Can a Data-Driven Economy Yield More Equality?
MIT Professor Alex Pentland thinks it can
By Irving Wladawsky-Berger
Many pundits are talking about the need for post-pandemic business resiliency. MIT Professor Alex “Sandy Pentland goes one step further: Not only does he want digital technologies to reinvigorate the economy, but also to “spread the economic benefits throughout society.”
“With each major crisis, be it war, pandemic, or major new technology, there has been a need to reinvent the relationships between individuals, businesses, and government,” Pentland writes in the first chapter of Building the New Economy. Pentland, also a leader of the MIT Initiative on the Digital Economy (IDE), cites two major historical examples. In the early 20th century, the rise of mass manufacturing led to the creation of regulations governing working conditions and pay, health rules for mass-produced foods, and laws to prevent monopolies that stifled competition. Then, the decades following WWII saw greater access to higher education, racial and gender progress, and increased support for scientific research and medical advances.
“Today we face two simultaneous disruptions: One is the COVID-19 pandemic and resulting economic shock, and the second is the rise of pervasive digital data, crypto systems, and artificial intelligence (AI).” The two disruptions are highly interrelated. Digital technologies have been deployed to fight the global pandemic as well as helping us stay connected as we practice social distancing.
But these same technologies are also increasing the already high levels of disinformation and fraud, threatening privacy rights with well-meaning public health technology measures, and are likely to impact employment as institutions accelerate their embrace of digitization, AI, and automation.
“These problems highlight the need to reinvent the ways data and AI are used in all of societies’ civic and government systems, both to guarantee that future pandemics can be handled better and to reinvigorate the economy but also to spread the economic benefits throughout society.”
High resilience in the face of an uncertain, changing environment is the essence of evolution and natural selection. Building a new post-pandemic economy requires the creation of more agile, resilient systems and institutions to help us better adapt to an unpredictable future and withstand turbulent events like COVID-19.
In a resilient economy, power and decision-making should be distributed among a diverse set of stakeholders rather than concentrated in a few hands.
Building the New Economy includes 14 chapters by various authors, organized into four sections. Let me discuss a few of the key points in each section.
The human perspective: New types of engagement
“During the last 200 years, questions about concentration of power have emerged each time the economy has shifted to a new paradigm… As the economy was transformed by industrialization and then by consumer banking, powerful new players such as Standard Oil, J.P. Morgan, and a handful of others threatened the freedom of citizens. In order to provide a counterweight to these new powers, citizens joined together to form trade unions and cooperative banking institutions, which were federally chartered to represent their member’s interests. These citizen organizations helped balance the economic and social power between large and small players and between employers and workers.”
Similar questions are now being raised regarding data and AI. Who controls the vast amounts of data required to train deep learning algorithms and ensure that they do what we want them to do?
In a 2017 article, The Economist noted that data is the fuel of the future: “Data are to this century what oil was to the last one: a driver of growth and change.” Both oil refineries and data centers fulfill similar roles: “producing crucial feedstocks for the world economy.”
Data captures our behavior as we go about our daily life — what we buy, the web sites we access, the people we interact with, the locations our cell phones leave behind as we move around the world.
What if all this data belong to the individuals whose behavior it captures, not to the organizations that collect it? What measures do we now need to re-balance the vast amounts of data and economic power held by a small number of actors?
A chapter on Data Cooperatives argues for the formation of collective organization of citizens to move control of their data to a broader base of stakeholders that will ensure that the economy is more responsive to their needs as well as promote greater competition and innovation. The idea is not so radical when you consider that in the U.S., for example, “almost 100 million people are members of credit unions — not-for-profit institutions owned by their members, and already chartered to securely manage their members’ digital data and to represent them in a wide variety of financial transactions, including insurance, investments, and benefits. The question is, could we apply the same push for citizen power to the area of data rights in the ever-growing digital economy?”
Exploiting Data to make society work better
The book’s second section addresses the growing inequality of the past few decades, asking a few pertinent questions: “Can we make our financial systems less fragile, more transparent, and less winner-take-all? Can we make our health systems more agile and proactive? Can we spread financial and health benefits more widely? The new distributed, technology-enabled organizations that are emerging seem to offer this promise.”
A major reason for the explosive growth of Big Tech— Google, Facebook, Amazon, Alibaba, and Tencent, for example — has been the lack of Internet identity standards. Identity is essentially the collection of information associated with each specific individual. These companies use the vast amounts of data gathered from their customers to analyze their behavior across the digital and physical worlds and offer them products and services customized to their individual preferences. The more data a company has, the more customers it will attract with personalized offerings, and the more data it’s then able to gather. This creates network effects and economies of scale, leaving smaller companies without access to all that data at a huge economic disadvantage.
Blockchain and distributed ledger technologies (DLT)have the potential to address this lack of Internet identity standards by enabling the formation of trusted data ecosystems. Rather than keeping the data siloed within the institution that collected it, a variety of institutions share and exchange the critical data required to validate identities in a secure, decentralized manner without the need for large central platforms.
Data and AI: A new ecology
The Internet supports a huge variety of applications. Supporting a world with billions of data owners will similarly require a wide diversity of approaches to be able to handle the different problems of individuals, companies and governments. But, as is the case with the Internet, to work on a global scale, these diverse approaches must be interoperable, so that knowledge, trade, and interaction can flow seamlessly across company and national boundaries.
Interoperability of Distributed Systems, a chapter in the book’s third section, writes that the lack of interoperability across different blockchain and DLT platforms is a major impediment to their wide acceptance, as each platform seeks its own unique advantage rather than working together to establish a common set of marketplace standards. For blockchain to evolve into Internet 2.0 — a more secure, decentralized version of the Internet — these various platforms must embrace the principles of interoperability, survivability, and manageability that led to the success of Internet 1.0 during its decades of development. The chapter proposes a design framework for an interoperable blockchain/DLT architecture based on these Internet principles.
Legal Algorithms
The book’s final chapter discusses how to leverage computational systems to develop more transparent, accountable, and inclusive legal, civil, and government processes. “Code is law, and law is increasingly becoming code. This change is being driven by the growing need for access to justice and the ambition for greater efficiency and predictability in modern business. Most laws and regulations are just algorithms that human organizations execute, but now legal algorithms are beginning to be executed by computers as an extension of human bureaucracies.”
However, without the proper oversight, the migration of legal algorithms to computer platforms could displace human judgment and lead to negative, unintended consequences. We must thus ensure that these highly complex digital legal systems are safe, secure, and achieve the desired societal objectives.
This blog first appeared here on June 6.
