The path for AI in poor nations does not need to be paved with billions


Editorial in Nature: “Coinciding with US President Donald Trump’s tour of Gulf states last week, Saudi Arabia announced that it is embarking on a large-scale artificial intelligence (AI) initiative. The proposed venture will have state backing and considerable involvement from US technology firms. It is the latest move in a global expansion of AI ambitions beyond the existing heartlands of the United States, China and Europe. However, as Nature India, Nature Africa and Nature Middle East report in a series of articles on AI in low- and middle-income countries (LMICs) published on 21 May (see go.nature.com/45jy3qq), the path to home-grown AI doesn’t need to be paved with billions, or even hundreds of millions, of dollars, or depend exclusively on partners in Western nations or China…, as a News Feature that appears in the series makes plain (see go.nature.com/3yrd3u2), many initiatives in LMICs aren’t focusing on scaling up, but on ‘scaling right’. They are “building models that work for local users, in their languages, and within their social and economic realities”.

More such local initiatives are needed. Some of the most popular AI applications, such as OpenAI’s ChatGPT and Google Gemini, are trained mainly on data in European languages. That would mean that the model is less effective for users who speak Hindi, Arabic, Swahili, Xhosa and countless other languages. Countries are boosting home-grown apps by funding start-up companies, establishing AI education programmes, building AI research and regulatory capacity and through public engagement.

Those LMICs that have started investing in AI began by establishing an AI strategy, including policies for AI research. However, as things stand, most of the 55 member states of the African Union and of the 22 members of the League of Arab States have not produced an AI strategy. That must change…(More)”.

Assessing data governance models for smart cities: Benchmarking data governance models on the basis of European urban requirements


Paper by Yusuf Bozkurt, Alexander Rossmann, Zeeshan Pervez, and Naeem Ramzan: “Smart cities aim to improve residents’ quality of life by implementing effective services, infrastructure, and processes through information and communication technologies. However, without robust smart city data governance, much of the urban data potential remains underexploited, resulting in inefficiencies and missed opportunities for city administrations. This study addresses these challenges by establishing specific, actionable requirements for smart city data governance models, derived from expert interviews with representatives of 27 European cities. From these interviews, recurring themes emerged, such as the need for standardized data formats, clear data access guidelines, and stronger cross-departmental collaboration mechanisms. These requirements emphasize technology independence, flexibility to adapt across different urban contexts, and promoting a data-driven culture. By benchmarking existing data governance models against these newly established urban requirements, the study uncovers significant variations in their ability to address the complex, dynamic nature of smart city data systems. This study thus enhances the theoretical understanding of data governance in smart cities and provides municipal decision-makers with actionable insights for improving data governance strategies. In doing so, it directly supports the broader goals of sustainable urban development by helping improve the efficiency and effectiveness of smart city initiatives…(More)”.

The AI Policy Playbook


Playbook by AI Policymaker Network & Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH: “It moves away from talking about AI ethics in abstract terms but tells of building policies that work right-away in emerging economies and respond to immediate development priorities. The Playbook emphasises that a one-size-fits-all solution doesn’t work. Rather, it illustrates shared challenges—like limited research capacity, fragmented data ecosystems, and compounding AI risks—while spotlighting national innovations and success stories. From drafting AI strategies to engaging communities and safeguarding rights, it lays out a roadmap grounded in local realities….What can you expect to find in the AI Policy Playbook:

  1. Policymaker Interviews
    Real-world insights from policymakers to understand their challenges and best practices.
  2. Policy Process Analysis
    Key elements from existing policies to extract effective strategies for AI governance, as well as policy mapping.
  3. Case Studies
    Examples of successes and lessons learnt from various countries to provide practical guidance.
  4. Recommendations
    Concrete solutions and recommendations from actors in the field to improve the policy development process, including quick tips for implementation and handling challenges.

What distinguishes this initiative is its commitment to peer learning and co-creation. The Africa-Asia AI Policymaker Network comprises over 30 high-level government partners who anchor the Playbook in real-world policy contexts. This ensures that the frameworks are not only theoretically sound but politically and socially implementable…(More)”

Europe’s dream to wean off US tech gets reality check


Article by Pieter Haeck and Mathieu Pollet: “..As the U.S. continues to up the ante in questioning transatlantic ties, calls are growing in Europe to reduce the continent’s reliance on U.S. technology in critical areas such as cloud services, artificial intelligence and microchips, and to opt for European alternatives instead.

But the European Commission is preparing on Thursday to acknowledge publicly what many have said in private: Europe is nowhere near being able to wean itself off U.S. Big Tech.

In a new International Digital Strategy the EU will instead promote collaboration with the U.S., according to a draft seen by POLITICO, as well as with other tech players including China, Japan, India and South Korea. “Decoupling is unrealistic and cooperation will remain significant across the technological value chain,” the draft reads. 

It’s a reality check after a year that has seen calls for a technologically sovereign Europe gain significant traction. In December the Commission appointed Finland’s Henna Virkkunen as the first-ever commissioner in charge of tech sovereignty. After few months in office, European Parliament lawmakers embarked on an effort to draft a blueprint for tech sovereignty. 

Even more consequential has been the rapid rise of the so-called Eurostack movement, which advocates building out a European tech infrastructure and has brought together effective voices including competition economist Cristina Caffarra and Kai Zenner, an assistant to key European lawmaker Axel Voss.

There’s wide agreement on the problem: U.S. cloud giants capture over two-thirds of the European market, the U.S. outpaces the EU in nurturing companies for artificial intelligence, and Europe’s stake in the global microchips market has crumbled to around 10 percent. Thursday’s strategy will acknowledge the U.S.’s “superior ability to innovate” and “Europe’s failure to capitalise on the digital revolution.”

What’s missing are viable solutions to the complex problem of unwinding deep-rooted dependencies….(More)”

Hamburg Declaration on Responsible AI


Declaration by the United Nations Development Programme (UNDP), in partnership with the German Federal Ministry for Economic Cooperation and Development (BMZ): “We are at a crossroads. Despite the progress made in recent years, we need renewed commitment andvengagement to advance toward and achieve the Sustainable Development Goals (SDGs). Digital technologies, such as Artificial Intelligence (AI), can play a significant role in this regard. AI presents opportunities and risks in a world of rapid social, political, economic, ecological, and technological shifts. If developed and deployed responsibly, AI can drive sustainable development and benefit society, the economy, and the planet. Yet, without safeguards throughout the AI value chain, it may widen inequalities within and between countries and contribute to direct harm through inappropriate, illegal, or deliberate misuse. It can also contribute to human rights violations, fuel disinformation, homogenize creative and cultural expression, and harm the environment. These risks are likely to disproportionately affect low-income countries, vulnerable groups, and future generations. Geopolitical competition and market dependencies further amplify these risks…(More)”.

Children’s Voice Privacy: First Steps And Emerging Challenges


Paper by Ajinkya Kulkarni, et al: “Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children’s voices. Such an evaluation is essential, as children’s speech presents a distinct set of challenges when compared to that of adults. This study comprises three children’s datasets, six anonymization methods, and objective and subjective utility metrics for evaluation. Our results show that existing systems for adults are still able to protect children’s voice privacy, but suffer from much higher utility degradation. In addition, our subjective study displays the challenges of automatic evaluation methods for speech quality in children’s speech, highlighting the need for further research…(More)”. See also: Responsible Data for Children.

Silicon Valley Is at an Inflection Point


Article by Karen Hao: “…In the decade that I have observed Silicon Valley — first as an engineer, then as a journalist — I’ve watched the industry shift to a new paradigm. Tech companies have long reaped the benefits of a friendly U.S. government, but the Trump administration has made clear that it will now grant new firepower to the industry’s ambitions. The Stargate announcement was just one signal. Another was the Republican tax bill that the House passed last week, which would prohibit states from regulating A.I. for the next 10 years.

The leading A.I. giants are no longer merely multinational corporations; they are growing into modern-day empires. With the full support of the federal government, soon they will be able to reshape most spheres of society as they please, from the political to the economic to the production of science…(More)”.

Surveillance pricing: How your data determines what you pay


Article by Douglas Crawford: “Surveillance pricing, also known as personalized or algorithmic pricing, is a practice where companies use your personal data, such as your location, the device you’re using, your browsing history, and even your income, to determine what price to show you. It’s not just about supply and demand — it’s about you as a consumer and how much the system thinks you’re able (or willing) to pay.

Have you ever shopped online for a flight(new window), only to find that the price mysteriously increased the second time you checked? Or have you and a friend searched for the same hotel room on your phones, only to find your friend sees a lower price? This isn’t a glitch — it’s surveillance pricing at work.

In the United States, surveillance pricing is becoming increasingly prevalent across various industries, including airlines, hotels, and e-commerce platforms. It exists elsewhere, but in other parts of the world, such as the European Union, there is a growing recognition of the danger this pricing model presents to citizens’ privacy, resulting in stricter data protection laws aimed at curbing it. The US appears to be moving in the opposite direction…(More)”.

Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration


Position paper by Nicholas Vincent, Matthew Prewitt and Hanlin Li: “…argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as journalists, researchers, and creative professionals) need to be able to collectively bargain with AI product builders in order to receive reasonable terms and a sustainable return on the informational value they contribute. We argue that without increased market coordination or collective bargaining on the side of these primary information producers, AI will exacerbate a large-scale “information market failure” that will lead not only to undesirable concentration of capital, but also to a potential “ecological collapse” in the informational commons. On the other hand, collective bargaining in the information economy can create market frictions and aligned incentives necessary for a pro-social, sustainable AI future. We provide concrete actions that can be taken to support a coalitionbased approach to achieve this goal. For example, researchers and developers can establish technical mechanisms such as federated data management tools and explainable data value estimations, to inform and facilitate collective bargaining in the information economy. Additionally, regulatory and policy interventions may be introduced to support trusted data intermediary organizations representing guilds or syndicates of information producers…(More)”.

In a world first, Brazilians will soon be able to sell their digital data


Article by Gabriel Daros: “Last month, Brazil announced it is rolling out a data ownership pilot that will allow its citizens to manage, own, and profit from their digital footprint — the first such nationwide initiative in the world. 

The project is administered by Dataprev, a state-owned company that provides technological solutions for the government’s social programs. Dataprev is partnering with DrumWave, a California-based data valuation and monetization firm.

Today, “people get nothing from the data they share,” Brittany Kaiser, co-founder of the Own Your Data Foundation and board adviser for DrumWave, told Rest of World. “Brazil has decided its citizens should have ownership rights over their data.”

In monetizing users’ data, Brazil is ahead of the U.S., where a 2019 “data dividend” initiative by California Governor Gavin Newsom never took off. The city of Chicago successfully monetizes government data including transportation and education. If implemented, Brazil’s will be the first public-private partnership that allows citizens, rather than companies, to get a share of the global data market, currently valued at $4 billion and expected to grow to over $40 billion by 2034.

The pilot involves a small group of Brazilians who will use data wallets for payroll loans. When users apply for a new loan, the data in the contract will be collected in the data wallets, which companies will be able to bid on. Users will have the option to opt out. It works much like third-party cookies, but instead of simply accepting or declining, people can choose to make money…(More)”.