God-like: A 500-Year History of Artificial Intelligence in Myths, Machines, Monsters

Curated on Posted on by Stefaan Verhulst

Book by Kester Brewin: “In the year 1600 a monk is burned at the stake for claiming to have built a device that will allow him to know all things.

350 years later, having witnessed ‘Trinity’ – the first test of the atomic bomb – America’s leading scientist outlines a memory machine that will help end war on earth.

25 years in the making, an ex-soldier finally unveils this ‘machine for augmenting human intellect’, dazzling as he stands ‘Zeus-like, dealing lightning with both hands.’

AI is both stunningly new and rooted in ancient desires. As we finally welcome this ‘god-like’ technology amongst us, what can learn from the myths and monsters of the past about how to survive alongside our greatest ever invention?…(More)”.

Bring on the Policy Entrepreneurs

Curated on Posted on by Stefaan Verhulst

Article by Erica Goldman: “Teaching early-career researchers the skills to engage in the policy arena could prepare them for a lifetime of high-impact engagement and invite new perspectives into the democratic process.

In the first six months of the COVID-19 pandemic, the scientific literature worldwide was flooded with research articles, letters, reviews, notes, and editorials related to the virus. One study estimates that a staggering 23,634 unique documents were published between January 1 and June 30, 2020, alone.

Making sense of that emerging science was an urgent challenge. As governments all over the world scrambled to get up-to-date guidelines to hospitals and information to an anxious public, Australia stood apart in its readiness to engage scientists and decisionmakers collaboratively. The country used what was called a “living evidence” approach to synthesizing new information, making it available—and helpful—in real time.

Each week during the pandemic, the Australian National COVID‑19 Clinical Evidence Taskforce came together to evaluate changes in the scientific literature base. They then spoke with a single voice to the Australian clinical community so clinicians had rapid, evidence-based, and nationally agreed-upon guidelines to provide the clarity they needed to care for people with COVID-19.

This new model for consensus-aligned, evidence-based decisionmaking helped Australia navigate the pandemic and build trust in the scientific enterprise, but it did not emerge overnight. It took years of iteration and effort to get the living evidence model ready to meet the moment; the crisis of the pandemic opened a policy window that living evidence was poised to surge through. Australia’s example led the World Health Organization and the United Kingdom’s National Institute for Health and Care Excellence to move toward making living evidence models a pillar of decisionmaking for all their health care guidelines. On its own, this is an incredible story, but it also reveals a tremendous amount about how policies get changed…(More)”.

Navigating the Future of Work: Perspectives on Automation, AI, and Economic Prosperity

Curated on Posted on by Stefaan Verhulst

Report by Erik Brynjolfsson, Adam Thierer and Daron Acemoglu: “Experts and the media tend to overestimate technology’s negative impact on employment. Case studies suggest that technology-induced unemployment fears are often exaggerated, evidenced by the McKinsey Global Institute reversing its AI forecasts and the growth in jobs predicted to be at high risk of automation.

Flexible work arrangements, technical recertification, and creative apprenticeship models offer real-time learning and adaptable skills development to prepare workers for future labor market and technological changes.

AI can potentially generate new employment opportunities, but the complex transition for workers displaced by automation—marked by the need for retraining and credentialing—indicates that the productivity benefits may not adequately compensate for job losses, particularly among low-skilled workers.

Instead of resorting to conflictual relationships, labor unions in the US must work with employers to support firm automation while simultaneously advocating for worker skill development, creating a competitive business enterprise built on strong worker representation similar to that found in Germany…(More)”.

Meta to shut off data access to journalists

Curated on Posted on by Stefaan Verhulst

Article by Sara Fischer: “Meta plans to officially shutter CrowdTangle, the analytics tool widely used by journalists and researchers to see what’s going viral on Facebook and Instagram, the company’s president of global affairs Nick Clegg told Axios in an interview.

Why it matters: The company plans to instead offer select researchers access to a set of new data tools, but news publishers, journalists or anyone with commercial interests will not be granted access to that data.

The big picture: The effort comes amid a broader pivot from Meta away from news and politics and more toward user-generated viral videos.

  • Meta acquired CrowdTangle in 2016 at a time when publishers were heavily reliant on the tech giant for traffic.
  • In recent years, it’s stopped investing in the tool, making it less reliable.

The new research tools include Meta’s Content Library, which it launched last year, and an API, or backend interface used by developers.

  • Both tools offer researchers access to huge swaths of data from publicly accessible content across Facebook and Instagram.
  • The tools are available in 180 languages and offer global data.
  • Researchers must apply for access to those tools through the Inter-university Consortium for Political and Social Research at the University of Michigan, which will vet their requests…(More)”

A typology of artificial intelligence data work

Curated on Posted on by Stefaan Verhulst

Article by James Muldoon et al: “This article provides a new typology for understanding human labour integrated into the production of artificial intelligence systems through data preparation and model evaluation. We call these forms of labour ‘AI data work’ and show how they are an important and necessary element of the artificial intelligence production process. We draw on fieldwork with an artificial intelligence data business process outsourcing centre specialising in computer vision data, alongside a decade of fieldwork with microwork platforms, business process outsourcing, and artificial intelligence companies to help dispel confusion around the multiple concepts and frames that encompass artificial intelligence data work including ‘ghost work’, ‘microwork’, ‘crowdwork’ and ‘cloudwork’. We argue that these different frames of reference obscure important differences between how this labour is organised in different contexts. The article provides a conceptual division between the different types of artificial intelligence data work institutions and the different stages of what we call the artificial intelligence data pipeline. This article thus contributes to our understanding of how the practices of workers become a valuable commodity integrated into global artificial intelligence production networks…(More)”.

How artificial intelligence can facilitate investigative journalism

Curated on Posted on by Stefaan Verhulst

Article by Luiz Fernando Toledo: “A few years ago, I worked on a project for a large Brazilian television channel whose objective was to analyze the profiles of more than 250 guardianship counselors in the city of São Paulo. These elected professionals have the mission of protecting the rights of children and adolescents in Brazil.

Critics had pointed out that some counselors did not have any expertise or prior experience working with young people and were only elected with the support of religious communities. The investigation sought to verify whether these elected counselors had professional training in working with children and adolescents or had any relationships with churches.

After requesting the counselors’ resumes through Brazil’s access to information law, a small team combed through each resume in depth—a laborious and time-consuming task. But today, this project might have required far less time and labor. Rapid developments in generative AI hold potential to significantly scale access and analysis of data needed for investigative journalism.

Many articles address the potential risks of generative AI for journalism and democracy, such as threats AI poses to the business model for journalism and its ability to facilitate the creation and spread of mis- and disinformation. No doubt there is cause for concern. But technology will continue to evolve, and it is up to journalists and researchers to understand how to use it in favor of the public interest.

I wanted to test how generative AI can help journalists, especially those that work with public documents and data. I tested several tools, including Ask Your PDF (ask questions to any documents in your computer), Chatbase (create your own chatbot), and Document Cloud (upload documents and ask GPT-like questions to hundreds of documents simultaneously).

These tools make use of the same mechanism that operates OpenAI’s famous ChatGPT—large language models that create human-like text. But they analyze the user’s own documents rather than information on the internet, ensuring more accurate answers by using specific, user-provided sources…(More)”.

AI-enhanced Collective Intelligence: The State of the Art and Prospects

Curated on Posted on by Stefaan Verhulst

Paper by Hao Cui and Taha Yasseri: “The current societal challenges exceed the capacity of human individual or collective effort alone. As AI evolves, its role within human collectives is poised to vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, when synergized, can achieve a level of collective intelligence that surpasses the collective capabilities of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising a cognition layer, a physical layer, and an information layer. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. The interplay among these agents shapes the overall structure and dynamics of the system. We explore how agents’ diversity and interactions influence the system’s collective intelligence. Furthermore, we present an analysis of real-world instances of AI-enhanced collective intelligence. We conclude by addressing the potential challenges in AI-enhanced collective intelligence and offer perspectives on future developments in this field…(More)”.

Youth Media Literacy Program Fact Checking Manual

Curated on Posted on by Stefaan Verhulst

Internews: “As part of the USAID-funded Advancing Rights in Southern Africa Program (ARISA), Internews developed the Youth Media Literacy Program to enhance the digital literacy skills of young people. Drawing from university journalism students, and young leaders from civil society organizations in Botswana, Eswatini, Lesotho, and South Africa, the program equipped 124 young people to apply critical thinking to online communication and practice improved digital hygiene and digital security practices. The Youth Media Literacy Program Fact Checking Manual was developed to provide additional support and tools to combat misinformation and disinformation and improve online behavior and security…(More)”.

How to Run a Public Records Audit with a Team of Students

Curated on Posted on by Stefaan Verhulst

Article by By Lam Thuy Vo: “…The Markup (like many other organizations) uses public record requests as an important investigative tool, and we’ve published tips for fellow journalists on how to best craft their requests for specific investigations. But based on where government institutions are located, public record laws vary. Generally, government institutions are required to release documents to anyone who requests them, except when information falls under a specific exemption, like information that invades an individual’s privacy or if there are trade secrets. Federal institutions are governed by the Freedom of Information Act (FOIA), but state or local government agencies have their own state freedom of information laws, and they aren’t all identical. 

Public record audits take a step back. By sending the same freedom of information (FOI) request to agencies around the country, audits can help journalists, researchers and everyday people track which agency will release records and which may not, and if they’re complying with state laws. According to the national freedom of information coalition, “audits have led to legislative reforms and the establishment of ombudsman positions to represent the public’s interests.” 

The basics of auditing is simple: Send the same FOI request to different government agencies, document how you followed up, and document the outcome. Here’s how we coordinated this process with student reporters…(More)”.

Riders in the smog

Curated on Posted on by Stefaan Verhulst

Article by Zuha Siddiqui, Samriddhi Sakuna and Faisal Mahmud: “…To better understand air quality exposure among gig workers in South Asia, Rest of World gave three gig workers — one each in Lahore, New Delhi, and Dhaka — air quality monitors to wear throughout a regular shift in January. The Atmotube Pro monitors continually tracked their exposure to carcinogenic pollutants — specifically PM1, PM2.5, and PM10 (different sizes of particulate matter), and volatile organic compounds such as benzene and formaldehyde.

The data revealed that all three workers were routinely exposed to hazardous levels of pollutants. For PM2.5, referring to particulates that are 2.5 micrometers in diameter or less — which have been linked to health risks including heart attacks and strokes — all riders were consistently logging exposure levels more than 10 times the World Health Organization’s recommended daily average of 15 micrograms per cubic meter. Manu Sharma, in New Delhi, recorded the highest PM2.5 level of the three riders, hitting 468.3 micrograms per cubic meter around 6 p.m. Lahore was a close second, with Iqbal recording 464.2 micrograms per cubic meter around the same time.

Alongside tracking specific pollutants, the Atmotube Pro gives an overall real-time air quality score (AQS) from 0–100, with zero being the most severely polluted, and 100 being the cleanest. According to Atmo, the company that makes the Atmotube monitors, a reading of 0–20 should be considered a health alert, under which conditions “everyone should avoid all outdoor exertion.” But the three gig workers found their monitors consistently displayed the lowest possible score…(More)”.