OECD Digital Economy Outlook 2024

Curated on Posted on by Stefaan Verhulst

OECD Report: “The most recent phase of digital transformation is marked by rapid technological changes, creating both opportunities and risks for the economy and society. The Volume 2 of the OECD Digital Economy Outlook 2024 explores emerging priorities, policies and governance practices across countries. It also examines trends in the foundations that enable digital transformation, drive digital innovation and foster trust in the digital age. The volume concludes with a statistical annex…

In 2023, digital government, connectivity and skills topped the list of digital policy priorities. Increasingly developed at a high level of government, national digital strategies play a critical role in co-ordinating these efforts. Nearly half of the 38 countries surveyed develop these strategies through dedicated digital ministries, up from just under a quarter in 2016. Among 1 200 policy initiatives tracked across the OECD, one-third aim to boost digital technology adoption, social prosperity, and innovation. AI and 5G are the most often-cited technologies…(More)”

The Emerging Age of AI Diplomacy

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Article by Sam Winter-Levy: “In a vast conference room, below chandeliers and flashing lights, dozens of dancers waved fluorescent bars in an intricately choreographed routine. Green Matrix code rained down in the background on a screen that displayed skyscrapers soaring from a desert landscape. The world was witnessing the emergence of “a sublime and transcendent entity,” a narrator declared: artificial intelligence. As if to highlight AI’s transformative potential, a digital avatar—Artificial Superintelligence One—approached a young boy and together they began to sing John Lennon’s “Imagine.” The audience applauded enthusiastically. With that, the final day dawned on what one government minister in attendance described as the “world’s largest AI thought leadership event.”

This surreal display took place not in Palo Alto or Menlo Park but in Riyadh, Saudi Arabia, at the third edition of the city’s Global AI Summit, in September of this year. In a cavernous exhibition center next to the Ritz Carlton, where Crown Prince Mohammed bin Salman imprisoned hundreds of wealthy Saudis on charges of corruption in 2017,robots poured tea and mixed drinks. Officials in ankle-length white robes hailed Saudi Arabia’s progress on AI. American and Chinese technology companies pitched their products and announced memorandums of understanding with the government. Attendantsdistributed stickers that declared, “Data is the new oil.”

For Saudi Arabia and its neighbor, the United Arab Emirates (UAE), AI plays an increasingly central role in their attempts to transform their oil wealth into new economic models before the world transitions away from fossil fuels. For American AI companies, hungry for capital and energy, the two Gulf states and their sovereign wealth funds are tantalizing partners. And some policymakers in Washington see a once-in-a-generation opportunity to promise access to American computing power in a bid to lure the Gulf states away from China and deepen an anti-Iranian coalition in the Middle East….The two Gulf states’ interest in AI is not new, but it has intensified in recent months. Saudi Arabia plans to create a $40 billion fund to invest in AI and has set up Silicon Valley–inspired startup accelerators to entice coders to Riyadh. In 2019, the UAE launched the world’s first university dedicated to AI, and since 2021, the number of AI workers in the country has quadrupled, according to government figures. The UAE has also released a series of open-source large language models that it claims rival those of Google and Meta, and earlier this year it launched an investment firm focused on AI and semiconductors that could surpass $100 billion in assets under management…(More)”.

Cross-border data flows in Africa: Continental ambitions and political realities

Curated on Posted on by Stefaan Verhulst

Paper by Melody Musoni, Poorva Karkare and Chloe Teevan: “Africa must prioritise data usage and cross-border data sharing to realise the goals of the African Continental Free Trade Area and to drive innovation and AI development. Accessible and shareable data is essential for the growth and success of the digital economy, enabling innovations and economic opportunities, especially in a rapidly evolving landscape.

African countries, through the African Union (AU), have a common vision of sharing data across borders to boost economic growth. However, the adopted continental digital policies are often inconsistently applied at the national level, where some member states implement restrictive measures like data localisation that limit the free flow of data.

The paper looks at national policies that often prioritise domestic interests and how those conflict with continental goals. This is due to differences in political ideologies, socio-economic conditions, security concerns and economic priorities. This misalignment between national agendas and the broader AU strategy is shaped by each country’s unique context, as seen in the examples of Senegal, Nigeria and Mozambique, which face distinct challenges in implementing the continental vision.

The paper concludes with actionable recommendations for the AU, member states and the partnership with the European Union. It suggests that the AU enhances support for data-sharing initiatives and urges member states to focus on policy alignment, address data deficiencies, build data infrastructure and find new ways to use data. It also highlights how the EU can strengthen its support for Africa’s datasharing goals…(More)”.

AI helped Uncle Sam catch $1 billion of fraud in one year. And it’s just getting started

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Article by Matt Egan: “The federal government’s bet on using artificial intelligence to fight financial crime appears to be paying off.

Machine learning AI helped the US Treasury Department to sift through massive amounts of data and recover $1 billion worth of check fraud in fiscal 2024 alone, according to new estimates shared first with CNN. That’s nearly triple what the Treasury recovered in the prior fiscal year.

“It’s really been transformative,” Renata Miskell, a top Treasury official, told CNN in a phone interview.

“Leveraging data has upped our game in fraud detection and prevention,” Miskell said.

The Treasury Department credited AI with helping officials prevent and recover more than $4 billion worth of fraud overall in fiscal 2024, a six-fold spike from the year before.

US officials quietly started using AI to detect financial crime in late 2022, taking a page out of what many banks and credit card companies already do to stop bad guys.

The goal is to protect taxpayer money against fraud, which spiked during the Covid-19 pandemic as the federal government scrambled to disburse emergency aid to consumers and businesses.

To be sure, Treasury is not using generative AI, the kind that has captivated users of OpenAI’s ChatGPT and Google’s Gemini by generating images, crafting song lyrics and answering complex questions (even though it still sometimes struggles with simple queries)…(More)”.

Machines of Loving Grace

Curated on Posted on by Stefaan Verhulst

Essay by Dario Amodei: “I think and talk a lot about the risks of powerful AI. The company I’m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I’m a pessimist or “doomer” who thinks AI will be mostly bad or dangerous. I don’t think that at all. In fact, one of my main reasons for focusing on risks is that they’re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.

In this essay I try to sketch out what that upside might look like—what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I’m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one…(More)”.

The Unaccountability Machine — why do big systems make bad decisions?

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FT Review of book by Dan Davies: “The starting point of Davies’ entertaining, insightful book is that the uncontrolled proliferation of accountability sinks is one of the central drivers of what historian Adam Tooze calls the “polycrisis” of the 21st century. Their influence reaches far beyond frustrated customers endlessly on hold to “computer says no” service departments. In finance, banking crises regularly recur — yet few individual bankers are found at fault. If politicians’ promises flop, they complain they have no power; the Deep State is somehow to blame.

The origin of the problem, Davies argues, is the managerial revolution that began after the second world war, abetted by the advent of cheap computing power and the diffusion of algorithmic decision-making into every sphere of life. These systems have ended up “acting like a car’s crumple-zone to shield any individual manager from a disastrous decision”, he writes. While attractive from the individual’s perspective, they scramble the feedback on which society as a whole depends.

Yet the story, Davies continues, is not so simple. Seen from another perspective, accountability sinks are entirely reasonable responses to the ever-increasing complexity of modern economies. Standardisation and explicit policies and procedures offer the only feasible route to meritocratic recruitment, consistent service and efficient work. Relying on the personal discretion of middle managers would simply result in a different kind of mess…(More)”.

China’s Hinterland Becomes A Critical Datascape

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Article by Gary Zhexi Zhang: “In 2014, the southwestern province of Guizhou, a historically poor and mountainous area, beat out rival regions to become China’s first “Big Data Comprehensive Pilot Zone,” as part of a national directive to develop the region — which is otherwise best known as an exporter of tobacco, spirits and coal — into the infrastructural backbone of the country’s data industry. Since then, vast investment has poured into the province. Thousands of miles of highway and high-speed rail tunnel through the mountains. Driving through the province can feel vertiginous: Of the hundred highest bridges in the world, almost half are in Guizhou, and almost all were built in the last 15 years.

In 2015, Xi Jinping visited Gui’an New Area to inaugurate the province’s transformation into China’s “Big Data Valley,” exemplifying the central government’s goal to establish “high quality social and economic development,” ubiquitously advertised through socialist-style slogans plastered on highways and city streets…(More)”.

Regulating the Direction of Innovation

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Paper by Joshua S. Gans: “This paper examines the regulation of technological innovation direction under uncertainty about potential harms. We develop a model with two competing technological paths and analyze various regulatory interventions. Our findings show that market forces tend to inefficiently concentrate research on leading paths. We demonstrate that ex post regulatory instruments, particularly liability regimes, outperform ex ante restrictions in most scenarios. The optimal regulatory approach depends critically on the magnitude of potential harm relative to technological benefits. Our analysis reveals subtle insurance motives in resource allocation across research paths, challenging common intuitions about diversification. These insights have important implications for regulating emerging technologies like artificial intelligence, suggesting the need for flexible, adaptive regulatory frameworks…(More)”.

Rejecting Public Utility Data Monopolies

Curated on Posted on by Stefaan Verhulst

Paper by Amy L. Stein: “The threat of monopoly power looms large today. Although not the telecommunications and tobacco monopolies of old, the Goliaths of Big Tech have become today’s target for potential antitrust violations. It is not only their control over the social media infrastructure and digital advertising technologies that gives people pause, but their monopolistic collection, use, and sale of customer data. But large technology companies are not the only private companies that have exclusive access to your data; that can crowd out competitors; and that can hold, use, or sell your data with little to no regulation. These other private companies are not data companies, platforms, or even brokers. They are public utilities.

Although termed “public utilities,” these entities are overwhelmingly private, shareholder-owned entities. Like private Big Tech, utilities gather incredible amounts of data from customers and use this data in various ways. And like private Big Tech, these utilities can exercise exclusionary and self-dealing anticompetitive behavior with respect to customer data. But there is one critical difference— unlike Big Tech, utilities enjoy an implied immunity from antitrust laws. This state action immunity has historically applied to utility provision of essential services like electricity and heat. As utilities find themselves in the position of unsuspecting data stewards, however, there is a real and unexplored question about whether their long- enjoyed antitrust immunity should extend to their data practices.

As the first exploration of this question, this Article tests the continuing application and rationale of the state action immunity doctrine to the evolving services that a utility provides as the grid becomes digitized. It demonstrates the importance of staunching the creep of state action immunity over utility data practices. And it recognizes the challenges of developing remedies for such data practices that do not disrupt the state-sanctioned monopoly powers of utilities over the provision of essential services. This Article analyzes both antitrust and regulatory remedies, including a new customer- focused “data duty,” as possible mechanisms to enhance consumer (ratepayer) welfare in this space. Exposing utility data practices to potential antitrust liability may be just the lever that is needed to motivate states, public utility commissions, and utilities to develop a more robust marketplace for energy data…(More)”.

Harnessing Technology for Inclusive Prosperity

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Book edited by Brahima Sangafowa Coulibaly and Zia Qureshi: “Transformative new technologies are reshaping economies and societies. But as they create new opportunities, they also pose new challenges, not least of which is rising inequality. Increased disparities and related anxieties are stoking societal discontent and political ferment. Harnessing technological transformation in ways that foster its benefits, contain risks, and build inclusive prosperity is a major public policy challenge of our time and one that motivates this book.

In what ways are the new technologies altering markets, business models, work, and, in turn, economic growth and income distribution? How are they affecting inequality within advanced and emerging economies and the prospects for economic convergence between them? What are the implications for public policy? What new thinking and adaptations are needed to realign institutions and policies, at national and global levels, with the new dynamics of the digital era?

This book addresses these questions. It seeks to promote ideas and actions to manage digital transformation and the latest advances in artificial intelligence with foresight and purpose to shape a more prosperous and inclusive future…(More)”