AI By the People, For the People


Article by Billy Perrigo/Karnataka: “…To create an effective English-speaking AI, it is enough to simply collect data from where it has already accumulated. But for languages like Kannada, you need to go out and find more.

This has created huge demand for datasets—collections of text or voice data—in languages spoken by some of the poorest people in the world. Part of that demand comes from tech companies seeking to build out their AI tools. Another big chunk comes from academia and governments, especially in India, where English and Hindi have long held outsize precedence in a nation of some 1.4 billion people with 22 official languages and at least 780 more indigenous ones. This rising demand means that hundreds of millions of Indians are suddenly in control of a scarce and newly-valuable asset: their mother tongue.

Data work—creating or refining the raw material at the heart of AI— is not new in India. The economy that did so much to turn call centers and garment factories into engines of productivity at the end of the 20th century has quietly been doing the same with data work in the 21st. And, like its predecessors, the industry is once again dominated by labor arbitrage companies, which pay wages close to the legal minimum even as they sell data to foreign clients for a hefty mark-up. The AI data sector, worth over $2 billion globally in 2022, is projected to rise in value to $17 billion by 2030. Little of that money has flowed down to data workers in India, Kenya, and the Philippines.

These conditions may cause harms far beyond the lives of individual workers. “We’re talking about systems that are impacting our whole society, and workers who make those systems more reliable and less biased,” says Jonas Valente, an expert in digital work platforms at Oxford University’s Internet Institute. “If you have workers with basic rights who are more empowered, I believe that the outcome—the technological system—will have a better quality as well.”

In the neighboring villages of Alahalli and Chilukavadi, one Indian startup is testing a new model. Chandrika works for Karya, a nonprofit launched in 2021 in Bengaluru (formerly Bangalore) that bills itself as “the world’s first ethical data company.” Like its competitors, it sells data to big tech companies and other clients at the market rate. But instead of keeping much of that cash as profit, it covers its costs and funnels the rest toward the rural poor in India. (Karya partners with local NGOs to ensure access to its jobs go first to the poorest of the poor, as well as historically marginalized communities.) In addition to its $5 hourly minimum, Karya gives workers de-facto ownership of the data they create on the job, so whenever it is resold, the workers receive the proceeds on top of their past wages. It’s a model that doesn’t exist anywhere else in the industry…(More)”.

Public Policy and Technological Transformations in Africa


Book edited by Gedion Onyango: “This book examines the links between public policy and Fourth Industrial Revolution (4IR) technological developments in Africa. It broadly assesses three key areas – policy entrepreneurship, policy tools and citizen participation – in order to better understand the interfaces between public policy and technological transformations in African countries. The book presents incisive case studies on topics including AI policies, mobile money, e-budgeting, digital economy, digital agriculture and digital ethical dilemmas in order to illuminate technological proliferation in African policy systems. Its analysis considers the broader contexts of African state politics and governance. It will appeal to students, instructors, researchers and practitioners interested in governance and digital transformations in developing countries…(More)”.

Data Collaboratives: Enabling a Healthy Data Economy Through Partnerships


Paper by Stefaan Verhulst (as Part of the Digital Revolution and New Social Contract Program): “…Overcoming data silos is key to addressing these data asymmetries and promoting a healthy data economy. This is equally true of silos that exist within sectors as it is of those among sectors (e.g., between the public and private sectors). Today, there is a critical mismatch between data supply and demand. The data that could be most useful rarely gets applied to the social, economic, cultural, and political problems it could help solve. Data silos, driven in large part by deeply entrenched asymmetries and a growing sense of “ownership,” are stunting the public good potential of data.

This paper presents a framework for responsible data sharing and reuse that could increase sharing between the public and private sectors to address some of the most entrenched asymmetries. Drawing on theoretical and empirical material, we begin by outlining how a period of rapid datafication—the Era of the Zettabyte—has led to data asymmetries that are increasingly deleterious to the public good. Sections II and III are normative. Having outlined the nature and scope of the problem, we present a number of steps and recommendations that could help overcome or mitigate data asymmetries. In particular, we focus on one institutional structure that has proven particularly promising: data collaboratives, an emerging model for data sharing between sectors. We show how data collaboratives could ease the flow of data between the public and private sectors, helping break down silos and ease asymmetries. Section II offers a conceptual overview of data collaboratives, while Section III provides an approach to operationalizing data collaboratives. It presents a number of specific mechanisms to build a trusted sharing ecology….(More)”.

Revisiting the Behavioral Revolution in Economics 


Article by Antara Haldar: “But the impact of the behavioral revolution outside of microeconomics remains modest. Many scholars are still skeptical about incorporating psychological insights into economics, a field that often models itself after the natural sciences, particularly physics. This skepticism has been further compounded by the widely publicized crisis of replication in psychology.

Macroeconomists, who study the aggregate functioning of economies and explore the impact of factors such as output, inflation, exchange rates, and monetary and fiscal policy, have, in particular, largely ignored the behavioral trend. Their indifference seems to reflect the belief that individual idiosyncrasies balance out, and that the quirky departures from rationality identified by behavioral economists must offset each other. A direct implication of this approach is that quantitative analyses predicated on value-maximizing behavior, such as the dynamic stochastic general equilibrium models that dominate policymaking, need not be improved.

The validity of these assumptions, however, remains uncertain. During banking crises such as the Great Recession of 2008 or the ongoing crisis triggered by the recent collapse of Silicon Valley Bank, the reactions of economic actors – particularly financial institutions and investors – appear to be driven by herd mentality and what John Maynard Keynes referred to as “animal spirits.”…

The roots of economics’ resistance to the behavioral sciences run deep. Over the past few decades, the field has acknowledged exceptions to the prevailing neoclassical paradigm, such as Elinor Ostrom’s solutions to the tragedy of the commons and Akerlof, Michael Spence, and Joseph E. Stiglitz’s work on asymmetric information (all four won the Nobel Prize). At the same time, economists have refused to update the discipline’s core assumptions.

This state of affairs can be likened to an imperial government that claims to uphold the rule of law in its colonies. By allowing for a limited release of pressure at the periphery of the paradigm, economists have managed to prevent significant changes that might undermine the entire system. Meanwhile, the core principles of the prevailing economic model remain largely unchanged.

For economics to reflect human behavior, much less influence it, the discipline must actively engage with human psychology. But as the list of acknowledged exceptions to the neoclassical framework grows, each subsequent breakthrough becomes a potentially existential challenge to the field’s established paradigm, undermining the seductive parsimony that has been the source of its power.

By limiting their interventions to nudges, behavioral economists hoped to align themselves with the discipline. But in doing so, they delivered a ratings-conscious “made for TV” version of a revolution. As Gil Scott-Heron famously reminded us, the real thing will not be televised….(More)”.

Challenge-Based Learning, Research, and Innovation


Book by Arturo Molina and Rajagopal: “Challenge-based research focuses on addressing societal and environmental problems. One way of doing so is by transforming existing businesses to profitable ventures through co-creation and co-evolution. Drawing on the resource-based view, this book discusses how social challenges can be linked with the industrial value-chain through collaborative research, knowledge sharing, and transfer of technology to deliver value. 

The work is divided into three sections: Part 1 discusses social challenges, triple bottom line, and entrepreneurship as drivers for research, learning, and innovation while Part 2 links challenge-based research to social and industrial development in emerging markets. The final section considers research-based innovation and the role of technology, with the final chapter bridging concepts and practices to shape the future of society and industry. The authors present the RISE paradigm, which integrates people (society), planet (sustainability), and profit (industry and business) as critical constructs for socio-economic and regional development. 

Arguing that the converging of society and industry is essential for the business ecosystem to stay competitive in the marketplace, this book analyzes possible approaches to linking challenge-based research with social and industrial innovations in the context of sectoral challenges like food production, housing, energy, biotechnology, and sustainability. It will serve as a valuable resource to researchers interested in topics such as social challenges, innovation, technology, sustainability, and society-industry linkage…(More)”.

Africa fell in love with crypto. Now, it’s complicated


Article by Martin K.N Siele: “Chiamaka, a former product manager at a Nigerian cryptocurrency startup, has sworn off digital currencies. The 22-year-old has weathered a layoff and lost savings worth 4,603,500 naira ($9,900) after the collapse of FTX in November 2022. She now works for a corporate finance company in Lagos, earning a salary that is 45% lower than her previous job.

“I used to be bullish on crypto because I believed it could liberate Africans financially,” Chiamaka, who asked to be identified by a pseudonym as she was concerned about breaching her contract with her current employer, told Rest of World. “Instead, it has managed to do the opposite so far … at least to me and a few of my friends.”

Chiamaka is among the tens of millions of Africans who bought into the cryptocurrency frenzy over the last few years. According to one estimate in mid-2022, around 53 million Africans owned crypto — 16.5% of the total global crypto users. Nigeria led with over 22 million users, ranking fourth globally. Blockchain startups and businesses on the continent raised $474 million in 2022, a 429% increase from the previous year, according to the African Blockchain Report. Young African creatives also became major proponents of non-fungible tokens (NFTs), taking inspiration from pop culture and the continent’s history. Several decentralized autonomous organizations (DAOs), touted as the next big thing, emerged across Africa…(More)”.

The Future of Compute


Independent Review by a UK Expert Panel: “…Compute is a material part of modern life. It is among the critical technologies lying behind innovation, economic growth and scientific discoveries. Compute improves our everyday lives. It underpins all the tools, services and information we hold on our handheld devices – from search engines and social media, to streaming services and accurate weather forecasts. This technology may be invisible to the public, but life today would be very different without it.

Sectors across the UK economy, both new and old, are increasingly reliant upon compute. By leveraging the capability that compute provides, businesses of all sizes can extract value from the enormous quantity of data created every day; reduce the cost and time required for research and development (R&D); improve product design; accelerate decision making processes; and increase overall efficiency. Compute also enables advancements in transformative technologies, such as AI, which themselves lead to the creation of value and innovation across the economy. This all translates into higher productivity and profitability for businesses and robust economic growth for the UK as a whole.

Compute powers modelling, simulations, data analysis and scenario planning, and thereby enables researchers to develop new drugs; find new energy sources; discover new materials; mitigate the effects of climate change; and model the spread of pandemics. Compute is required to tackle many of today’s global challenges and brings invaluable benefits to our society.

Compute’s effects on society and the economy have already been and, crucially, will continue to be transformative. The scale of compute capabilities keeps accelerating at pace. The performance of the world’s fastest compute has grown by a factor of 626 since 2010. The compute requirements of the largest machine learning models has grown 10 billion times over the last 10 years. We expect compute demand to significantly grow as compute capability continues to increase. Technology today operates very differently to 10 years ago and, in a decade’s time, it will have changed once again.

Yet, despite compute’s value to the economy and society, the UK lacks a long-term vision for compute…(More)”.

A model for a participative approach to digital competition regulation


Policy Brief by Christophe Carugati: “Digital competition regulations often put in place participative approaches to ensure competition in digital markets. The participative approach aims to involve regulated firms, stakeholders and regulators in the design of compliance measures. The approach is particularly relevant in complex and fast-evolving digital markets, where whole industries often depend on the behaviours of the regulated firms. The participative approach enables stakeholders and regulated firms to design compliance measures that are optimal for all because they ensure legal certainty for regulated firms, save time for regulators and take into account the views of stakeholders.

However, the participative approach is subject to regulatory capture. The regulated firms and stakeholders might try to promote their interests to the regulator. This could result in endless discussions at best, and the adoption of inappropriate solutions following intense lobbying at worst.

A governance model is necessary to ensure that the participative approach works without risks of regulatory capture. The model should define clearly each participant’s role, duties and rights. There should be: 1) equal and transparent access of all stakeholders to the dialogue; 2) the presentation of tangible and evidence-based solutions from stakeholders and regulated firms; 3) public decisions from the regulator that contain assessments of the proposed solutions, with guidance to clarify rules; and 4) compliance measures proposed by the regulated firm in line with the guidance. The model should provide an assessment framework for the proposed solutions to identify the most effective. The assessment should rely on the principle of proportionality to assess whether the proposed compliance measure is proportionate, to ensure the effectiveness of the regulation. Finally, the model should safeguard against regulatory capture thanks to transparency rules and external monitoring…(More)”

Predicting Socio-Economic Well-being Using Mobile Apps Data: A Case Study of France


Paper by Rahul Goel, Angelo Furno, and Rajesh Sharma: “Socio-economic indicators provide context for assessing a country’s overall condition. These indicators contain information about education, gender, poverty, employment, and other factors. Therefore, reliable and accurate information is critical for social research and government policing. Most data sources available today, such as censuses, have sparse population coverage or are updated infrequently. Nonetheless, alternative data sources, such as call data records (CDR) and mobile app usage, can serve as cost-effective and up-to-date sources for identifying socio-economic indicators.
This work investigates mobile app data to predict socio-economic features. We present a large-scale study using data that captures the traffic of thousands of mobile applications by approximately 30 million users distributed over 550,000 km square and served by over 25,000 base stations. The dataset covers the whole France territory and spans more than 2.5 months, starting from 16th March 2019 to 6th June 2019. Using the app usage patterns, our best model can estimate socio-economic indicators (attaining an R-squared score upto 0.66). Furthermore, using models’ explainability, we discover that mobile app usage patterns have the potential to reveal socio-economic disparities in IRIS. Insights of this study provide several avenues for future interventions, including users’ temporal network analysis and exploration of alternative data sources…(More)”.

Data Free Flow with Trust: Overcoming Barriers to Cross-Border Data Flows


Briefing Paper by the WEF: “The movement of data across country borders is essential to the global economy. When data flows across borders, it is possible to deliver more to more people and produce more benefits for people and planet. This briefing paper highlights the importance of such data flows and urges global leaders in the public and private sectors to take collective action to work towards a shared understanding of them with a view to implementing “Data Free Flow with Trust” (DFFT) – an umbrella concept for facilitating trust-based data exchanges. This paper reviews the current challenges facing DFFT, take stock of progress made so far, offer direction for policy mechanisms and concrete tools for businesses and, more importantly, promote global discussions about how to realize DFFT from the perspectives of policy and business…(More)”.