Government of the Data (Part 1: From census to digital IDs)
Phuah Eng Chye (6 June 2020)
Yasha Levine notes “governments have been counting their people since the beginning of recorded history. You can find descriptions of censuses in the Old Testament, on Sumerian cuneiform tablets, and in the writings of the ancient Greeks. There were censuses in pre-modern Europe. Most American colonies kept population records, too. Governments counted people for two main reasons: raising state revenue and waging war. They needed to know who and what to tax, and they needed to know how many fighting-age men could be mobilized. It was the U.S. Constitution that added a third and novel reason for counting people: representational democracy…To the framers of the Constitution, the census came first because it determined taxation and the balance of congressional political power. Under the Constitution, the number of seats in the House of Representatives apportioned to each state would be based on population, which meant the government needed to know the precise number of people living in each state”.
It was a massive task to process data manually. Yasha Levine notes “with every passing decade, the census took longer to complete. It was filled with errors and undercounts, which led to nasty scandals and accusations that the data was being manipulated for political ends…The census was taking nearly 10 years to complete, meaning the results were outdated even before they came in…on top of having to enumerate a rapidly growing population, government officials began to cram the census with more and more questions: data on occupations, literacy levels, criminal histories, medical conditions, home ownership, economic trends, and a whole lot of probing about people’s race and immigration status. As the 19th century drew to a close, census officials had started transforming what should have been a simple head count into a system of racial surveillance”.
Technological advances opened the door for governments to exercise greater control. Herman Hollerith’s invented a tabulating machine, the world’s first functional mass-produced computer, that could “process data with blazing speed and accuracy” and enable “fine-grained analysis on a mass scale”. “Overnight, Hollerith’s tabulator technology had transformed census taking from a simple head count into something that looked very much like a crude form of mass surveillance”.
Yasha Levine observed “to the race-obsessed political class, it was a revolutionary development. They could finally put the nation’s ethnic makeup under the microscope. The data seemed to confirm the nativists’ worst fears: Poor, illiterate immigrants were swarming America’s cities, breeding like rabbits, and outstripping native Anglo-American birth rates…Immediately following the census, the states and the federal government passed a flurry of laws that heavily restricted immigration…The data provided by Hollerith’s invention did not cause the racism, nativism, and eugenics that saw class and poverty through the lens of breeding rather than politics and economic policy. But it gave those fears concrete shape – and it provided data to which those fears could be hitched”.
The introduction of welfare systems entrenched digital identification (ID) systems. Katie Fitzpatrick relates that “when the Social Security program launched in the mid-1930s…unique identifier tagged to each American citizen…For opponents of Social Security, the number was evidence of state overreach…missed in these debates, however, was how enthusiastically citizens would embrace their SSNs…as proof of economic security and political belonging…If the Social Security number posed a risk to privacy by making citizens more visible to the administrative state, this was a risk that, for much of the SSN’s history, seemed worth taking…Americans in the 1930s had good reason to embrace their SSNs; they also could not have imagined the wealth of personal data that would be tied to those numbers by the 1970s”.
ID systems are now widely deployed with scope for expansion in many countries. Based on the World Bank’s ID4D database, a McKinsey Global Institute (MGI) report highlights that “almost one billion people globally lack any form of legally recognized identification. An additional 3.4 billion who have some type of legally recognized identification have limited ability to use it in the digital world. The remaining 3.2 billion have a legally recognized identity and participate in the digital economy but may not be able to use that ID effectively and efficiently online”.
“Many digital ID programs have achieved low coverage levels, with the percentage of the population included as low as single digits. Most enable only a small fraction of the nearly 100 uses we have identified for digital ID. Several existing programs with low adoption rates have been affected by limited functionality, poor user experience, and difficulties coordinating across stakeholders. Adoption of the eID in Nigeria stalled in 2017 amid issues with public-private partnerships used to launch the program and difficulty integrating uses and functionality of more than 13 separate identification systems run by separate government agencies. Gov.UK Verify in the United Kingdom has experienced slower than expected adoption – currently less than 10 percent of the population – and has so far been limited to a relatively small set of government-related uses. Overall, most existing digital ID programs do not yet capture all potential value, and additional opportunity exists for greater value creation”.
The MGI report notes the pace of adoption will accelerate as “the opportunity for value creation through digital ID is growing as technology improves, implementation costs decline, and access to smartphones and the internet increases daily. The foundational digital infrastructure that supports digital ID grows in reach and drops in cost every day. More than four billion people currently have access to the internet, and nearly a quarter-billion new users came online for the first time in 2017. The technology needed for digital ID is now ready and more affordable than ever, making it possible for emerging economies to leapfrog paper-based approaches to identification”.
MGI estimates that for some emerging economies, “basic digital ID alone could unlock 50 to 70 percent of the full economic potential, assuming adoption rates of about 70 percent. In the United States and United Kingdom, where conventional alternatives and robust digital ecosystems already exist, nearly all potential value requires advanced digital ID…We find that in 2030, digital ID has the potential to create economic value equivalent to 6 percent of GDP in emerging economies on a per-country basis and 3 percent in mature economies, assuming high levels of adoption. In emerging economies, much of the value could be captured even through basic digital ID with essential functionalities. For mature economies, many processes are already digital and potential for improvement is more limited, necessitating advanced digital ID programs with data-sharing features. Of the potential value, we estimate that in emerging economies, some 65 percent could accrue to individuals, while in mature economies, about 40 percent could flow to individuals”.
MGI also points out that “digital ID can also unlock non-economic value, potentially furthering progress toward ideals that cannot be captured through quantitative analysis, including those of inclusion, rights protection, and transparency. Digital ID can promote increased and more inclusive access to education, healthcare, and labor markets; can aid safe migration; and can contribute to greater levels of civic participation. For example, in Estonia, over 30 percent of individuals vote online …Digital ID can also help enforce rights nominally enshrined in law…in India, the right of residents to claim subsidized food…digital ID could help in the elimination of child labor and help enforce laws against child marriage…An accurate, up-to-date death registration system can help curb social protection fraud, and a reliable, authentic voter registry is essential to reduce voter fraud and ensure the overall integrity of the electoral process”.
Overall, ID systems have evolved from simple registries to census-IDs and now to sophisticated digital ID systems. Each progressive step elevates management capabilities. In manual systems, data is static and has limited application. Digital ID systems can be comprehensive and real time. The capabilities and connectivity of digital ID is approaching a take-off point which will expand its usage as well as its vulnerabilities.
Katie Fitzpatrick (6 December 2018) “Always watching: The linked history of privacy and surveillance in America”. The Nation. https://www.thenation.com/article/in-americas-panopticon/
Olivia White, Anu Madgavkar, James Manyika, Deepa Mahajan, Jacques Bughin, Mike McCarthy, Owen Sperling (April 2019) “Digital identification: A key to inclusive growth”. McKinsey Global Institute (MGI). https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/digital-identification-a-key-to-inclusive-growth
Phuah Eng Chye (21 December 2019) “The debate on regulating surveillance”.
Phuah Eng Chye (4 January 2020) “The economics and regulation of privacy”.
Phuah Eng Chye (18 January 2020) “Big data and the future for privacy”.
Phuah Eng Chye (15 February 2020) “The costs of privacy regulation”
Phuah Eng Chye (29 February 2020) “The journey from privacy to transparency (and back again)”. http://economicsofinformationsociety.com/the-journey-from-privacy-to-transparency-and-back-again/
Phuah Eng Chye (14 March 2020) “Features of transparency”.
Phuah Eng Chye (28 March 2020) “The transparency paradigm”.
Phuah Eng Chye (11 April 2020) “Anonymity, opacity and zones”.
Phuah Eng Chye (25 April 2020) “Public and private roles in managing data (Part 1: Surveillance)”. http://economicsofinformationsociety.com/public-and-private-roles-in-managing-data-part-1-surveillance/
Phuah Eng Chye (9 May 2020) “Public and private roles in managing data (Part 2: Data sharing)”. http://economicsofinformationsociety.com/public-and-private-roles-in-managing-data-part-2-data-sharing/
Phuah Eng Chye (23 May 2020) “Public and private roles in managing data (Part 3: Evolving roles)”. http://economicsofinformationsociety.com/public-and-private-roles-in-managing-data-part-3-evolving-roles/
Yasha Levine (30 April 2019) “The racist-and high tech-origins of America’s modern census”. Medium. https://onezero.medium.com/the-racist-and-high-tech-origins-of-americas-modern-census-44ba984c28af