A crisis of legitimacy


Blair Sheppard and Ceri-Ann Droog at Strategy and Business: “For the last 70 years the world has done remarkably well. According to the World Bank, the number of people living in extreme poverty today is less than it was in 1820, even though the world population is seven times as large. This is a truly remarkable achievement, and it goes hand in hand with equally remarkable overall advances in wealth, scientific progress, human longevity, and quality of life.

But the organizations that created these triumphs — the most prominent businesses, governments, and multilateral institutions of the post–World War II era — have failed to keep their implicit promises. As a result, today’s leading organizations face a global crisis of legitimacy. For the first time in decades, their influence, and even their right to exist, are being questioned.

Businesses are also being held accountable in new ways for the welfare, prosperity, and health of the communities around them and of the general public. Our own global firm, PwC, is among these businesses. The accusations facing any individual enterprise may or may not be justified, but the broader attitudes underlying them must be taken seriously.

The causes of this crisis of legitimacy have to do with five basic challenges affecting every part of the world:

  • Asymmetry: Wealth disparity and the erosion of the middle class
  • Disruption: Abrupt technological changes and their destructive effects
  • Age: Demographic pressures as the average life span of human beings increases and the birth rate falls
  • Populism: Growing populism and rejection of the status quo, with associated nationalism and global fracturing
  • Trust: Declining confidence in the prevailing institutions that make our systems work.

(We use the acronym ADAPT to list these challenges because it evokes the inherent change in our time and the need for institutions to respond with new attitudes and behaviors.)

Source: strategy-business.com/ADAPT

A few other challenges, such as climate change and human rights issues, may occur to you as equally important. They are not included in this list because they are not at the forefront of this particular crisis of legitimacy in the same way. But they are affected by it; if leading businesses and global institutions lose their perceived value, it will be harder to address every other issue affecting the world today.

Ignoring the crisis of legitimacy is not an option — not even for business leaders who feel their primary responsibility is to their shareholders. If we postpone solutions too long, we could go past the point of no return: The cost of solving these problems will be too high. Brexit could be a test case. The costs and difficulties of withdrawal could be echoed in other political breakdowns around the world. And if you don’t believe that widespread economic and political disruption is possible right now, then consider the other revolutions and abrupt, dramatic changes in sovereignty that have occurred in the last 250 years, often with technological shifts and widespread dissatisfaction as key factors….(More)”.

The 100 Questions Initiative: Sourcing 100 questions on key societal challenges that can be answered by data insights


100Q Screenshot

Press Release: “The Governance Lab at the NYU Tandon School of Engineering announced the launch of the 100 Questions Initiative — an effort to identify the most important societal questions whose answers can be found in data and data science if the power of data collaboratives is harnessed.

The initiative, launched with initial support from Schmidt Futures, seeks to address challenges on numerous topics, including migration, climate change, poverty, and the future of work.

For each of these areas and more, the initiative will seek to identify questions that could help unlock the potential of data and data science with the broader goal of fostering positive social, environmental, and economic transformation. These questions will be sourced by leveraging “bilinguals” — practitioners across disciplines from all over the world who possess both domain knowledge and data science expertise.

The 100 Questions Initiative starts by identifying 10 key questions related to migration. These include questions related to the geographies of migration, migrant well-being, enforcement and security, and the vulnerabilities of displaced people. This inaugural effort involves partnerships with the International Organization for Migration (IOM) and the European Commission, both of which will provide subject-matter expertise and facilitation support within the framework of the Big Data for Migration Alliance (BD4M).

“While there have been tremendous efforts to gather and analyze data relevant to many of the world’s most pressing challenges, as a society, we have not taken the time to ensure we’re asking the right questions to unlock the true potential of data to help address these challenges,” said Stefaan Verhulst, co-founder and chief research and development officer of The GovLab. “Unlike other efforts focused on data supply or data science expertise, this project seeks to radically improve the set of questions that, if answered, could transform the way we solve 21st century problems.”

In addition to identifying key questions, the 100 Questions Initiative will also focus on creating new data collaboratives. Data collaboratives are an emerging form of public-private partnership that help unlock the public interest value of previously siloed data. The GovLab has conducted significant research in the value of data collaboration, identifying that inter-sectoral collaboration can both increase access to information (e.g., the vast stores of data held by private companies) as well as unleash the potential of that information to serve the public good….(More)”.

Africa must reap the benefits of its own data


Tshilidzi Marwala at Business Insider: “Twenty-two years ago when I was a doctoral student in artificial intelligence (AI) at the University of Cambridge, I had to create all the AI algorithms I needed to understand the complex phenomena related to this field.

For starters, AI is a computer software that performs intelligent tasks that normally require human beings, while an algorithm is a set of rules that instruct a computer to execute specific tasks. In that era, the ability to create AI algorithms was more important than the ability to acquire and use data.

Google has created an open-source library called TensorFlow, which contains all the developed AI algorithms. This way Google wants people to develop applications (apps) using their software, with the payoff being that Google will collect data on any individual using the apps developed with TensorFlow.

Today, an AI algorithm is not a competitive advantage but data is. The World Economic Forum calls data the new “oxygen”, while Chinese AI specialist Kai-Fu Lee calls it the new “oil”.

Africa’s population is increasing faster than in any region in the world. The continent has a population of 1.3-billion people and a total nominal GDP of $2.3-trillion. This increase in the population is in effect an increase in data, and if data is the new oil, it is akin to an increase in oil reserve.

Even oil-rich countries such as Saudi Arabia do not experience an increase in their oil reserve. How do we as Africans take advantage of this huge amount of data?

There are two categories of data in Africa: heritage and personal. Heritage data resides in society, whereas personal data resides in individuals. Heritage data includes data gathered from our languages, emotions and accents. Personal data includes health, facial and fingerprint data.

Facebook, Amazon, Apple, Netflix and Google are data companies. They trade data to advertisers, banks and political parties, among others. For example, the controversial company Cambridge Analytica harvested Facebook data to influence the presidential election that potentially contributed to Donald Trump’s victory in the US elections.

The company Google collects language data to build an application called Google Translate that translates from one language to another. This app claims to cover African languages such as Zulu, Yoruba and Swahili. Google Translate is less effective in handling African languages than it is in handling European and Asian languages.

Now, how do we capitalise on our language heritage to create economic value? We need to build our own language database and create our own versions of Google Translate.

An important area is the creation of an African emotion database. Different cultures exhibit emotions differently. These are very important in areas such as safety of cars and aeroplanes. If we can build a system that can read pilots’ emotions, this would enable us to establish if a pilot is in a good state of mind to operate an aircraft, which would increase safety.

To capitalise on the African emotion database, we should create a data bank that captures emotions of African people in various parts of the continent, and then use this database to create AI apps to read people’s emotions. Mercedes-Benz has already implemented the “Attention Assist”, which alerts drivers to fatigue.

Another important area is the creation of an African health database. AI algorithms are able to diagnose diseases better than human doctors. However, these algorithms depend on the availability of data. To capitalise on this, we need to collect such data and use it to build algorithms that will be able to augment medical care….(More)”.

Principles and Policies for “Data Free Flow With Trust”


Paper by Nigel Cory, Robert D. Atkinson, and Daniel Castro: “Just as there was a set of institutions, agreements, and principles that emerged out of Bretton Woods in the aftermath of World War II to manage global economic issues, the countries that value the role of an open, competitive, and rules-based global digital economy need to come together to enact new global rules and norms to manage a key driver of today’s global economy: data. Japanese Prime Minister Abe’s new initiative for “data free flow with trust,” combined with Japan’s hosting of the G20 and leading role in e-commerce negotiations at the World Trade Organization (WTO), provides a valuable opportunity for many of the world’s leading digital economies (Australia, the United States, and European Union, among others) to rectify the gradual drift toward a fragmented and less-productive global digital economy. Prime Minister Abe is right in proclaiming, “We have yet to catch up with the new reality, in which data drives everything, where the D.F.F.T., the Data Free Flow with Trust, should top the agenda in our new economy,” and right in his call “to rebuild trust toward the system for international trade. That should be a system that is fair, transparent, and effective in protecting IP and also in such areas as e-commerce.”

The central premise of this effort should be a recognition that data and data-driven innovation are a force for good. Across society, data innovation—the use of data to create value—is creating more productive and innovative economies, transparent and responsive governments, better social outcomes (improved health care, safer and smarter cities, etc.).3But to maximize the innovative and productivity benefits of data, countries that support an open, rules-based global trading system need to agree on core principles and enact common rules. The benefits of a rules-based and competitive global digital economy are at risk as a diverse range of countries in various stages of political and economic development have policy regimes that undermine core processes, especially the flow of data and its associated legal responsibilities; the use of encryption to protect data and digital activities and technologies; and the blocking of data constituting illegal, pirated content….(More)”.

Airbnb and New York City Reach a Truce on Home-Sharing Data


Paris Martineau at Wired: “For much of the past decade, Airbnb and New York City have been embroiled in a high-profile feud. Airbnb wants legitimacy in its biggest market. City officials want to limit home-sharing platforms, which they argue exacerbate the city’s housing crisis and pose safety risks by allowing people to transform homes into illegal hotels.

Despite years of lawsuits, countersuits, lobbying campaigns, and failed attempts at legislation, progress on resolving the dispute has been incremental at best. The same could be said for many cities around the nation, as local government officials struggle to come to grips with the increasing popularity of short-term rental platforms like Airbnb, HomeAway, and VRBO in high-tourism areas.

In New York last week, there were two notable breaks in the logjam. On May 14, Airbnb agreed to give city officials partially anonymized host and reservation data for more than 17,000 listings. Two days later, a judge ordered Airbnb to turn over more detailed and nonanonymized information on dozens of hosts and hundreds of guests who have listed or stayed in more than a dozen buildings in Manhattan, Brooklyn, and Queens in the past seven years.

In both cases, the information will be used by investigators with the Mayor’s Office of Special Enforcement to identify hosts and property owners who may have broken the city’s notoriously strict short-term rental laws by converting residences into de facto hotels by listing them on Airbnb.

City officials originally subpoenaed Airbnb for the data—not anonymized—on the more than 17,000 listings in February. Mayor Bill de Blasio called the move an effort to force the company to “come clean about what they’re actually doing in this city.” The agreement outlining the data sharing was signed as a compromise on May 14, according to court records.

In addition to the 17,000 listings identified by the city, Airbnb will also share data on every listing rented through its platform between January 1, 2018, and February 18, 2019, that could have potentially violated New York’s short-term rental laws. The city prohibits rentals of an entire apartment or home for less than 30 days without the owner present in the unit, making many stays traditionally associated with services like Airbnb, HomeAway, and VRBO illegal. Only up to two guests are permitted in the short-term rental of an apartment or room, and they must be given “free and unobstructed access to every room and to each exit within the apartment,” meaning hosts can’t get around the ban on whole-apartment rentals by renting out three separate private rooms at once….(More)”.

Smart Villages in the EU and Beyond


Book edited by Anna Visvizi, Miltiadis D. Lytras, and György Mudri: “Written by leading academics and practitioners in the field, Smart Villages in the EU and Beyond offers a detailed insight into issues and developments that shape the debate on smart villages, together with concepts, developments and policymaking initiatives including the EU Action for Smart Villages.This book derives from the realization that the implications of the increasing depopulation of rural areas across the EU is a pending disaster. This edited collection establishes a framework for action today, which will lead to sustainable revitalization of rural areas tomorrow.Using country-specific case studies, the chapters examine how integrated and ICT-conscious strategies and policy actions focused on wellbeing, sustainability and solidarity could provide a long-term solution in the revitalization of villages across the EU and elsewhere. Best practices pertinent to precision farming, energy diversification, tourism, entrepreneurship are discussed in detail.As an in-depth exploration of the Smart Village on a multinational scale, this book will serve as an indispensable resource for students, researchers and policy leaders in the fields of politics, strategic management and urban and rural studies….(More)”.

The State of Open Data


Open Access Book edited by Tim Davies, Stephen B. Walker, Mor Rubinstein and Fernando Perini: “It’s been ten years since open data first broke onto the global stage. Over the past decade, thousands of programmes and projects around the world have worked to open data and use it to address a myriad of social and economic challenges. Meanwhile, issues related to data rights and privacy have moved to the centre of public and political discourse. As the open data movement enters a new phase in its evolution, shifting to target real-world problems and embed open data thinking into other existing or emerging communities of practice, big questions still remain. How will open data initiatives respond to new concerns about privacy, inclusion, and artificial intelligence? And what can we learn from the last decade in order to deliver impact where it is most needed? 

The State of Open Data brings together over 60 authors from around the world to address these questions and to take stock of the real progress made to date across sectors and around the world, uncovering the issues that will shape the future of open data in the years to come….(More)”.

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity


Paper by Edward L. Glaeser, Hyunjin Kim and Michael Luca: “Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of local economic activity at the local level. However, these statistics typically appear only after multi-year lags, and the public-facing versions are aggregated to the county or ZIP code level. In contrast, crowdsourced data from online platforms such as Yelp are often contemporaneous and geographically finer than official government statistics. Glaeser, Kim, and Luca present evidence that Yelp data can complement government surveys by measuring economic activity in close to real time, at a granular level, and at almost any geographic scale. Changes in the number of businesses and restaurants reviewed on Yelp can predict changes in the number of overall establishments and restaurants in County Business Patterns. An algorithm using contemporaneous and lagged Yelp data can explain 29.2 percent of the residual variance after accounting for lagged CBP data, in a testing sample not used to generate the algorithm. The algorithm is more accurate for denser, wealthier, and more educated ZIP codes….(More)”.

See all papers presented at the NBER Conference on Big Data for 21st Century Economic Statistics here.

Trust, Control, and the Economics of Governance


Book by Philipp Herold: “In today’s world, we cooperate across legal and cultural systems in order to create value. However, this increases volatility, uncertainty, complexity, and ambiguity as challenges for societies, politics, and business. This has made governance a scarce resource. It thus is inevitable that we understand the means of governance available to us and are able to economize on them. Trends like the increasing role of product labels and a certification industry as well as political movements towards nationalism and conservatism may be seen as reaction to disappointments from excessive cooperation. To avoid failures of cooperation, governance is important – control through e.g. contracts is limited and in governance economics trust is widely advertised without much guidance on its preconditions or limits.

This book draws on the rich insight from research on trust and control, and accommodates the key results for governance considerations in an institutional economics framework. It provides a view on the limits of cooperation from the required degree of governance, which can be achieved through extrinsic motivation or building on intrinsic motivation. Trust Control Economics thus inform a more realistic expectation about the net value added from cooperation by providing a balanced view including the cost of governance. It then becomes clear how complex cooperation is about ‘governance accretion’ where limited trustworthiness is substituted by control and these control instances need to be governed in turn.

Trust, Control, and the Economics of Governance is a highly necessary development of institutional economics to reflect progress made in trust research and is a relevant addition for practitioners to better understand the role of trust in the governance of contemporary cooperation-structures. It will be of interest to researchers, academics, and students in the fields of economics and business management, institutional economics, and business ethics….(More)”.

The Importance of Data Access Regimes for Artificial Intelligence and Machine Learning


JRC Digital Economy Working Paper by Bertin Martens: “Digitization triggered a steep drop in the cost of information. The resulting data glut created a bottleneck because human cognitive capacity is unable to cope with large amounts of information. Artificial intelligence and machine learning (AI/ML) triggered a similar drop in the cost of machine-based decision-making and helps in overcoming this bottleneck. Substantial change in the relative price of resources puts pressure on ownership and access rights to these resources. This explains pressure on access rights to data. ML thrives on access to big and varied datasets. We discuss the implications of access regimes for the development of AI in its current form of ML. The economic characteristics of data (non-rivalry, economies of scale and scope) favour data aggregation in big datasets. Non-rivalry implies the need for exclusive rights in order to incentivise data production when it is costly. The balance between access and exclusion is at the centre of the debate on data regimes. We explore the economic implications of several modalities for access to data, ranging from exclusive monopolistic control to monopolistic competition and free access. Regulatory intervention may push the market beyond voluntary exchanges, either towards more openness or reduced access. This may generate private costs for firms and individuals. Society can choose to do so if the social benefits of this intervention outweigh the private costs.

We briefly discuss the main EU legal instruments that are relevant for data access and ownership, including the General Data Protection Regulation (GDPR) that defines the rights of data subjects with respect to their personal data and the Database Directive (DBD) that grants ownership rights to database producers. These two instruments leave a wide legal no-man’s land where data access is ruled by bilateral contracts and Technical Protection Measures that give exclusive control to de facto data holders, and by market forces that drive access, trade and pricing of data. The absence of exclusive rights might facilitate data sharing and access or it may result in a segmented data landscape where data aggregation for ML purposes is hard to achieve. It is unclear if incompletely specified ownership and access rights maximize the welfare of society and facilitate the development of AI/ML…(More)”