From Fragmentation to Coordination: The Case for an Institutional Mechanism for Cross-Border Data Flows

Curated on Posted on by Stefaan Verhulst

Report by the World Economic Forum: “Digital transformation of the global economy is bringing markets and people closer. Few conveniences of modern life – from international travel to online shopping to cross-border payments – would exist without the free flow of data.

Yet, impediments to free-flowing data are growing. The “Data Free Flow with Trust (DFFT)” concept is based on the idea that responsible data concerns, such as privacy and security, can be addressed without obstructing international data transfers. Policy-makers, trade negotiators and regulators are actively working on this, and while important progress has been made, an effective and trusted international cooperation mechanism would amplify their progress.

This white paper makes the case for establishing such a mechanism with a permanent secretariat, starting with the Group of Seven (G7) member-countries, and ensuring participation of high-level representatives of multiple stakeholder groups, including the private sector, academia and civil society.

This new institution would go beyond short-term fixes and catalyse long-term thinking to operationalize DFFT…(More)”.

DMA: rules for digital gatekeepers to ensure open markets start to apply

Curated on Posted on by Stefaan Verhulst

Press Release: “The EU Digital Markets Act (DMA) applies from today. Now that the DMA applies, potential gatekeepers that meet the quantitative thresholds established have until 3 July to notify their core platform services to the Commission. ..

The DMA aims to ensure contestable and fair markets in the digital sector. It defines gatekeepers as those large online platforms that provide an important gateway between business users and consumers, whose position can grant them the power to act as a private rule maker, and thus create a bottleneck in the digital economy. To address these issues, the DMA defines a series of specific obligations that gatekeepers will need to respect, including prohibiting them from engaging in certain behaviours in a list of do’s and don’ts. More information is available in the dedicated Q&A…(More)”.

Networks: An Economics Approach

Curated on Posted on by Stefaan Verhulst

Book by Sanjeev Goyal: “Networks are everywhere: the infrastructure that brings water into our homes, the social networks made up of our friends and families, the supply chains connecting cities, people, and goods. These interconnections contain economic trade-offs: for example, should an airline operate direct flights between cities or route all its flights through a hub? Viewing networks through an economics lens, this textbook considers the costs and benefits that govern their formation and functioning.

Networks are central to an understanding of the production, consumption, and information that lie at the heart of economic activity. Sanjeev Goyal provides advanced undergraduate and graduate students with an accessible and comprehensive introduction to the economics research on networks of the past twenty-five years. Each chapter introduces a theoretical model illustrated with the help of case studies and formal proofs. After introducing the theoretical concepts, Goyal examines economic networks, including infrastructure, security, market power, and financial networks. He then covers social networks, with chapters on coordinating activity, communication and learning, information networks, epidemics, and impersonal markets. Finally, Goyal locates social and economic networks in a broader context covering networked markets, economic development, trust, and group networks in their relation to markets and the state…(More)”.

Valuing the U.S. Data Economy Using Machine Learning and Online Job Postings

Curated on Posted on by Stefaan Verhulst

Paper by J Bayoán Santiago Calderón and Dylan Rassier: “With the recent proliferation of data collection and uses in the digital economy, the understanding and statistical treatment of data stocks and flows is of interest among compilers and users of national economic accounts. In this paper, we measure the value of own-account data stocks and flows for the U.S. business sector by summing the production costs of data-related activities implicit in occupations. Our method augments the traditional sum-of-costs methodology for measuring other own-account intellectual property products in national economic accounts by proxying occupation-level time-use factors using a machine learning model and the text of online job advertisements (Blackburn 2021). In our experimental estimates, we find that annual current-dollar investment in own-account data assets for the U.S. business sector grew from $84 billion in 2002 to $186 billion in 2021, with an average annual growth rate of 4.2 percent. Cumulative current-dollar investment for the period 2002–2021 was $2.6 trillion. In addition to the annual current-dollar investment, we present historical-cost net stocks, real growth rates, and effects on value-added by the industrial sector…(More)”.

Knowledge monopolies and the innovation divide: A governance perspective

Curated on Posted on by Stefaan Verhulst

Paper by Hani Safadi and Richard Thomas Watson: “The rise of digital platforms creates knowledge monopolies that threaten innovation. Their power derives from the imposition of data obligations and persistent coupling on platform participation and their usurpation of the rights to data created by other participants to facilitate information asymmetries. Knowledge monopolies can use machine learning to develop competitive insights unavailable to every other platform participant. This information asymmetry stifles innovation, stokes the growth of the monopoly, and reinforces its ascendency. National or regional governance structures, such as laws and regulatory authorities, constrain economic monopolies deemed not in the public interest. We argue the need for legislation and an associated regulatory mechanism to curtail coercive data obligations, control, eliminate data rights exploitation, and prevent mergers and acquisitions that could create or extend knowledge monopolies…(More)”.

The Case for Including Data Stewardship in ESG

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst: “Amid all the attention to environmental, social, and governance factors in investing, better known as ESG, there has been relatively little emphasis on governance, and even less on data governance. This is a significant oversight that needs to be addressed, as data governance has a crucial role to play in achieving environmental and social goals. 

Data stewardship in particular should be considered an important ESG practice. Making data accessible for reuse in the public interest can promote social and environmental goals while boosting a company’s efficiency and profitability. And investing in companies with data-stewardship capabilities makes good sense. But first, we need to move beyond current debates on data and ESG.

Several initiatives have begun to focus on data as it relates to ESG. For example, a recent McKinsey report on ESG governance within the banking sector argues that banks “will need to adjust their data architecture, define a data collection strategy, and reorganize their data governance model to successfully manage and report ESG data.” Deloitte recognizes the need for “a robust ESG data strategy.” PepsiCo likewise highlights its ESG Data Governance Program, and Maersk emphasizes data ethics as a key component in its ESG priorities.

These efforts are meaningful, but they are largely geared toward using data to measure compliance with environmental and social commitments. They don’t do much to help us understand how companies are leveraging data as an asset to achieve environmental and social goals. In particular, as I‘ve written elsewhere, data stewardship by which privately held data is reused for public interest purposes is an important new component of corporate social responsibility, as well as a key tool in data governance. Too many data-governance efforts are focused simply on using data to measure compliance or impact. We need to move beyond that mindset. Instead, we should adopt a data stewardship approach, where data is made accessible for the public good. There are promising signs of change in this direction…(More)”.

ESG data governance: A growing imperative for banks

Curated on Posted on by Stefaan Verhulst

Article and Report by Daniel Heller, Andreas Reiter, Sebastian Schöbl, and Henning Soller: “The banking industry is facing mounting pressure to meet fast-changing demands in environmental, social, and governance (ESG) issues. New and evolving regulations call for greater transparency and disclosure of ESG-related data (see sidebar, “ESG regulatory and disclosure requirements”). Stakeholders and investors are increasing their scrutiny of the effects investment decisions have on the climate and society. Consumers are holding banks to higher ESG standards as well—in 2019, about 14 percent of total client-driven revenues were controlled by consumers whose banking preferences were influenced by concern about purpose and sustainability.

To meet these expectations, banks must adapt their IT systems to systematically collect, aggregate, and report on a broad range of ESG data. However, many financial institutions still do not have a comprehensive approach to integrating ESG data into their existing risk reporting.

Moving toward this goal will require significant changes to the IT infrastructure, from applications to data integration, architecture, and governance. New applications include not only the management and capture of ESG data but also financed emissions models, climate risk models, ESG scorecards, climate stress tests, and climate-adjusted ratings. ESG data must be woven into existing processes, such as credit approvals and decision making. And banks will need to adjust their data architecture, define a data collection strategy, and reorganize their data governance model to successfully manage and report ESG data.

Investing in the right priorities from the beginning will enable banking IT leaders to quickly build these new capabilities and solutions without accumulating technical debt…(More)”

Data Brokers and the Sale of Americans’ Mental Health Data

Curated on Posted on by Stefaan Verhulst

Report by Joanne Kim: “This report includes findings from a two-month-long study of data brokers and data on U.S. individuals’ mental health conditions. The report aims to make more transparent the data broker industry and its processes for selling and exchanging mental health data about depressed and anxious individuals. The research is critical as more depressed and anxious individuals utilize personal devices and software-based health-tracking applications (many of which are not protected by the Health Insurance Portability and Accountability Act), often unknowingly putting their sensitive mental health data at risk. This report finds that the industry appears to lack a set of best practices for handling individuals’ mental health data, particularly in the areas of privacy and buyer vetting. It finds that there are data brokers which advertise and are willing and able to sell data concerning Americans’ highly sensitive mental health information. It concludes by arguing that the largely unregulated and black-box nature of the data broker industry, its buying and selling of sensitive mental health data, and the lack of clear consumer privacy protections in the U.S. necessitate a comprehensive federal privacy law or, at the very least, an expansion of HIPAA’s privacy protections alongside bans on the sale of mental health data on the open market…(More)”.

The Power of Citizen Science

Curated on Posted on by Stefaan Verhulst

Lauren Kirchner at ConsumerReport: “You’ve heard of Erin Brockovich, the law clerk without a science degree who exposed the existence of a dangerous contaminant polluting a town’s groundwater, a toxic hazard that otherwise might have stayed invisible.

She’s not the first person to practice “citizen science” to powerful effect, nor will she be the last.

Maybe you’ve wondered whether that plastic container you’re about to zap in the microwave is really safe to use or whether your favorite chipped coffee mug is exposing you to toxic paint. Some particularly enterprising people who’ve had similar concerns have also wondered—but then took the extra step of testing the chemical makeup of what they were concerned about and then publicized the results.

These citizen testers aren’t professional chemists or government regulators, but all of them were able to raise red flags and spark important conversations about the health hazards that can be hiding in our homes and lives…(More)”.

8 Strategies for Chief Data Officers to Create — and Demonstrate — Value

Curated on Posted on by Stefaan Verhulst

Article by Thomas H. Davenport, Richard Y. Wang, and Priyanka Tiwari: “The chief data officer (CDO) role was only established in 2002, but it has grown enormously since then. In one recent survey of large companies, 83% reported having a CDO. This isn’t surprising: Data and approaches to understanding it (analytics and AI) are incredibly important in contemporary organizations. What is eyebrow-raising, however, is that the CDO job is terribly ill-defined. Sixty-two percent of CDOs surveyed in the research we describe below reported that the CDO role is poorly understood, and incumbents of the job have often met with diffuse expectations and short tenures. There is a clear need for CDOs to focus on adding visible value to their organizations.

Part of the problem is that traditional data management approaches are unlikely to provide visible value in themselves. Many nontechnical executives don’t really understand the CDO’s work and struggle to recognize when it’s being done well. CDOs are often asked to focus on preventing data problems (defense-oriented initiatives) and such data management projects as improving data architectures, data governance, and data quality. But data will never be perfect, meaning executives will always be somewhat frustrated with their organization’s data situation. While improvements in data management may be difficult to recognize or measure, major problems such as hacks, breaches, lost or inaccessible data, or poor quality are much easier to recognize than improvements.

So how can CDOs demonstrate that they’re creating value?…(More)”