We Need To Talk About Climate: How Citizens’ Assemblies Can Help Us Solve The Climate Crisis


Book by Graham Smith: “Citizens’ assemblies bring the shared wisdom of ordinary people into political decision-making. How might they help us address the climate crisis? The transition to net zero and climate resilient societies requires deep social and economic transformations that will have significant effects on citizens’ lives. Such a transition needs to engage the public directly. Climate assemblies show us how this can be done.

This book explains the variety of climate assemblies that have taken place so far at local, national and international levels and explains why they have captured the imagination of government and activists alike. It examines the different contexts and designs of climate assemblies and assesses their impact. Drawing lessons from current practice, the book demonstrates how assemblies can take us beyond the shortcomings of electoral and partisan politics and how they can have a real and lasting impact on climate policy and politics…(More)”.

Uniting the UK’s Health Data: A Huge Opportunity for Society’


The Sudlow Review (UK): “…Surveys show that people in the UK overwhelmingly support the use of their health data with appropriate safeguards to improve lives. One of the review’s recommendations calls for continued engagement with patients, the public, and healthcare professionals to drive forward developments in health data research.

The review also features several examples of harnessing health data for public benefit in the UK, such as the national response to the COVID-19 pandemic. But successes like these are few and far between due to complex systems and governance. The review reveals that:

  • Access to datasets is difficult or slow, often taking months or even years.
  • Data is accessible for analysis and research related to COVID-19, but not to tackle other health conditions, such as other infectious diseases, cancer, heart disease, stroke, diabetes and dementia.
  • More complex types of health data generally don’t have national data systems (for example, most lab testing data and radiology imaging).
  • Barriers like these can delay or prevent hundreds of studies, holding back progress that could improve lives…

The Sudlow Review’s recommendations provide a pathway to establishing a secure and trusted health data system for the UK:

  1. Major national public bodies with responsibility for or interest in health data should agree a coordinated joint strategy to recognise England’s health data for what they are: a critical national infrastructure.
  2. Key government health, care and research bodies should establish a national health data service in England with accountable senior leadership.
  3. The Department of Health and Social Care should oversee and commission ongoing, coordinated, engagement with patients, public, health professionals, policymakers and politicians.
  4. The health and social care departments in the four UK nations should set a UK-wide approach to streamline data access processes and foster proportionate, trustworthy data governance.
  5. National health data organisations and statistical authorities in the four UK nations should develop a UK-wide system for standards and accreditation of secure data environments (SDEs) holding data from the health and care system…(More)”.

Once Upon a Crime: Towards Crime Prediction from Demographics and Mobile Data


Paper by Andrey Bogomolov, Bruno Lepri, Jacopo Staiano, Nuria Oliver, Fabio Pianesi, and Alex Pentland: “In this paper, we present a novel approach to predict crime in a geographic space from multiple data sources, in particular mobile phone and demographic data. The main contribution of the proposed approach lies in using aggregated and anonymized human behavioral data derived from mobile network activity to tackle the crime prediction problem. While previous research efforts have used either background historical knowledge or offenders’ profiling, our findings support the hypothesis that aggregated human behavioral data captured from the mobile network infrastructure, in combination with basic demographic information, can be used to predict crime. In our experimental results with real crime data from London we obtain an accuracy of almost 70% when predicting whether a specific area in the city will be a crime hotspot or not. Moreover, we provide a discussion of the implications of our findings for data-driven crime analysis…(More)”.

Federated Data Infrastructures for Scientific Use


Policy paper by the German Council for Scientific Information Infrastructures: “…provides an overview and a comparative in-depth analysis of the emerging research (and research related) data infrastructures NFDI, EOSC, Gaia-X and the European Data Spaces. In addition, the Council makes recommendations for their future development and coordination. The RfII notes that access to genuine high-quality research data and related core services is a matter of basic public supply and strongly advises to achieve coherence between the various initiatives and approaches…(More)”.

Lottocracy: Democracy Without Elections


Book by Alexander Guerrero: “Democracy is in trouble. The system isn’t working. Inequality increases, many can barely get by, the elite control our political institutions. The earth, our only home, gets warmer year by year. We are deeply divided, unable to work together to address the problems we face. What if elections are the problem?

Lottocracy makes the case that electoral representative democracy—although the best form of government that has been tried—runs into deep problems in the modern world.

But it is not a message of despair. To the contrary. Lottocracy sets out a detailed vision of a new kind of democracy, as system that uses lotteries, rather than elections, to select our political representatives.

Perhaps we can use this wild ancient idea to build a new, better democracy for the 21st century and beyond…(More)”.

Critical Datafication Literacy


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)”.

Inside the New Nonprofit AI Initiatives Seeking to Aid Teachers and Farmers in Rural Africa


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)”.

The Routledge Handbook of Artificial Intelligence and Philanthropy


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)”.

Conversational Swarms of Humans and AI Agents enable Hybrid Collaborative Decision-making


Paper by Louis Rosenberg et al: “Conversational Swarm Intelligence (CSI) is an AI-powered communication and collaboration technology that allows large, networked groups (of potentially unlimited size) to hold thoughtful conversational deliberations in real-time. Inspired by the efficient decision-making dynamics of fish schools, CSI divides a human population into a set of small subgroups connected by AI agents. This enables the full group to hold a unified conversation. In this study, groups of 25 participants were tasked with selecting a roster of players in a real Fantasy Baseball contest. A total of 10 trials were run using CSI. In half the trials, each subgroup was augmented with a fact-providing AI agent referred to herein as an Infobot. The Infobot was loaded with a wide range of MLB statistics. The human participants could query the Infobot the same way they would query other persons in their subgroup. Results show that when using CSI, the 25-person groups outperformed 72% of individually surveyed participants and showed significant intelligence amplification versus the mean score (p=0.016). The CSI-enabled groups also significantly outperformed the most popular picks across the collected surveys for each daily contest (p<0.001). The CSI sessions that used Infobots scored slightly higher than those that did not, but it was not statistically significant in this study. That said, 85% of participants agreed with the statement ‘Our decisions were stronger because of information provided by the Infobot’ and only 4% disagreed. In addition, deliberations that used Infobots showed significantly less variance (p=0.039) in conversational content across members. This suggests that Infobots promoted more balanced discussions in which fewer members dominated the dialog. This may be because the infobot enabled participants to confidently express opinions with the support of factual data…(More)”.

Annoyed Redditors tanking Google Search results illustrates perils of AI scrapers


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)”.