective data stewardship in higher education institutions by elaborating on a critical literature review, coupled with practical engagement in open data stewardship at universities, provided insights into the roles and responsibilities of data stewards. In response to these identified needs, the paper proposes a structured training framework and comprehensive curriculum for data stewardship, a direct response to the gaps identified in the literature. It addresses five key competence categories for open data stewards, aligning them with current trends and essential skills and knowledge in the field. By advocating for a structured approach to data stewardship education, this work sets the foundation for improved data management in universities and serves as a critical step towards professionalizing the role of data stewards in higher education. The emphasis on the role of open data stewards is expected to advance data accessibility and sharing practices, fostering increased transparency, collaboration, and innovation in academic research. This approach contributes to the evolution of universities into open ecosystems, where there is free flow of data for global education and research advancement…(More)”.
Article by Scharon Harding: “A trend on Reddit that sees Londoners giving false restaurant recommendations in order to keep their favorites clear of tourists and social media influencers highlights the inherent flaws of Google Search’s reliance on Reddit and Google’s AI Overview.
In May, Google launched AI Overviews in the US, an experimental feature that populates the top of Google Search results with a summarized answer based on an AI model built into Google’s web rankings. When Google first debuted AI Overview, it quickly became apparent that the feature needed work with accuracy and its ability to properly summarize information from online sources. AI Overviews are “built to only show information that is backed up by top web results,” Liz Reid, VP and head of Google Search, wrote in a May blog post. But as my colleague Benj Edwards pointed out at the time, that setup could contribute to inaccurate, misleading, or even dangerous results: “The design is based on the false assumption that Google’s page-ranking algorithm favors accurate results and not SEO-gamed garbage.”
As Edwards alluded to, many have complained about Google Search results’ quality declining in recent years, as SEO spam and, more recently, AI slop float to the top of searches. As a result, people often turn to the Reddit hack to make Google results more helpful. By adding “site:reddit.com” to search results, users can hone their search to more easily find answers from real people. Google seems to understand the value of Reddit and signed an AI training deal with the company that’s reportedly worth $60 million per year…(More)”.
The Observatory includes over 80 examples from several domains and geographies–ranging from supporting administrative work within the legal department of the Government of France to assisting researchers across the African continent in navigating cross-border data sharing laws. The examples include generative AI chatbots to improve access to services, conversational tools to help analyze data, datasets to improve the quality of the AI output, and more. A key feature of the Observatory is its categorization across our Spectrum of Scenarios framework, shown below. Through this effort, we aim to bring together the work already being done and identify ways to use generative AI for the public good.
This Observatory is an attempt to grapple with the work currently being done to apply generative AI in conjunction with official open data. It does not make a value judgment on their efficacy or practices. Many of these examples have ethical implications, which merit further attention and study.
From September through October, we added to the Observatory:
Bayaan Platform: A conversational tool by the Statistics Centre Abu Dhabi that provides decision makers with data analytics and visualization support.
Berufsinfomat: A generative AI tool for career coaching in Austria.
ChatTCU: A chatbot for Brazil’s Federal Court of Accounts.
City of Helsinki’s AI Register: An initiative aimed at leveraging open city data to enhance civic services and facilitate better engagement with residents.
Climate Q&A: A generative AI chatbot that provides information about climate change based on scientific reports.
DataLaw.Bot: A generative AI tool that disseminates data sharing regulations with researchers across several African countries…(More)”.
Article by Si Ying Thian: “In South Korea, open government data is powering artificial intelligence (AI) innovations in the private sector.
Take the case of TTCare which may be the world’s first mobile application to analyse eye and skin disease symptoms in pets.
AI Hub allows users to search by industry, data format and year (top row), with the data sets made available based on the particular search term “pet” (bottom half of the page). Image: AI Hub, provided by courtesy of Baek
The AI model was trained on about one million pieces of data – half of the data coming from the government-led AI Hub and the rest collected by the firm itself, according to the Korean newspaper Donga.
AI Hub is an integrated platform set up by the government to support the country’s AI infrastructure.
TTCare’s CEO Heo underlined the importance of government-led AI training data in improving the model’s ability to diagnose symptoms. The firm’s training data is currently accessible through AI Hub, and any Korean citizen can download or use it.
The government has been pushing the boundaries of what it can do with open data – beyond just making data usable by providing APIs. Application Programming Interfaces, or APIs, make it easier for users to tap on open government data to power their apps and services.
There is now rising interest from public sector agencies to tap on such data to train AI models, said South Korea’s National Information Society Agency (NIA)’s Principal Manager, Dongyub Baek, although this is still at an early stage.
Baek sits in NIA’s open data department, which handles policies, infrastructure such as the National Open Data Portal, as well as impact assessments of the government initiatives…(More)”
Report by Digital Impact Alliance: “In 2024, the northern hemisphere recorded the hottest summer overall, the hottest day, and the hottest ever month of August. That same month – August 2024 – this warming fueled droughts in Italy and intensified typhoons that devastated parts of the Philippines, Taiwan, and China. The following month, new research calculated that warming is costing the global economy billions of dollars: an increase in extreme heat and severe drought costs about 0.2% of a country’s GDP.
These are only the latest stories and statistics that illustrate the growing costs of climate change – data points that have emerged in the short time since we published our second Spotlight on unlocking climate data with open transaction networks.
This third paper in the series continues the work of the Joint Learning Network on Unlocking Data for Climate Action (Climate Data JLN). This multi-disciplinary network identified multiple promising models to explore in the context of unlocking data for climate action. This Spotlight paper examines the third of these models: data spaces. Through examination of data spaces in action, the paper analyzes the key elements that render them more or less applicable to specific climate-related data sets. Data spaces are relatively new and mostly conceptual, with only a handful of implementations in process and concentrated in a few geographic areas. While this model requires extensive up-front work to agree upon governance and technical standards, the result is an approach that overcomes trust and financing issues by maintaining data sovereignty and creating a marketplace for data exchange…(More)”.
Article by Filip Bialy: “AI plays a central role in the 2024 US presidential election, as a tool for disinformation and as a key policy issue. But its significance extends beyond these, connecting to an emerging ideology known as TESCREAL, which envisages AI as a catalyst for unprecedented progress, including space colonisation. After this election, TESCREALism may well have more than one representative in the White House, writes Filip Bialy
In June 2024, the essay Situational Awareness by former OpenAI employee Leopold Aschenbrenner sparked intense debate in the AI community. The author predicted that by 2027, AI would surpass human intelligence. Such claims are common among AI researchers. They often assert that only a small elite – mainly those working at companies like OpenAI – possesses inside knowledge of the technology. Many in this group hold a quasi-religious belief in the imminent arrival of artificial general intelligence (AGI) or artificial superintelligence (ASI)…
These hopes and fears, however, are not only religious-like but also ideological. A decade ago, Silicon Valley leaders were still associated with the so-called Californian ideology, a blend of hippie counterculture and entrepreneurial yuppie values. Today, figures like Elon Musk, Mark Zuckerberg, and Sam Altman are under the influence of a new ideological cocktail: TESCREAL. Coined in 2023 by Timnit Gebru and Émile P. Torres, TESCREAL stands for Transhumanism, Extropianism, Singularitarianism, Cosmism, Rationalism, Effective Altruism, and Longtermism.
While these may sound like obscure terms, they represent ideas developed over decades, with roots in eugenics. Early 20th-century eugenicists such as Francis Galton promoted selective breeding to enhance future generations. Later, with advances in genetic engineering, the focus shifted from eugenics’ racist origins to its potential to eliminate genetic defects. TESCREAL represents a third wave of eugenics. It aims to digitise human consciousness and then propagate digital humans into the universe…(More)”
