Future-Proofing Transparency: Re-Thinking Public Record Governance For the Age of Big Data

Curated on Posted on by Stefaan Verhulst

Paper by Beatriz Botero Arcila: “Public records, public deeds, and even open data portals often include personal information that can now be easily accessed online. Yet, for all the recent attention given to informational privacy and data protection, scant literature exists on the governance of personal information that is available in public documents. This Article examines the critical issue of balancing privacy and transparency within public record governance in the age of Big Data.

With Big Data and powerful machine learning algorithms, personal information in public records can easily be used to infer sensitive data about people or aggregated to create a comprehensive personal profile of almost anyone. This information is public and open, however, for many good reasons: ensuring political accountability, facilitating democratic participation, enabling economic transactions, combating illegal activities such as money laundering and terrorism financing, and facilitating. Can the interest in record publicity coexist with the growing ease of deanonymizing and revealing sensitive information about individuals?

This Article addresses this question from a comparative perspective, focusing on US and EU access to information law. The Article shows that the publicity of records was, in the past and not withstanding its presumptive public nature, protected because most people would not trouble themselves to go to public offices to review them, and it was practical impossible to aggregate them to draw extensive profiles about people. Drawing from this insight and contemporary debates on data governance, this Article challenges the binary classification of data as either published or not and proposes a risk-based framework that re-insert that natural friction to public record governance by leveraging techno-legal methods in how information is published and accessed…(More)”.

Creating Real Value: Skills Data in Learning and Employment Records

Curated on Posted on by Stefaan Verhulst

Article by Nora Heffernan: “Over the last few months, I’ve asked the same question to corporate leaders from human resources, talent acquisition, learning and development, and management backgrounds. The question is this:

What kind of data needs to be included in learning and employment records to be of greatest value to you in your role and to your organization?

By data, I’m talking about credential attainment, employment history, and, emphatically, verified skills data: showing at an individual level what a candidate or employee knows and is able to do.

The answer varies slightly by industry and position, but unanimously, the employers I’ve talked to would find the greatest value in utilizing learning and employment records that include verified skills data. There is no equivocation.

And as the national conversation about skills-first talent management continues to ramp up, with half of companies indicating they plan to eliminate degree requirements for some jobs in the next year, the call for verified skill data will only get louder. Employers value skills data for multiple reasons…(More)”.

Defending the rights of refugees and migrants in the digital age

Curated on Posted on by Stefaan Verhulst

Primer by Amnesty International: “This is an introduction to the pervasive and rapid deployment of digital technologies in asylum and migration management systems across the globe including the United States, United Kingdom and the European Union. Defending the rights of refugees and migrants in the digital age, highlights some of the key digital technology developments in asylum and migration management systems, in particular systems that process large quantities of data, and the human rights issues arising from their use. This introductory briefing aims to build our collective understanding of these emerging technologies and hopes to add to wider advocacy efforts to stem their harmful effects…(More)”.

AI for Good: Applications in Sustainability, Humanitarian Action, and Health

Curated on Posted on by Stefaan Verhulst

Book by Juan M. Lavista Ferres, and William B. Weeks: “…delivers an insightful and fascinating discussion of how one of the world’s most recognizable software companies is tackling intractable social problems with the power of artificial intelligence (AI). In the book, you’ll see real in-the-field examples of researchers using AI with replicable methods and reusable AI code to inspire your own uses.

The authors also provide:

  • Easy-to-follow, non-technical explanations of what AI is and how it works
  • Examples of the use of AI for scientists working on mitigating climate change, showing how AI can better analyze data without human bias, remedy pattern recognition deficits, and make use of satellite and other data on a scale never seen before so policy makers can make informed decisions
  • Real applications of AI in humanitarian action, whether in speeding disaster relief with more accurate data for first responders or in helping address populations that have experienced adversity with examples of how analytics is being used to promote inclusivity
  • A deep focus on AI in healthcare where it is improving provider productivity and patient experience, reducing per-capita healthcare costs, and increasing care access, equity, and outcomes
  • Discussions of the future of AI in the realm of social benefit organizations and efforts…(More)”

The Cult of AI

Curated on Posted on by Stefaan Verhulst

Article by Robert Evans: “…Cult members are often depicted in the media as weak-willed and foolish. But the Church of Scientology — long accused of being a cult, an allegation they have endlessly denied — recruits heavily among the rich and powerful. The Finders, a D.C.-area cult that started in the 1970s, included a wealthy oil-company owner and multiple members with Ivy League degrees. All of them agreed to pool their money and hand over control of where they worked and how they raised their children to their cult leader. Haruki Murakami wrote that Aum Shinrikyo members, many of whom were doctors or engineers, “actively sought to be controlled.”

Perhaps this feels like a reach. But the deeper you dive into the people — and subcultures that are pushing AI forward — the more cult dynamics you begin to notice.

I should offer a caveat here: There’s nothing wrong with the basic technology we call “AI.” That wide banner term includes tools as varied as text- or facial-recognition programs, chatbots, and of course sundry tools to clone voices and generate deepfakes or rights-free images with odd numbers of fingers. CES featured some real products that harnessed the promise of machine learning (I was particularly impressed by a telescope that used AI to clean up light pollution in images). But the good stuff lived alongside nonsense like “ChatGPT for dogs” (really just an app to read your dog’s body language) and an AI-assisted fleshlight for premature ejaculators. 

And, of course, bad ideas and irrational exuberance are par for the course at CES. Since 1967, the tech industry’s premier trade show has provided anyone paying attention with a preview of how Big Tech talks about itself, and our shared future. But what I saw this year and last year, from both excited futurist fanboys and titans of industry, is a kind of unhinged messianic fervor that compares better to Scientology than to the iPhone…(More)”.

Why Machines Learn: The Elegant Maths Behind Modern AI

Curated on Posted on by Stefaan Verhulst

Book by Anil Ananthaswamy: “Machine-learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether someone gets bail. They now influence discoveries in chemistry, biology and physics – the study of genomes, extra-solar planets, even the intricacies of quantum systems.

We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. It took the development of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see all around us today. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules…(More)”.

Governing Data and AI to Protect Inner Freedoms Includes a Role for IP

Curated on Posted on by Stefaan Verhulst

Article by Giuseppina (Pina) D’Agostino and Robert Fay: “Generative artificial intelligence (AI) has caught regulators everywhere by surprise. Its ungoverned and growing ubiquity is similar to that of the large digital platforms that play an important role in the work and personal lives of billions of individuals worldwide. These platforms rely on advertising revenue dependent on user data derived from numerous undisclosed sources, including through covert tracking of interactions on digital platforms, surveillance of conversations, monitoring of activity across platforms and acquisition of biometric data through immersive virtual reality games, just to name a few.

This complex milieu creates a suite of public policy challenges. One of the most important yet least explored is the intersection of intellectual property (IP), data governance, AI and the platforms’ underlying business model. The global scale, the quasi-monopolistic dominance enjoyed by the large platforms, and their control over data and data analytics have explicit implications for fundamental human rights, including freedom of thought…(More)”.

Selecting Anticipatory Methods for Migration Policy: Eight Key Elements To Consider

Curated on Posted on by Stefaan Verhulst

Blog by Sara Marcucci, Stefaan Verhulst, and Alina Menocal Peters: “Over the past several weeks, we’ve embarked on a journey exploring anticipatory methods for migration policy. Our exploration has taken us through the value proposition, challenges, taxonomy, and practical applications of these innovative methods. In this concluding blog, we unveil eight key considerations that policymakers’ may want to consider when choosing an anticipatory method for migration policy. By dissecting these factors, our intent is to equip decision-makers to navigate the complexities inherent in selecting anticipatory methodologies. 

  1. Nature and Determinants of Migration

When addressing migration policy challenges, the multifaceted nature of the type of migration is important when selecting anticipatory methods. Indeed, the specific challenges associated with anticipating migration can vary widely based on the context, causes, and characteristics of the movement. The complexity of the question at hand often determines the selection of methods or approaches. For instance, managing the integration of displaced populations following a conflict involves intricate factors such as cultural adaptation, economic integration, and community dynamics. If the question is about understanding the inferences and drivers that can predict migration patterns, methods like Cross-impact Analysis or System Dynamics Modeling can prove to be valuable. These can facilitate a comprehensive assessment of interdependencies and potential ripple effects, offering policymakers insights into the dynamic and interconnected nature of challenges associated with migration…(More)…See also Special Series on Anticipating Migration.

Guardrails: Guiding Human Decisions in the Age of AI

Curated on Posted on by Stefaan Verhulst

Book by Urs Gasser and Viktor Mayer-Schönberger: “When we make decisions, our thinking is informed by societal norms, “guardrails” that guide our decisions, like the laws and rules that govern us. But what are good guardrails in today’s world of overwhelming information flows and increasingly powerful technologies, such as artificial intelligence? Based on the latest insights from the cognitive sciences, economics, and public policy, Guardrails offers a novel approach to shaping decisions by embracing human agency in its social context.

In this visionary book, Urs Gasser and Viktor Mayer-Schönberger show how the quick embrace of technological solutions can lead to results we don’t always want, and they explain how society itself can provide guardrails more suited to the digital age, ones that empower individual choice while accounting for the social good, encourage flexibility in the face of changing circumstances, and ultimately help us to make better decisions as we tackle the most daunting problems of our times, such as global injustice and climate change.

Whether we change jobs, buy a house, or quit smoking, thousands of decisions large and small shape our daily lives. Decisions drive our economies, seal the fate of democracies, create war or peace, and affect the well-being of our planet. Guardrails challenges the notion that technology should step in where our own decision making fails, laying out a surprisingly human-centered set of principles that can create new spaces for better decisions and a more equitable and prosperous society…(More)”.

Collective action for responsible AI in health

Curated on Posted on by Stefaan Verhulst

OECD Report: “Artificial intelligence (AI) will have profound impacts across health systems, transforming health care, public health, and research. Responsible AI can accelerate efforts toward health systems being more resilient, sustainable, equitable, and person-centred. This paper provides an overview of the background and current state of artificial intelligence in health, perspectives on opportunities, risks, and barriers to success. The paper proposes several areas to be explored for policy-makers to advance the future of responsible AI in health that is adaptable to change, respects individuals, champions equity, and achieves better health outcomes for all.

The areas to be explored relate to trust, capacity building, evaluation, and collaboration. This recognises that the primary forces that are needed to unlock the value from artificial intelligence are people-based and not technical…(More)”