Book by Adam Jabłoński and Marek Jabłoński: “Filling a gap in the current literature, this book addresses the social approach to the design and use of innovative business models in the digital economy. It focuses on three areas that are of increasing importance to businesses and industry today: social issues and sustainability; digitization; and new economic business models, specifically the sharing and circular economies. The authors aim to solve current scientific concerns around the conceptualization and operationalization of social business models, addressing management intentions and the impact of these models on society. Based on observation of social phenomena and the authors’ research and practical experience, the book highlights best practices for designing and assessing social business models….(More)”.
Kenya passes data protection law crucial for tech investments
George Obulutsa and Duncan Miriri at Reuters: “Kenyan President Uhuru Kenyatta on Friday approved a data protection law which complies with European Union legal standards as it looks to bolster investment in its information technology sector.
The East African nation has attracted foreign firms with innovations such as Safaricom’s M-Pesa mobile money services, but the lack of safeguards in handling personal data has held it back from its full potential, officials say.
“Kenya has joined the global community in terms of data protection standards,” Joe Mucheru, minister for information, technology and communication, told Reuters.
The new law sets out restrictions on how personally identifiable data obtained by firms and government entities can be handled, stored and shared, the government said.
Mucheru said it complies with the EU’s General Data Protection Regulation which came into effect in May 2018 and said an independent office will investigate data infringements….
A lack of data protection legislation has also hampered the government’s efforts to digitize identity records for citizens.
The registration, which the government said would boost its provision of services, suffered a setback this year when the exercise was challenged in court.
“The lack of a data privacy law has been an enormous lacuna in Kenya’s digital rights landscape,” said Nanjala Nyabola, author of a book on information technology and democracy in Kenya….(More)”.
Finland’s model in utilising forest data
Report by Matti Valonen et al: “The aim of this study is to depict the Finnish Forest Centre’s Metsään.fiwebsite’s background, objectives and implementation and to assess its needs for development and future prospects. The Metsään.fi-service included in the Metsään.fi-website is a free e-service for forest owners and corporate actors (companies, associations and service providers) in the forest sector, which aim is to support active decision-making among forest owners by offering forest resource data and maps on forest properties, by making contacts with the authorities easier through online services and to act as a platform for offering forest services, among other things.
In addition to the Metsään.fi-service, the website includes open forest data services that offer the users national forest resource data that is not linked with personal information.
Private forests are in a key position as raw material sources for traditional and new forest-based bioeconomy. In addition to wood material, the forests produce non-timber forest products (for example berries and mushrooms), opportunities for recreation and other ecosystem services.
Private forests cover roughly 60 percent of forest land, but about 80 percent of the domestic wood used by forest industry. In 2017 the value of the forest industry production was 21 billion euros, which is a fifth of the entire industry production value in Finland. The forest industry export in 2017 was worth about 12 billion euros, which covers a fifth of the entire export of goods. Therefore, the forest sector is important for Finland’s national economy…(More)”.
Geolocation Data for Pattern of Life Analysis in Lower-Income Countries
Report by Eduardo Laguna-Muggenburg, Shreyan Sen and Eric Lewandowski: “Urbanization processes in the developing world are often associated with the creation of informal settlements. These areas frequently have few or no public services exacerbating inequality even in the context of substantial economic growth.
In the past, the high costs of gathering data through traditional surveying methods made it challenging to study how these under-served areas evolve through time and in relation to the metropolitan area to which they belong. However, the advent of mobile phones and smartphones in particular presents an opportunity to generate new insights on these old questions.
In June 2019, Orbital Insight and the United Nations Development Programme (UNDP) Arab States Human Development Report team launched a collaborative pilot program assessing the feasibility of using geolocation data to understand patterns of life among the urban poor in Cairo, Egypt.
The objectives of this collaboration were to assess feasibility (and conditionally pursue preliminary analysis) of geolocation data to create near-real time population density maps, understand where residents of informal settlements tend to work during the day, and to classify universities by percentage of students living in informal settlements.
The report is organized as follows. In Section 2 we describe the data and its limitations. In Section 3 we briefly explain the methodological background. Section 4 summarizes the insights derived from the data for the Egyptian context. Section 5 concludes….(More)”.
Restrictions on Privacy and Exploitation in the Digital Economy: A Competition Law Perspective
Paper by Nicholas Economides and Ioannis Lianos: “The recent controversy on the intersection of competition law with the protection of privacy, following the emergence of big data and social media is a major challenge for competition authorities worldwide. Recent technological progress in data analytics may greatly facilitate the prediction of personality traits and attributes from even a few digital records of human behaviour.
There are different perspectives globally as to the level of personal data protection and the role competition law may play in this context, hence the discussion of integrating such concerns in competition law enforcement may be premature for some jurisdictions. However, a market failure approach may provide common intellectual foundations for the assessment of harms associated to the exploitation of personal data, even when the specific legal system does not formally recognize a fundamental right to privacy.
The paper presents a model of market failure based on a requirement provision in the acquisition of personal information from users of other products/services. We establish the economic harm from the market failure and the requirement using the traditional competition law toolbox and focusing more on situations in which the restriction on privacy may be analysed as a form of exploitation. Eliminating the requirement and the market failure by creating a functioning market for the sale of personal information is imperative. This emphasis on exploitation does not mean that restrictions on privacy may not result from exclusionary practices. However, we analyse this issue in a separate study.
Besides the traditional analysis of the requirement and market failure, we note that there are typically informational asymmetries between the data controller and the data subject. The latter may not be aware that his data was harvested, in the first place, or that the data will be processed by the data controller for a different purpose or shared and sold to third parties. The exploitation of personal data may also result from economic coercion, on the basis of resource-dependence or lock-in of the user, the latter having no other choice, in order to enjoy the consumption of a specific service provided by the data controller or its ecosystem, in particular in the presence of dominance, than to consent to the harvesting and use of his data. A behavioural approach would also emphasise the possible internalities (demand-side market failures) coming out of the bounded rationality, or the fact that people do not internalise all consequences of their actions and face limits in their cognitive capacities.
The paper also addresses the way competition law could engage with exploitative conduct leading to privacy harm, both for ex ante and ex post enforcement.
With regard to ex ante enforcement, the paper explores how privacy concerns may be integrated in merger control as part of the definition of product quality, the harm in question being merely exploitative (the possibility the data aggregation provides to the merged entity to exploit (personal) data in ways that harm directly consumers), rather than exclusionary (harming consumers by enabling the merged entity to marginalise a rival with better privacy policies), which is examined in a separate paper.
With regard to ex post enforcement, the paper explores different theories of harm that may give rise to competition law concerns and suggest specific tests for their assessment. In particular, we analyse old and new exploitative theories of harm relating to excessive data extraction, personalised pricing, unfair commercial practices and trading conditions, exploitative requirement contracts, behavioural manipulation.
We are in favour of collective action to restore the conditions of a well-functioning data market and the paper makes several policy recommendations….(More)”.
From Transactions Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending
Paper by Aditya Aladangady et al: “Access to timely information on consumer spending is important to economic policymakers. The Census Bureau’s monthly retail trade survey is a primary source for monitoring consumer spending nationally, but it is not well suited to study localized or short-lived economic shocks. Moreover, lags in the publication of the Census estimates and subsequent, sometimes large, revisions diminish its usefulness for real-time analysis. Expanding the Census survey to include higher frequencies and subnational detail would be costly and would add substantially to respondent burden. We take an alternative approach to fill these information gaps. Using anonymized transactions data from a large electronic payments technology company, we create daily estimates of retail spending at detailed geographies. Our daily estimates are available only a few days after the transactions occur, and the historical time series are available from 2010 to the present. When aggregated to the national leve l, the pattern of monthly growth rates is similar to the official Census statistics. We discuss two applications of these new data for economic analysis: First, we describe how our monthly spending estimates are useful for real-time monitoring of aggregate spending, especially during the government shutdown in 2019, when Census data were delayed and concerns about the economy spiked. Second, we show how the geographic detail allowed us quantify in real time the spending effects of Hurricanes Harvey and Irma in 2017….(More)”.
Toolkit to Help Community Leaders Drive Sustainable, Inclusive Growth
The Mastercard Center for Inclusive Growth: “… is unveiling a groundbreaking suite of tools that will provide local leaders with timely data-driven insights on the current state of and potential for inclusive growth in their communities. The announcement comes as private and public sector leaders gather in Washington for the inaugural Global Inclusive Growth Summit.
For the first time the new Inclusive Growth Toolkit brings together a clear, simple view of social and economic growth in underserved communities across the U.S., at the census-tract level. This was created in response to growing demand from community leaders for more evidence-based insights, to help them steer impact investment dollars to locally-led economic development initiatives, unlock the potential of neighborhoods, and improve quality of life for all.
The initial design of the toolkit is focused on driving sustainable growth for the 37+ million people living in the 8700+ QOZs throughout the United States. This comprehensive picture reveals that neighborhoods can look very different and may require different types of interventions to achieve successful and sustainable growth.
The Inclusive Growth Toolkit includes:
- The Inclusive Growth Score – an interactive online map where users can view measures of inclusion and growth and then download a PDF Scorecard for any of the QOZs at census tract level.
A deep-dive analytics consultancy service that provides community leaders with customized insights to inform policy decisions, prospectus development, and impact investor discussions….(More)”.
The Economics of Artificial Intelligence
Book edited by Ajay Agrawal, Joshua Gans and Avi Goldfarb: “Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI.
It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions…. (More)”
Digital dystopia: how algorithms punish the poor
Ed Pilkington at The Guardian: “All around the world, from small-town Illinois in the US to Rochdale in England, from Perth, Australia, to Dumka in northern India, a revolution is under way in how governments treat the poor.
You can’t see it happening, and may have heard nothing about it. It’s being planned by engineers and coders behind closed doors, in secure government locations far from public view.
Only mathematicians and computer scientists fully understand the sea change, powered as it is by artificial intelligence (AI), predictive algorithms, risk modeling and biometrics. But if you are one of the millions of vulnerable people at the receiving end of the radical reshaping of welfare benefits, you know it is real and that its consequences can be serious – even deadly.
The Guardian has spent the past three months investigating how billions are being poured into AI innovations that are explosively recasting how low-income people interact with the state. Together, our reporters in the US, Britain, India and Australia have explored what amounts to the birth of the digital welfare state.
Their dispatches reveal how unemployment benefits, child support, housing and food subsidies and much more are being scrambled online. Vast sums are being spent by governments across the industrialized and developing worlds on automating poverty and in the process, turning the needs of vulnerable citizens into numbers, replacing the judgment of human caseworkers with the cold, bloodless decision-making of machines.
At its most forbidding, Guardian reporters paint a picture of a 21st-century Dickensian dystopia that is taking shape with breakneck speed…(More)”.
The Economics of Social Data: An Introduction
Paper by Dirk Bergemann and Alessandro Bonatti: “Large internet platforms collect data from individual users in almost every interaction on the internet. Whenever an individual browses a news website, searches for a medical term or for a travel recommendation, or simply checks the weather forecast on an app, that individual generates data. A central feature of the data collected from the individuals is its social aspect. Namely, the data captured from an individual user is not only informative about this specific individual, but also about users in some metric similar to the individual. Thus, the individual data is really social data. The social nature of the data generates an informational externality that we investigate in this note….(More)”.