How tax data unlocks new insights for industrial policy


OECD article: “Value-added tax (VAT) is a consumption tax applied at each stage of the supply chain whenever value is added to goods or services. Businesses collect and remit VAT. The VAT data that are collected represent a breakthrough in studying production networks because they capture actual transactions between firms at an unprecedented level of detail. Unlike traditional business surveys or administrative data that might tell us about a firm’s size or industry, VAT records show us who does business with whom and for how much.

This data is particularly valuable because of its comprehensive coverage. In Estonia, for example, all VAT-registered businesses must report transactions above €1,000 per month, creating an almost complete picture of significant business relationships in the economy.

At least 15 countries now have such data available, including Belgium, Chile, Costa Rica, Estonia, and Italy. This growing availability creates opportunities for cross-country comparison and broader economic insights…(More)”.

On the Shoulders of Others: The Importance of Regulatory Learning in the Age of AI


Paper by Urs Gasser and Viktor Mayer-Schonberger: “…International harmonization of regulation is the right strategy when the appropriate regulatory ends and means are sufficiently clear to reap efficiencies of scale and scope. When this is not the case, a push for efficiency through uniformity is premature and may lead to a suboptimal regulatory lock-in: the establishment of a rule framework that is either inefficient in the use of its means to reach the intended goal, or furthers the wrong goal, or both.


A century ago, economist Joseph Schumpeter suggested that companies have two distinct strategies to achieve success. The first is to employ economies of scale and scope to lower their cost. It’s essentially a push for improved efficiency. The other strategy is to invent a new product (or production process) that may not, at least initially, be hugely efficient, but is nevertheless advantageous because demand for the new product is price inelastic. For Schumpeter this was the essence of innovation. But, as Schumpeter also argued, innovation is not a simple, linear, and predictable process. Often, it happens in fits and starts, and can’t be easily commandeered or engineered.


As innovation is hard to foresee and plan, the best way to facilitate it is to enable a wide variety of different approaches and solutions. Public policies in many countries to foster startups and entrepreneurship stems from this view. Take, for instance, the policy of regulatory sandboxing, i.e. the idea that for a limited time certain sectors should not or only lightly be regulated…(More)”.

A.I. Is Prompting an Evolution, Not an Extinction, for Coders


Article by Steve Lohr: “John Giorgi uses artificial intelligence to make artificial intelligence.

The 29-year-old computer scientist creates software for a health care start-up that records and summarizes patient visits for doctors, freeing them from hours spent typing up clinical notes.

To do so, Mr. Giorgi has his own timesaving helper: an A.I. coding assistant. He taps a few keys and the software tool suggests the rest of the line of code. It can also recommend changes, fetch data, identify bugs and run basic tests. Even though the A.I. makes some mistakes, it saves him up to an hour many days.

“I can’t imagine working without it now,” Mr. Giorgi said.

That sentiment is increasingly common among software developers, who are at the forefront of adopting A.I. agents, assistant programs tailored to help employees do their jobs in fields including customer service and manufacturing. The rapid improvement of the technology has been accompanied by dire warnings that A.I. could soon automate away millions of jobs — and software developers have been singled out as prime targets.

But the outlook for software developers is more likely evolution than extinction, according to experienced software engineers, industry analysts and academics. For decades, better tools have automated some coding tasks, but the demand for software and the people who make it has only increased.

A.I., they say, will accelerate that trend and level up the art and craft of software design.

“The skills software developers need will change significantly, but A.I. will not eliminate the need for them,” said Arnal Dayaratna, an analyst at IDC, a technology research firm. “Not anytime soon anyway.”

The outlook for software engineers offers a window into the impact that generative A.I. — the kind behind chatbots like OpenAI’s ChatGPT — is likely to have on knowledge workers across the economy, from doctors and lawyers to marketing managers and financial analysts. Predictions about the technology’s consequences vary widely, from wiping out whole swaths of the work force to hyper-charging productivity as an elixir for economic growth…(More)”.

The New Control Society


Essay by Jon Askonas: “Let me tell you two stories about the Internet. The first story is so familiar it hardly warrants retelling. It goes like this. The Internet is breaking the old powers of the state, the media, the church, and every other institution. It is even breaking society itself. By subjecting their helpless users to ever more potent algorithms to boost engagement, powerful platforms distort reality and disrupt our politics. YouTube radicalizes young men into misogynists. TikTok turns moderate progressives into Hamas supporters. Facebook boosts election denialism; or it censors stories doubting the safety of mRNA vaccines. On the world stage, the fate of nations hinges on whether Twitter promotes color revolutions, WeChat censors Hong Kong protesters, and Facebook ads boost the Brexit campaign. The platforms are producing a fractured society: diversity of opinion is running amok, consensus is dead.

The second story is very different. In the 2023 essay “The age of average,” Alex Murrell recounts a project undertaken in the 1990s by Russian artists Vitaly Komar and Alexander Melamid. The artists commissioned a public affairs firm to poll over a thousand Americans on their ideal painting: the colors they liked, the subjects they gravitated toward, and so forth. Using the aggregate data, the artists created a painting, and they repeated this procedure in a number of other countries, exhibiting the final collection as an art exhibition called The People’s Choice. What they found, by and large, was not individual and national difference but the opposite: shocking uniformity — landscapes with a few animals and human figures with trees and a blue-hued color palette..(more)”.

Generative AI for data stewards: enhancing accuracy and efficiency in data governance


Paper by Ankush Reddy Sugureddy: “The quality of data becomes an essential component for the success of an organisation in a world that is largely influenced by data, where data analytics is becoming increasingly popular in the process of informing strategic decisions. The failure to improve the quality of the data can lead to undesirable outcomes such as poor decisions, ineffective strategies, dysfunctional operations, lost commercial prospects, and abrasion of the consumer. In the process of organisations shifting their focus towards transformative methods such as generative artificial intelligence, several use cases may emerge that have the potential to aid the improvement of data quality. Streamlining procedures such as data classification, metadata management, and policy enforcement can be accomplished by the incorporation of generative artificial intelligence into data governance frameworks. This, in turn, reduces the workload of human data stewards and minimises the possibility of human error. In order to ensure compliance with legal standards such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), generative artificial intelligence may analyse enormous datasets by utilising machine learning algorithms to discover patterns, inconsistencies, and compliance issues…(More)”.

In Online Democracy, Fun Is Imperative


Essay by Joe Mathews: “Governments around the world, especially those at the subnational and local levels, find themselves stuck in a vise. Planetary problems like climate change, disease, and technological disruption are not being addressed adequately by national governments. Everyday people, whose lives have been disrupted by those planetary problems, press the governments closer to them to step up and protect them. But those governments lack the technical capacity and popular trust to act effectively against bigger problems.

To build trust and capacity, many governments are moving governance into the digital world and asking their residents to do more of the work of government themselves. Some cities, provinces, and political institutions have tried to build digital platforms and robust digital environments where residents can improve service delivery and make government policy themselves.

However, most of these experiments have been failures. The trouble is that most of these platforms cannot keep the attention of the people who are supposed to use them. Too few of the platforms are designed to make online engagement compelling. So, figuring out how to make online engagement in government fun is actually a serious question for governments seeking to work more closely with their people.

What does fun look like in this sphere? I first witnessed a truly fun and engaging digital tool for citizen governance in Rome in 2018. While running a democracy conference with Mayor Virginia Raggi and her team, they were always on their phones, and not just to answer emails or texts. They were constantly on a digital environment called Rousseau.

Rousseau was named after Jean-Jacques Rousseau, the eighteenth-century philosopher and author of The Social Contract. In that 1762 book, Rousseau argued that city-states (like his hometown of Geneva) were more naturally suited to democracy than nation-states (especially big nations like France). He also wrote that the people themselves, not elected representatives, were the best rulers through what we today call direct democracy…(More)”.

Data Sovereignty and Open Sharing: Reconceiving Benefit-Sharing and Governance of Digital Sequence Information


Paper by Masanori Arita: “There are ethical, legal, and governance challenges surrounding data, particularly in the context of digital sequence information (DSI) on genetic resources. I focus on the shift in the international framework, as exemplified by the CBD-COP15 decision on benefit-sharing from DSI and discuss the growing significance of data sovereignty in the age of AI and synthetic biology. Using the example of the COVID-19 pandemic, the tension between open science principles and data control rights is explained. This opinion also highlights the importance of inclusive and equitable data sharing frameworks that respect both privacy and sovereign data rights, stressing the need for international cooperation and equitable access to data to reduce global inequalities in scientific and technological advancement…(More)”.

Organisations in the Age of Algorithms


Article by Phanish Puranam: “When Google’s CEO Sundar Pichai recently revealed that 25 percent of the company’s software is now machine-generated, it underscored how quickly artificial intelligence is reshaping the workplace. 

What does this mean for how we organise and manage? Will there still be room for humans in tomorrow’s organisations? And what might their work conditions look like? I tackle these questions in my new book Re-Humanize: How to Build Human-Centric Organizations in the Age of Algorithms”. 

The answers are not a given. They will depend on what we choose to do – what kinds of organisations we design. I make the case that successful organisation designs will have to pursue both goal-centricity (i.e. achieving objectives) and human-centricity (i.e. creating social environments that people find attractive). A myopic focus on only one or the other will not bode well for us.

The dual purpose of organisations

Why focus on organisations at a time when technology seems to be making such exciting strides? This was the very first question that INSEAD alumna Joanna Gordon asked me in a recent digital@INSEAD webinar. 

My answer: Homo sapienss most impressive accomplishments, from building the pyramids to developing Covid-19 vaccines, are not individual achievements. They were possible only because many people worked together effectively. “How to organise groups to attain goals” is our oldest general-purpose technology (GPT!). 

But there is more. To humans, organisations don’t just help accomplish goals. We are a species that has evolved to survive and thrive in groups, and organisations (i.e. groups with goals) are the natural habitat of Homo sapiens. They provide us with a sense of community and, as research has shown, help us strike a balance between our needs for social connection, individual autonomy and feeling capable and effective…(More)”.

Critical Data Studies: An A to Z Guide to Concepts and Methods


Book by Rob Kitchin: “Critical Data Studies has come of age as a vibrant, interdisciplinary field of study. Taking data as its primary analytical focus, the field theorises the nature of data; examines how data are produced, managed, governed and shared; investigates how they are used to make sense of the world and to perform practical action; and explores whose agenda data-driven systems serve.

This book is the first comprehensive A-Z guide to the concepts and methods of Critical Data Studies, providing succinct definitions and descriptions of over 400 key terms, along with suggested further reading. The book enables readers to quickly navigate and improve their comprehension of the field, while also acting as a guide for discovering ideas and methods that will be of value in their own studies…(More)”

Introduction to the Foundations and Regulation of Generative AI


Chapter by Philipp Hacker, Andreas Engel, Sarah Hammer and Brent Mittelstadt: “… introduces The Oxford Handbook of the Foundations and Regulation of Generative AI, outlining the key themes and questions surrounding the technical development, regulatory governance, and societal implications of generative AI. It highlights the historical context of generative AI, distinguishes it from traditional AI, and explores its diverse applications across multiple domains, including text, images, music, and scientific discovery. The discussion critically assesses whether generative AI represents a paradigm shift or a temporary hype. Furthermore, the chapter extensively surveys both emerging and established regulatory frameworks, including the EU AI Act, the GDPR, privacy and personality rights, and copyright, as well as global legal responses. We conclude that, for now, the “Old Guard” of legal frameworks regulates generative AI more tightly and effectively than the “Newcomers,” but that may change as the new laws fully kick in. The chapter concludes by mapping the structure of the Handbook…(More)”