Rethinking Dual-Use Technology


Article by Artur Kluz and Stefaan Verhulst: “A new concept of “triple use” — where technology serves commercial, defense, and peacebuilding purposes — may offer a breakthrough solution for founders, investors and society to explore….

As a result of the resurgence of geopolitical tensions, the debate about the applications of dual-use technology is intensifying. The core issue founders, tech entrepreneurs, venture capitalists (VCs), and limited partner investors (LPs) are examining is whether commercial technologies should increasingly be re-used for military purposes. Traditionally, the majority of  investors (including limited partners) have prohibited dual-use tech in their agreements. However, the rapidly growing dual-use market, with its substantial addressable size and growth potential, is compelling all stakeholders to reconsider this stance. The pressure for innovations, capital returns and Return On Investment (ROI) is driving the need for a solution. 

These discussions are fraught with moral complexity, but they also present an opportunity to rethink the dual-use paradigm and foster investment in technologies aimed at supporting peace. A new concept of “triple use”— where technology serves commercial, defense, and peacebuilding purposes — may offer an innovative and more positive avenue for founders, investors and society to explore. This additional re-use, which remains in an incipient state, is increasingly being referred to as PeaceTech. By integrating terms dedicated to PeaceTech in new and existing investment and LP agreements, tech companies, founders and venture capital investors can be also required to apply their technology for peacebuilding purposes. This approach can expand the applications of emerging technologies to also include conflict prevention, reconstruction or any humanitarian aspects.

However, current efforts to use technologies for peacebuilding are impeded by various obstacles, including a lack of awareness within the tech sector and among investors, limited commercial interest, disparities in technical capacity, privacy concerns, international relations and political complexities. In the below we examine some of these challenges, while also exploring certain avenues for overcoming them — including approaching technologies for peace as a “triple use” application. We will especially try to identify examples of how tech companies, tech entrepreneurs, accelerators, and tech investors including VCs and LPs can commercially benefit and support “triple use” technologies. Ultimately, we argue, the vast potential — largely untapped — of “triple use” technologies calls for a new wave of tech ecosystem transformation and public and private investments as well as the development of a new field of research…(More)”.

Policy fit for the future: the Australian Government Futures primer


Primer by Will Hartigan and Arthur Horobin: “Futures is a systematic exploration of probable, possible and preferable future developments to inform present-day policy, strategy and decision-making. It uses multiple plausible scenarios of the future to anticipate and make sense of disruptive change. It is also known as strategic foresight...

This primer provides an overview of Futures methodologies and their practical application to policy development and advice. It is a first step for policy teams and officers interested in Futures: providing you with a range of flexible tools, ideas and advice you can adapt to your own policy challenges and environments.

This primer was developed by the Policy Projects and Taskforce Office in the Department of Prime Minister and Cabinet. We have drawn on expertise from inside and outside of government –including through our project partners, the Futures Hub at the National Security College in the Australian National University. 

This primer has been written by policy officers, for policy officers –with a focus on practical and tested approaches that can support you to create policy fit for the future…(More)”.

The Data That Powers A.I. Is Disappearing Fast


Article by Kevin Roose: “For years, the people building powerful artificial intelligence systems have used enormous troves of text, images and videos pulled from the internet to train their models.

Now, that data is drying up.

Over the past year, many of the most important web sources used for training A.I. models have restricted the use of their data, according to a study published this week by the Data Provenance Initiative, an M.I.T.-led research group.

The study, which looked at 14,000 web domains that are included in three commonly used A.I. training data sets, discovered an “emerging crisis in consent,” as publishers and online platforms have taken steps to prevent their data from being harvested.

The researchers estimate that in the three data sets — called C4, RefinedWeb and Dolma — 5 percent of all data, and 25 percent of data from the highest-quality sources, has been restricted. Those restrictions are set up through the Robots Exclusion Protocol, a decades-old method for website owners to prevent automated bots from crawling their pages using a file called robots.txt.

The study also found that as much as 45 percent of the data in one set, C4, had been restricted by websites’ terms of service.

“We’re seeing a rapid decline in consent to use data across the web that will have ramifications not just for A.I. companies, but for researchers, academics and noncommercial entities,” said Shayne Longpre, the study’s lead author, in an interview.

Data is the main ingredient in today’s generative A.I. systems, which are fed billions of examples of text, images and videos. Much of that data is scraped from public websites by researchers and compiled in large data sets, which can be downloaded and freely used, or supplemented with data from other sources…(More)”.

Precision public health in the era of genomics and big data


Paper by Megan C. Roberts et al: “Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level—thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for ‘precision’ to enhance traditional public health approaches…(More)”.

Integrating Artificial Intelligence into Citizens’ Assemblies: Benefits, Concerns and Future Pathways


Paper by Sammy McKinney: “Interest in how Artificial Intelligence (AI) could be used within citizens’ assemblies (CAs) is emerging amongst scholars and practitioners alike. In this paper, I make four contributions at the intersection of these burgeoning fields. First, I propose an analytical framework to guide evaluations of the benefits and limitations of AI applications in CAs. Second, I map out eleven ways that AI, especially large language models (LLMs), could be used across a CAs full lifecycle. This introduces novel ideas for AI integration into the literature and synthesises existing proposals to provide the most detailed analytical breakdown of AI applications in CAs to date. Third, drawing on relevant literature, four key informant interviews, and the Global Assembly on the Ecological and Climate crisis as a case study, I apply my analytical framework to assess the desirability of each application. This provides insight into how AI could be deployed to address existing  challenges facing CAs today as well as the concerns that arise with AI integration. Fourth, bringing my analyses together, I argue that AI integration into CAs brings the potential to enhance their democratic quality and institutional capacity, but realising this requires the deliberative community to proceed cautiously, effectively navigate challenging trade-offs, and mitigate important concerns that arise with AI integration. Ultimately, this paper provides a foundation that can guide future research concerning AI integration into CAs and other forms of democratic innovation…(More)”.

Drivers of Trust in Public Institutions


Press Release: “In an increasingly challenging environment – marked by successive economic shocks, rising protectionism, the war in Europe and ongoing conflicts in the Middle East, as well as structural challenges and disruptions caused by rapid technological developments, climate change and population aging – 44% of respondents now have low or no trust in their national government, surpassing the 39% of respondents who express high or moderately high trust in national government, according to a new OECD report.  

OECD Survey on Drivers of Trust in Public Institutions – 2024 Results, presents findings from the second OECD Trust Survey, conducted in October and November 2023 across 30 Member countries. The biennial report offers a comprehensive analysis of current trust levels and their drivers across countries and public institutions. 

This edition of the Trust Survey confirms the previous finding that socio-economic and demographic factors, as well as a sense of having a say in decision making, affect trust. For example, 36% of women reported high or moderately high trust in government, compared to 43% of men. The most significant drop in trust since 2021 is seen among women and those with lower levels of education. The trust gap is largest between those who feel they have a say and those who feel they do not have a say in what the government does. Among those who report they have a say, 69% report high or moderately high trust in their national government, whereas among those who feel they do not only 22% do…(More)”.

Big Tech-driven deliberative projects


Report by Canning Malkin and Nardine Alnemr: “Google, Meta, OpenAI and Anthropic have commissioned projects based on deliberative democracy. What was the purpose of each project? How was deliberation designed and implemented, and what were the outcomes? In this Technical Paper, Malkin and Alnemr describe the commissioning context, the purpose and remit, and the outcomes of these deliberative projects. Finally, they offer insights on contextualising projects within the broader aspirations of deliberative democracy…(More)”.

Mapping the Landscape of AI-Powered Nonprofits


Article by Kevin Barenblat: “Visualize the year 2050. How do you see AI having impacted the world? Whatever you’re picturing… the reality will probably be quite a bit different. Just think about the personal computer. In its early days circa the 1980s, tech companies marketed the devices for the best use cases they could imagine: reducing paperwork, doing math, and keeping track of forgettable things like birthdays and recipes. It was impossible to imagine that decades later, the larger-than-a-toaster-sized devices would be smaller than the size of Pop-Tarts, connect with billions of other devices, and respond to voice and touch.

It can be hard for us to see how new technologies will ultimately be used. The same is true of artificial intelligence. With new use cases popping up every day, we are early in the age of AI. To make sense of all the action, many landscapes have been published to organize the tech stacks and private sector applications of AI. We could not, however, find an overview of how nonprofits are using AI for impact…

AI-powered nonprofits (APNs) are already advancing solutions to many social problems, and Google.org’s recent research brief AI in Action: Accelerating Progress Towards the Sustainable Development Goals shows that AI is driving progress towards all 17 SDGs. Three goals that stand out with especially strong potential to be transformed by AI are SDG 3 (Good Health and Well-Being), SDG 4 (Quality Education), and SDG 13 (Climate Action). As such, this series focuses on how AI-powered nonprofits are transforming the climate, health care, and education sectors…(More)”.

The Collaboverse: A Collaborative Data-Sharing and Speech Analysis Platform


Paper by Justin D. Dvorak and Frank R. Boutsen: “Collaboration in the field of speech-language pathology occurs across a variety of digital devices and can entail the usage of multiple software tools, systems, file formats, and even programming languages. Unfortunately, gaps between the laboratory, clinic, and classroom can emerge in part because of siloing of data and workflows, as well as the digital divide between users. The purpose of this tutorial is to present the Collaboverse, a web-based collaborative system that unifies these domains, and describe the application of this tool to common tasks in speech-language pathology. In addition, we demonstrate its utility in machine learning (ML) applications…

This tutorial outlines key concepts in the digital divide, data management, distributed computing, and ML. It introduces the Collaboverse workspace for researchers, clinicians, and educators in speech-language pathology who wish to improve their collaborative network and leverage advanced computation abilities. It also details an ML approach to prosodic analysis….

The Collaboverse shows promise in narrowing the digital divide and is capable of generating clinically relevant data, specifically in the area of prosody, whose computational complexity has limited widespread analysis in research and clinic alike. In addition, it includes an augmentative and alternative communication app allowing visual, nontextual communication…(More)”.

Finding, distinguishing, and understanding overlooked policy entrepreneurs


Paper by Gwen Arnold, Meghan Klasic, Changtong Wu, Madeline Schomburg & Abigail York: “Scholars have spent decades arguing that policy entrepreneurs, change agents who work individually and in groups to influence the policy process, can be crucial in introducing policy innovation and spurring policy change. How to identify policy entrepreneurs empirically has received less attention. This oversight is consequential because scholars trying to understand when policy entrepreneurs emerge, and why, and what makes them more or less successful, need to be able to identify these change agents reliably and accurately. This paper explores the ways policy entrepreneurs are currently identified and highlights issues with current approaches. We introduce a new technique for eliciting and distinguishing policy entrepreneurs, coupling automated and manual analysis of local news media and a survey of policy entrepreneur candidates. We apply this technique to the empirical case of unconventional oil and gas drilling in Pennsylvania and derive some tentative results concerning factors which increase entrepreneurial efficacy…(More)”.