Drivers of Trust in Public Institutions

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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)”.

The Digital Economy Report 2024

Curated on Posted on by Stefaan Verhulst

Report by UNCTAD: “…underscores the urgent need for environmentally sustainable and inclusive digitalization strategies.

Digital technology and infrastructure depend heavily on raw materials, and the production and disposal of more and more devices, along with growing water and energy needs are taking an increasing toll on the planet.

For example, the production and use of digital devices, data centres and information and communications technology (ICT) networks account for an estimated 6% to 12% of global electricity use.

Developing countries bear the brunt of the environmental costs of digitalization while reaping fewer benefits. They export low value-added raw materials and import high value-added devices, along with increasing digital waste. Geopolitical tensions over critical minerals, abundant in many of these countries, complicate the challenges.

The report calls for bold action from policymakers, industry leaders and consumers. It urges a global shift towards a circular digital economy, focusing on circularity by design through durable products, responsible consumption, reuse and recycling, and sustainable business models…(More)”.

The era of predictive AI Is almost over

Curated on Posted on by Stefaan Verhulst

Essay by Dean W. Ball: “Artificial intelligence is a Rorschach test. When OpenAI’s GPT-4 was released in March 2023, Microsoft researchers triumphantly, and prematurely, announced that it possessed “sparks” of artificial general intelligence. Cognitive scientist Gary Marcus, on the other hand, argued that Large Language Models like GPT-4 are nowhere close to the loosely defined concept of AGI. Indeed, Marcus is skeptical of whether these models “understand” anything at all. They “operate over ‘fossilized’ outputs of human language,” he wrote in a 2023 paper, “and seem capable of implementing some automatic computations pertaining to distributional statistics, but are incapable of understanding due to their lack of generative world models.” The “fossils” to which Marcus refers are the models’ training data — these days, something close to all the text on the Internet.

This notion — that LLMs are “just” next-word predictors based on statistical models of text — is so common now as to be almost a trope. It is used, both correctly and incorrectly, to explain the flaws, biases, and other limitations of LLMs. Most importantly, it is used by AI skeptics like Marcus to argue that there will soon be diminishing returns from further LLM development: We will get better and better statistical approximations of existing human knowledge, but we are not likely to see another qualitative leap toward “general intelligence.”

There are two problems with this deflationary view of LLMs. The first is that next-word prediction, at sufficient scale, can lead models to capabilities that no human designed or even necessarily intended — what some call “emergent” capabilities. The second problem is that increasingly — and, ironically, starting with ChatGPT — language models employ techniques that combust the notion of pure next-word prediction of Internet text…(More)”

Your Driving App Is Leading You Astray

Curated on Posted on by Stefaan Verhulst

Article by Julia Angwin: “…If you use a navigation app, you probably have felt helpless anger when your stupid phone endangers your life, and the lives of all the drivers around you, to potentially shave a minute or two from your drive time. Or maybe it’s stuck you on an ugly freeway when a glorious, ocean-hugging alternative lies a few miles away. Or maybe it’s trapped you on a route with no four-way stops, ignoring a less stressful solution that doesn’t leave you worried about a car barreling out of nowhere.

For all the discussion of the many extraordinary ways algorithms have changed our society and our lives, one of the most impactful, and most infuriating, often escapes notice. Dominated by a couple of enormously powerful tech monopolists that have better things to worry about, our leading online mapping systems from Google and Apple are not nearly as good as they could be.

You may have heard the extreme stories, such as when navigation apps like Waze and Google Maps apparently steered drivers into lakes and onto impassable dirt roads, or when jurisdictions beg Waze to stop dumping traffic onto their residential streets. But the reality is these apps affect us, our roads and our communities every minute of the day. Primarily programmed to find the fastest route, they endanger and infuriate us on a remarkably regular basis….

The best hope for competition relies on the success of OpenStreetMap. Its data underpins most maps other than Google, including Amazon, Facebook and Apple, but it is so under-resourced that it only recently hired paid systems administrators to ensure its back-end machines kept running….In addition, we can promote competition by using the few available alternatives. To navigate cities with public transit, try apps such as Citymapper that offer bike, transit and walking directions. Or use the privacy-focused Organic Maps…(More)”.

Exploring Digital Biomarkers for Depression Using Mobile Technology

Curated on Posted on by Stefaan Verhulst

Paper by Yuezhou Zhang et al: “With the advent of ubiquitous sensors and mobile technologies, wearables and smartphones offer a cost-effective means for monitoring mental health conditions, particularly depression. These devices enable the continuous collection of behavioral data, providing novel insights into the daily manifestations of depressive symptoms.

We found several significant links between depression severity and various behavioral biomarkers: elevated depression levels were associated with diminished sleep quality (assessed through Fitbit metrics), reduced sociability (approximated by Bluetooth), decreased levels of physical activity (quantified by step counts and GPS data), a slower cadence of daily walking (captured by smartphone accelerometers), and disturbances in circadian rhythms (analyzed across various data streams).
Leveraging digital biomarkers for assessing and continuously monitoring depression introduces a new paradigm in early detection and development of customized intervention strategies. Findings from these studies not only enhance our comprehension of depression in real-world settings but also underscore the potential of mobile technologies in the prevention and management of mental health issues…(More)”

Future of Professionals

Curated on Posted on by Stefaan Verhulst

Report by Thomson Reuters: “First, the productivity benefits we have been promised are now becoming more apparent. As AI adoption has become widespread, professionals can more tangibly tell us about how they will use this transformative technology and the greater efficiency and value it will provide. The most common use cases for AI-powered technology thus far include drafting documents, summarizing information, and performing basic research. Second, there’s a tremendous sense of excitement about the value that new AI-powered technology can bring to the day-to-day lives of the professionals we surveyed. While more than half of professionals said they’re most excited about the benefits that new AI-powered technologies can bring in terms of time-savings, nearly 40% said the new value that will be brought is what excites them the most.

This report highlights how AI could free up that precious commodity of time. As with the adoption of all new technology, change appears moderate and the impact incremental. And yet, within the year, our respondents predicted that for professionals, AI could free up as much as four hours a week. What will they do with 200 extra hours of time a year? They might reinvest that time in strategic work, innovation, and professional development, which could help companies retain or advance their competitive advantage. Imagine the broader impact on the economy and GDP from this increased efficiency. For US lawyers alone, that is a combined 266 million hours of increased productivity. That could translate into $100,000 in new, billable time per lawyer each year, based on current average rates – with similar productivity gains projected across various professions. The time saved can also be reinvested in professional development, nurturing work-life balance, and focusing on wellness and mental health. Moreover, the economic and organizational benefits of these time-savings are substantial. They could lead to reduced operational costs and higher efficiency, while enabling organizations to redirect resources toward strategic initiatives, fostering growth and competitiveness.

Finally, it’s important to acknowledge there’s still a healthy amount of reticence among professionals to fully adopt AI. Respondents are concerned primarily with the accuracy of outputs, and almost two-thirds of respondents agreed that data security is a vital component of responsible use. These concerns aren’t trivial, and they warrant attention as we navigate this new era of technology. While AI can provide tremendous productivity benefits to professionals and generate greater value for businesses, that’s only possible if we build and use this technology responsibly.”…(More)”.